Wearable sensors for continuous personalized dosimetry for targeted radionuclide therapy

Abstract

Devices, systems, software, and methods are provided for calculating the total percent injected activity per milliliter of tissue (%IA / mL) delivered to tumors and organs at risk (OARs) in a subject administered radiopharmaceutical therapy. The methods utilize optical fiber-based or chip-based gamma counters capable of monitoring real-time uptake of a radiopharmaceutical by a tumor or OAR over the course of treatment. Medical imaging is used to identify the locations of tumors and OARs in the subject for positioning counters on a wearable structure or on the skin of the subject to monitor the uptake of the radiopharmaceutical. An algorithm is provided that automatically calculates %IA / mL for tumors and OARs from the gamma count rate recorded by a sparse set of gamma counters along with apriori knowledge of tumor, OAR, and gamma counter locations. The systems and methods can be used for continuous, real-time dosimetry of multiple tumors and OARs non-invasively.

Description

WEARABLE SENSORS FOR CONTINUOUS PERSONALIZED DOSIMETRY FOR TARGETEDRADIONUCLIDE THERAPYCROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims benefit of U.S. Provisional Patent Application No. 63 / 538,174, filed September 13, 2023, which application is incorporated herein by reference in its entirety.BACKGROUND OF THE INVENTION

[0002] Radiotherapy is highly effective in treating cancer. However, the delivery of radiation using conventional external beam radiotherapy (EBRT) to treat widespread metastatic disease is limited due to the dose delivered to normal tissues and the logistics of treating many sites of disease. Moreover, it is challenging to treat all sites of metastatic disease using EBRT since microscopic pockets of disease are not visible under diagnostic imaging. Recent advances in the treatment of metastatic neuroendocrine cancers and prostate cancer have fostered significant interest in both developing targeted radionuclide therapies (TRT) for maximal therapeutic benefit and in extending these therapies to other cancers. Molecularly targeted radionuclide therapy enables systemic delivery of radiation through the chelation of radioactive isotopes with tumor-specific ligands, including small molecules, antibodies, and derivatives thereof. The radioligand is administered intravenously and circulates inside the body, attaches to cancer cells, and emits localized radiation, selectively damaging nearby cells (on the range of microns to millimeters depending on the radioisotope used). The goal of TRT is to deliver a sufficient dose to tumors over multiple treatment cycles to ablate cancer cells, while minimizing unwanted dose deposition to radiosensitive organs at risk (OARs), such as the kidneys, salivary glands, liver, spleen, and bone marrow Moreover, RPT has recently shown promise in the treatment of metastatic castrate resistant prostate cancer (mCRPC), and has redefined treatment in metastatic cancer. Virtually incurable, 20% of all prostate cancer deaths are now due to mCRPC (Scher et al. (2015) PLoS One 10(10):e0139440), despite significant advances in androgen inhibitors (de Bono et al. (2011 ) N Engl J Med 364(21 ):1995-2005, Scher et al. (2012) N Engl J Med 367(13):1187-1197) and effective treatments remain an unmet need (Nussbaum et al. (2016) Prostate Cancer Prostatic Dis. 19(2):11 1 -21 ). While treatment of localized and newly diagnosed metastatic prostate cancer have seen tremendous strides in recent years with new androgen blocking agents, improved imaging, surgical and radiation techniques, the number of men developing mCRPC is increasing (Scher et al. (2015), supra). The incidence of mCPRC in the US is growing at roughly 1 ,7% / year, estimated at 36,100 in 2009 and increasing to 42,970 in 2020 (Scher et al. (2015), supra). With few treatment options, mCRPC patients continueto have markedly poor survival (-13-30 months (Halabi et al. (2016) Journal of Clinical Oncology 34(14):1652-1659)) and are in dire need of additional therapeutic options that overcome mechanisms of resistance. Current strategies such as androgen inhibition, chemotherapy (median survival 18-19 months) (Tannock et al. (2004) N Engl J Med 351 (15):1502-1512, Petrylak et al. (2004) N Engl J Med 351 (15):1513-1520) or T-cell therapy (Higano et al. (2009) Cancer 115(16):3670-3679) offer only incremental benefit (median survival 26 months), but inevitably fail (Hotte et al. (2010) Curr Oncol 17 Suppl 2:S72-9). Patients failing first line chemotherapy survive only 12-16 months. While radiation is highly effective against prostate cancer, it cannot be delivered to widespread metastatic disease using conventional external beam techniques as discussed due to the toxicity of irradiating significant amounts of normal tissue. Recently, the Food and Drug Administration (FDA) approved177Lu-PSMA-617, a p-particle emitting radioligand therapy, for the treatment of mCRPC (Sartor et al. (2021 ) New England Journal of Medicine 385:1091 -1103, Study of 177Lu-PSMA-617 In Metastatic Castrate-Resistant Prostate Cancer (VISION), Identifier NCT0351 1664 (2022, May 9 - 2022, August 11 ), Aghdam et al. (2019) World J Nucl Med. 18(3):258- 265, Kratochwil et al. (2016) J Nucl Med. 57(8):1170-1176). Prostate-specific membrane antigen (PSMA) is a type II transmembrane glutamate carboxypeptidase that is highly expressed in mCRPC lesions. Elevated expression of PSMA serves as an independent biomarker of poor prognosis, with its expression increasing in high-grade or metastatic tumors, and is commonly absent in benign prostate tissue (Sartor et al., supra).

[0003] Similar to the goals of stereotactic ablative radiotherapy, where the radiation dose to tumors of interest are maximized while minimizing dose to surrounding tissues, theranostic radioligand therapies aim to maximize the tumor uptake of the radionuclide while minimizing the undesired dose deposition and toxicity to organs at risk (OAR) such as the kidneys, bladder, and bone marrow. In current clinical trials and practice,177Lu-PSMA-617 is administered using a standard dosing, or “one- size fits all”, strategy. This treatment strategy overlooks common patient-to-patient heterogeneities including (1 ) varying tumor grades, and hence varying levels of PSMA expression, (2) anatomical and physiological variations including those in tumor vasculature, radionuclide retention, and excretion rates, (3) day-to-day variations including heart rate, blood pressure, and blood flow rate, and (4) on-target but off-tumor toxicity from radionuclide binding to PSMA-expressing OAR (Aghdam et al. (2019) World J Nucl Med. 18(3):258-265, Ling et al. (2022) Pharmaceutics. 14(10):2166, Membreno et al. (2019) Mol Pharm 16(5):2259-2263). This approach compromises critical dosing and fractionation modulations that could improve clinical outcomes (Emmett et al. (2020) J Clin Oncol 2020;38:5557, Lunger et al. (2020) Translational Andrology And Urology, 10(10):3963-3971 ). Therefore, chronic biodistribution measurements for each patient over several half-lives and over allfractions is vital in evaluating and optimizing for treatment response (Kratochwil et al. (2016) J Nucl Med. 57(8):1170-1 176, Nautiyal et al. (2022) Nucl Med Commun. 43(4):369-377, Kabasakal et al. (2017) Mol Imaging Radionucl Ther. 26(2):62-68).

[0004] Single photon emission computed tomography (SPECT) is the current state-of-the-art dosimetry technique in radioligand therapy. Despite advances in SPECT imaging and reconstruction algorithms, this dosimetry method only provides a whole-body snapshot at a single time point, leaving patient-specific chronic dosimetry as an unmet need. Due to the lack of universal availability of SPECT, long acquisition times, and high cost overhead, it is logistically infeasible for every patient to have multiple scans during the course of treatment. At most one SPECT scan per treatment cycle is taken, if any at all. The total dose is often calculated by simply fitting a representative biodistribution curve (Violet et al. (2019) Journal of Nuclear Medicine 60(4):517-523, Jackson et al. (2020) Journal of Nuclear Medicine 61 (7):1030-1036) to this one point. However, this is insufficient as variations in the time to maximum (tmax) uptake as well as the effective half-life (Teff the time it takes for the dose to become half) for metastatic lesions can be 50% and 30%, respectively. This uncertainty in dose estimation translates to dose variations of more than 70% over the course of treatment (Peters et al. (2022) Eur J Nucl Med Mol Imaging 8;49(4) : 1101 -1112).

[0005] There remains a need for an improved platform for real-time, chronic in vivo dosimetry to supplement the current medical imaging modalities.SUMMARY OF THE INVENTION

[0006] Devices, systems, software, and methods are provided for calculating the total percent injected activity per milliliter of tissue (%IA / mL) delivered to tumors and organs at risk in a subject administered radiopharmaceutical therapy (RPT). The methods utilize optical fiber-based or chipbased gamma sensors or counters capable of monitoring real-time uptake of a radiopharmaceutical by a tumor or OAR during and across all fractions over the course of treatment. Medical imaging is used to identify the locations of tumors and OARs in the subject in order to position counters on a wearable structure or on the skin of the subject to monitor the uptake of the radiopharmaceutical. In addition, an algorithm is provided that automatically calculates %IA / mL for tumors and OARs from the gamma count rate recorded by a sparse set of gamma counters along with the a priori knowledge of tumor, OAR, and gamma counter locations. The system and methods disclosed herein can be used for continuous, real-time dosimetry of multiple tumors and OARs non-invasively and with high accessibility.

[0007] Fundamentally, this platform is unique in that it synergistically integrates an algorithmic approach to significantly reduce the amount of data (and therefore spatial coverage) needed toaccurately reconstruct TRT dosimetry and SPECT images. This platform utilizes prior knowledge of the location of tumor and OARs in combination with strategically placed sensors or sparsely placed sensors. Second, this platform uses integrated circuit technology to enable sensors that have pixels that operate asynchronously, which enables determination of the energy and direction of incident photons, as well as allowing highly multiplexed arrays of sensors on the patient. The sensors are scalable in area, but remain thin (<300 microns). In some embodiments, the sensors are arranged in stacks to enable energy resolution and acquire directional photon information - which further enhances spatial resolution and accuracy of detection of the radionuclide distribution. The sensors have minimal thickness and weight, which enables many sensors to be used at a single time as a wearable. This platform is capable of performing single photon sensing for image reconstruction, analogously to SPECT, unlike positron emission tomography-based imaging, where two temporally coincident photons must be detected. No collimators are needed. Rather, the flux of single photons (gamma) is captured at different known locations on the surface of the patient to reconstruct the distribution of gamma emissions within the body, and thereby the dosimetry to tumors and organs at risk. The platform also makes use of the angle of the incident photon (in contrast to collimators which eliminate all angles except for a narrow window of incident angles) to back-calculate the distribution of gamma-emitting radionuclides. This approach allows for a greater number of gamma photons to be measured at a single spatial point, potentially increasing the signal to noise ratio, and speeding up the time to gather the amount of data required for accurate image reconstruction. In some embodiments, a chip-based platform is provided capable of a highly scalable architecture, allowing many chip-based sensors to be placed on the body. In some embodiments, asynchronous pixel operation is used within each sensor. In some embodiments, sensor stacking is used, as described below, to enable energy resolution and / or incident direction resolution in a form factor that is < 5 mm thick. Moreover, the use of SPECT emitters allows a greater selection of radionuclides to be imaged and importantly, allows for imaging of the distribution of TRT.

[0008] In one aspect, a gamma photon counter is provided, the gamma photon counter comprising: a Y2C>3-Eu-doped phosphor, wherein a y-photon incident on the surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum, suitable for solid-state photon detection; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3-EU doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on thesurface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.

[0009] In certain embodiments, the photodiode is an avalanche photodiode (APD). In some embodiments, the APD is a silicon APD.

[0010] In certain embodiments, the photodiode is a single photon avalanche diode (SPAD).

[0011] In certain embodiments, the detector further comprises multiple power supplies to control circuit cooling, quenching and reset, and high voltage biasing.

[0012] In certain embodiments, the detector further comprises a high voltage regulator.

[0013] In certain embodiments, the opaque material has an optical density (OD) of at least 4. In some embodiments, the opaque material is a black light-absorbing material such as, but not limited to, black optical tape.

[0014] In certain embodiments, the incoming gamma photons reaching the surface of the detector are uncollimated.

[0015] In certain embodiments, the digital counter is configured in a field-programmable gate array (FPGA).

[0016] In certain embodiments, the gamma photon counter further comprises a clock configured to produce a clock signal, wherein the digital counter uses the clock signal to count numbers of y- photon detection events per a period of time.

[0017] In certain embodiments, the gamma photon counter further comprises a level shifter, wherein the level shifter is configured in circuitry to ensure logic level compatibility with the digital counter.

[0018] In certain embodiments, the gamma photon counter further comprises a data storage unit in communication with the digital counter, wherein the data storage unit is configured to store a plurality of gamma photon count records for a plurality of y-photon detection events.

[0019] In certain embodiments, the gamma photon counter further comprises a data processing unit in communication with the data storage unit, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.

[0020] In certain embodiments, the gamma photon counter is attached to a wearable structure. In some embodiments, the gamma photon counter is attached to a fabric or an adhesive patch. In some embodiments, the gamma photon counter is attached to clothing such as, but not limited to, a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

[0021] In certain embodiments, the gamma photon counter has a diameter less than or equal to 2.5 mm.

[0022] In another aspect, a gamma photon counter is provided, the gamma photon counter comprising: a detector implemented as an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises at least one reverse biased diode, wherein a y-photon incident on the surface of the reverse biased diode generates a voltage pulse across the reverse biased diode. In some embodiments the reverse biased diode is connected to an amplifier and then a digital counter. In other embodiments, the reverse biased is connected to a voltage buffer before being connected to a voltage amplifier and subsequently connected to a digital counter. The digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse generated across the reverse biased diode by each y-photon incident on the surface. In some embodiments, the chip further comprises an on-chip memory configured to store a plurality of gamma photon count records for a plurality of y-photon detection events. In some embodiments, the chip further comprises a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time. In some embodiments, the chip further comprises custom digital logic circuitry, wherein the digital logic circuitry is configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0023] In another aspect, a gamma photon counter is provided, the gamma photon counter comprising: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements. In some embodiments, each pixel in the array comprises silicon diodes connected to an amplifier. In some embodiments, each pixel operates asynchronously, meaning that each pixel can register a gamma interaction without reading out the entire array. This allows much greater time resolution, and enables near single particle sensitivity on the array. This feature enables determination of the incident direction of the gamma photon, which then enables improved image reconstruction with fewer incident gammas (when compared to purely counting gammas without directional information). With respect to the diodes, in some embodiments, the diodes are reversed biased. In other embodiments the diodes have zero voltage bias. With respect to the pixel architecture, in some embodiments, this is a differential structure, in which the two diodes are connected to the inputs of a differential amplifier. Leveraging the sparsity of photon hits, the most likely event is where only a single diode is hit at any one time, producing a differential pulse at the output of the amplifier. This structure has the advantage of mitigating offsets associated with the properties of the diode, or reset or other circuitry that will have an effect on the baseline voltage (signal) across the diode, as any mismatch between the two diodes appears as input offset of the amplifier and can cause the amplifier to operate in a low gain region, or ‘rail’ (saturate) to the point it is not active at all. Thus, the differential structure preserves the ability of the amplifier tooperate with some inherent variation of the sensing diodes across the chip. The pulse from each diode is generated by the following: wherein an incident gamma photon breaks bonds in the silicon, generating electron-hole pairs that in turn generate a pulse of charge (Qp) in the silicon diode, which is accumulated on a parasitic diode capacitor (Cdiode). This generates a small voltage pulse across the diode (Vp= Qp / Cdiode). The use of integrated circuit technology enables ultra-small diode capacitances, increasing Vp, and allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity gain voltage amplifier. Each of these buffered outputs connects to the inputs of a differential amplifier. In some embodiments, to mitigate DC voltage offset at the output due to fabrication variability from pixel-to-pixel and chip-to-chip that may cause variability in detector sensitivity, a voltage integrator is bootstrapped from the output of the amplifier to one of its inputs in a negative feedback configuration. The voltage integrator also accepts a desired DC voltage that sets the voltage at the output of the amplifier. This ensures that the sensitivity of each of the pixels across the chip is approximately the same. In order to tune each diode in each pixel to a desired sensitivity, the output of the amplifier is connected to two level shifters: one that shifts the DC level of the amplifier output up to only amplify the voltage pulse from the first diode, and the other that shifts the DC level of the amplifier output down to only amplify the voltage pulse from the second diode. The amounts these DC levels are shifted are set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert the bits stored into an analog shift in voltage. These shifted and amplified voltage pulses are then digitized using a series of inverters. Capacitors at the inputs of the last inverters increase signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of either silicon diode. The chip also comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0024] In another aspect, a gamma photon counter is provided, the gamma photon counter comprising: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements, wherein each pixel comprises a single reverse- biased silicon diode connected to a unity gain voltage buffer. Buffered voltage output from the unity gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed- loop amplifier is either pre-set or configurable using in-pixel memory and DAC. A y-photon incidenton a surface of the silicon diode generates a voltage pulse across the diode and is subsequently buffered and amplified by a fixed, process-invariant gain. This voltage pulse is then digitized using a series of inverters, which are connected to digital counters to quantify the total number of gamma photons detected in a certain time frame. Each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of the silicon diode. The chip further comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic circuitry configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0025] In certain embodiments, the detector is optimized for sensitivity by decreasing the diode capacitance. In some embodiments, the diode size is 0.1 pm to 0.5 pm x 0.1 pm to 0.5 pm. In some embodiments, the diode size is 0.5 pm to 1 pm x 0.5 pm to 1 pm. In some embodiments, the diode size is the minimum size available for a complementary metal-oxide semiconductor (CMOS) process (which is continually decreasing).

[0026] In certain embodiments, the detector is optimized to tradeoff between both pixel fill factor and sensitivity, wherein the diode size is 1 pm to 1 .5 pm x 1 pm to 1 .5 pm.

[0027] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity, wherein the diode size is 1 .5 pm to 3 pm x 1 .5 pm to 3 pm.

[0028] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity, wherein the diode size is 3 pm to 10 pm x 3 pm to 10 pm.

[0029] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity, wherein the diode size is 10 pm to 50 pm x 10 pm to 50 pm.

[0030] The detector may have any suitable shape such as a curved or polygonal shape. In some embodiments, the shape of the detector is circular, oval, semicircular, spherical, cylindrical, triangular, square, rectangular, pentagonal, hexagonal, octagonal, diamond-shaped, or parallelogram-shaped. In certain embodiments the detector has sides ranging from 0.1 pm to 50 pm in length.

[0031] In certain embodiments, the on-chip memory is static random-access memory (SRAM).

[0032] In certain embodiments, the chip has a surface area of less than or equal to 1 mm2.

[0033] In certain embodiments, the chip has a thickness of less than or equal to 0.5 mm.

[0034] In certain embodiments, the chip has a surface area of less than or equal to 10 mm2(e.g., in order to increase the measured gamma photon flux incident on the sensor).

[0035] In certain embodiments, the chip has a surface area of less than or equal to 1 cm2(e.g., in order to increase the measured gamma photon flux incident on the sensor).

[0036] In certain embodiments, the chip has a surface area of 1 cm2to 5 cm2(e.g., in order to increase the measured gamma photon flux incident on the sensor).

[0037] In certain embodiments, the chip comprises a plurality of detectors. In some embodiments, the plurality of detectors is organized in a detector array.

[0038] In certain embodiments, multiple sensors are integrated together to create larger sensing arrays.

[0039] In certain embodiments, a chip-based sensor has a form factor with a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm. In some embodiments, the form factor has a thickness ranging from 1 mm to 1 cm, 1 mm to 5 mm, or 1 mm to 3 mm, including any thickness within these ranges such as 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, 10 mm, 12 mm, 14 mm, 16 mm, 18 mm, 20 mm, 25 mm, 30 mm, 35 mm, 40 mm, 45 mm, 50 mm, 55 mm, 60 mm, 65 mm, 70 mm, 75 mm, 80 mm, 85 mm, 90 mm, 95 mm, or 1 cm.

[0040] In certain embodiments, the chip is covered with a material capable of Compton scattering of gamma photons. The Compton scattering material may include, but is not limited to, lead, tungsten, or bismuth. Compton scattering of gamma photons that collide with the material generates lower energy photons (typically <100 keV) that have a higher interaction probability with the detector due to the photoelectric effect and additionally creates secondary electrons from the collision with the primary gamma photon, which have a high interaction probability with the detector. In some embodiments, these secondary electrons generated from the gamma photons are detected by the detector. Both of these energy conversions can be accomplished using a thin high-density layer of a Compton scattering material on top of the detector or on the back of the detector (e.g., covering the bulk silicon), which can boost the signal of the detector, increase its sensitivity, and minimize data acquisition times.

[0041] In certain embodiments the energy of the incoming photons can be determined by measuring the ratio of detector counts with a plurality of detectors having varying thicknesses of attenuating material. The attenuating material may include lead, tungsten, bismuth, or other high-density material. For example, lower energy photons have an exponentially higher probability of interaction with lead, and can be detected without or in certain instances with a very thin layer of lead. Higher energy photons are selectively measured by creating a subsequently thicker layer of lead on top of other detectors to completely attenuate lower energy photons and only allow high energy photons to pass through. This process can be repeated with layers of different thicknesses in order to allow forenergy resolution of an incoming gamma photon flux consisting of multiple primary energy emissions to be determined. Since the energies of gamma photons will be a distribution at varying thicknesses of lead, an understanding of the likelihood of detecting a photon of a certain energy with a detector of a certain lead thickness can be determined using multiphysics simulation, and can be used to separate the detected counts of each energy.

[0042] In certain embodiments, chip-based gamma detectors that are capable of determining the energy resolution of an incoming flux of gamma photons are provided. In some embodiments, the chip-based gamma detectors are placed in a vertical stack with each detector separated from the other with a thin layer of an attenuating material (see FIG. 33A), which may include lead, tungsten, bismuth, or other high-density material.

[0043] In certain embodiments, the plurality of chip-based gamma detectors is stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm, or greater than or equal to 1 mm and less than 3 mm, or greater than or equal to 0.1 mm and less than 1 mm.

[0044] In certain embodiments, the plurality of chip-based gamma detectors is stacked with a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm. In some embodiments, the form factor has a thickness ranging from 1 mm to 1 cm, 1 mm to 5 mm, or 1 mm to 3 mm, including any thickness within these ranges such as 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, 10 mm, 12 mm, 14 mm, 16 mm, 18 mm, 20 mm, 25 mm, 30 mm, 35 mm, 40 mm, 45 mm, 50 mm, 55 mm, 60 mm, 65 mm, 70 mm, 75 mm, 80 mm, 85 mm, 90 mm, 95 mm, or 1 cm.

[0045] In certain embodiments, chip-based gamma detectors that are capable of determining the energy resolution of an incoming flux of gamma photons are placed in the same plane to give energy resolution in approximately the same spatial area. In some embodiments, each detector has varying thickness of an attenuating material such as lead, tungsten, bismuth, or other high-density material placed on their surface or above the bulk silicon.

[0046] In certain embodiments on-chip circuitry is tuned to be responsive to a range of linear energy transfer (LET), such that the combination and distribution of signals from various pixels with known LET responsivity enable the determination of the incident energies of incoming gamma photons. For example, low energy photons have higher LET and can be detected with a pixel with low gain that only detects low energy photons and not higher energy photons with higher LET, which do not produce a signal. On the same chip or a neighboring chip, pixels with higher gain are included to amplify the low LET from higher energy photons. The pixels with higher gain are responsive to both lower energy photons and higher energy photons. By combining the statistics from sets of pixelswith lower gain and sets of pixels with higher gain, the energy distribution of incoming gamma photons can be determined.

[0047] In certain embodiments, a combination of all the above methods for energy resolution is used to determine the energy distribution of incoming gamma photons.

[0048] In certain embodiments, a pixel sensor is also responsive to electrons generated by the gamma photons. For example, electrons may be generated by gamma photons by the photoelectric effect, wherein a gamma ray transfers all its energy to an electron resulting in ejection of the electron from an atom. Alternatively, electrons may be generated from gamma photons by Compton scattering, which similarly results in ejection of an electron from an atom, wherein the gamma ray retains some of its energy and is scattered in a different direction. In some embodiments, electrons are generated from gamma photons in a patient administered a radiopharmaceutical comprising a gamma-emitting radionuclide, in a layer of material placed in between the patient and a pixel sensor, or in silicon of a diode upon collision with a gamma photon. Electrons bombarding a silicon diode create electron-hole pairs in the silicon that generate voltage pulses across the silicon diode, which can be detected similarly to those produced by gamma photons with the chip-based devices described herein. In certain embodiments, a pixel sensor detects both gamma photons and electrons generated by gamma photons.

[0049] In certain embodiments, gamma photon sensors are stacked on top of each other to enable incident angle measurements of incoming photons. In some embodiments, the stacked sensors are equipped with fast readout circuitry for an array of gamma sensing elements to allow for near instantaneous detection of the same incident gamma photon passing between two sensors in the stack. In some embodiments, this near instantaneous detection of incident gamma photons is accomplished by having asynchronous pixel operation, such that each pixel samples the gamma hit, and transmits the time of the hit, the pixel location, and the signal from the gamma hit, which is related to the LET of the gamma counter. The angle shift of the gamma photon passing from the top sensor to the underlying sensor can be used to calculate the incident gamma photon angle on the sensor stack by evaluating the numerical equations that govern Compton scattering physics. Angular measurements of incoming gamma photons give an additional dimension of information when reconstructing dose information in tumors and OAR over the course of therapy, and enable the use of a fewer number of sensors around the patient.

[0050] In certain embodiments, the clock signal is generated by a frequency locked loop (FLL) oscillator. The clock beacon to the FLL is generated from an off-chip crystal oscillator.

[0051] In certain embodiments, the clock signal is generated directly from an off-chip crystal oscillator.

[0052] In certain embodiments the clock signal and control signals are generated from an external computer, FPGA, cellular phone, or other control device.

[0053] In certain embodiments, the on-chip energy storage device or the off-chip energy storage device comprises a battery, a capacitor, or a photovoltaic system. In some embodiments, the battery is rechargeable.

[0054] In certain embodiments, the gamma photon counter is wired to a power source, control source (FGPA, computer, laptop, phone), and data collection unit. In certain embodiments the data is uploaded wirelessly to the cloud.

[0055] In certain embodiments, the gamma photon counter is wireless and communicates with a central computer.

[0056] In certain embodiments, the gamma photon counter further comprises a data processing unit in communication with the on-chip memory, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.

[0057] In certain embodiments, sensors will be organized into small arrays and interconnected with one another to allow for efficient and compact communication to and from each sensor in the array. This prevents excessive wiring that becomes difficult when placing many sensors around the patient. This also allows for low power consumption by avoiding the use of additional readout and communication circuitry for every additional chip. Interconnecting the sensors in small arrays allows for higher count recordings, which directly shortens the required recording time to achieve a sufficient signal-to-noise ratio (SNR) for dose reconstruction in tumors and OAR. In certain embodiments, many of these small interconnected arrays of sensors may be used simultaneously. In this embodiment, each small, interconnected array will be connected to one another and used with a single common communication and readout circuit to prevent excessive wiring, lower power consumption, and reduce the complexity of data collection during the course of therapy. In certain embodiments, the gamma photon counter is attached to a wearable structure. In some embodiments, the gamma photon counter is attached to a fabric or an adhesive patch. In some embodiments, the gamma photon counter is attached to clothing such as, but not limited to a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

[0058] In another aspect, a wearable system is provided, the wearable system comprising a plurality of gamma photon counters (e.g., optical fiber-based gamma photon counters or chip-based gamma photon counters), described herein, attached to a wearable structure.

[0059] In certain embodiments, the wearable structure is clothing or adhesive patches.

[0060] In certain embodiments, the plurality of gamma photon counters is arranged on the patient (or subject) either on a piece of clothing (that is relatively fixed in position relative to the patient), harness, or with adhesive stickers, or any other mechanism such that the position of the sensors is relatively fixed in relation to the patient or subject. The first subset of these gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject; and wherein a second subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject.

[0061] In certain embodiments, medical imaging is used to determine the positioning of each gamma photon counter on the clothing relative to all the tumors and organs at risk in the patient. In some embodiments, the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).

[0062] In certain embodiments, the plurality of gamma photon counters is arranged in an array on the clothing.

[0063] In certain embodiments, each gamma photon counter of the plurality is attached to skin of the subject using adhesive patches.

[0064] In certain embodiments, the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

[0065] In another aspect, a computer implemented method for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject is provided, the computer performing steps comprising: a) receiving gamma photon count data from a plurality of gamma photon counters, wherein each gamma photon counter has a known location; b) receiving an image of the subject, wherein the image shows locations of the one or more tumors and the one or more organs at risk in the subject, and locations of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) measuring volumes of the one or more tumors and organs at risk using the image; e) mapping centroid locations of each gamma photon counter on the image; f) performing distributed point source (DPS) modelling to generate a distribution of gamma photon-emitting point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) calculate probabilities for each gammaphoton counter that the gamma photons, counted by the gamma photon counter, were received from a gamma photon emitting point source within the boundaries of a particular tumor or organ at risk based on an assumption that counts per second (CPS) falloff correlates with 1 / (distance between the centroid location of the gamma photon counter and the gamma photon emitting point source)2and CPS values are attenuated by an empirically derived factor Q which accounts for attenuation and scattering of gamma photons in tissue, and ii) estimate probable fractions of counts counted by each gamma photon counter that correspond to a particular tumor or organ at risk; g) estimating total counts for each tumor and organ at risk using a Monte Carlo Markov Chain (MCMC) algorithm based on the gamma photon count data from the plurality of counters and parameter estimates of the probable fractions of counts counted by each gamma photo counter that correspond to a particular tumor or organ at risk from the DPS modelling; h) calculating the total %IA / ml for the one or more tumors and organs at risk in the subject based on said estimating the total counts for each tumor and organ at risk and dividing by the volumes of the one or more tumors and organs at risk measured from the image; and i) displaying the total %IA / mL for the one or more tumors and the one or more organs at risk in the subject.

[0066] In certain embodiments, performing DPS modelling comprises creating a DPS model matrix ( W) denoting the counts per second (CPS) per pCi contributed from each tumor or organ at risk to each gamma photon counter of the plurality, wherein the CPS per pCi are multiplied by an unknown activity in pCi of the total tumor or total organ at risk activity in pCi, wherein values in the DPS model matrix ( W) are estimated based on knowledge of the location of each tumor and each organ at risk from the image and the known locations of each gamma photon counter; and decomposing the DPS model matrix ( W) into a matrix ( / 3) and a vector (or), wherein the matrix (J3) denotes the fraction of each gamma photon counter’s CPS that comes from a certain tumor or organ at risk, wherein the fraction is scaled up by the vector (or), wherein the vector (or) is each gamma photon counter’s CPS per injected pCi of activity.

[0067] In certain embodiments, the vector or is estimated by conducting a DPS titration simulation.

[0068] In certain embodiments, the matrix ( / 3) is initially estimated by i) assuming each tumor and each organ at risk uptakes an equal amount of the radionuclide, wherein the total amount of the radionuclide administered to the subject is known, and ii) assigning the same activity to all of the tumors and organs at risk for said estimating the probable fractions of counts per pCi of activity counted by each counter that correspond to a particular tumor or organ at risk. This estimate is based on taking each point source in the DPS model and estimating the probability of a count per pCi of activity by utilizing the 1 / (distance between the centroid location of the gamma photon counter and the gamma photon emitting point source)2relationship of point sources. When the distance betweenthe detector and the point source is large in tissue, this value is also attenuated by an empirically derived factor Q which accounts for the attenuation and scattering of gamma photons in tissue

[0069] In certain embodiments, factor Q is derived empirically by taking each gamma counter and characterizing its detected counts per second (CPS) at finely swept depths in water away from a 1 mm (2 uL) point source of the radioligand being utilized. This sweep is repeated in air. The factor difference between the two curves at each distance is estimated, and this represents the non-linear factor that scattering and attenuation contributes to each point source. Based on the distance in tissue from each detector to each point source in the DPS model a unique factor Q is assigned to each source.

[0070] In certain embodiments, the computer implemented method further comprises using adaptive Metropolis (AM) optimization, wherein a Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm.

[0071] In certain embodiments, the computer implemented method further comprises iterative optimization techniques including but not limited to gradient descent, least squares minimization, and brute force global minimization.

[0072] In certain embodiments, the computer implemented method further comprises segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid locations of each gamma photon counter are segmented.

[0073] In certain embodiments, the plurality of gamma photon counters comprises on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons, wherein the computer implemented method further comprises calculating incident energies of the incoming gamma photons based on combination and distribution of signals from pixels with known LET responsivity. In some embodiments, the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET

[0074] In certain embodiments, the plurality of detectors is arranged in a vertical stack. In some embodiments, each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material. In some embodiments, each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack. In some embodiments, each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits atime that the incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel. In some embodiments, the computer implemented method further comprises calculating the incident gamma photon angle with respect to the vertical stack by measuring an angle shift (e.g., due to Compton scattering) of the incident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack.

[0075] In certain embodiments, the plurality of detectors is in a planar arrangement in a spatial area, wherein the computer implemented method further comprises determining the energies of the incoming gamma photons in the spatial area.

[0076] In another aspect, a non-transitory computer-readable medium is provided, the non-transitory computer-readable medium comprising program instructions that, when executed by a processor in a computer, causes the processor to perform the method, described herein, for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject.

[0077] In another aspect, a kit comprising the non-transitory computer-readable medium described herein and instructions for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject is provided.

[0078] In another aspect, a system is provided, the system comprising: a) a plurality of gamma photon counters (e.g., optical fiber-based gamma photon counters or chip-based gamma photon counters), described herein, attached to a wearable structure; b) a power source; c) a processor, wherein the processor is programmed to calculate the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject according to a computer implemented method described herein; d) an external data receiving device connected to the processor, wherein the external data receiving device receives the gamma photon count data from the plurality of gamma photon counters and transmits the gamma photon count data to the processor; and e) a display component that displays the %IA / mL for one or more tumors and one or more organs at risk in a subject.

[0079] In certain embodiments, the plurality of gamma photon counters is attached to clothing or adhesive patches.

[0080] In certain embodiments, a first subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each gamma photon counter of the first subset on the clothing is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters isarranged on the clothing such that when the wearable material is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset on the clothing is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

[0081] In certain embodiments, the plurality of gamma photon counters is arranged in an array on the clothing.

[0082] In certain embodiments, each gamma photon counter of the plurality is attached to skin of the subject using the adhesive patches.

[0083] In certain embodiments, the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

[0084] In certain embodiments, a first subset of the plurality of gamma photon counters are attached to the skin of the subject with adhesive patches such that the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each gamma photon counter of the first subset with the adhesive patches is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters are attached to the skin of the subject with adhesive patches such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gammaemitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset with the adhesive patches is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

[0085] In certain embodiments, the power source is an external power source, an internal power source, or a combination thereof. In some embodiments, the external power source is an ultrasound transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radiofrequency (RF) transducer. In some embodiments, the internal power source comprises a battery, a radionuclide, or a photovoltaic system.

[0086] In certain embodiments, the power source is used to provide power to the detector.

[0087] In certain embodiments, the external power source is portable.

[0088] In certain embodiments, the external data receiving device comprises a wireless communication unit. In some embodiments, the wireless communication unit utilizes a wirelesscommunication protocol using an electromagnetic carrier wave (e.g., a radio wave, microwave, or an infrared carrier wave) or ultrasound to receive data from the internal data storage unit.

[0089] In certain embodiments, the processor is provided by a computer or handheld device (e.g., a cell phone or tablet).

[0090] In certain embodiments, the connections for the sensors are done with wiring on the patients body or embedded in their clothing or other supportive apparatus, connecting power, data, clock, and any other necessary inputs and outputs. Each sensor is designed with a unique ID and communication protocol to share a common data line(s) for output, allowing many sensors to be multiplexed together using a small set of sharable connections. In some instances, nodes of FIFO memory are used to buffer information from a subset of sensors and output them when the common data line is free.

[0091] In certain embodiments, the display further displays an image of the tumors and organs at risk obtained by medical imaging of the subject.

[0092] In certain embodiments, the display further displays the centroid locations of each gamma photon counter superimposed on the image.

[0093] In certain embodiments, the display further displays the boundary lines surrounding each tumor and organ at risk superimposed on the image.

[0094] In certain embodiments, the display further displays the distribution of gamma photonemitting point sources according to the distributed point source (DPS) modelling superimposed on the image.

[0095] In certain embodiments, the display further displays labels with information regarding the tumors and organs at risk superimposed on the image.

[0096] In another aspect, a method of using a system, described herein, for measuring tumor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide in a subject is provided, the method comprising: performing medical imaging to identify locations of one or more tumors and one or more organs at risk in the subject; positioning a first subset of the plurality of gamma photon counters on the wearable structure such that the first subset of gamma photon counters can monitor the uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by the one or more tumors in the subject; positioning a second subset of the plurality of gamma photon counters on the wearable structure such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by the one or more organs at risk in the subject; and calculating the total percent injected activity per milliliter of tissue (%IA / mL) for the one or more tumors and the one or more organs at risk in the subject according to the computer implemented method.

[0097] In certain embodiments, the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).

[0098] In certain embodiments, the method further comprises placing fiducial stickers on skin of the subject at planned locations for said positioning of the plurality of gamma photon counters.

[0099] In certain embodiments, the plurality of gamma photon counters is attached to the wearable structure, wherein the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters on the wearable structure. In some embodiments, the wearable structure is clothing or adhesive patches.

[0100] In certain embodiments, the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters using a plurality of adhesive patches to adhere the plurality of gamma photon counters to the skin of the subject.

[0101] In certain embodiments, the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs. In some embodiments, the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

[0102] In certain embodiments, the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging. In some embodiments, the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL

[0103] In certain embodiments, the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide. In some embodiments, the alpha-emitting radionuclide is 149Tb,223Ra, or225Ac. In some embodiments, the beta-emitting radionuclide is32P,90Y,1311,89Sr, 152Tb,153Sm,161Tb,166Ho, or177Lu.

[0104] In certain embodiments, the radionuclide is conjugated to a small molecule, a peptide, or an antibody.

[0105] In certain embodiments, the method is performed during or after administering targeted radionuclide therapy to the subject.

[0106] In certain embodiments, the radiopharmaceutical therapy comprises administering a radioactive drug, a radioimmunotherapeutic agent, or a radiopeptide to the subject.

[0107] In certain embodiments, the targeted radionuclide therapy comprises administering177Lu-PSMA-617 or225Ac-PSMA-617 to the subject for treatment of prostate cancer.BRIEF DESCRIPTION OF THE DRAWINGS

[0108] FIGS. 1A-1 D. Sparse Gamma Sensing Network and %IA / g Reconstruction in Real-Time. (FIG. 4A) a pre-therapeutic PET / CT scan is taken to identify which tumors and OAR will be responsive to177Lu-PSMA-617 therapy based on SUV. CT fiducial stickers are placed on the skin to mark the locations the probes will be placed. (FIG. 4B) Frequent y recordings using a sparse probe sensing network are taken after administration of RPT. (FIG. 4C) Structure of y probe optical sensing front end. (FIG. 4D) Raw uncollimated y recordings are transformed into %IA / mL data for both tumors and OAR using our novel reconstruction algorithm. This information can be used to evaluate if sufficient dose is administered to tumors and ensure that toxicity to OARs has not occurred.

[0109] FIGS. 2A-2C. Conceptual Workflow of Reconstruction Algorithm. (FIG. 2A, top) Sparse y sensing network setup and circuitry (FIG. 2A, bottom) Decomposition of recorded y-CPS distribution into the unknown total tumor and OAR activity multiplied by matrix W. Matrix W can be further decomposed into matrix |3 and vector a. (FIG. 2B, top) Matrix p can be derived using a DPS model from an annotated CT scan. (FIG. 2B, bottom) Vector a can be derived a comparison between an experimental and simulated titration experiment (FIG. 2C) MCMC is used to create probabilistic estimates of the tumor / OAR activities that, when transformed by matrix W, give the most similar y- CPS distribution to what is measured experimentally.

[0110] FIGS. 3A-3F. Phantom Experimental Setup and Reconstruction. (FIG. 3A) Experimental setup of phantom experiment (FIG. 3B) Sensor and vial positions used (FIG. 3C) Converged DPS model of phantom experiment (FIG. 3D) Convergence plot of reconstructed activity as more sensors are added to phantom (FIG. 3E) Converged MCMC y-CPS compared to the experimental y-CPS. (FIG. 3F) Probabilistic distributions of activity guess for the four vials with N=4, N=10, and N=16 sensors added to the phantom.

[0111] FIGS. 4A-4B Experimental Workflow of Gamma Sensing Network and Reconstruction Workflow Applied to In Vivo Models. (FIG. 4A) Overall experimental workflow including SQ-injection of human prostate cancer cell lines to create 4 different mouse models, placement of mouse in custom scaffold, injection of the radionuclide, measurement setup, SPECT / CT setup, and reconstruction, (FIG. 4B) Experimental y-CPS measurements of mouse, placement of scaffold into SPECT / CT, and SPECT / CT with visible probe locations.

[0112] FIGS. 5A-5D. Evolution of DPS Model Across Time Points. (FIG. 5A) SPECT / CT scan of the same mouse (M4) at 0 hour, 6 hours, 12 hours, 24 hours, and 48 hours post-injection. The %IA / mL colorbar scale is from 0 to 6%, (FIG. 5B) Annotated CT scan for M4’s 6 hours post-injection time point. Tumors, kidneys, and bladder are annotated. Body and probe annotations not shown forclarity. (FIG. 5C) Convergence of DPS model from equal activity in each segmented volume to the true prediction. (FIG. 5D) The converged DPS model solution for M4 at 0 hour, 6 hours, 12 hours, 24 hours, and 48 hours post-injection. The figures match qualitatively well to SPECT / CT.

[0113] FIGS. 6A-6I. %IA / g Reconstruction of all Tumors, Kidneys, and Bladder Across Timepoints. Radiopharmaceutical uptake by (FIG. 6A) left-flank PC3-pip tumor of M1 , (FIG. 6B) right-flank and left-flank PC3-pip tumors of M2, (FIG. 6C) left-flank and right-back PC3-pip tumors of M3, (FIG. 6D) right-flank, left-flank, and right-back PC3-pip tumors of M4, (FIG. 6E) PC3-flu tumors of M1 and M3, (FIG. 6F) kidneys of all four mice, and (FIG. 6G) bladders of all four mice. (FIG. 6H) Linearity and 1 to 1 mapping of reconstructed %IA / mL and %IA / mL from SPECT / CT. (FIG. 61) Linearity and 1 to 1 mapping of reconstructed total tumor activity and total tumor activity from SPECT / CT.

[0114] FIGS. 7A-7C. Linearity and Dynamic Range of Custom Gamma Counter with Activity. (FIG. 7A) Experimental setup to measure the linearity and dynamic range of the custom gamma counter, (FIG. 7B) Linearity of the developed counter with177Lu activity from 0.5 pCi to 3 mCi, (FIG. 7C) Absolute error between linear fit and recorded y-CPS.

[0115] FIGS. 8A-8B. Accounting for Counter-to-Counter Variations in Sensitivity. (FIG. 8A) Experimental setup and scaffold to ensure fair comparison of sensitivity with177Lu activity between all the sensing probes, (FIG. 8B) Titration results and sensitivity plots for each of the 8 sensors used in the in vivo experiments.

[0116] FIGS. 9A-9D. Simulated Titration for Deriving Vector a. (FIG. 9A) Titration y-sensitivity experimental setup, (FIG. 9B) CT scan with segmented VOI to create a DPS model with, (FIG. 9C) DPS titration model, (FIG. 9D) Sensitivity plot of DPS model titration for comparison to the actual experimental sensitivity to derive vector a.

[0117] FIGS. 10A-10C. Tradeoff of CPS with Distance and DPS Model Accuracy of Non-Linearity. (FIG. 10A) Experimental setup of distance sweep, (FIG. 10B) Comparison between experimental tradeoff between y-CPS and distance, and that derived from the DPS model, (FIG. 10C) Relative error in y-CPS between the DPS model and the experimental measurement.

[0118] FIGS. 11A-11 D. Ex-Vivo Tumor Activity Reconstruction. (FIG. 11A) Experimental setup of ex-vivo tumor measurement with custom y-counter, (FIG. 11 B) SPECT / CT of ex-vivo tumor with annotated CT, (FIG. 1 C) DPS model of experiment, (FIG. 11 D) DPS model accuracy compared to ex vivo gamma counting and SPECT / CT.

[0119] FIGS. 12A-12C. Accuracy in Modelling Matrix W using a DPS Model. (FIG. 12A) Vial configurations used to derive the mapping matrix between activity and y-CPS, W. Vial 1 is moved to all four positions of interest and the counts received from each gamma counter from a specifictumor / OAR can be derived experimentally. (FIG. 12B) Experimentally derived weight matrix. (FIG. 12C) Weight matrix derived from the DPS model.

[0120] FIGS. 13A-13E. Real-Time Relaying of y-CPS from Each Component of Sparse Gamma Counting Network. Real-time y-CPS from all 8 counters across the 10 minute recording period at (FIG. 13A) 0 hour, (FIG. 13B) 6 hours, (FIG. 13C) 12 hours, (FIG. 13D) 24 hours, and (FIG. 13E) 48 hours post-injection. The placement of each probe is also shown.

[0121] FIGS. 14A-14D. Conceptual Workflow and Optical Fiber Gamma Probe Design. (FIG. 14A) a custom two tumor in vivo model derived from two cancer cell lines is administered an RPT being studied and (FIG. 14B) measured using the proposed y counting system at very fine intervals with short acquisition times. (FIG. 14C) At the last time point, a single SPECT / CT or ex vivo y counting is done to convert the gamma counts to %IA / mL. (FIG. 14D, left) An optical fiber with compacted Y2O3- Eu doped phosphor and optically isolating tape is interfaced to readout circuitry (FIG. 14D, right) including single photon detection of scintillated y, voltage level-shifting, digital counters, and data readout.

[0122] FIGS. 15A-15F. Gamma Photon Probe Characterization and Optimization. (FIG. 15A)177Lu titration phantom experiment setup. (FIG. 15B)177Lu titration real time transient results of y CPS with activities ranging from 0.5pCi / mL to 0.5mCi / mL. (FIG. 15C) Poisson fit of recorded y CPS distribution, as count variation can be attributed to the Poisson nature of radioactive decay. (FIG. 15D) Average CPS from the proposed system is highly linear with activity, for activities ranging from 0.1 pCi to 0.5mCi. (FIG. 15E) The absolute error in CPS for the activity range of interest (FIG. 15F) Two handheld probes were used in this study and sensitivity calibration was performed using the setup in (c) as well.

[0123] FIGS. 16A-16E. In Vivo Experimental Workflow. (FIG. 16A) SQ injection of PC3-pip and PC3- flu cells into flanks of mice M1 -M16. (FIG. 16B) After 14 days the two tumors grew to be palpable, and 600pCi of177Lu-PSMA-617 was administered to mice M1-M16 via tail-vein injection. (FIG. 16C) One y probe is placed behind each tumor in mice M1 -M16, while under anesthesia, for 2 hours. M1 - M15 are monitored at a single time point post injection (p.i.), but M16 is chronically monitored over five timepoints p.i.. M16 also has two additional probes placed vertically above the left and right kidneys to track kidney (OAR) uptake and clearance. (FIG. 16D) Immediately after their respective 2-hour measurement, mouse M1 -M15 are euthanized and a SPECT / CT is taken. M16 is not euthanized and is chronically monitored, with SPECT / CTs taken after each y probe acquisition. (FIG. 16E) The tumors of mice M1 -M15 are dissected, and a small sample of the tumor is taken to perform ex vivo dosimetry.

[0124] FIGS. 17A-17E. Representative SPECT Scans and Gamma Probe Counts of PC3-pip and PC3-flu Tumors of M1-M15. (FIG. 17A) SPECT scans show progression of177Lu-PSMA-617 activity accumulation in PC3-pip and PC3-flue tumors at five time points taken at the end of every custom gamma probe recording. ((FIG. 17B) Real-time y probe recordings over the two hour recording period before the respective SPECT scan was taken. ((FIG. 17C) Average slope of transient waveforms per hour from 6-50 hours post injection. ((FIG. 17D) Derived chronic biodistribution curve from proposed system over 50 hours post injection. ((FIG. 17E) Therapeutic ratio between the PC3- pip tumor counts to the PC3-flu tumor counts over 50 hours post injection.

[0125] FIGS. 18A-18F. Evaluation of Chronic Monitoring Accuracy with SPECT / CT and Biodistribution for M1 -M15. Chronic biodistribution curve from (FIG. 18A) SPECT / CT and (FIG. 18B) ex vivo y-counting. (FIG. 18C) Comparison of CPS with the tumor activity / tumor volume extracted from SPECT. (FIG. 18D) %IA / mL error histogram between the system and SPECT / CT. (FIG. 18E) Comparison of CPS with the tumor activity normalized to the tumor volume extracted from ex vivo y- counting. (FIG. 18F) %IA / mL error histogram between the system and ex vivo y-counting.

[0126] FIGS. 19A-19G. Monitoring of a Single Mouse M16 Over Multiple Time Points. Biodistribution curve from (FIG. 19A) the proposed system and (FIG. 19B) SPECT / CT for both tumors and kidneys. (FIG. 19C) Comparison of CPS with the activity from SPECT. (FIG. 19D) %IA / mL error histogram between the system and SPECT / CT. Convergence in (FIG. 19E) average %IA / mL error, (FIG. 19F) R2, (FIG. 19G) and linear fit slope with measurement time before SPECT / CT.

[0127] FIG. 20. (left) IVIS image generated (with an 180s integration time) of133Ba point source planted on disk with 3D printed fiber cap with optimized 500pm thick Y2O3-EU doped phosphor. This was repeated for 8 different thicknesses, (right) Normalized total counts from IVIS versus scintillator thickness over a 180s integration time.

[0128] FIGS. 21A-21 B. Dark count of each APD before a full titration experiment with 30 minute exposure per vial vs. dark count after the full titration experiment for (FIG. 21 A) probe 1 and (FIG. 21 B) probe 2 used for the in vivo experiments.

[0129] FIGS. 22A-22B. Dark count of each APD in a light-sealed box vs. in a well-lit room for (FIG. 22A) probe 1 and (FIG. 22B) probe 2 used for the in vivo experiments.

[0130] FIGS. 23A-23D. (FIG. 23A) Experimental setup to test the developed system’s transfer function with distance and to test if the lead thickness was sufficient to prevent cross-contamination of recorded gamma CPS. A 365 pCi177Lu Vial was swept from 0 to 3 cm away from the sensor face as well as 0 to 6 cm laterally. (FIG. 23B) Transfer function between recorded gamma CPS and distance away from the sensor face. (FIG. 23C) Probability of detection for the weighted averageenergy gamma photon from177Lu for various thickness of lead. (FIG. 23D) Measurement of lateral distance transfer function with and without 1 mm thick lead tape.

[0131] FIGS. 24A-24B. Measured CPS from outside of a225Ac 2x dilution with the proposed system. Each vial was measured for 30 minutes. (FIG. 24A) Average CPS from the proposed system is highly linear with225Ac activity, for activities ranging from 7 nCi to 500 nCi in 1 ml. (FIG. 24B) The absolute error in CPS for the activity range of interest.

[0132] FIG. 25. Overview Wearable, scalable network of gamma counters are needed to optimize therapeutic ratio.

[0133] FIG. 26. Custom Single Gamma Photon Counter Setup. Avalanche photodiodes coupled to scintillator through optical fiber. Two of the counters are measuring the177Lu and ^Ac activity that is diluted in 1 mL of saline.

[0134] FIG. 27. Measured counts of177Lu Titration over therapeutic range.

[0135] FIG. 28. Measured counts of225Ac Titration over therapeutic range.

[0136] FIGS. 29. Phantom Vial Experimental Setup, (a) 8 gamma probe sensors slotted into the sides of a custom water tank, (b) Removable lid to hold vials containing varying activities of Lu-177, (c) Water tank with 5 slots per side for gamma sensor placement.

[0137] FIGS. 30A-30D. Distributed Point Source Modelling (FIG. 30A) 3D volumes of 4 vials of177Lu are represented as distributed point sources in silico, in relation to 8 gamma counting sensors surrounding them. (FIG. 30B) Top view: Vials and corresponding predicted signals on sparse gamma detectors. In Silico, the activity in each vial is changed, the simulation re-run, and a new set of detector values is obtained. This process is repeated to build a library of sensor network values that correspond to specific activity arrangements. (FIGS. 30C, 30D) Accuracy of MCMC Activity Map Reconstruction Algorithm Using Sparse Gamma Counters The simulated data in (FIG. 30A) is measured using a phantom (shown in FIG. 29). Using recordings of 14 uncollimated gamma counters placed around 4 vials filled with varying177Lu activities. Known (true) activities are shown by the horizontal lines in (FIG. 30D). (FIG. 30C) The MCMC algorithm predicts the four vial activities such that the average gamma counts per second predicted by the model matches the actual recording. (FIG. 30D) We incrementally add sensors until sufficient information is obtained such that the algorithm converges to the correct activity specified by the dotted horizontal lines. This provides proof of concept that a sparse set of sensitive gamma counters can correctly identify the activity in a priori known locations.

[0138] FIG. 31 . Prototype of SENTRI chip sensor showing central pixel array, on chip memory (SRAM control), digital clock (FLL) and digital control circuits (Main digital). The chip is custom designed in the Anwar lab and measures < 1 mm2and is fabricated in a 65-nanometer process through TSMC (Taiwan Semiconductor Manufacturing Company).

[0139] FIG. 32.111ln Titration with SENTRI Chip Compared to Gamma Probe recorded counts / min using chip-based solution over large specific activity range and recorded counts / sec using custom developed gamma counter.

[0140] FIGS. 33A-33B. Resolving Energy of Incoming Gamma Photons with Sensor Stack (FIG. 33A, left) Sensor stack is placed on the skin of the patient at various locations and detects incoming gamma photons (FIG. 33A, right) View of the sensor stack exposed to a flux of different gamma photon energies. The sensor stack discerns the incoming energy based on tunable LET sensitivity of each chip and / or attenuating materials between each chip (FIG. 33B) The true gamma photon energy distribution versus the energy distribution resolved from the counts detected by each sensor in the stack.

[0141] FIG. 34. System Architecture and Pixel Timing Diagram.

[0142] FIG. 35. Pixel Architecture and Photon Energy Binning Scheme.

[0143] FIGS. 36A-36E. SRT Experimental Results. (FIG. 36A) transient counts; (FIG. 36B) linearity with cumulative dose; (FIG. 36C) binning of beam energies; (FIG. 36D) measured dose with depth in tissue; (FIG. 36E) error in ASIC dose vs. state-of-the-art.

[0144] FIG. 37. ASIC Summary: die micrograph.DETAILED DESCRIPTION OF THE INVENTION

[0145] Devices, systems, software, and methods are provided for calculating the total percent injected activity per milliliter of tissue (%IA / mL) delivered to tumors and OARs in a subject administered radiopharmaceutical therapy. The methods utilize optical fiber-based or chip-based gamma counters capable of monitoring real-time uptake of a radiopharmaceutical by a tumor or OAR over the course of treatment. Medical imaging is used to identify the locations of tumors and OARs in the subject for positioning counters on a wearable structure or on the skin of the subject to monitor the uptake of the radiopharmaceutical. In addition, an algorithm is provided that automatically calculates %IA / mL for tumors and OARs from the gamma count rate recorded by a sparse set of gamma counters along with a priori knowledge of tumor, OAR, and gamma counter locations. The systems and methods, disclosed herein, can be used for continuous, real-time dosimetry of multiple tumors and OARs non-invasively.

[0146] Before the present devices, systems, software, and methods are described, it is to be understood that this invention is not limited to the particular devices, systems, software, and methods described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the appended claims.

[0147] Where a range of values is provided, it is understood that each intervening value, to the tenth of the unit of the lower limit unless the context clearly dictates otherwise, between the upper and lower limits of that range is also specifically disclosed. Each smaller range between any stated value or intervening value in a stated range and any other stated or intervening value in that stated range is encompassed within the invention. The upper and lower limits of these smaller ranges may independently be included or excluded in the range, and each range where either, neither or both limits are included in the smaller ranges is also encompassed within the invention, subject to any specifically excluded limit in the stated range. Where the stated range includes one or both of the limits, ranges excluding either or both of those included limits are also included in the invention.

[0148] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, some potential and preferred methods and materials are now described. All publications mentioned herein are incorporated herein by reference to disclose and describe the methods and / or materials in connection with which the publications are cited. It is understood that the present disclosure supersedes any disclosure of an incorporated publication to the extent there is a contradiction.

[0149] As will be apparent to those of skill in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features which may be readily separated from or combined with the features of any of the other several embodiments without departing from the scope or spirit of the present invention. Any recited method can be carried out in the order of events recited or in any other order which is logically possible.

[0150] It must be noted that as used herein and in the appended claims, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a photon" includes a plurality of such photons and reference to "the radionuclide" includes reference to one or more radionuclides and equivalents thereof, such as radioactive nuclides, radioisotopes, or radioactive isotopes, known to those skilled in the art, and so forth.

[0151] The publications discussed herein are provided solely for their disclosure prior to the filing date of the present application. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such publication by virtue of prior invention. Further, the dates of publication provided may be different from the actual publication dates which may need to be independently confirmed.Definitions

[0152] The term "about," particularly in reference to a given quantity, is meant to encompass deviations of plus or minus five percent.

[0153] The terms "tumor," "cancer" and "neoplasia" are used interchangeably and refer to a cell or population of cells whose growth, proliferation or survival is greater than growth, proliferation or survival of a normal counterpart cell, e.g., a cell proliferative, hyperproliferative or differentiative disorder. Typically, the growth is uncontrolled. The term "malignancy" refers to invasion of nearby tissue. The term "metastasis" or a secondary, recurring or recurrent tumor, cancer or neoplasia refers to spread or dissemination of a tumor, cancer or neoplasia to other sites, locations or regions within the subject, in which the sites, locations or regions are distinct from the primary tumor or cancer. Neoplasia, tumors, and cancers include benign, malignant, metastatic and non-metastatic types, and include any stage (I, II, III, IV or V) or grade (G1 , G2, G3, etc.) of neoplasia, tumor, or cancer, or a neoplasia, tumor, cancer or metastasis that is progressing, worsening, stabilized or in remission. In particular, the terms "tumor," "cancer" and "neoplasia" include carcinomas, such as squamous cell carcinoma, adenocarcinoma, adenosquamous carcinoma, anaplastic carcinoma, large cell carcinoma, and small cell carcinoma, and include cancers such as, but are not limited to, pancreatic cancer, lung cancer (non-small cell lung cancer, small cell lung cancer), gastric cancer, ovarian cancer, endometrial cancer, colorectal cancer, oral cancer, skin cancer, cholangiocarcinoma, head and neck cancer, breast cancer, ovarian cancer, melanoma, peripheral neuroma, glioblastoma, adrenocortical carcinoma, AIDS-related lymphoma, anal cancer, bladder cancer, meningioma, glioma, astrocytoma, cervical cancer, chronic myeloproliferative disorders, colon cancer, endometrial cancer, ependymoma, esophageal cancer, Ewing's sarcoma, extracranial germ cell tumors, extrahepatic bile duct cancer, gallbladder cancer, gastrointestinal carcinoid tumors, gestational trophoblastic tumors, hairy cell leukemia, Hodgkin lymphoma, non-Hodgkin lymphoma, hypopharyngeal cancer, islet cell carcinoma, Kaposi sarcoma, laryngeal cancer, leukemia, lip cancer, oral cavity cancer, liver cancer, malignant mesothelioma, medulloblastoma, Merkel cell carcinoma, metastatic squamous neck cell carcinoma, multiple myeloma and other plasma cell neoplasms, mycosis fungoides and the Sezary syndrome, myelodysplastic syndromes, nasopharyngeal cancer, neuroblastoma, oropharyngeal cancer, bone cancers, including osteosarcoma and malignant fibrous histiocytoma of bone, paranasal sinus cancer, parathyroid cancer, penile cancer, pheochromocytoma, pituitary tumors, prostate cancer, rectal cancer, renal cell cancer, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, small intestine cancer, soft tissue sarcoma, supratentorial primitive neuroectodermal tumors, pineoblastoma, testicular cancer, thymoma, thymic carcinoma, thyroid cancer, transitional cell cancer of the renal pelvis and ureter,urethral cancer, uterine sarcoma, vaginal cancer, vulvar cancer, and Wilm's tumor and other childhood kidney tumors.

[0154] The terms “radionuclide”, “radioisotope”, “radioactive nuclide”, and “radioactive isotope” are used interchangeably and refer to an atom with an unstable nucleus that emits ionizing radiation or particles. Radionuclides may emit gamma radiation, alpha particles, beta particles, or positrons. In particular, the terms include positron-emitting radionuclides suitable for positron emission tomography (PET) imaging such as, but not limited to,64Cu,89Zr,68Ga,177Lu,82Rb,86Y,11C,13N,15O, and18F; and gamma-emitting radionuclides suitable for single photon emission computed tomography (SPECT) imaging or gamma cameras (planar imaging) such as, but not limited to,46Sc, S7Ga,99mTc,111In,123l,131l,155Tb, and177Lu. The terms may also include alpha-emitting radionuclides such as, but not limited to,149Tb,223Ra, or225Ac and beta-emitting radionuclides such as, but not limited to,32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, and177Lu, which are suitable for radionuclide therapy. In addition, the terms include radionuclides used in theranostic agents, which can be used for both therapy and imaging. Such theranostic agents may include a radionuclide that can be used for both imaging and radiotherapy (e.g., iodine-131 and lutetium-177 are gamma and beta emitters, which can be used for both imaging and therapy) or a theranostic agent comprising both a diagnostic radionuclide and a therapeutic radionuclide. Alternatively, a theranostic agent may comprise a radionuclide linked to a non-radioactive therapeutic agent (e.g., radiopharmaceuticals, radioimmunotherapeutic agents, and radiopeptides).

[0155] The terms “individual”, “subject”, “recipient”, and “patient” are used interchangeably herein and refer to any mammalian subject for whom diagnosis, treatment, or therapy is desired, particularly humans. "Mammal" for purposes of treatment refers to any animal classified as a mammal, including human and non-human mammals such as non-human primates, including chimpanzees and other apes and monkey species; laboratory animals such as mice, rats, rabbits, hamsters, guinea pigs, and chinchillas; domestic animals such as dogs and cats; and farm animals such as sheep, goats, pigs, horses and cows.

[0156] The term “user” as used herein refers to a person that interacts with a device and / system disclosed herein for performing one or more steps of the presently disclosed methods. The user may be the patient receiving treatment. The user may be a health care practitioner, such as, the patient’s physician.

[0157] A "therapeutically effective dose" or “therapeutic dose” is an amount sufficient to effect desired clinical results (i.e., achieve therapeutic efficacy). A therapeutically effective dose can be administered in one or more administrations.

[0158] "Pharmaceutically acceptable excipient or carrier" refers to an excipient that may optionally be included in the compositions of the invention and that causes no significant adverse toxicological effects to the patient.

[0159] "Pharmaceutically acceptable salt" includes, but is not limited to, amino acid salts, salts prepared with inorganic acids, such as chloride, sulfate, phosphate, diphosphate, bromide, and nitrate salts, or salts prepared from the corresponding inorganic acid form of any of the preceding, e.g., hydrochloride, etc., or salts prepared with an organic acid, such as malate, maleate, fumarate, tartrate, succinate, ethylsuccinate, citrate, acetate, lactate, methanesulfonate, benzoate, ascorbate, para-toluenesulfonate, palmoate, salicylate and stearate, as well as estolate, gluceptate and lactobionate salts. Similarly salts containing pharmaceutically acceptable cations include, but are not limited to, sodium, potassium, calcium, aluminum, lithium, and ammonium (including substituted ammonium).

[0160] “Isolated” refers to an entity of interest that is in an environment different from that in which it may naturally occur. “Isolated” is meant to include entities that are within samples that are substantially enriched for the entity of interest and / or in which the entity of interest is partially or substantially purified.

[0161] The term "conjugated" refers to the joining by covalent or noncovalent means of two compounds or agents (e.g., binding agent specific for a tumor marker conjugated to a radionuclide).

[0162] A "ligand" or "binding agent" is any molecule that can be used to target a radionuclide to a cell, tissue, or other target. In certain embodiments, the ligand is a molecule that selectively binds to a target analyte of interest (e.g., cancer antigen) with high binding affinity. By high binding affinity is meant a binding affinity of at least about 104M, usually at least about 106M or higher, e.g., 109M or higher. The ligand may be any of a variety of different types of molecules, as long as it exhibits the requisite binding affinity for the target analyte when conjugated to a radionuclide. In certain embodiments, the ligand has medium or even low affinity for its target analyte, e.g., less than about 10-4M. As such, the ligand may be a small molecule or large molecule ligand. By small molecule ligand is meant a ligand having a size of less than 10,000 daltons, usually ranging in size from about 50 to about 5,000 daltons, and more usually from about 100 to about 1000 daltons in molecular weight. By large molecule is meant a ligand having a size of more than 10,000 daltons in molecular weight.

[0163] A small molecule ligand may be any molecule, as well as binding portion or fragment thereof, that is capable of binding with the requisite affinity to the target analyte of interest (e.g., cellular marker). Generally, the small molecule is a small organic molecule that is capable of binding to the target analyte of interest. The small molecule will include one or more functional groups necessaryfor structural interaction with the target analyte, e.g., groups necessary for hydrophobic, hydrophilic, electrostatic or even covalent interactions. Where the target analyte is a protein, the drug moiety will include functional groups necessary for structural interaction with proteins, such as hydrogen bonding, hydrophobic-hydrophobic interactions, electrostatic interactions, etc., and will typically include at least an amine, amide, sulfhydryl, carbonyl, hydroxyl or carboxyl group, preferably at least two of the functional chemical groups. The small molecule will also comprise a region that may be modified and / or participate in conjugation to a radionuclide, without substantially adversely affecting the small molecule's ability to bind to its target analyte.

[0164] Small molecule ligands may comprise cyclical carbon or heterocyclic structures and / or aromatic or polyaromatic structures substituted with one or more of the above functional groups. Small molecule ligands may also include organic compounds comprising alkyl groups (including alkanes, alkenes, alkynes and heteroalkyl), aryl groups (including arenes and heteroaryl), alcohols, ethers, amines, aldehydes, ketones, acids, esters, amides, cyclic compounds, heterocyclic compounds (including purines, pyrimidines, benzodiazepins, beta-lactams, tetracylines, cephalosporins, and carbohydrates), steroids (including estrogens, androgens, cortisone, ecodysone, etc.), alkaloids (including ergots, vinca, curare, pyrollizdine, and mitomycines), organometallic compounds, hetero-atom bearing compounds, amino acids, and nucleosides. Small molecules may include structures found among biomolecules, including peptides, carbohydrates, fatty acids, vitamins, steroids, purines, pyrimidines, derivatives, structural analogs or combinations thereof.

[0165] The small molecule may be derived from a naturally occurring or synthetic compound that may be obtained from a wide variety of sources, including libraries of synthetic or natural compounds. For example, numerous means are available for random and directed synthesis of a wide variety of organic compounds and biomolecules, including the preparation of randomized oligonucleotides and oligopeptides. Alternatively, libraries of natural compounds in the form of bacterial, fungal, plant and animal extracts are available or readily produced. Additionally, natural or synthetically produced libraries and compounds are readily modified through conventional chemical, physical and biochemical means, and may be used to produce combinatorial libraries. Known small molecules may be subjected to directed or random chemical modifications, such as acylation, alkylation, esterification, amidification, etc. to produce structural analogs.

[0166] As such, the small molecule may be obtained from a library of naturally occurring or synthetic molecules, including a library of compounds produced through combinatorial means, i.e., a compound diversity combinatorial library. When obtained from such libraries, the small molecule employed will have demonstrated some desirable affinity for the protein target in a convenientbinding affinity assay. Combinatorial libraries, as well as methods for the production and screening, are known in the art and described in: U.S. Pat. Nos. 5,741 ,713; 5,734,018; 5,731 ,423; 5,721 ,099; 5,708,153; 5,698,673; 5,688,997; 5,688,696; 5,684,711 ; 5,641 ,862; 5,639,603; 5,593,853;5,574,656; 5,571 ,698; 5,565,324; 5,549,974; 5,545,568; 5,541 ,061 ; 5,525,735; 5,463,564;5,440,016; 5,438,1 19; 5,223,409, the disclosures of which are herein incorporated by reference.

[0167] Small molecule ligands may also include known drugs that selectively bind to receptors on cells, including, without limitation, growth factor receptors, receptor tyrosine kinases, receptor protein serine / threonine kinases, G-protein coupled receptors, cytokine receptors, lectin receptors, and folate receptors. For example, anti-cancer drugs that bind to such cellular receptors may be used as ligands to target radionuclides to cancer cells. Exemplary drugs that may be used as ligands to target cancer cells include, without limitation, Acitinib, Afatinib, Axitinib, Erlotinib, Cabozantinib, Crizotinib, Gefitinib, Imatinib, Ibrutinib, Lapatinib, Neovastat, Nilotinib, Pazopanib, Perifosine, Ponatinib, Regorafenib, Sorafenib, Sunitinib, Trametinib, and Vandetenib.

[0168] As pointed out, the ligand can also be a large molecule. Of particular interest as large molecule ligands are antibodies, as well as binding fragments and mimetics thereof. Also suitable for use as binding agents are peptoids and aptamers. The ligand or binding agent may include a domain or moiety that can be covalently attached to a radionuclide without substantially abolishing the binding affinity for its target analyte (e.g., cellular marker).

[0169] The term "antibody" encompasses monoclonal antibodies as well as hybrid antibodies, altered antibodies, chimeric antibodies, and humanized antibodies. The term antibody includes: hybrid (chimeric) antibody molecules (see, for example, Winter et al. (1991 ) Nature 349:293-299; and U.S. Pat. No. 4,816,567); F(ab')2 and F(ab) fragments; Fvmolecules (noncovalent heterodimers, see, for example, Inbar et al. (1972) Proc Natl Acad Sci USA 69:2659-2662; and Ehrlich et al. (1980) Biochem 19:4091 -4096); single-chain Fv molecules (scFv) (see, e.g., Huston et al. (1988) Proc Natl Acad Sci USA 85:5879-5883); nanobodies or single-domain antibodies (sdAb) (see, e.g., Wang et al. (2016) Int J Nanomedicine 1 1 :3287-3303, Vincke et al. (2012) Methods Mol Biol 91 1 :15-26; dimeric and trimeric antibody fragment constructs; minibodies (see, e.g., Pack et al. (1992) Biochem 31 :1579-1584; Cumber et al. (1992) J Immunology 14913:120-126); diabodies, tetrabodies, affibodies, camelid antibodies, humanized antibody molecules (see, e.g., Riechmann et al. (1988) Nature 332:323-327; Verhoeyan et al. (1988) Science 239:1534-1536; and U.K. Patent Publication No. GB 2,276,169, published 21 Sep. 1994); and, any functional fragments obtained from such molecules, wherein such fragments retain specific-binding properties of the parent antibody molecule.

[0170] "Fv" is an antibody fragment which contains an antigen-recognition and -binding site. This region consists of a dimer of one heavy- and one light-chain variable domain in tight, non-covalent association. It is in this configuration that the three CDRs of each variable domain interact to define an antigen-binding site on the surface of the VH-VL dimer. Collectively, the six CDRs confer antigenbinding specificity to the antibody. However, even a single variable domain (or half of an Fv comprising only three CDRs specific for an antigen) has the ability to recognize and bind antigen, although often at a lower affinity than the entire binding site.

[0171] "Single-chain Fv" or "scFv" antibody fragments comprise the VHand VLdomains of an antibody, wherein these domains are present in a single polypeptide chain. Generally, the Fv polypeptide further comprises a polypeptide linker between the VH and VL domains which enables the scFv to form the desired structure for antigen binding. For a review of scFv see, for example, Pluckthun, A. in The Pharmacology of Monoclonal Antibodies, vol. 113, Rosenburg and Moore eds., Springer- Verlag, New York, pp. 269-315 (1994).

[0172] The term "diabodies" refers to small antibody fragments with two antigen-binding sites, which fragments comprise a heavy-chain variable domain (VH) connected to a light-chain variable domain (VL) on the same polypeptide chain (VH-VL). By using a linker that is too short to allow pairing between the two domains on the same chain, the domains are forced to pair with the complementary domains of another chain and create two antigen-binding sites. Diabodies are described more fully in, for example, EP 404,097; WO 93 / 11161 ; and Holliger et al., (1993) Proc. Natl. Acad. Sci. USA, 90: 6444-6448.

[0173] The term "affibody molecule" refers to a molecule that consists of three alpha helices with 58 amino acids and has a molar mass of about 6 kDa. A monoclonal antibody, for comparison, is 150 kDa, and a single-domain antibody, the smallest type of antigen-binding antibody fragment, 12-15 kDa. See, for exemplary details of affibody structures and uses, Orlova, A; Magnusson, M; Eriksson, T L; Nilsson, M; Larsson, B; Hoiden-Guthenberg, I; Widstrom, C; Carlsson, J et al. (2006). "Tumor imaging using a picomolar affinity HER2 binding affibody molecule", Cancer Res. 66 (8): 4339-48. Exemplary Affibody. Molecules are commercially available from Abeam Corp. Cambridge Mass.

[0174] The phrase "specifically (or selectively) binds" with reference to binding of an antibody or other binding agent to an antigen or analyte (e.g., cellular marker such as a tumor-marker) refers to a binding reaction that is determinative of the presence of the antigen or analyte in a heterogeneous population of proteins and other biologies. Thus, under designated assay conditions, the specified antibodies or other binding agents bind to a particular antigen or analyte at at least two times the background and do not substantially bind in a significant amount to other molecules present in the sample. Specific binding to an antigen or analyte under such conditions may require an antibody orother binding agent that is selected for its specificity for a particular antigen or analyte. For example, antibodies raised to an antigen from specific species such as rat, mouse, or human can be selected to obtain only those antibodies that are specifically immunoreactive with the antigen and not with other proteins, except for polymorphic variants and alleles. This selection may be achieved by subtracting out antibodies that cross-react with molecules from other species. A variety of immunoassay formats may be used to select antibodies specifically immunoreactive with a particular antigen. For example, solid-phase ELISA immunoassays are routinely used to select antibodies specifically immunoreactive with a protein (see, e.g., Harlow & Lane. Antibodies, A Laboratory Manual (1988), for a description of immunoassay formats and conditions that can be used to determine specific immunoreactivity). Typically, a specific or selective reaction will be at least twice background signal or noise and more typically more than 10 to 100 times background.Optical Fiber-Based Gamma-Photon Counter

[0175] In one aspect, an optical fiber-based gamma-photon counter is provided, which can be used in real-time monitoring of uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide in tumors and organs at risk in a subject undergoing radioligand therapy. The optical fiber-based gamma-photon counter comprises i) a Y203-Eu-doped phosphor, wherein a y-photon incident on the surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum, suitable for solid-state photon detection; ii) a detector comprising a photodiode; iii) an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3-EU doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; iv) a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and v) an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor. In some embodiments, the incoming gamma photons reaching the surface of the detector are uncollimated. FIGS. 1 C and 2A show schematics of an exemplary optical fiber-based gamma-photon counter and its circuitry, respectively.

[0176] Any photodiode suitable for detecting the scintillation light can be used in the detector. Examples include an avalanche photodiode (APD) and a single photon avalanche diode (SPAD), among others. The detector will typically include multiple power supplies to control circuit cooling, quenching and reset, and high voltage biasing. For example, an APD can be used with a 2 volt power supply to control the circuit cooling, a 5 volt power supply to control the quenching and reset, and a30 volt power supply to control the high voltage biasing (see Example 1). In some embodiments, the detector also includes a high voltage regulator.

[0177] The optical fiber is enclosed in an opaque material to shield the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor. The opaque material preferably has an optical density (OD) of at least 4. In some cases, the optical fiber is wrapped with a black light-absorbing material such as black optical tape to eliminate stray light.

[0178] A digital counter is used to count the number of y-photon detection events, i.e., the voltage pulses produced by the semiconductor photodiode detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor. In some embodiments, the digital counter is configured in a field-programmable gate array (FPGA). In certain embodiments, the gamma photon counter further comprises a clock configured to produce a clock signal representing time, wherein the digital counter uses the clock signal to count numbers of y- photon detection events per a set period of time (e.g., counts per second (CPS)). In some embodiments, the gamma photon counter further comprises a level shifter, wherein the level shifter is configured in circuitry to ensure logic level compatibility with the digital counter (see, e.g., FIGS. 2A and 14D).

[0179] The digital output of the digital counter can be stored by a data storage unit. For example, an internal data storage unit (memory) or an external data storage unit in communication with or connected to the digital counter, either with a wire or wirelessly, can be configured to store a plurality of gamma photon count records for a plurality of y-photon detection events. The data storage component may be of any type capable of storing information, and may utilize, e.g., FLASH memory, metal-oxide-semiconductor (MOS) memory, random-access memory (RAM), dynamic randomaccess memory (DRAM), static random-access memory (SRAM), synchronous dynamic randomaccess memory (SDRAM), or any other write-capable memory.

[0180] In certain embodiments, the optical fiber-based gamma-photon counter further comprises a first wireless communication unit in communication with the data storage unit and an external data receiving device comprising a second wireless communication unit. In some embodiments, the first wireless communication unit utilizes a wireless communication protocol using an electromagnetic carrier wave (e.g., radio wave, microwave, or infrared) or ultrasound to transfer data from the data storage unit to the external data receiving device comprising the second wireless communication unit. For example, the first wireless communication unit may utilize a radio-frequency communication protocol or an ultrasound communication protocol to transfer data from the data storage unit to the external data receiving device comprising the second wireless communication unit. The datareceiving device may include, without limitation, acomputer or handheld device, such as a cell phone or tablet. In certain embodiments the data is uploaded wirelessly to the cloud.

[0181] In certain embodiments, the components of the gamma photon counter, including the Y2O3- Eu-doped phosphor, detector, and digital counter are configured in an application-specific integrated circuit (ASIC) on a chip. In some embodiments, the chip comprises an internal power source or energy storage device such as a capacitor or battery to supply power to the chip, for example, for operation of the digital counter, detector, and clock. The on-chip power source or energy storage device can include, without limitation, lithium ion batteries, silver oxide batteries, or chip-type electric double layer capacitors. In some embodiments, the battery is rechargeable.

[0182] In some embodiments, the optical fiber-based gamma-photon counter further comprises an edge computing device connected to the data storage unit, wherein the edge computing device receives gamma photon count data. In some embodiments, the on-chip edge computing device is programmed to partially process the count data, which is subsequently transmitted to an external data processing unit to complete data processing. In certain embodiments, the data storage unit is in communication with an external data processing unit, wherein the data processing unit is programmed to calculate total %IA / ml for one or more tumors and one or more organs at risk in a subject from a plurality of gamma photon count records from multiple gamma photon counters, as described further below.Chip-Based Gamma-Photon Counters

[0183] In another aspect, chip-based gamma photon counters are provided, which can also be used in real-time monitoring of uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide in tumors and organs at risk in a subject. Fundamentally, this platform is unique in that it synergistically integrates an algorithmic approach to significantly reduce the amount of data (and therefore spatial coverage) needed to accurately reconstruct TRT dosimetry and SPECT images. This platform utilizes prior knowledge of the location of tumor and OARs in combination with strategically placed sensors or sparsely placed sensors. Second, this platform uses integrated circuit technology to enable sensors that have pixels that operate asynchronously, which enables determination of the energy and direction of incident photons, as well as allowing highly multiplexed arrays of sensors on the patient. The sensors are scalable in area, but remain thin (<300 microns). In some embodiments, the sensors are arranged in stacks to enable energy resolution and acquire directional photon information - which further enhances spatial resolution and accuracy of detection of the radionuclide distribution. The sensors have minimal thickness and weight, which enables many sensors to be used at a single time as a wearable. This platform is capable of performing singlephoton sensing for image reconstruction, analogously to SPECT, unlike positron emission tomography-based imaging, where two temporally coincident photons must be detected. Not only are no collimators needed but rather the flux of single photons (gamma) is captured at different known locations on the surface of the patient to reconstruct the distribution of gamma emissions within the body, and thereby the dosimetry to tumors and organs at risk. The platform also makes use of the angle of the incident photon (in contrast to collimators which eliminate all angles except for a narrow window of incident angles) to back-calculate the distribution of gamma-emitting radionuclides. This approach allows for a greater number of gamma photons to be measured at a single spatial point, potentially increasing the signal to noise ratio, and speeding up the time to gather the amount of data required for accurate image reconstruction. In some embodiments, a chip-based platform is provided capable of a highly scalable architecture, allowing many chip-based sensors to be placed on the body. In some embodiments, asynchronous pixel operation is used within each sensor. In some embodiments, sensor stacking is used, as described below, to enable energy resolution and / or incident direction resolution in a form factor that is < 5 mm thick. Moreover, the use of SPECT emitters allows a greater selection of radionuclides to be imaged and importantly, allows for imaging of the distribution of TRT.

[0184] In some embodiments, the chip-based gamma photon counter comprises a detector comprising at least one silicon diode, wherein y-photons are detected by the voltage pulses they produce when they hit silicon of a diode. Without being bound by theory, the gamma photons break bonds in the silicon of the diode resulting in electron-hole pairs that generate a charge pulse in the diode, which is accumulated on a capacitor to generate the voltage pulse across the diode. In some embodiments, the chip-based gamma photon counter comprises an array of pixels, wherein each pixel is a gamma-sensing element. FIG. 31 shows an exemplary chip-based gamma-photon counter with an array of pixels.

[0185] The detector may have any suitable shape such as a curved or polygonal shape. In some embodiments, the shape of the detector is circular, oval, semicircular, spherical, cylindrical, triangular, square, rectangular, pentagonal, hexagonal, octagonal, diamond-shaped, or parallelogram-shaped. In certain embodiments the detector has sides ranging from 0.1 pm to 50 pm in length, including any length within this range such as 0.1 pm, 0.2 pm, 0.3 pm, 0.4 pm, 0.5 pm, 0.6 pm, 0.7 pm, 0.8 pm, 0.9 pm, 1 .0 pm, 1 .5 pm, 2.0 pm, 2.5 pm, 3.0 pm, 3.5 pm, 4.0 pm, 4.5 pm, 5.0 pm, 5.5 pm, 6.0 pm, 6.5 pm, 7.0 pm, 8.5 pm, 9.0 pm, 10 pm, 11 pm, 12 pm, 13 pm, 14 pm, 15 pm, 16 pm, 17 pm, 18 pm, 19 pm, 20 pm, 21 pm, 22 pm, 23 pm, 24 pm, 25 pm, 26 pm, 27 pm, 28 pm, 29 pm, 30 pm, 31 pm, 32 pm, 33 pm, 34 pm, 35 pm, 36 pm, 37 pm, 38 pm, 39 pm, 40 pm, 41 pm, 42 pm, 43 pm, 44 pm, 45 pm, 46 pm, 47 pm, 48 pm, 49 pm, or 50 pm.

[0186] In certain embodiments, chip-based gamma photon counter has a form factor with a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm. In some embodiments, the form factor has a thickness ranging from 1 mm to 1 cm, 1 mm to 5 mm, or 1 mm to 3 mm, including any thickness within these ranges such as 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, 10 mm, 12 mm, 14 mm, 16 mm, 18 mm, 20 mm, 25 mm, 30 mm, 35 mm, 40 mm, 45 mm, 50 mm, 55 mm, 60 mm, 65 mm, 70 mm, 75 mm, 80 mm, 85 mm, 90 mm, 95 mm, or 1 cm.

[0187] In certain embodiments, the chip-based gamma photon counter comprises: a detector implemented as an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises at least one reverse biased diode. A y-photon incident on the surface of the reverse biased diode generates a voltage pulse across the reverse biased diode. In some embodiments the reverse biased diode is connected to an amplifier and then a digital counter. In other embodiments, the reverse biased is connected to a voltage buffer before being connected to a voltage amplifier and subsequently connected to a digital counter. The digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse generated across the reverse biased diode by each y-photon incident on the surface. The chip also comprises an on-chip memory configured to store a plurality of gamma photon count records for a plurality of y-photon detection events. A digital clock is configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time. Custom digital logic circuitry is provided on the chip, wherein the digital logic circuitry is configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0188] In certain embodiments, the chip-based gamma photon counter comprises: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements. Each pixel contains a reverse-biased silicon diode connected to a unity gain voltage buffer. Buffered voltage output from the unity gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed-loop amplifier is either pre-set or configurable using in-pixel memory and DAC. A y-photon incident on a surface of the silicon diode generates a voltage pulse across the diode and is subsequently buffered and amplified by a fixed, process-invariant gain. This voltage pulse is then digitized using a series of inverters, which are connected to digital counters to quantify the total number of gamma photons detected in a certain time frame. Each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of the silicon diode. The chip further comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a pluralityof y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic circuitry configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0189] In certain embodiments, the chip-based gamma photon counter comprises: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements. In some embodiments, each pixel in the array comprises two silicon diodes connected to an amplifier. An incident gamma photon breaks bonds in the silicon, generating electron-hole pairs that in turn generate a pulse of charge (Qp) in the silicon diode, which is accumulated on a parasitic diode capacitor (Cdiode)- This generates a small voltage pulse across the diode (Vp= Qp / Cdiode). The use of integrated circuit technology enables ultra-small diode capacitances, increasing Vp, and allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity gain voltage amplifier. Each of these buffered outputs connects to the inputs of a differential amplifier. To mitigate DC voltage offset at the output due to fabrication variability from pixel-to-pixel and chip-to-chip that may cause variability in detector sensitivity, a voltage integrator is bootstrapped from the output of the amplifier to one of it’s inputs in a negative feedback configuration. The voltage integrator also accepts a desired DC voltage that sets the voltage at the output of the amplifier. This ensures that the sensitivity of each of the pixels across the chip is approximately the same. In order to tune each diode in each pixel to a desired sensitivity, the output of the amplifier is connected to two level shifters: one that shifts the DC level of the amplifier output up to only amplify the voltage pulse from the first diode, and the other that shifts the DC level of the amplifier output down to only amplify the voltage pulse from the second diode. The amount these DC levels are shifted are set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert the bits stored into an analog shift in voltage. These shifted and amplified voltage pulses are then digitized using a series of inverters. Capacitors at the inputs of the last inverters increase signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of either silicon diode. The chip also comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0190] In another aspect, a gamma photon counter is provided, the gamma photon counter comprising: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements. In some embodiments, each pixel in the array comprises silicon diodes connected to an amplifier. In some embodiments, each pixel operates asynchronously, meaning that each pixel can register a gamma interaction without reading out the entire array. This allows much greater time resolution, and enables near single particle sensitivity on the array. This feature enables determination of the incident direction of the gamma photon, which then enables improved image reconstruction with fewer incident gammas (when compared to purely counting gammas without directional information). With respect to the diodes, in some embodiments, the diodes are reversed biased. In other embodiments the diodes have zero voltage bias. With respect to the pixel architecture, in some embodiments, this is a differential structure, in which the two diodes are connected to the inputs of a differential amplifier. Leveraging the sparsity of photon hits, the most likely event is where only a single diode is hit at any one time, producing a differential pulse at the output of the amplifier. This structure has the advantage of mitigating offsets associated with the properties of the diode, or reset or other circuitry that will have an effect on the baseline voltage (signal) across the diode, as any mismatch between the two diodes appears as input offset of the amplifier and can cause the amplifier to operate in a low gain region, or ‘rail’ (saturate) to the point it is not active at all. Thus the differential structure preserves the ability of the amplifier to operate with some inherent variation of the sensing diodes across the chip. The pulse from each diode is generated by the following: wherein an incident gamma photon breaks bonds in the silicon, generating electron-hole pairs that in turn generate a pulse of charge (Qp) in the silicon diode, which is accumulated on a parasitic diode capacitor (Cdiode). This generates a small voltage pulse across the diode (Vp= Qp / Cdiode). The use of integrated circuit technology enables ultra-small diode capacitances, increasing Vp, and allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity gain voltage amplifier. Each of these buffered outputs connects to the inputs of a differential amplifier. In some embodiments, to mitigate DC voltage offset at the output due to fabrication variability from pixel-to-pixel and chip-to-chip that may cause variability in detector sensitivity, a voltage integrator is bootstrapped from the output of the amplifier to one of its inputs in a negative feedback configuration. The voltage integrator also accepts a desired DC voltage that sets the voltage at the output of the amplifier. This ensures that the sensitivity of each of the pixels across the chip is approximately the same. In order to tune each diode in each pixel to a desired sensitivity, the output of the amplifier is connected to two level shifters: one that shifts the DC level of the amplifier output up to only amplify the voltage pulse from the first diode, and the other that shifts the DC level of the amplifier output down to only amplify the voltage pulse from the seconddiode. The amounts these DC levels are shifted are set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert the bits stored into an analog shift in voltage. These shifted and amplified voltage pulses are then digitized using a series of inverters. Capacitors at the inputs of the last inverters increase signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of either silicon diode. The chip also comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0191] In certain embodiments, the chip is covered with a material capable of Compton scattering of gamma photons. The Compton scattering material may include, but is not limited to, lead, tungsten, or bismuth. Compton scattering of gamma photons that collide with the material generates lower energy photons (typically <100 keV) that have a higher interaction probability with the detector due to the photoelectric effect and additionally creates secondary electrons from the inelastic collision with the primary gamma photon, which have a high interaction probability with the detector. In some embodiments, these secondary electrons generated from the gamma photons are detected by the detector. Both of these energy conversions can be accomplished using a thin high-density layer of a Compton scattering material on top of the detector or on the back of the detector (e.g., covering the bulk silicon), which can boost the signal of the detector, increase its sensitivity, and minimize data acquisition times.

[0192] In certain embodiments the energy of the incoming photons can be determined by measuring the ratio of detector counts with a plurality of detectors having varying thicknesses of attenuating material. The attenuating material may include lead, tungsten, bismuth, or other high-density material. For example, lower energy photons have an exponentially higher probability of interaction with lead, and can be detected without or in certain instances with a very thin layer of lead. Higher energy photons are selectively measured by creating a subsequently thicker layer of lead on top of other detectors to completely attenuate lower energy photons and only allow high energy photons to pass through. This process can be repeated with layers of different thicknesses in order to allow for energy resolution of an incoming gamma photon flux consisting of multiple primary energy emissions to be determined. Since the energies of gamma photons will be a distribution at varying thicknesses of lead, an understanding of the likelihood of detecting a photon of a certain energy with a detectorof a certain lead thickness can be determined using multiphysics simulation, and can be used to separate the detected counts of each energy.

[0193] In certain embodiments, chip-based gamma detectors, capable of energy resolution and / or incident direction resolution of an incoming flux of gamma photons, are provided. In some embodiments, the chip-based gamma detectors are placed in a vertical stack with each detector separated from the other with a thin layer of an attenuating material, which may include lead, tungsten, bismuth, or other high-density material. An exemplary embodiment is shown in FIG. 33A, which depicts a plurality of chip-based gamma detectors arranged in a vertical stack.

[0194] In certain embodiments, chip-based gamma detectors are stacked on top of each other (i.e., to create a gamma sensor stack), which enables incident angle measurements of incoming photons. In some embodiments, the stacked chip-based gamma detectors are each equipped with fast readout circuitry for their array of pixels (i.e., gamma sensing elements) to allow for near instantaneous detection of the same incident gamma photon passing between two chip-based gamma detectors in the stack. In some embodiments, this near instantaneous detection of incident gamma photons is accomplished by having asynchronous pixel operation, such that each pixel samples the gamma photon, and transmits the time that the gamma photon hits the detector, the pixel location on the detector, and the signal, which is related to the LET of the gamma detector. The angle shift of the gamma photon passing from the chip-based gamma detector at the top of the stack to an underlying chip-based gamma detector can be used to calculate the incident gamma photon angle on the gamma sensor stack by evaluating the numerical equations that govern Compton scattering physics. Angular measurements of incoming gamma photons provide an additional dimension of information when reconstructing dose information in tumors and OAR over the course of therapy, and enable the use of a fewer number of sensors around the patient.

[0195] In some embodiments, the chip-based gamma detectors are stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm. In some embodiments, chip-based gamma detectors are stacked with a stack thickness of greater than or equal to 1 mm and less than 3 mm. In some embodiments, chip-based gamma detectors are stacked with a stack thickness of greater than or equal to 0.1 mm and less than 1 mm.

[0196] In some embodiments, the chip-based gamma detectors are stacked with a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm. In some embodiments, the form factor has a thickness ranging from 1 mm to 1 cm, 1 mm to 5 mm, or 1 mm to 3 mm, including any thickness within these ranges such as 1 mm, 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9mm, 10 mm, 12 mm, 14 mm, 16 mm, 18 mm, 20 mm, 25 mm, 30 mm, 35 mm, 40 mm, 45 mm, 50 mm, 55 mm, 60 mm, 65 mm, 70 mm, 75 mm, 80 mm, 85 mm, 90 mm, 95 mm, or 1 cm.

[0197] In certain embodiments, chip-based gamma detectors that are capable of determining the energy resolution of an incoming flux of gamma photons are placed in the same plane to give energy resolution in approximately the same spatial area. In some embodiments, each detector has varying thickness of an attenuating material such as lead, tungsten, bismuth, or other high-density material placed on their surface or above the bulk silicon.

[0198] In certain embodiments, on-chip circuitry is tuned to be responsive to a range of linear energy transfer (LET), such that the combination and distribution of signals from various pixels with known LET responsivity enable the determination of the incident energies of incoming gamma photons. For example, low energy photons have higher LET and can be detected with a pixel with low gain that only detects low energy photons and not higher energy photons with higher LET, which do not produce a signal. On the same chip or a neighboring chip, pixels with higher gain are included to amplify the low LET from higher energy photons. The pixels with higher gain are responsive to both lower energy photons and higher energy photons. By combining the statistics from sets of pixels with lower gains and sets of pixels with higher gains, the energy distribution of incoming gamma photons can be determined.

[0199] In certain embodiments, a combination of two or more or all the above methods for energy resolution is used to determine the energy distribution of incoming gamma photons.

[0200] In certain embodiments, a pixel sensor is also responsive to electrons generated by the gamma photons. Electrons may be generated by gamma photons by the photoelectric effect, wherein a gamma ray transfers all its energy to an electron resulting in ejection of the electron from an atom. Alternatively, electrons may be generated from gamma photons by Compton scattering, which similarly results in ejection of an electron from an atom, wherein the gamma ray retains some of its energy and is scattered in a different direction. In some cases, electrons are generated from gamma photons in a patient administered a radiopharmaceutical comprising a gamma-emitting radionuclide, in a layer of material placed in between the patient and a pixel sensor, or in silicon of a diode upon collision with a gamma photon. Electrons bombarding a silicon diode create electron-hole pairs in the silicon that generate voltage pulses across the silicon diode, which can be detected similarly to those produced by gamma photons with the chip-based devices described herein.

[0201] The number of diodes contained in a pixel array (e.g., for detection of gamma photons or electrons generated by gamma photons) may vary. In certain embodiments, a pixel array includes two or more diodes, such as 10 or more, 50 or more, 100 or more, 500 or more, 1000 or more, 2000 or more, 3000 or more, or 4000 or more, including 5000 or more, e.g., about 2 to 10 diodes, about10 to 100 diodes, about 100 to 500 diodes, about 500 to 1000 diodes, about 1000 to 2000 diodes, about 2000 to 3000 diodes, about 3000 to 4000 diodes, or about 4000 to 5000 diodes, including any number of diodes in these ranges such as 2, 4, 6, 8, 10, 20, 40, 60, 80, 100, 120, 140, 160, 180, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750, 800, 850, 900, 950, 1000, 1500, 2000, 2500, 3000, 3500, 4000, 4500, or 5000 diodes. In one embodiment, the pixel array comprises 4,096 diodes. The diodes may be arranged in a regular repeating pattern (e.g., a grid, such as a grid with about 1 pm to 10 pm spacing between diodes), or no pattern. Ultra-small micron-scale diodes having high sensitivity for detection of single gamma photons can be used in such arrays. Micron-scale photodiodes are commercially available, for example, from X-FAB Silicon Foundries (Erfurt, Germany) and Taiwan Semiconductor Manufacturing Company (Hsinchu Science Park, Taiwan). Such diodes can be used in massively parallel arrays for detection of gamma photons with high sensitivity. In some embodiments, thousands of such micron-scale gamma ray-sensitive photodiodes are included in pixel arrays on a millimeter-scale chip.

[0202] In some embodiments, the pixel array is optimized for sensitivity by decreasing the diode capacitance. In some embodiments, the diode size is the minimum size available for the CMOS process (which is continually decreasing). In some embodiments, the diode size is 0.1 pm to 0.5 pm x 0.1 pm to 0.5 pm. In some embodiments, the diode size is 0.5 pm to 1 pm x 0.5 pm to 1 pm

[0203] In some embodiments, the pixel array is optimized to provide a tradeoff between both pixel fill factor and sensitivity by setting the diode size to 1 pm to 1 .5 pm x 1 pm to 1 .5 pm.

[0204] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity by setting the diode size to 1 .5 pm to 3 pm x 1 .5 pm to 3 pm.

[0205] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity by setting the diode size to 3 pm to 10 pm x 3 pm to 10 pm.

[0206] In certain embodiments, the detector is optimized to increase fill factor with a tradeoff in sensitivity by setting the diode size to 10 pm to 50 pm x 10 pm to 50 pm.

[0207] In some embodiments, the diodes are connected to an amplifier to improve sensitivity of detection of gamma photons. For a description of suitable amplifiers and amplification circuitry, see, e.g., Lee et al. (2020) Int J Part Ther 6(3):35-109; Lee et al. (2020) A 64x64 Implantable Real-Time Single-Charged-Particle Radiation Detector for Cancer Therapy, IEEE International Solid- State Circuits Conference - (ISSCC), IEEE p. 506-508 (ieeexplore.ieee.org / document / 9063125); herein incorporated by reference in their entireties.

[0208] A digital counter is used to count the number of y-photon detection events, i.e., the voltage pulses produced by a y-photon incident on the surface of a silicon diode. In certain embodiments, the chip-based gamma photon counter further comprises a clock configured to produce a clock signalrepresenting time, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a set period of time (e.g., counts per second (CPS)). In some embodiments, the clock signal is generated by a frequency locked loop (FLL) oscillator (see, e.g., FIG. 31 ). A clock beacon to the FLL may be generated from an off-chip crystal oscillator. In other embodiments, the clock signal is generated directly from an off-chip crystal oscillator. In certain embodiments the clock signal and control signals are generated from an external computer, FPGA, cellular phone, or other control device.

[0209] The digital output of the digital counter can be stored in an internal data storage unit (memory) or an external data storage unit in communication with or connected to the digital counter, either with a wire or wirelessly. The data storage unit can be configured to store a plurality of gamma photon count records for a plurality of y-photon detection events. The data storage component may be of any type capable of storing information, and may utilize, e.g., FLASH memory, metal-oxide- semiconductor (MOS) memory, random-access memory (RAM), dynamic random-access memory (DRAM), static random-access memory (SRAM), synchronous dynamic random-access memory (SDRAM), or any other write-capable memory. In certain embodiments, the gamma photon counter comprises on-chip memory in the form of static random-access memory (SRAM).

[0210] In certain embodiments, the chip-based gamma-photon counter further comprises a first wireless communication unit in communication with the internal data storage unit (memory) and an external data receiving device comprising a second wireless communication unit. In some embodiments, the first wireless communication unit utilizes a wireless communication protocol using an electromagnetic carrier wave (e.g., radio wave, microwave, or infrared) or ultrasound to transfer data from the data storage unit to the external data receiving device comprising the second wireless communication unit. For example, the first wireless communication unit may utilize a radio-frequency communication protocol or an ultrasound communication protocol to transfer data from the data storage unit to the external data receiving device comprising the second wireless communication unit. The data receiving device may include, without limitation, a computer or handheld device, such as a cell phone or tablet. In certain embodiments the data is uploaded wirelessly to the cloud.

[0211] In some embodiments, the chip-based gamma-photon counter further comprises an edge computing device connected to the internal data storage unit (memory), wherein the edge computing device receives gamma photon count data. In some embodiments, the on-chip edge computing device is programmed to partially process the count data, which is subsequently transmitted to an external data processing unit to complete data processing. In certain embodiments, the data storage unit is in communication with an external data processing unit, wherein the data processing unit is programmed to calculate total %IA / ml for one or more tumors and one or more organs at risk in asubject from a plurality of gamma photon count records from multiple gamma photon counters, as described further below.

[0212] In some embodiments, the chip comprises an internal power source or energy storage device such as a capacitor or battery to supply power to the chip, for example, for operation of the digital counter, detector, and clock. The on-chip power source or energy storage device can include, without limitation, lithium ion batteries, silver oxide batteries, or chip-type electric double layer capacitors. In some embodiments, the battery is rechargeable.

[0213] In some embodiments, power is transmitted to the chip from an external transducer. Examples of external transducers include an ultrasound transducer, an electromagnetic (EM) transducer, an inductive transducer, and a radiofrequency (RF) transducer, among others. In certain embodiments, the chip further comprises an energy storage device such as a capacitor or a rechargeable battery to store electrical energy output from a piezoelectric substrate in response to receiving ultrasound power or an antenna in response to receiving RF power or electromagnetic power, wherein the capacitor or rechargeable battery supplies power to the chip for operation of the chip. In some embodiments a piezoelectric substrate and / or battery or storage capacitor are assembled on a solid support (e.g., board) containing a chip. In certain embodiments, the gamma photon counter comprises a precharged battery, and does not receive external power or recharge, in which case, after discharging, the battery remains until it is removed.

[0214] Several voltage regulators may be used to generate the on-chip voltages for circuit operation and on-chip clock generation. In embodiments where power is transferred from an external transducer, the gamma photon counter further comprises a voltage rectifier and several voltage regulators to generate the on-chip voltages for circuit operation. Multiple voltage sources at various levels can be generated on-chip to power circuitry on the chip. In some embodiments, the clock signal is derived from a transducer signal. An analog to digital converter (ADC) can also be included on the chip. Examples of an ADC include an 8-bit differential SAR ADC with a 0.5 V or 1 V maximum range and a 10-bit SAR ADC with a 0.5 V or 1 V maximum range, among others.Wearable System

[0215] A wearable system comprising a plurality of gamma photon counters (e.g., optical fiber-based gamma photon counters or chip-based gamma-photon counters) attached to a wearable structure is provided for monitoring radioactivity delivered to tumors and organs at risk in a subject. The counters are positioned based on each patient’s unique tumor distribution. Patients can be continually monitored or monitored at set intervals of time by placing the counters at desired locations on a wearable material that can be worn continuously or taken on and off and worn just for the timeneeded for acquisition of count data (e.g., 10 minutes) at home, in a clinic, or in a hospital setting. A wearable system circumvents the need for bulky scintillating crystals and collimators by taking advantage of the longer image acquisition times that are possible because the counters are wearable.

[0216] Medical imaging (e.g., SPECT, PET, or CT) of a subject provides information regarding the positions of the gamma photon counters with respect to the tumors and organs at risk in the subject and limits the patient surface area that needs to be imaged. In some embodiments, an image of a subject is used to position gamma photon counters on a wearable structure to monitor the uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by particular tumors and organs at risk in a subject. The count data from a plurality of wearable counters can be uploaded to a computer for calculation of the dose distribution of the radiopharmaceutical comprising the gammaemitting radionuclide in the tumors and organs at risk in the subject using computer implemented methods described further below. Such a wearable system can provide convenient continuous dosimetry for a patient and reduce the need for hospital-based medical imaging.

[0217] The term “wearable” includes any structure capable of being worn or carried on the body of a subject similarly to an item of clothing. A plurality of the gamma photon counters, described herein, can be attached to any suitable type of wearable material that allows a counter to monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor or organ at risk in the subject. In some cases, a plurality of gamma photon counters is attached to any number of different structures for wearing on different portions of the body. For example, the wearable structure may take the form of an adhesive patch or clothing such as a vest, shirt, shorts, pants, hat, shoe, glove, and body sleeve, among others, and may include a combination of two or more of any of the foregoing. In some embodiments, different sizes of a wearable system may be made available to accommodate individuals of different sizes. For example, a range of sizes of a particular wearable system may be provided for accommodating different body types ranging from adults to children, short to tall individuals, slim to overweight or obese individuals, or any other range of body types. In some cases, adjustability may be provided by either the elasticity of a structure associated with the body portion, adjustable components such as straps and fasteners, adjustable detector positions, and / or any other appropriate arrangement or feature. In some cases, the wearable structure may be attached to the associated body portion using any appropriate method including, for example, the inherent elasticity of a material, straps, elastic bands, snaps, ties, hook and loop fasteners, clips, tape, or adhesives, and / or any other applicable method of attaching and / or fitting the structures to a related body portion. In some embodiments, a plurality of gamma photon counters is attached to clothing belonging to the subject to be monitored.

[0218] In some embodiments, the wearable structure provides freedom of movement for a subject wearing the system due to the use of wireless connections, visual indicators, a power source (e.g. batteries, capacitors, wireless power transmission, etc.), and / or storage for later download of gamma photon count data. In other embodiments, the wearable structure has a wired connection to a processor and / or data storage device, or otherwise limits the movement of a subject.

[0219] In some embodiments, the wearable system comprises 10 to 1000 gamma photon counters attached to the wearable structure, The precise number of counters attached to a wearable structure (e.g., for counting counts from uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor or organ at risk) may vary and will depend on a patient’s unique tumor distribution and the number needed to provide the sensitivity and resolution needed to monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide. In certain embodiments, the wearable structure includes 10 or more counters, such as 20 or more, including 50 or more, 100 or more, 250 or more, 500 or more, or a 1000, or more counters, e.g., about 100 to 1000 counters, about 200 to 800 counters, about 300 to 600 counters, about 400 to 500 counters, or any number of counters within these ranges such as 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 120, 140, 160, 180, 200, 220, 240, 260, 280, 300, 320, 340, 360, 380, 400, 420, 440, 460, 480, 500, 520, 540, 560, 580, 600, 620, 640, 660, 680, 700, 720, 740, 760, 780, 800, 820, 840, 860, 880, 900, 920, 940, 960, 980, or 1000 counters. In some embodiments, the counters may be arranged in a regular repeating pattern (e.g., a grid, such as a grid with about 1 cm to 10 cm spacing between counters), or no pattern. In certain embodiments, the positioning of each counter is determined based on medical imaging (e.g., PET, CT, or SPECT) of the subject to determine where the tumors and organs at risk are located in the subject such that when the wearable structure is worn by the subject, the counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by the tumors or organs at risk.

[0220] In certain embodiments, a first subset of the plurality of counters is arranged on clothes such that when the clothes is worn by a subject, the first subset of counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject; and a second subset of the plurality of counters is arranged on the clothes such that when the clothes is worn by the subject, the second subset of counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by an organ at risk in the subject. In certain embodiments, the positioning of each counter of the first subset on the clothes is determined based on medical imaging of the subject to determine where the tumor is located in the subject and positioning of each counter of the second subset on the clothes is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

[0221] The clothes comprising the plurality of counters attached to it may be any suitable type of clothing for the purpose such as a vest, shirt, shorts, pants, hat, shoe, glove, and body sleeve, among others. The choice of type of clothing will depend on the locations of the tumors and organs at risk in the subject. For example, a vest or shirt comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by tumors in the lungs, stomach, intestines, bladder, prostate, and the like. In another example, shorts or pants comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by tumors in the legs or thighs. In a further example, a hat comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by tumors in the brain.

[0222] In other embodiments, a plurality of counters is attached to the skin of a subject with adhesive patches. The counters may be arranged in a regular repeating pattern (e.g., a grid, such as a grid with about 1 cm to 10 cm spacing between counters), or no pattern. Alternatively, the positioning of each counter on the skin may be determined based on medical imaging (e.g., PET, CT, or SPECT) of the subject to determine where the tumors and organs at risk are located in the subject such that when the counters are attached to the skin with an adhesive patch, the counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by the tumors or organs at risk.

[0223] In some embodiments, a first subset of the plurality of counters are attached to the skin with adhesive patches such that the first subset of counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each counter of the first subset with the adhesive patches is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of counters is attached to the skin with adhesive patches such that the second subset of counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each counter of the second subset with the adhesive patches is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

[0224] The wearable system may be used to monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide, for example, during or after administration to a subject. In some embodiments, the radiopharmaceutical is a radioactive drug, a radioimmunotherapeutic agent, or a radiopeptide. In some embodiments, the wearable system is used to monitor tumor and OAR uptake of a gamma-emitting radionuclide used in SPECT imaging such as, but not limited to,46Sc,67Ga, 99mTc,111ln,123l,1311,155Tb,177Lu,133Xe, and201TL In some embodiments, the wearable system is used to monitor tumor and OAR uptake of a radiopharmaceutical comprising an alpha-emittingradionuclide such as, but not limited to,149Tb,223Ra, and225Ac. In some embodiments, the wearable system is used to monitor tumor and OAR uptake of a radiopharmaceutical comprising a betaemitting radionuclide such as, but not limited to,32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, and 177Lu.

[0225] The wearable system may be used to monitor a subject treated with a theranostic agent for treatment of cancer. In some embodiments, the theranostic agent comprises a gamma-emitting radionuclide conjugated to a binding agent that specifically binds to a cancer marker. Radionuclides may be conjugated to any agent that specifically binds to a cancer marker of interest (e.g., tumorspecific antigen or tumor-associated antigen). In some embodiments, the binding agent binds to a cancer marker of interest with high affinity. Examples of binding agents include, without limitation, antibodies, antibody fragments, antibody mimetics, and aptamers as well as small molecules, peptides, peptoids, or ligands that bind selectively to cellular markers. The conjugates used in the subject methods include at least one radionuclide attached to the binding agent. In some embodiments, a radionuclide conjugate is used that comprises a binding agent that selectively binds to a cancer cell-specific marker. In some embodiments, multiple radionuclide conjugates are used, wherein the different radionuclide conjugates bind to different markers on cancer cells of the same cell-type or different cell-types.

[0226] In certain embodiments, the binding agent comprises an antibody that specifically binds to the marker of interest. Any type of antibody may be used in radionuclide conjugates, including, without limitation, monoclonal antibodies, polyclonal antibodies, as well as hybrid antibodies, altered antibodies, chimeric antibodies, and humanized antibodies. Antibodies may include hybrid (chimeric) antibody molecules (see, for example, Winter et al. (1991 ) Nature 349:293-299; and U.S. Pat. No. 4,816,567); F(ab')2and F(ab) fragments; Fvmolecules (noncovalent heterodimers, see, for example, Inbar et al. (1972) Proc Natl Acad Sci USA 69:2659-2662; and Ehrlich et al. (1980) Biochem 19:4091 - 4096); single-chain Fv molecules (scFv) (see, e.g., Huston et al. (1988) Proc Natl Acad Sci USA 85:5879-5883); nanobodies or single-domain antibodies (sdAb) (see, e.g., Wang et al. (2016) Int J Nanomedicine 11 :3287-3303, Vincke et al. (2012) Methods Mol Biol 911 :15-26; dimeric and trimeric antibody fragment constructs; minibodies (see, e.g., Pack et al. (1992) Biochem 31 :1579-1584; Cumber et al. (1992) J Immunology 149B:120-126); diabodies, tetrabodies, affibodies, camelid antibodies, humanized antibody molecules (see, e.g., Riechmann et al. (1988) Nature 332:323-327; Verhoeyan et al. (1988) Science 239:1534-1536; and U.K. Patent Publication No. GB 2,276,169, published 21 Sep. 1994); and, any functional fragments obtained from such molecules, wherein such fragments retain specific-binding properties of the parent antibody molecule.

[0227] In other embodiments, the binding agent comprises an aptamer that specifically binds to the marker of interest. Any type of aptamer may be used, including a DNA, RNA, xeno-nucleic acid (XNA), or peptide aptamer that specifically binds to the tumor antigen. Such aptamers can be identified, for example, by screening a combinatorial library. Nucleic acid aptamers (e.g., DNA or RNA aptamers) that bind selectively to a target tumor antigen can be produced by carrying out repeated rounds of in vitro selection or systematic evolution of ligands by exponential enrichment (SELEX). Peptide aptamers that bind to a marker of interest may be isolated from a combinatorial library and improved by directed mutation or repeated rounds of mutagenesis and selection. For a description of methods of producing aptamers, see, e.g., Aptamers: Tools for Nanotherapy and Molecular Imaging (R.N. Veedu ed., Pan Stanford, 2016), Nucleic Acid and Peptide Aptamers: Methods and Protocols (Methods in Molecular Biology, G. Mayer ed., Humana Press, 2009), Nucleic Acid Aptamers: Selection, Characterization, and Application (Methods in Molecular Biology, G. Mayer ed., Humana Press, 2016), Aptamers Selected by Cell-SELEX for Theranostics (\N. Tan, X. Fang eds., Springer, 2015), Cox et al. (2001) Bioorg. Med. Chem. 9(10):2525-2531 ; Cox et al. (2002) Nucleic Acids Res. 30(20): e108, Kenan et al. (1999) Methods Mol. Biol. 118:217-231 ; Platella et al. (2016) Biochim. Biophys. Acta Nov 16 pii: S0304-4165(16)30447-0, and Lyu et al. (2016) Theranostics 6(9) :1440-1452; herein incorporated by reference in their entireties.

[0228] In other embodiments, the binding agent comprises an antibody mimetic. Any type of antibody mimetic may be used, including, but not limited to, affibody molecules (Nygren (2008) FEBS J. 275 (11):2668-2676), affilins (Ebersbach et al. (2007) J. Mol. Biol. 372 (1 ):172-185), affimers (Johnson et al. (2012) Anal. Chem. 84 (15):6553-6560), affitins (Krehenbrink et al. (2008) J. Mol. Biol. 383 (5):1058-1068), alphabodies (Desmet et al. (2014) Nature Communications 5:5237), anticalins (Skerra (2008) FEBS J. 275 (11 ):2677-2683), avimers (Silverman et al. (2005) Nat. Biotechnol. 23 (12):1556-1561 ), darpins (Stumpp et al. (2008) Drug Discov. Today 13 (15-16):695- 701), fynomers (Grabulovski et al. (2007) J. Biol. Chem. 282 (5):3196-3204), and monobodies (Koide et al. (2007) Methods Mol. Biol. 352:95-109).

[0229] In other embodiments, the binding agent comprises a small molecule ligand. Small molecule ligands encompass numerous chemical classes, e.g., small organic compounds having a molecular weight of less than about 10,000 daltons, less than about 5,000 daltons, or less than about 2,500 daltons. The small molecule will include one or more functional groups necessary for structural interaction with the target analyte, e.g., groups necessary for hydrophobic, hydrophilic, electrostatic or even covalent interactions. Where the target analyte is a protein (e.g., cellular marker), the ligand will include functional groups necessary for structural interaction with proteins, such as hydrogen bonding, hydrophobic-hydrophobic interactions, electrostatic interactions, etc., and will typicallyinclude at least an amine, amide, sulfhydryl, carbonyl, hydroxyl or carboxyl group, or preferably at least two of the functional chemical groups. The small molecule may also comprise a region that may be modified and / or participate in conjugation to a radionuclide, without substantially adversely affecting the small molecule's ability to bind to its target analyte.

[0230] Small molecule ligands can comprise cyclical carbon or heterocyclic structures and / or aromatic or polyaromatic structures substituted with one or more of the above functional groups. Small molecule ligands may also include organic compounds comprising alkyl groups (including alkanes, alkenes, alkynes and heteroalkyl), aryl groups (including arenes and heteroaryl), alcohols, ethers, amines, aldehydes, ketones, acids, esters, amides, cyclic compounds, heterocyclic compounds (including purines, pyrimidines, benzodiazepins, beta-lactams, tetracylines, cephalosporins, and carbohydrates), steroids (including estrogens, androgens, cortisone, ecodysone, etc.), alkaloids (including ergots, vinca, curare, pyrollizdine, and mitomycines), organometallic compounds, hetero-atom bearing compounds, amino acids, and nucleosides. Small molecule ligands are also found among biomolecules including peptides, carbohydrates, fatty acids, steroids, purines, pyrimidines, derivatives, structural analogs, or combinations thereof. The small molecule may be derived from a naturally occurring or synthetic compound that may be obtained from a wide variety of sources, including libraries of synthetic or natural compounds. For example, numerous means are available for random and directed synthesis of a wide variety of organic compounds and biomolecules, including the preparation of randomized oligonucleotides and oligopeptides. Alternatively, libraries of natural compounds in the form of bacterial, fungal, plant and animal extracts are available or readily produced. Additionally, natural or synthetically produced libraries and compounds are readily modified through conventional chemical, physical and biochemical means, and may be used to produce combinatorial libraries. Known small molecules may be subjected to directed or random chemical modifications, such as acylation, alkylation, esterification, amidification, etc. to produce structural analogs.

[0231] As such, the small molecule may be obtained from a library of naturally occurring or synthetic molecules, including a library of compounds produced through combinatorial means, i.e., a compound diversity combinatorial library. When obtained from such libraries, the small molecule employed will have demonstrated some desirable affinity for the protein target in a convenient binding affinity assay. Combinatorial libraries, as well as methods for the production and screening, are known in the art and described in: U.S. Pat. Nos. 5,741 ,713; 5,734,018; 5,731 ,423; 5,721 ,099; 5,708,153; 5,698,673; 5,688,997; 5,688,696; 5,684,711 ; 5,641 ,862; 5,639,603; 5,593,853;5,574,656; 5,571 ,698; 5,565,324; 5,549,974; 5,545,568; 5,541 ,061 ; 5,525,735; 5,463,564;5,440,016; 5,438,1 19; 5,223,409, the disclosures of which are herein incorporated by reference.

[0232] Small molecule ligands may also include known drugs that selectively bind to receptors on cells, including, without limitation, growth factor receptors, receptor tyrosine kinases, receptor protein serine / threonine kinases, G-protein coupled receptors, cytokine receptors, lectin receptors, folate receptors, prostate-specific membrane antigen (PSMA), carbonic anhydrase IX receptor, and biotin receptors. For example, anti-cancer drugs that bind to such cellular receptors may be used as ligands to target radionuclides to cancer cells. Exemplary drugs that may be used as ligands to target cancer cells include, without limitation, Acitinib, Afatinib, Axitinib, Erlotinib, Cabozantinib, Crizotinib, Gefitinib, Imatinib, Ibrutinib, Lapatinib, Neovastat, Nilotinib, Pazopanib, Perifosine, Ponatinib, Regorafenib, Sorafenib, Sunitinib, Trametinib, and Vandetenib.

[0233] Exemplary tumor-specific antigens and tumor-associated antigens include, without limitation, oncogene protein products, mutated or dysregulated tumor suppressor proteins, oncovirus proteins, oncofetal antigens, mutated or dysregulated differentiation antigens, overexpressed or aberrantly expressed cellular proteins (e.g., mutated or aberrantly expressed growth factors, mitogens, receptor tyrosine kinases, cytoplasmic tyrosine kinases, serine / threonine kinases and their regulatory subunits, G proteins, and transcription factors), and altered cell surface glycolipids and glycoproteins on cancerous cells. For example, tumor-specific antigens and tumor-associated antigens may include without limitation, dysregulated or mutated RAS, WNT, MYO, ERK, TRK, CTAG1 B, MAGEA1 , Bcr-Abl, p53, c-Sis, epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), vascular endothelial growth factor receptor (VEGFR), HER2 / neu, Src- family, Syk-ZAP-70 family proteins, and BTK family of tyrosine kinases, Abl, Raf kinase, cyclin- dependent kinases, alphafetoprotein (AFP), carcinoembryonic antigen (CEA), CA-125, MUC-1 , epithelial tumor antigen (ETA), tyrosinase, melanoma-associated antigen (MAGE), and other abnormal or dysregulated proteins expressed on cancerous cells. In some embodiments, the cancer- targeted binding agent binds to a tumor antigen of interest with high affinity.

[0234] In certain embodiments, the tumor marker targeted by a binding agent is the urokinase plasminogen activator receptor (uPAR) or urokinase plasminogen activator (uPA). A number of anti- uPAR antibodies are available including the 2G10 antibody, which inhibits the uPAR interaction with urokinase plasminogen activator, and anti- uPAR antibody, 3C6, which inhibits the association of uPAR with |31 integrin (see, e.g., LeBeau et al. (2013) Cancer Res. 73(7):2070-2081 ). Anti-PAR and anti-uPA antibodies can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing uPAR or uPA, respectively, including, without limitation, those of breast cancer including triple negative breast cancer, pancreas cancer, prostate cancer, and melanoma.

[0235] In certain embodiments, the tumor marker targeted by a binding agent is PD-L1 . A number of anti-PD-L1 antibodies are commercially available including durvalumab, pembrolizumab, atezolizumab and avelumab. Other anti-PD-L1 antibodies include C4 and DFO-C4 (see, e.g., Truillet C et al. (2018) Bioconjug. Chem. 29(1 ):96-103). Such anti-PD-L1 antibodies can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing PD-L1 , including, without limitation, those of melanoma, lung cancer, including non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), head and neck cancer, Hodgkin lymphoma, stomach cancer, prostate cancer, bladder cancer, urothelial carcinoma, breast cancer including triple-negative breast cancer (TNBC), hepatocellular carcinoma (HCC), Merkel cell carcinoma, and renal cell carcinoma.

[0236] In certain embodiments, the tumor marker targeted by a binding agent is the epidermal growth factor receptor (EGFR). A number of anti-EGFR antibodies are available including panitumumab, cetuximab, zalutumumab, nimotuzumab, and matuzumab, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing EGFR, including, without limitation, those of head and neck cancer, colorectal cancer, lung cancer, ovarian cancer, breast cancer, endometrial cancer, cervical cancer, bladder cancer, gastric cancer, and esophageal cancer. A number of small molecule drugs are also available that target EGFR including, without limitation, Gefitinib, Erlotinib, Lapatinib, Sorafenib, and Vandetenib, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing EGFR, according to the methods described herein.

[0237] In other embodiments, the tumor marker targeted by a binding agent is HER2. A number of anti-HER2 antibodies are also available including trastuzumab, pertuzumab, and margetuximab, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing HER2, including, without limitation, those of breast cancer, ovarian cancer, stomach cancer, lung cancer, uterine cancer, gastric cancer, colon cancer, head and neck cancer, and salivary duct carcinoma. A number of small molecule drugs are also available that target HER2 including, without limitation, Lapatinib and Neratinib, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing HER2, according to the methods described herein.

[0238] In other embodiments, the tumor marker targeted by a binding agent is the epithelial cell adhesion molecule (EpCAM) 17-1 A. A number of anti-EpCAM 17-1 A antibodies are also available including edrecolomab, catumaxomab, and nofetumomab, which can be conjugated radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing EpCAM 17-1 A to detect cancerous cells in epithelial-derived neoplasms and various carcinomas, such as lungcancer, gastrointestinal cancer, breast cancer, ovarian cancer, pancreatic cancer, renal cancer, cervical cancer, colorectal cancer, and bladder cancer.

[0239] In other embodiments, the tumor marker targeted by a binding agent is CD20. A number of anti-CD20 antibodies are also available including rituximab, tositumomab, ocrelizumab, obinutuzumab, ocaratuzumab, ofatumumab, ibritumomab tiuxetan, ublituximab, and veltuzumab, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing CD20, including, without limitation, those of lymphoma such as, but not limited to, marginal zone lymphoma, Hodgkins lymphoma, non-Hodgkins lymphoma; leukemia such as, but not limited to, chronic lymphocytic leukemia, acute lymphoblastic leukemia, myelogenous leukemia, and chemotherapy-resistant hairy cell leukemia; and thyroid cancer.

[0240] In other embodiments, the tumor marker targeted by a binding agent is CD52. A number of anti-CD52 antibodies are also available including alemtuzumab, which can be conjugated radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing CD52, including, without limitation, those of lymphoma such as, but not limited to, cutaneous T-cell lymphoma (CTCL) and T-cell lymphoma and chronic lymphocytic leukemia (CLL).

[0241] In other embodiments, the tumor marker targeted by a binding agent is CD22. A number of anti-CD22 antibodies are also available including inotuzumab, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing CD22, including, without limitation, those of leukemia such as, but not limited to, lymphoblastic leukemia and hairy cell leukemia; lymphoma, and lung cancer.

[0242] In other embodiments, the tumor antigen targeted by a binding agent is CD19. A number of anti-C19 antibodies are also available including blinatumomab, MEDI-551 and MOR-208, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing CD19, including, without limitation, those of B-cell neoplasms, non-Hodgkin lymphoma (NHL), chronic lymphocytic leukemia (CLL), acute lymphoblastic leukemia (ALL), and multiple myeloma (MM).

[0243] In certain embodiments, the tumor marker targeted by a binding agent is carcinoembryonic antigen (CEA). A number of anti-CEA antibodies are available including arcitumomab, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing CEA, including, without limitation, those of colorectal carcinoma, gastric carcinoma, pancreatic carcinoma, lung carcinoma, breast carcinoma, and medullary thyroid carcinoma.

[0244] In certain embodiments, the tumor marker targeted by a binding agent is prostate-specific membrane antigen (PSMA). A number of anti-PSMA antibodies are available including capromab, PSMA30 nanobody, and IAB2M minibody, which can be conjugated to radionuclides for use inimaging or radioligand therapy for treatment of cancerous cells expressing PSMA, including, without limitation, those of prostate cancer. A number of small molecule drugs are also available that target PSMA including, without limitation, zinc binding compounds linked to a glutamate isostere or glutamate, phosphonate-, phosphate-, and phosphoramidates and ureas, fluciclovine (Axumin), MIP- 1072, MIP-1095, N-(N-((S)-1 ,3-dicarboxypropyl) carbamoyl)-4-(18F)fluorobenzyl-L-cysteine (18F- DCFBC), which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing PSMA, according to the methods described herein.

[0245] In certain embodiments, the tumor marker targeted by a binding agent is the folate receptor (FR). A number of anti-FR antibodies are available including farletuzumab and m909, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing FR, including, without limitation, those of ovarian cancer, breast cancer, lung cancer, pleura cancer, cervical cancer, endometrial cancer, kidney cancer, bladder cancer and brain cancer, The small molecule, folate, can also be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing FR, according to the methods described herein.

[0246] In certain embodiments, the tumor marker targeted by a binding agent is a matrixmetalloproteinase (MMP), including, without limitation, MMP1 , MMP3, MMP7, MMP9, MMP10, MMP1 1 , MMP12, MMP13, and MMP14. A number of anti-MMP antibodies are available including, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing MMPs, including, without limitation, those of ovarian cancer, breast cancer, lung cancer, prostate cancer, stomach cancer, thyroid cancer, skin cancer, brain cancer, kidney cancer, colon cancer, bladder cancer, esophageal cancer, endometrial cancer, hepatocellular cancer, and head and neck cancer. Endogenous glycoprotein inhibitors such as tissue inhibitor of metalloproteinases (TIMPs), including TIMP-1 , TIMP-2, TIMP-3, and TIMP-4 as well as a number of small molecule drugs are available that target MMPs including, without limitation, doxycycline, marimastat (BB-2516), and cipemastat, which can be conjugated to radionuclides for use in imaging or radioligand therapy for treatment of cancerous cells expressing MMPs, according to the methods described herein.

[0247] Chelating agents can be included in theranostic agents to confer metal binding capability. In some embodiments, a theranostic agent comprises a chelating agent wherein the chelating agent forms a complex with a radionuclide metal ion. Exemplary chelating agents include, without limitation, 1 ,4,7,10-tetraazacyclododecane-1 ,4,7,10-tetraacetic acid (DOTA), 1 ,4,7-triazacyclononane- N,N',N"-triacetic acid (NOTA), ethylenediaminetetraacetic acid (EDTA), diethylenetriaminepentaacetic acid (DTPA), 1 ,4,7-triazacyclononane-N,N’,N”-triacetic acid (NOTA), ({4-[2-(bis-carboxymethyl-amino)-ethyl]-7-carboxymethyl-[1 ,4,7]triazonan-1 -yljacetic acid (NETA),and p-bromoacetamido-benzyl-tetraethylaminetetraacetic acid (TETA), porphyrins, polyamines, crown ethers, bis-thiosemicarbazones, polyoximes, and like groups known to be useful for this purpose.Systems and Computer Implemented Methods

[0248] The present disclosure provides systems and computer implemented methods which find use in practicing the subject methods. In some embodiments, the system may include: a processor programmed to calculate the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject; and a display component for displaying the total %IA / ml for the one or more tumors and one or more organs at risk. The system may also comprise one or more graphic boards for processing and outputting graphical information to the display component. For example, the display may be used to display an image of the tumors and organs at risk obtained of the subject by medical imaging. In some embodiments, a computer implemented method is used for calculating the total %IA / ml for one or more tumors and one or more organs at risk in a subject. The injected activity may be from a radiopharmaceutical comprising a gamma-emitting radionuclide which may also emit particles such as alpha particles or beta particles. The processor can be programmed to perform steps of a computer implemented method comprising: a) receiving gamma photon count data from a plurality of gamma photon counters, wherein each gamma photon counter has a known location; b) receiving an image of the subject, wherein the image shows locations of the one or more tumors and the one or more organs at risk in the subject, and locations of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) measuring volumes of the one or more tumors and organs at risk using the image; e) mapping centroid locations of each gamma photon counter on the image; f) performing distributed point source (DPS) modelling to generate a distribution of gamma photon-emitting point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) calculate probabilities for each gamma photon counter that the gamma photons, counted by the gamma photon counter, were received from a gamma photon emitting point source within the boundaries of a particular tumor or organ at risk based on an assumption that counts per second (CPS) falloff correlates with 1 / (distance between the centroid location of the gamma photon counter and the gamma photon emitting point source)2, and CPS values are attenuated by an empirically derived factor Q which accounts for attenuation and scattering of gamma photons in tissue, and ii) estimate probable fractions of counts counted by each gamma photon counter that correspond to a particular tumor or organ at risk; g) estimating total counts for each tumor and organ at risk using aMonte Carlo Markov Chain (MCMC) algorithm based on the gamma photon count data from the plurality of counters and parameter estimates of the probable fractions of counts counted by each gamma photo counter that correspond to a particular tumor or organ at risk from the DPS modelling; h) calculating the total %IA / ml for the one or more tumors and organs at risk in the subject based on said estimating the total counts for each tumor and organ at risk and dividing by the volumes of the one or more tumors and organs at risk measured from the image; and i) displaying the total %IA / mL for the one or more tumors and the one or more organs at risk in the subject.

[0249] In certain embodiments, performing DPS modelling comprises creating a DPS model matrix ( W) denoting the counts per second (CPS) per pCi contributed from each tumor or organ at risk to each gamma photon counter of the plurality, wherein the CPS per pCi are multiplied by an unknown activity in pCi of the total tumor or total organ at risk activity in pCi, wherein values in the DPS model matrix ( 1 / 7) are estimated based on knowledge of the location of each tumor and each organ at risk from the image and the known locations of each gamma photon counter; and decomposing the DPS model matrix ( W) into a matrix ( / 3) and a vector (or), wherein the matrix (J3) denotes the fraction of each gamma photon counter’s CPS that comes from a certain tumor or organ at risk, wherein the fraction is scaled up by the vector (a), wherein the vector (a) is each gamma photon counter’s CPS per injected pCi of activity. In some embodiments, the vector a is estimated by conducting a DPS titration simulation. In some embodiments, the matrix ( / 3) is initially estimated by i) assuming each tumor and each organ at risk uptakes an equal amount of the radionuclide, wherein the total amount of the radionuclide administered to the subject is known, and ii) assigning the same activity to all of the tumors and organs at risk for said estimating the probable fractions of counts counted by each counter that correspond to a particular tumor or organ at risk.

[0250] In some embodiments, the empirically derived factor Q is determined by a method comprising: measuring detected CPS for each gamma photon counter at different distances in water from a gamma photon emitting point source; measuring detected CPS for each gamma photon counter at different distances in air from the gamma photon emitting point source; deriving a nonlinear factor representing scattering and attenuation for each gamma photon emitting point source based on differences between the CPS detected in water and air at each distance; and using the non-linear factor to calculate a unique factor Q for each gamma photon emitting point source in the subject based on distances in tissue between each gamma photon counter and each gamma photon emitting point source.

[0251] In some embodiments, the computer implemented method further comprises using adaptive Metropolis (AM) optimization, wherein a Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm. In some embodiments, thecomputer implemented method further comprises performing iterative optimization by a method comprising using gradient descent, least squares minimization, or brute force global minimization, or a combination thereof.

[0252] In some embodiments, the plurality of gamma photon counters comprises on-chip circuitry tuned to be responsive to a range of LET from incoming gamma photons, wherein the computer implemented method further comprises calculating incident energies of the incoming gamma photons based on combination and distribution of signals from pixels with known LET responsivity. In some embodiments, the plurality of gamma photon counters comprises a plurality of detectors, wherein each detector of the plurality comprises an attenuating material of a different thickness to allow resolution of incoming gamma photons having different energies, wherein the computer implemented method further comprises calculating likelihood of detecting a gamma photon of a certain energy with each detector of the plurality using a multiphysics simulation to separate detected counts of each detector by gamma photon energy.

[0253] In certain embodiments, the plurality of gamma photon counters comprises on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons, wherein the computer implemented method further comprises calculating incident energies of the incoming gamma photons based on combination and distribution of signals from pixels with known LET responsivity. In some embodiments, the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET

[0254] In certain embodiments, the computer implemented method uses gamma photon count data from chip-based gamma photon counters comprising a plurality of detectors arranged in a vertical stack. In some embodiments, each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material. In some embodiments, each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack. In some embodiments, each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits a time that the incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel. In some embodiments, the computer implemented method further comprises calculating the incident gamma photon angle with respect to the vertical stack by measuring an angle shift (e.g., due to Compton scattering) of theincident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack.

[0255] In certain embodiments, the computer implemented method uses gamma photon count data from chip-based gamma photon counters comprising a plurality of detectors in a planar arrangement in a spatial area, wherein the computer implemented method further comprises determining energies of incoming gamma photons in the spatial area.

[0256] In certain embodiments, the computer implemented method further comprises segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid locations of each gamma photon counter are segmented. Any suitable method known in the art can be used for image segmentation. Various software programs are currently available for image segmentation, including, but not limited to, the llastik Toolkit, which uses a random forest classifier for cell segmentation, DeepCell, which uses a deep-learning algorithm utilizing deep convolutional neural networks for cell segmentation, Open Segmentation Framework (OpSeF), which semi-automates image segmentation using deep learning convolutional neural networks with the user manually providing some training data, CellSeg, which uses a mask region-convolutional neural network (R-CNN) for image segmentation, CODEX image processing pipeline software, which uses reference cellular markers, a reference nuclear stain, and a reference membrane stain to aid image segmentation, and CellProfiler, which uses conventional thresholding to classify a pixel as foreground if it is brighter than a certain “threshold” intensity value, illumination correction, declustering, and watershed segmentation to identify cells in images. For a description of image segmentation techniques and software, see, e.g., Kreshuk et al. (2019) Methods Mol. Biol. 2040:449-463, Kreshuk et al. (2014) PLoS One 9(2):e87351 , David A. Van Valen et al. (2016) PLoS Comput. Biol. 12(1 1 ):e1005177, Dobson et al. (2021 ) Curr. Protoc. 1 (5):e89, Stirling et al. (2021 ) BMC Bioinformatics 22(1 ):433, Soliman (2015) Biol Proced Online 17:11 , Schapiro et al. (2017) Nat. Methods 14:873-876, Ljosa et al. (2009) PLoS Comput. Biol. 5(12):e1000603, and Lee et al. (2022) BMC Bioinformatics 23(1 ):46; herein incorporated by reference. The image of the tumors and organs at risk in a subject may be obtained by any suitable medical imaging technique, including, without limitation, positron emission tomography (PET), computed tomography (CT), and single photon emission computed tomography (SPECT).

[0257] The methods can be implemented in digital electronic circuitry, or in computer software, firmware, or hardware. The disclosed and other embodiments can be implemented as one or more computer program products, i.e., one or more modules of computer program instructions encoded on a computer readable medium for execution by, or to control the operation of, a data processing apparatus. The computer readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of matter effecting a machine-readable propagated signal, or any combination thereof.

[0258] A computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code). A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

[0259] In a further aspect, the system for performing the computer implemented method, as described, may include a processor, a storage component (i.e., memory), a display component, and other components typically present in general purpose computers. In some embodiments, the various steps, components, and computing systems described in connection with the embodiments disclosed herein are implemented or performed by a machine, such as a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor can be a microprocessor, but in the alternative, the processor can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. A processor can include primarily digital or analog components. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a graphics processor unit, a mainframe computer, a digital signal processor, a portable computing device, a personal organizer, a device controller, and a computational engine within an appliance, among others.

[0260] The steps of a method, process, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module, engine, and associated databases can reside in memory resources such as in RAM memory, FRAM memory, flash memory, ROMmemory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of non-transitory computer-readable storage medium, media, or physical computer storage known in the art. An exemplary storage medium can be coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor and the storage medium can reside as discrete components in a user terminal.

[0261] The storage component stores information accessible by the processor, including instructions that may be executed by the processor and data that may be retrieved, manipulated or stored by the processor. The storage component includes instructions, including instructions for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject. The computer processor is coupled to the storage component and configured to execute the instructions stored in the storage component in order to receive count data from a plurality of counters and an image of one or more tumors and organs at risk in the subject and analyze the data and image according to one or more algorithms, as described herein.

[0262] The display component displays the total %IA / ml for the one or more tumors and organs at risk in the subject. In some embodiments, the display further displays an image of the tumors and organs at risk along with boundary lines surrounding each tumor and organ at risk and mapped centroid locations for each counter superimposed on the image. In some embodiments, the display further shows the distribution of radionuclide point sources (e.g., gamma photon-emitting or particleemitting radionuclide point sources) within the boundaries of each tumor and organ at risk, as determined by distributed point source (DPS) modelling. In addition, the display may further show labels with information regarding the tumors and organs at risk superimposed on the image. In some embodiments, the labels are color coded to differentiate different tumors and / or organs at risk.

[0263] The instructions may be any set of instructions to be executed directly (such as machine code) or indirectly (such as scripts) by the processor. In that regard, the terms "instructions," "steps" and "programs" may be used interchangeably herein. The instructions may be stored in object code form for direct processing by the processor, or in any other computer language including scripts or collections of independent source code modules that are interpreted on demand or compiled in advance.

[0264] Data may be retrieved, stored or modified by the processor in accordance with the instructions. For instance, although the system is not limited by any particular data structure, the data may be stored in computer registers, in a relational database as a table having a plurality of different fields and records, XML documents, or flat files. The data may also be formatted in anycomputer-readable format such as, but not limited to, binary values, ASCII or Unicode. Moreover, the data may comprise any information sufficient to identify the relevant information, such as numbers, descriptive text, proprietary codes, pointers, references to data stored in other memories (including other network locations) or information which is used by a function to calculate the relevant data.

[0265] In certain embodiments, the processor and storage component may comprise multiple processors and storage components that may or may not be stored within the same physical housing. For example, some of the instructions and data may be stored on removable CD-ROM and others within a read-only computer chip. Some or all of the instructions and data may be stored in a location physically remote from, yet still accessible by, the processor. Similarly, the processor may comprise a collection of processors which may or may not operate in parallel.

[0266] In some embodiments, the method can be performed using a cloud computing system. In these embodiments, gamma photon count data files, images of patients obtained by medical imaging, and the programming can be exported to a cloud computer, which runs the program, and returns an output to the user.

[0267] Components of systems for carrying out the presently disclosed methods are further described in the examples below.Kits

[0268] Also provided are kits comprising a wearable gamma photon counter system comprising a plurality of counters (e.g., optical fiber-based gamma photon counters or chip-based gamma photon counters) for monitoring radioactivity delivered to tumors and organs at risk in a subject from radiopharmaceutical therapy or imaging, as described herein. In some embodiments, the kit comprises software for carrying out the computer implemented methods, described herein, for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and organs at risk in a subject. In some embodiments, the kit comprises a non-transitory computer- readable medium and instructions for calculating the total %IA / ml for the one or more tumors and organs at risk in a subject, as described herein. In some embodiments, the kit comprises a system comprising a processor programmed to calculate the total %IA / ml for one or more tumors and organs at risk in a subject according to a computer implemented method described herein; and a display component for displaying the %IA / ml for the one or more tumors and organs at risk in the subject

[0269] In certain embodiments, the kit comprises an optical fiber-based gamma photon counter comprising: a Y203-Eu-doped phosphor, wherein a y-photon incident on the surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum, suitable for solid-statephoton detection; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3-EU doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.

[0270] In certain embodiments, the kit comprises a chip-based gamma photon counter comprising: a detector implemented as an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises at least one reverse biased diode, wherein a y-photon incident on the surface of the reverse biased diode generates a voltage pulse across the reverse biased diode. In some embodiments the reverse biased diode is connected to an amplifier and then a digital counter. In other embodiments, the reverse biased is connected to a voltage buffer before being connected to a voltage amplifier and subsequently connected to a digital counter. The digital counter counts y- photon detection events, wherein each y-photon detection event corresponds to the voltage pulse generated across the reverse biased diode by each y-photon incident on the surface. In some embodiments, the chip further comprises an on-chip memory configured to store a plurality of gamma photon count records for a plurality of y-photon detection events. In some embodiments, the chip further comprises a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time. In some embodiments, the chip further comprises custom digital logic circuitry, wherein the digital logic circuitry is configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0271] In certain embodiments, the kit comprises a chip-based gamma photon counter comprising: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements. In some embodiments, each pixel in the array comprises two silicon diodes connected to an amplifier, wherein an incident gamma photon breaks bonds in the silicon, generating electron-hole pairs that in turn generate a pulse of charge (Qp) in the silicon diode, which is accumulated on a parasitic diode capacitor (Cdiode). This generates a small voltage pulse across the diode (Vp= Qp / Cdiode). The use of integrated circuit technology enables ultra-small diode capacitances, increasing Vp, and allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity gain voltage amplifier. Each of these buffered outputs connects to the inputsof a differential amplifier. To mitigate DC voltage offset at the output due to fabrication variability from pixel-to-pixel and chip-to-chip that may cause variability in detector sensitivity, a voltage integrator is bootstrapped from the output of the amplifier to one of it’s inputs in a negative feedback configuration. The voltage integrator also accepts a desired DC voltage that sets the voltage at the output of the amplifier. This ensures that the sensitivity of each of the pixels across the chip is approximately the same. In order to tune each diode in each pixel to a desired sensitivity, the output of the amplifier is connected to two level shifters: one that shifts the DC level of the amplifier output up to only amplify the voltage pulse from the first diode, and the other that shifts the DC level of the amplifier output down to only amplify the voltage pulse from the second diode. The amounts these DC levels are shifted are set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert the bits stored into an analog shift in voltage. These shifted and amplified voltage pulses are then digitized using a series of inverters. Capacitors at the inputs of the last inverters increase signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of either silicon diode. The chip also comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0272] In certain embodiments, the kit comprises a chip-based gamma photon counter comprising: a detector implemented as an ASIC on a chip, wherein the detector comprises an array of pixels that are each gamma sensing elements, wherein each pixel comprises a reverse-biased silicon diode connected to a unity gain voltage buffer. Buffered voltage output from the unity gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed-loop amplifier is either pre-set or configurable using in-pixel memory and DAC. A y-photon incident on a surface of the silicon diode generates a voltage pulse across the diode and is subsequently buffered and amplified by a fixed, process-invariant gain. This voltage pulse is then digitized using a series of inverters, which are connected to digital counters to quantify the total number of gamma photons detected in a certain time frame. Each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of the silicon diode. The chip further comprises an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on thechip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and custom digital logic circuitry configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0273] In certain embodiments the kit comprises a wearable structure comprising a plurality of gamma photon counters (e.g., optical fiber-based gamma photon counters or chip-based gamma photon counters). In some embodiments, the wearable structure is clothing such as a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve. The choice of clothing type will depend on the location of the tumors in the subject. For example, a vest or shirt comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by tumors in the lungs, stomach, intestines, bladder, prostate, and the like. Pants comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by tumors in the legs. A hat comprising a plurality of counters may be suitable for detecting uptake of a radiopharmaceutical comprising a gammaemitting radionuclide by tumors in the brain. In certain embodiments, a first subset of the plurality of gamma photon counters is arranged on the wearable structure such that when the wearable structure is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject; and a second subset of the plurality of gamma photon counters is arranged on the wearable structure such that when the wearable structure is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject. In certain embodiments, the positioning of each gamma photon counter of the first subset on the wearable structure is determined based on medical imaging of the subject to determine where the tumor is located in the subject and positioning of each gamma photon counter of the second subset on the wearable structure is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject. In some embodiments, the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT). In certain embodiments, the plurality of gamma photon counters is arranged in an array on the wearable structure.

[0274] In certain embodiments the kit further comprises a plurality of adhesive patches for attaching a plurality of counters (e.g., optical fiber-based gamma photon counters or chip-based gamma photon counters) to the skin.

[0275] In addition to the above components, the subject kits may further include (in certain embodiments) instructions for practicing the subject methods. These instructions may be present in the subject kits in a variety of forms, one or more of which may be present in the kit. One form in which these instructions may be present is as printed information on a suitable medium or substrate, e.g., a piece or pieces of paper on which the information is printed, in the packaging of the kit, in a package insert, and the like. Yet another form of these instructions is a computer readable medium, e.g., diskette, compact disk (CD), flash drive, and the like, on which the information has been recorded. Yet another form of these instructions that may be present is a website address which may be used via the internet to access the information at a removed site.Examples of Non-Limiting Aspects of the Disclosure

[0276] Aspects, including embodiments, of the present subject matter described above may be beneficial alone or in combination, with one or more other aspects or embodiments. Without limiting the foregoing description, certain non-limiting aspects of the disclosure numbered 1 -177 are provided below. As will be apparent to those of skill in the art upon reading this disclosure, each of the individually numbered aspects may be used or combined with any of the preceding or following individually numbered aspects. This is intended to provide support for all such combinations of aspects and is not limited to combinations of aspects explicitly provided below.1 . A gamma photon counter comprising: a Y2C>3-Eu-doped phosphor, wherein a y-photon incident on a surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3- Eu doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.2. The gamma photon counter of aspect 1 , wherein the photodiode is an avalanche photodiode (APD).3. The gamma photon counter of aspect 2, wherein the APD is a silicon APD.4. The gamma photon counter of aspect 1 , wherein the photodiode is a single photon avalanche diode (SPAD).5. The gamma photon counter of any one of aspects 1 -4, wherein the detector further comprises multiple power supplies to control circuit cooling, quenching and reset, and high voltage biasing.6. The gamma photon counter of aspect 5, wherein the multiple power supplies comprise a 2 volt power supply to control the circuit cooling, a 5 volt power supply to control the quenching and reset, and a 30 volt power supply to control the high voltage biasing.7. The gamma photon counter of any one of aspects 1 -6, wherein the detector further comprises a high voltage regulator.8. The gamma photon counter of any one of aspects 1 -7, wherein the opaque material has an optical density (OD) of at least 4.9. The gamma photon counter of aspect 8, wherein the opaque material is a black lightabsorbing material.10. The gamma photon counter of aspect 9, wherein the black light-absorbing material is black optical tape.11 . The gamma photon counter of any one of aspects 1 -10, wherein the scintillation light is red visible light.12. The gamma photon counter of aspect 11 , wherein the red visible light has a wavelength of about 610 nm.13. The gamma photon counter of any one of aspects 1 -12, wherein incoming gamma photons reaching the surface of the detector are uncollimated.14. The gamma photon counter of any one of aspects 1 -13, wherein the digital counter is configured in a field-programmable gate array (FPGA).15. The gamma photon counter of any one of aspects 1 -14, wherein the digital counter has a sampling frequency of at least 150 MHz.16. The gamma photon counter of any one of aspects 1 -16, further comprising a clock configured to produce a clock signal, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time.17. The gamma photon counter of aspect 16, wherein the period of time is one second.18. The gamma photon counter of any one of aspects 1 -17, further comprising a level shifter, wherein the level shifter is configured in circuitry to ensure logic level compatibility with the digital counter.19. The gamma photon counter of aspect 18, wherein the level shifter is a 1 -bit level shifter.20. The gamma photon counter of any one of aspects 1 -19, further comprising a data storage unit in communication with the digital counter, wherein the data storage unit is configured to store a plurality of gamma photon count records for a plurality of y-photon detection events.21 . The gamma photon counter of aspect 20, further comprising a data processing unit in communication with the data storage unit, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.22. The gamma photon counter of any one of aspects 1 -21 , wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.23. The gamma photon counter of aspect 22, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL24. The gamma photon counter of any one of aspects 1 -23, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.25. The gamma photon counter of aspect 24, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.26. The gamma photon counter of aspect 24, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.27. The gamma photon counter of any one of aspects 1 -26, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.28. The gamma photon counter of aspect 28, wherein the gamma photon counter is attached to a fabric or an adhesive patch.29. The gamma photon counter of any one of aspects 1-28, wherein the gamma photon counter is attached to a wearable structure.30. The gamma photon counter of aspect 29, wherein the wearable structure is clothing.31 . The gamma photon counter of aspect 30, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.32. The gamma photon counter of any one of aspects 1-31 , wherein the gamma photon counter has a diameter less than or equal to 2.5 mm.33. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises a reverse biased diode, wherein a y-photon incident on a surface of the reverse biased diode generates a voltage pulse across the reverse biased diode;a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of the reverse biased diode; an on-chip memory configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and a custom digital logic circuitry on the chip, wherein the custom digital logic circuitry is configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.34. The gamma photon counter of aspect 33, further comprising a voltage amplifier configured in circuitry between the reverse biased diode and the digital counter.35. The gamma photon counter of aspect 34, further comprising a voltage buffer configured in circuitry between the reverse biased diode and the voltage amplifier.36. The gamma photon counter of any one of aspects 33-35, wherein the on-chip memory is static random-access memory (SRAM).37. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a silicon diode, wherein a Y-photon incident on a surface of the silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential closed-loop amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential closed-loop amplifier, wherein voltage gain is either pre-set or configurable using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified by a fixed process-invariant gain;an inverter chain comprising a plurality of inverters connected to amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of the silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.38. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a pair of silicon diodes comprising a first silicon diode and a second silicon diode, wherein a y-photon incident on a surface of either the first silicon diode or the second silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential amplifier; a voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets voltage output of the differential amplifier, wherein the voltage integrator is bootstrapped from the differential amplifier output to the differential amplifier input in a negative feedback configuration; a pair of level shifters connected to output of the differential amplifier, wherein the pair of level shifters comprises two level shifters comprising a first level shifter that shifts a direct current (DC) level of the output of the differential amplifier up to amplify only the voltage pulse from the first diode, and a second level shifter that shifts the DC level of the differential amplifier output down to only amplify the voltage pulse from the second diode, wherein an amount the DC level is shifted is setusing on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert stored bits into an analog shift in voltage; an inverter chain comprising a plurality of inverters connected to amplified and shifted voltage output from the pair of level shifters, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of either the first silicon diode or the second silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.39. The gamma photon counter of aspect 37 or 38, wherein the silicon diodes are reversed biased or have zero voltage bias.40. The gamma photon counter of any one of aspects 37-39, wherein the detector is optimized for sensitivity by decreasing the capacitance of the silicon diodes.41 . The gamma photon counter of any one of aspects 33-40, wherein the diode size is 0.1 pm to 0.5 |im x 0.1 pm to 0.5 |im or 0.5 pm to 1 pm x 0.5 pm to 1 pm.42. The gamma photon counter of any one of aspects 33-41 , wherein the diode size is the smallest size available for use in a complementary metal-oxide-semiconductor (CMOS) process.43. The gamma photon counter of any one of aspects 37-42, wherein the detector is optimized with a tradeoff between pixel fill factor and sensitivity.44. The gamma photon counter of aspect 43, wherein the diode size is 1 pm to 1 .5 pm x 1 pm to 1.5 pm.45. The gamma photon counter of any one of aspects 37-42, wherein the detector is optimized to increase fill factor with a tradeoff in sensitivity.46. The gamma photon counter of aspect 45, wherein the diode size is 1 .5 pm to 3 pm x 1 .5 pm to 3 pm, 3 pm to 10 pm x 3 pm to 10 pm, or 10 pm to 50 pm x 10 pm to 50 pm.47. The gamma photon counter of any one of aspects 33-46, wherein the detector has a curved shape or a polygonal shape.48. The gamma photon counter of aspect 47, wherein the polygonal shape is a triangular, square, rectangular, pentagonal, hexagonal, octagonal, diamond, or parallelogram shape.49. The gamma photon counter of aspect 47, wherein the curved shape is circular, semicircular, oval, spherical, or cylindrical.50. The gamma photon counter of any one of aspects 47-49, wherein the detector has sides ranging from 0.1 pm to 50 pm in length.51 . The gamma photon counter of any one of aspects 37-50, wherein the pixels in the array of pixels operate asynchronously.52. The gamma photon counter of any one of aspects 33-51 , wherein the chip is covered with a Compton scattering material.53. The gamma photon counter of aspect 52, wherein the Compton scattering material comprises lead, tungsten, or bismuth.54. The gamma photon counter of aspect 52 or 53, wherein the Compton scattering material is in a layer on top of the detector or on the back of the detector.55. The gamma photon counter of any one of aspects 37-54, further comprising on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons such that combination and distribution of signals from pixels with known LET responsivity enables determination of incident energies of the incoming gamma photons.56. The gamma photon counter of aspect 55, wherein the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET.57. The gamma photon counter of any one of aspects 33-56, wherein the chip comprises a plurality of detectors.58. The gamma photon counter of aspect 57, wherein each detector of the plurality comprises an attenuating material of a different thickness to allow resolution of incoming gamma photons having different energies.59. The gamma photon counter of aspect 58, wherein the attenuating material is lead, tungsten, bismuth, or iron.60. The gamma photon counter of aspect 58 or 59, wherein the plurality of detectors is arranged in a vertical stack.61 . The gamma photon counter of aspect 60, wherein each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material.62. The gamma photon counter of aspect 60 or 61 , wherein each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack.63. The gamma photon counter of aspect 62, wherein each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits a time thatthe incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel.64. The gamma photon counter of aspect 63, wherein an angle shift of the incident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack due to Compton scattering can be used to calculate the incident gamma photon angle with respect to the vertical stack.65. The gamma photon counter of any one of aspects 60-64, wherein the plurality of detectors is stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm, greater than or equal to 1 mm and less than 3 mm, or greater than or equal to 0.1 mm and less than 1 mm.66. The gamma photon counter of any one of aspects 60-65, wherein the vertical stack has a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm.67. The gamma photon counter of aspect 57 or 58, wherein the plurality of detectors is in a planar arrangement in a spatial area to allow said resolution of incoming gamma photons having different energies in the spatial area.68. The gamma photon counter of any one of aspects 33-67, wherein the chip has a surface area of less than or equal to 1 mm2.69. The gamma photon counter of any one of aspects 33-68, wherein the chip has a thickness of less than or equal to 1 cm, less than or equal to 5 mm, less than or equal to 3 mm, less than or equal to 1 mm, or less than or equal to 0.5 mm.70. The gamma photon counter of any one of aspects 33-69, wherein the clock signal is generated by a frequency locked loop (FLL) oscillator or an external computer, FPGA, tablet, cellular phone, or other control device.71. The gamma photon counter of aspect 70, further comprising an off-chip crystal oscillator, wherein a clock beacon to the FLL oscillator is generated by the off-chip crystal oscillator.72. The gamma photon counter of any one of aspects 33-69, further comprising an off- chip crystal oscillator, wherein the clock signal is generated directly from the off-chip crystal oscillator.73. The gamma photon counter of any one of aspects 33-72, wherein the on-chip energy storage device or the off-chip energy storage device comprises a battery, a capacitor, or a photovoltaic system.74. The gamma photon counter of aspect 73, wherein the battery is rechargeable.75. The gamma photon counter of any one of aspects 33-74, further comprising a data processing unit in communication with the on-chip memory or the on-chip data buffer, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.76. The gamma photon counter of any one of aspects 33-75, wherein the detector further detects electrons generated by gamma photons.77. The gamma photon counter of aspect 76, wherein the electrons are generated in a subject administered a radiopharmaceutical comprising a gamma-emitting radionuclide, in a layer of material positioned between the detector and the subject administered the radiopharmaceutical comprising the gamma-emitting radionuclide, or in silicon of the diodes of the detector.78. The gamma photon counter of any one of aspects 1 -77, wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.79. The gamma photon counter of aspect 78, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL80. The gamma photon counter of any one of aspects 1 -79, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.81 . The gamma photon counter of aspect 80, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.82. The gamma photon counter of aspect 80, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.83. The gamma photon counter of any one of aspects 1 -82, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.84. The gamma photon counter of any one of aspects 1-83, wherein the gamma photon counter is attached to a fabric or an adhesive patch.85. The gamma photon counter of any one of aspects 1-84, wherein the gamma photon counter is attached to a wearable structure.86. The gamma photon counter of aspect 85, wherein the wearable structure is clothing.87. The gamma photon counter of aspect 86, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.88. The gamma photon counter of any one of aspects 1-87, wherein the gamma photon counter is connected by a wire to a power source, a control source, and a data collection unit.89. The gamma photon counter of aspect 88, wherein the control source is a field programmable gate array (FGPA), a computer, a laptop, or a smartphone.90. The gamma photon counter of any one of aspects 1-89, wherein the gamma photon count data is uploaded wirelessly to a computer or a cloud server.91 . A wearable system comprising a plurality of gamma photon counters of any one of aspects 1 -90 attached to a wearable structure.92. The wearable system of aspect 91 , wherein the wearable structure is clothing or adhesive patches.93. The wearable system of aspect 92, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.94. The wearable system of aspect 92 or 93, wherein a first subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject; and wherein a second subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject.95. The wearable system of aspect 94, wherein positioning of each gamma photon counter on the clothing is determined based on medical imaging of the subject to determine where the tumor is located in the subject and positioning of each gamma photon counter of the second subset on the clothing is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.96. The wearable system of aspect 95, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).97. The wearable system of any one of aspects 92-96, wherein the plurality of gamma photon counters is arranged in an array on the clothing.98. The wearable system of aspect 92, wherein each gamma photon counter of the plurality is attached to skin of the subject using the adhesive patches.99. The wearable system of any one of aspects 91 -98, wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.100. The wearable system of aspect 99, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.101. The wearable system of aspect 99, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.102. A computer implemented method for calculating total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject, the computer performing steps comprising: a) receiving gamma photon count data from a plurality of gamma photon counters, wherein each gamma photon counter has a known location; b) receiving an image of the subject, wherein the image shows locations of the one or more tumors and the one or more organs at risk in the subject, and locations of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) measuring volumes of the one or more tumors and organs at risk using the image; e) mapping centroid locations of each gamma photon counter on the image; f) performing distributed point source (DPS) modelling to generate a distribution of gamma photon-emitting point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) calculate probabilities for each gamma photon counter that the gamma photons, counted by the gamma photon counter, were received from a gamma photon emitting point source within the boundaries of a particular tumor or organ at risk based on an assumption that counts per second (CPS) falloff correlates with 1 / (distance between the centroid location of the gamma photon counter and the gamma photon emitting point source)2and CPS values are attenuated by an empirically derived factor Q which accounts for attenuation and scattering of gamma photons in tissue, and ii) estimate probable fractions of counts counted by each gamma photon counter that correspond to a particular tumor or organ at risk; g) estimating total counts for each tumor and organ at risk using a Monte Carlo Markov Chain (MCMC) algorithm based on the gamma photon count data from the plurality of counters and parameter estimates of the probable fractions of counts counted by each gamma photo counter that correspond to a particular tumor or organ at risk from the DPS modelling; h) calculating the total %IA / ml for the one or more tumors and organs at risk in the subject based on said estimating the total counts for each tumor and organ at risk and dividing by the volumes of the one or more tumors and organs at risk measured from the image; andi) displaying the total %IA / mL for the one or more tumors and the one or more organs at risk in the subject.103. The computer implemented method of aspect 102, wherein said performing DPS modelling comprises: creating a DPS model matrix ( W) denoting the counts per second (CPS) per pCi contributed from each tumor or organ at risk to each gamma photon counter of the plurality, wherein the CPS per pCi are multiplied by an unknown activity in pCi of the total tumor or total organ at risk activity in pCi, wherein values in the DPS model matrix ( HZ) are estimated based on knowledge of the location of each tumor and each organ at risk from the image and the known locations of each gamma photon counter; and decomposing the DPS model matrix ( l / l / ) into a matrix ( / 3) and a vector (a), wherein the matrix (J3) denotes the fraction of each gamma photon counter’s CPS that comes from a certain tumor or organ at risk, wherein the fraction is scaled up by the vector (or), wherein the vector (a) is each gamma photon counter’s CPS per injected pCi of activity.104. The computer implemented method of aspect 103, wherein the vector a is estimated by conducting a DPS titration simulation.105. The computer implemented method of aspect 103 or 104, wherein the matrix ( / 3) is initially estimated by i) assuming each tumor and each organ at risk uptakes an equal amount of the radionuclide, wherein the total amount of the radionuclide administered to the subject is known, and ii) assigning the same activity to all of the tumors and organs at risk for said estimating the probable fractions of counts counted by each counter that correspond to a particular tumor or organ at risk.106. The computer implemented method of any one of aspects 102-105, further comprising using adaptive Metropolis (AM) optimization, wherein a Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm.107. The computer implemented method of any one of aspects 102-106, further comprising performing iterative optimization by a method comprising using gradient descent, least squares minimization, or brute force global minimization, or a combination thereof.108. The computer implemented method of any one of aspects 102-107, wherein the empirically derived factor Q is determined by a method comprising: measuring detected CPS for each gamma photon counter at different distances in water from a gamma photon emitting point source; measuring detected CPS for each gamma photon counter at different distances in air from the gamma photon emitting point source; deriving a non-linear factor representing scattering and attenuation for each gamma photon emitting point source based on differences between the CPS detected in water and air at each distance; and using the non-linear factor to calculate a unique factor Q for each gamma photon emitting point source in the subject based on distances in tissue between each gamma photon counter and each gamma photon emitting point source.109. The computer implemented method of any one of aspects 102-108, further comprising segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid locations of each gamma photon counter are segmented.110. The computer implemented method of any one of aspects 102-109, wherein each gamma photon counter of the plurality comprises: a Y203-Eu-doped phosphor, wherein a y-photon incident on a surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3- Eu doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.11 1. The computer implemented method of any one of aspects 102-109, wherein each gamma photon counter of the plurality comprises:a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a silicon diode, wherein a y-photon incident on a surface of the silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential closed-loop amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential closed-loop amplifier, wherein voltage gain is either pre-set or configurable using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified by a fixed process-invariant gain; an inverter chain comprising a plurality of inverters connected to amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of the silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.112. The computer implemented method of any one of aspects 102-109, wherein each gamma photon counter of the plurality comprises: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a pair of silicon diodes comprising a first silicon diode and a second silicon diode, wherein a y-photon incident on a surface of either the first silicon diode or the second silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse;a unity gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential amplifier; a voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets voltage output of the differential amplifier, wherein the voltage integrator is bootstrapped from the differential amplifier output to the differential amplifier input in a negative feedback configuration; a pair of level shifters connected to output of the differential amplifier, wherein the pair of level shifters comprises two level shifters comprising a first level shifter that shifts a direct current (DC) level of the output of the differential amplifier up to amplify only the voltage pulse from the first diode, and a second level shifter that shifts the DC level of the differential amplifier output down to only amplify the voltage pulse from the second diode, wherein an amount the DC level is shifted is set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert stored bits into an analog shift in voltage; an inverter chain comprising a plurality of inverters connected to amplified and shifted voltage output from the pair of level shifters, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of either the first silicon diode or the second silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.113. The computer implemented method of aspect 111 or 112, wherein the plurality of gamma photon counters comprises on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons, wherein the computer implemented method further comprises calculating incident energies of the incoming gamma photons based on combination and distribution of signals from pixels with known LET responsivity.114. The computer implemented method of aspect 1 13, wherein the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET.115. The computer implemented method of any one of aspects 102-114, wherein the plurality of gamma photon counters comprises a plurality of detectors, wherein each detector of the plurality comprises an attenuating material of a different thickness to allow resolution of incoming gamma photons having different energies, wherein the computer implemented method further comprises calculating likelihood of detecting a gamma photon of a certain energy with each detector of the plurality using a multiphysics simulation to separate detected counts of each detector by gamma photon energy.116. The computer implemented method of aspect 115, wherein the attenuating material is lead, tungsten, bismuth, or iron, wherein the likelihood of detecting a photon of a certain energy with a detector of a certain thickness of lead, tungsten, or iron is calculated using the multiphysics simulation.117. The computer implemented method of aspect 115 or 116, wherein the plurality of detectors is arranged in a vertical stack.118. The computer implemented method of aspect 117, wherein each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material.119. The computer implemented method of aspect 117 or 1 18, wherein each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack.120. The computer implemented method of aspect 119, wherein each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits a time thatthe incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel.121. The computer implemented method of aspect 120, further comprising calculating the incident gamma photon angle with respect to the vertical stack by measuring an angle shift of the incident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack due to Compton scattering.122. The computer implemented method of any one of aspects 1 17-121 , wherein the plurality of detectors is stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm, or greater than or equal to 1 mm and less than 3 mm, or greater than or equal to 0.1 mm and less than 1 mm.123. The computer implemented method of any one of aspects 117-122, wherein the vertical stack has a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm.124. The computer implemented method of aspect 115, wherein the plurality of detectors is in a planar arrangement in a spatial area, wherein the computer implemented method further comprises determining energies of incoming gamma photons in the spatial area.125. A non-transitory computer-readable medium comprising program instructions that, when executed by a processor in a computer, causes the processor to perform the method of any one of aspects 102-124.126. A kit comprising the non-transitory computer-readable medium of aspect 125 and instructions for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject.127. A system comprising : a) a plurality of gamma photon counters attached to a wearable structure; b) a power source;c) a processor, wherein the processor is programmed to calculate the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject according to the computer implemented method of any one of aspects 102-124; d) an external data receiving device connected to the processor, wherein the external data receiving device receives the gamma photon count data from the plurality of gamma photon counters and transmits the gamma photon count data to the processor; and e) a display component that displays the %IA / mL for one or more tumors and one or more organs at risk in a subject.128. The system of aspect 127, wherein the plurality of gamma photon counters is attached to clothing or adhesive patches.129. The system of aspect 128, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.130. The system of aspect 128 or 129, wherein a first subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each gamma photon counter of the first subset on the clothing is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters is arranged on the clothing such that when the wearable material is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset on the clothing is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.131. The system of aspect 128, wherein the plurality of gamma photon counters is arranged in an array on the clothing.132. The system of aspect 128, wherein each gamma photon counter of the plurality can be attached to skin of a subject using the adhesive patches.133. The system of aspect 132, wherein a first subset of the plurality of gamma photon counters can be attached to the skin of the subject with adhesive patches such that the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each gamma photon counter of the first subset with the adhesive patches is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters can be attached to the skin of the subject with adhesive patches such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset with the adhesive patches is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.134. The system of any one of aspects 127-133, wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.135. The system of aspect 134, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.136. The system of aspect 134, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.137. The system of any one of aspects 130-136, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).138. The system of any one of aspects 127-137, wherein the power source is an external power source, an internal power source, or a combination thereof.139. The system of aspect 138, wherein the external power source is an ultrasound transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radiofrequency (RF) transducer.140. The system of aspect 138, wherein the internal power source comprises a battery, a radionuclide, or a photovoltaic system.141. The system of any one of aspects 127-140, wherein the power source is used to provide power to the detector.142. The system of any one of aspects 138 or 139, wherein the external power source is portable.143. The system of any one of aspects 127-142, wherein the external data receiving device comprises a wireless communication unit.144. The system of aspect 143, wherein the wireless communication unit utilizes a wireless communication protocol using an electromagnetic carrier wave or ultrasound to receive data from the internal data storage unit.145. The system of aspect 144, wherein the electromagnetic carrier wave is a radio wave, microwave, or an infrared carrier wave.146. The system of any one of aspects 127-145, wherein the processor is provided by a computer or handheld device.147. The system of aspect 146, wherein the handheld device is a cell phone or tablet.148. The system of any one of aspects 127-147, wherein the display further displays an image of the tumors and organs at risk obtained by medical imaging of the subject.149. The system of any one of aspects 127-148, wherein the display further displays the centroid locations of each gamma photon counter superimposed on the image.150. The system of any one of aspects 127-149, wherein the display further displays the boundary lines surrounding each tumor and organ at risk superimposed on the image.151 . The system of any one of aspects 127-150, wherein the display further displays the distribution of gamma photon-emitting point sources according to the distributed point source (DPS) modelling superimposed on the image.152. The system of any one of aspects 127-151 , wherein the display further displays labels with information regarding the tumors and organs at risk superimposed on the image.153. The system any one of aspects 127-152, wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.154. The system of aspect 153, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL155. The system of any one of aspects 127-154, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.156. The system of aspect 155, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.157. The system of aspect 155, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.158. The system of any one of aspects 127-157, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.159. A method of using the system of any one of aspects 127-158 for measuring tumor uptake of radiopharmaceutical comprising a gamma-emitting radionuclide in a subject, the method comprising: performing medical imaging to identify locations of one or more tumors and one or more organs at risk in the subject; positioning a first subset of the plurality of gamma photon counters on the wearable structure such that the first subset of gamma photon counters can monitor the uptake of theradiopharmaceutical comprising the gamma-emitting radionuclide by the one or more tumors in the subject; positioning a second subset of the plurality of gamma photon counters on the wearable structure such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by the one or more organs at risk in the subject; and calculating the total percent injected activity per milliliter of tissue (%IA / mL) for the one or more tumors and the one or more organs at risk in the subject according to the computer implemented method.160. The method of aspect 159, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).161. The method of aspect 159 or 160, wherein the y-photon is emitted from a gamma rayemitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.162. The method of aspect 161 , wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL163. The method of any one of aspects 159-162, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.164. The method of aspect 163, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.165. The method of aspect 163, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.166. The method of any one of aspects 159-165, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.167. The method of any one of aspects 159-166, further comprising placing fiducial stickers on skin of the subject at planned locations for said positioning of the plurality of gamma photon counters.168. The method of aspect 167, wherein the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters on the wearable structure.169. The method of any one of aspects 159-168, wherein the wearable structure is clothing or adhesive patches.170. The method of aspect 169, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.171. The method of aspect 169, wherein the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters using a plurality of adhesive patches to adhere the plurality of gamma photon counters to the skin of the subject.172. The method of any one of aspects 159-171 , wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.173. The method of aspect 172, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.174. The method of aspect 172, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.175. The method of any one of aspects 159-174, wherein the method is performed during or after administering the radiopharmaceutical to the subject.176. The method of aspect 175, wherein the radiopharmaceutical is a radioactive drug, a radioimmunotherapeutic agent, or a radiopeptide.177. The method of aspect 176, wherein the radiopharmaceutical is177Lu-PSMA-617 or 225Ac-PSMA-617 administered to the subject for treatment of prostate cancer.

[0277] It will be apparent to one of ordinary skill in the art that various changes and modifications can be made without departing from the spirit or scope of the invention.EXPERIMENTAL

[0278] The following examples are put forth so as to provide those of ordinary skill in the art with a complete disclosure and description of how to make and use the present invention, and are not intended to limit the scope of what the inventors regard as their invention nor are they intended to represent that the experiments below are all or the only experiments performed. Efforts have been made to ensure accuracy with respect to numbers used (e.g. amounts, temperature, etc.) but some experimental errors and deviations should be accounted for. Unless indicated otherwise, parts are parts by weight, molecular weight is weight average molecular weight, temperature is in degrees Centigrade, and pressure is at or near atmospheric.

[0279] All publications and patent applications cited in this specification are herein incorporated by reference as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference.

[0280] The present invention has been described in terms of particular embodiments found or proposed by the present inventor to comprise preferred modes for the practice of the invention. It will be appreciated by those of skill in the art that, in light of the present disclosure, numerous modifications and changes can be made in the particular embodiments exemplified without departing from the intended scope of the invention. For example, due to codon redundancy, changes can be made in the underlying DNA sequence without affecting the protein sequence. Moreover, due to biological functional equivalency considerations, changes can be made in protein structure without affecting the biological action in kind or amount. All such modifications are intended to be included within the scope of the appended claims.Example 1A Sparse Uncollimated v Counting Network for Continuous, Real-Time Dose Reconstruction in Radiopharmaceutical TherapyIntroduction

[0281] Treatment of widespread, metastatic disease in cancer remains an unmet need. Radiation therapy is widely effective when directed at tumors at sufficient doses, either ablating them or hindering their growth. However, conventional, external beam-based methods of delivering radiotherapy to many sites in the body suffer from excessive dose to normal tissue, precluding use in widely disseminated metastatic disease. Radiopharmaceutical therapy (RPT) offers a drastically different method of radiation delivery by linking a radioactive isotope to a molecule targeting the tumor to selectively radiate cancer cells systemically, while sparing most normal tissues. Recently, this has shown promise in metastatic castration-resistant prostate cancer (mCRPC).

[0282] Virtually incurable, 20% of all prostate cancer deaths are now due mCRPC1despite significant advances in androgen inhibitors23, and effective treatments remain an unmet need4. The incidence of mCPRC in the US is growing, estimated at 36,100 in 2009 and increasing to 42,970 in 20201. With few treatment options, mCRPC patients continue to have markedly poor survival (~13- 30 months5) and are in dire need of additional therapeutic options that overcome mechanisms of resistance. Prostate cancer is an optimal disease to deploy RPT as the vast majority of patients (85- 90%1) have elevated levels of prostate-specific membrane antigen (PSMA), a type II transmembrane glutamate carboxypeptidase, that is commonly absent or only faintly expressed in benign prostate tissue10. Recently, the FDA approved177Lu-PSMA-617, a (3-particle emitting radioligand therapy, for the treatment of mCRPC10’11’12'13, after trials showed that participants treated with177Lu-PSMA-617 had improved overall survival of 15.3 months and improved progression-free survival of 8.7 months compared to 11.3 and 3.4 months using the current standard of care, respectively. Despite these promising results, ultimately patients progress. Given the known dose response of radiation dose with local control from external beam radiotherapy, knowledge of the dose delivered to the tumor is essential to tailor optimal treatment to each patient. However, this remains an unsolved necessity for RPT administration quality and safety.

[0283] Similar to the goals of stereotactic ablative radiotherapy, where the radiation dose to tumors of interest is maximized while minimizing dose to surrounding tissues, theranostic RPTs aim to maximize the tumor uptake of the radionuclide while minimizing the undesired dose deposition andtoxicity to organs at risk (OAR). For example in regards to prostate cancer, the OARs consist of excretory organs (e.g. kidneys and bladders for small molecules; liver for antibodies), organs that inherently express the target receptor (e.g. kidneys express PSMA1-4), or organs that are transiently exposed due to activity in the blood (e.g. bone marrow). In practice, RPT is administered using a standard dosing, or “one-size fits all”, strategy, as demonstrated in177Lu-PSMA-617 RPT where 200 mCi ofl77Lu-PSMA-617 is given every 6 weeks for up to 6 cycles. This treatment strategy overlooks the total integrated dose delivered to each tumor, as well as common patient-to-patient heterogeneities which ultimately govern the dose delivered, including (1 ) varying levels of PSMA expression, (2) variations in tumor uptake and ligand retention, (3) day-to-day variations including heart rate, blood flow, and excretion kinetics, and (4) on-target but off-tumor toxicity from radionuclide binding to PSMA-expressing OARs12’14 15. Additionally, due to both tumor retention, ligand circulating half-life, and the radionuclide half-life, accurate dosimetry methods benefit from measuring the total integrated dose over multiple half-lives of the chosen radionuclide. Given these factors that highly vary from patient-to-patient, a uniform dosing approach suboptimally administers dose to tumors in some patients and may provide greater than acceptable dose to OARs in others. This lack of continuous dosimetry precludes critical patient-specific dosing and fractionation modulations that could improve clinical outcomes4849. Therefore continuous dosimetry measurements for each patient (across multiple tumors and OARs) over several half-lives and over all fractions is vital in evaluating and optimizing for treatment response13’16’17.

[0284] Single photon emission computed tomography (SPECT) is the current state-of-the-art dosimetry technique in radioligand therapy. Despite advances in SPECT imaging and reconstruction algorithms, this dosimetry method only provides a whole-body snapshot at a single time point, leaving patient-specific continuous dosimetry as an unmet need. Due to the lack of universal availability of SPECT, long acquisition times, and high cost overhead, it is logistically infeasible for every patient to have multiple scans during the course of treatment. Due to challenges in reimbursement, logistics, and availability, at most, one SPECT scan per treatment cycle is taken, but most often, no SPECT dosimetry is performed. For patients with a single scan, the total dose is often calculated by simply fitting a representative biodistribution curve18 19to this one point. However, this is insufficient as variations in the time to maximum (tmax) uptake as well as the effective half-life (Ten the time it takes for the dose to become half) for metastatic lesions can be 50% and 30%, respectively. This uncertainty in dose estimation translates to dose variations of more than 70% over the course of the treatment20.

[0285] Given the shortcomings and practical limitations of modern dosimetry, a platform for realtime, continuous dosimetry is needed to complement the current state-of-the-art imaging modalities.Such a platform must satisfy the following requirements: 1 ) be able to reconstruct the percent injected activity per milliliter of tissue (%IA / mL) of all tumors and OAR of interest with high accuracy (within 1 %IA / mL of the true value), 2) be able to reconstruct %IA / mL of all tumors and OAR with short acquisition times (relative to the biodistribution kinetics), 3) have high sensitivity and dynamic range with radioligand activity, 4) be non-invasive, 5) be seamlessly integrated into the existing workflow for patients, and 6) be easily accessible and cost-effective to hospitals, patients, and clinicians. Despite efforts towards such a platform for continuous monitoring of radiopharmaceutical uptake in RPT, no previous works have satisfied all these requirements as discussed21'22’23’25,26'27'28'29’30.

[0286] To satisfy these requirements, we present a sparse y sensing network and reconstruction algorithm for real-time %IA / ml_ reconstruction in tumors and OARs, using a priori knowledge of patient anatomy (e.g., tumor and OAR location) relative to sensor positions. The proposed workflow involves utilizing the standard pre-therapy CT (from PET / CT in clinical implementation) to identify the lesions and OARs that will uptake RPT. The location the y sensing probes are placed on the skin are annotated using CT fiducial stickers (FIG. 1 A), allowing for a priori knowledge of the locations and size of all the tumors and OARs of interest relative to the probe locations. After RPT administration, patients are continually monitored at finely spaced time intervals by placing the y photon probes at the desired locations (FIG. 1 B). One implementation of this is to place the probe tips in a wearable vest that is worn for 10 minutes per acquisition. These uncollimated, continuous y photon recordings then need to be translated into %IA / mL in all tumors and OARs using the developed model. Biodistribution curves of all the tumors and OARs are created and a comprehensive picture of the total integrated dose per organ is obtained in order to make further clinical decisions regarding fractionation schedule, amount of injected activity, and augmentation using other cancer treatment options (FIG. 1 D).

[0287] We demonstrate a pre-clinical proof-of-concept of the system, algorithm, and workflow using l77Lu-PSMA-617. The proposed system was first verified using a custom water phantom containing four vials of varying activities of177Lu-PSMA-617. The system was then validated on four different mouse models with either 2 or 3 tumors with varying locations and from either PC3-pip or PC3-flu prostate cancer cell lines, administered177Lu-PSMA-617. The activity of each tumor, the kidneys, and the bladder were successfully reconstructed at 10 minutes, 6 hours, 12 hours, 24 hours, and 48 hours post-injection. The reconstruction of %IA / mL at each time point for all the tumors and OAR was highly linear with the activity from small-animal SPECT / CT.Results

[0288] The developed uncollimated, optical fiber-based y-photon sensor is highly linear with 177Lu-PSMA-617 activity. Custom y-photon counters were developed by coupling a high quantum efficiency Y2O3-EU doped phosphor to avalanche photodiodes (APD) using optical fibers. The APDs (Excelitas, SPCM-AQ4C) have high efficiency detection at the peak scintillation wavelength of the phosphor (610 nm), enabling a large dynamic range and sensitivity with detected counts per second (CPS). Since optical fibers are prone to visible light not emitted by the phosphor, 5 layers of 500um black optical tape with an optical density (OD) of 4, were used to enclose the fiber’s length. No lead was used on these fibers, leaving incoming y’s incident on the sensor face completely uncollimated (FIG. 1C). A y incident on the phosphor face is scintillated into 610 nm red light that creates an exponentially decaying voltage pulse at the APD sensing node. This pulse is buffered, fed through a comparator, and this now voltage pulse is fed into a 1 -bit 4.5V to 3.3V level shifter with a 50-ohm input impedance. The 3.3V voltage pulses are then counted using a field-programmable gate array (Opal Kelly XEM6010) with multiple digital counters with a sampling frequency of 150 MHz (FIG. 2A). The summed incoming counts are relayed to a PC every second using a custom Python interface. Eight probes were developed for this study.

[0289] The sensitivity and dynamic range of each of the developed probes was evaluated using a 2x dilution of177Lu-PSMA-617, ranging from 0.5 jtzCi to 3 mCi in 1 mL. The developed system was shown to be highly linear in this range with average CPS varying from 1 .38 to 11 ,055 CPS and an R2value of 0.999 (FIG. 7). Since there may be probe-to-probe variations in sensitivity to y’s, a custom 3D printed scaffold (FIG. 8A) was made to assist in probe calibration by holding the probes flush against the vials containing177Lu-PSMA-617. Each probe’s response to 50 pCi, 100 pCi, and 200 pCi vials was recorded, and a linear fit with no intercept was fit to the resulting CPS. The variation in the slope, or sensitivity (CPS / pCi), of each probe is shown in FIG. 8B, and each probe’s sensitivity is normalized to Probe 1 .

[0290] Modeling tumors and OARs as bounded uniform distributions of y-photon emitting point sources allows for reconstruction of their %IA / mL. Given a priori knowledge of tumor and OAR locations, N uncollimated y counting probe recordings, and the locations of these probes relative to the tumors and OAR (FIG. 2A), a mathematical framework for %IA / mL reconstruction was developed. The CPS recorded by each counter was decomposed into an unknown matrix ( l / l / ) multiplied by a vector containing the unknown total tumor or OAR activity in pCi, the quantity of interest (FIG. 2B). Matrix l / l / denotes the CPS per pCi contributed from each of the M tumors or OAR to each of the N y-photon counting probes. Since both l / l / , and the tumor and OAR activities are unknown, an approximation of one is needed to make an estimation of the other, and a prioriknowledge of tumor, OAR, and sensor location enables the estimation of matrix IV. Matrix IV can be further decomposed into matrix / 3 and vector or. Matrix / 3 denotes the probability that a probe’s CPS originates from a certain tumor or OAR. / 3 has the function of “unmixing” uncollimated y counts. Once the fraction of each probe’s CPS that each tumor or OAR contributes is known, vector a is used to scale these probabilities to CPS seen at each detector per pCi in each tumor and OAR.

[0291] Estimating matrix IV involves individually estimating matrix [3 and vector a separately. Matrix / 3 is estimated by utilizing the pre-therapy CT (from PET / CT in a clinical workflow). From the CT, all the tumors and OAR boundaries, and sensor locations can be segmented. These boundaries are inputs to a custom simulation framework that was developed. The tumor and OAR boundaries are used to uniformly distribute y emitting point sources within them to create a distributed point source (DPS) model of each tumor and OAR. Tumors and OARs are initialized to have the same activity, encoded by the number of point sources. Based on 1 / d2CPS falloff with distance (d) typical of a y emitting point source, the probability that a specific y-photon counting probe receives counts from a specific tumor or OAR is calculated by tracking how many photons from each of the tumors and OAR are detected by a specific probe and dividing this value by the total number of detected photons by that specific probe (FIG. 2C). In a clinical scale model attenuation and scattering both play an important role in counts detected at each probe position. To account for this, the aforementioned probability can be scaled by an attenuation and scattering factor, which is a function of the point source’s depth in tissue. This attenuation and scattering factor can be derived empirically by taking each y counter and characterizing its detected counts per second (CPS) at finely swept depths in water away from a point source of the radioligand being utilized. This sweep would be repeated in air and the factor difference between the two curves at each distance is estimated, and this represents the non-linear function of the attenuation and scattering factor as a function of distance. Based on the distance in tissue from each detector to each point source in the DPS model a unique attenuation and scattering factor can be assigned to each source. Vector a is estimated by conducting a titration simulation using a DPS model. Each probe has a slightly different sensitivity in CPS / pCi, due to variations in manufacturing, that is measured using an experimental titration shown in FIG. 8. A DPS model of the titration experiment is created by extracting the vial bounds from the CT and distributing point sources within these bounds (FIGS. 9A-9C). The DPS model also gives a certain CPS / pCi in simulation (FIG. 9D), and this ratio between the experimental and DPS model probe sensitivity is used to scale the simulated CPS to experimental CPS. This is a linear scaling factor, since the non-linearity of this system originates the relationship of flux with distance and the shape of tumors and OARs, and both factors are accounted for in the probabilities defined in / 3.

[0292] Given a and fi and hence an approximation of matrix IV, a Bayesian approach to approximating total tumor and OAR activity was taken. Since matrix W may have some inaccuracy in a few weight estimates due to the sparsity of the inverse problem, the optimization technique used in this paper utilizes Markov Chain Monte Carlo (MCMC) methods to explore the solution space of activities that gives the best representation of the recorded y CPS distribution measured experimentally, instead of purely minimizing the error between the predicted CPS and the recorded CPS. All the tumor and OAR activity guesses are initialized to the same activity and MCMC is run for 100,000 iterations or until convergence. MCMC provides probability density distributions of the total tumor activity guesses, allowing for visualization of the most probable solution space of the problem and the uncertainty in the estimate51.

[0293] The proposed system allows for activity reconstruction of spatially close 1 mL phantoms with wide ranging activities. To initially validate the workflow demonstrated in FIG. 2, a water phantom experiment was performed. A custom 3D printed ABS tank was designed with slots for y probes on the sides and filled with water. A seal-tight lid was placed on top of the water tank with holes for 1 mL eppendorf vials filled with varying concentrations of177Lu-PSMA-617. FIG. 3A shows the experimental water tank with 8 y probes around the periphery. To test the ability of the developed sensing network and algorithm to reconstruct the activity in each of the vials, 2-minute recordings were taken from 14 different locations spaced around the periphery of the water tank with 4 different activity vials as shown in FIG. 3B.

[0294] The converged solution of the DPS model after using all 14 y-photon probe recordings, and the simulated CPS at each of the sensor faces is shown in FIG. 3C. The convergence of predicted activities with each sensor added to the periphery is shown in FIG. 3D. After sensors 1 -3 are added around the periphery (e.g., Y-Z plane), the predicted activity of Vial 1 and Vial 2 converge to the correct solution. In contrast, the predicted activity of Vials 3 and 4 are close but more information about the regional y flux is needed to obtain a more accurate estimate. Since Vials 3 and 4 are closely spaced, the algorithm benefits from counters whose faces point in a different plane direction to distinguish which of the two vials has the higher activity uptake. As we add counters 4-8 in the same plane, the predicted activity of both Vial 1 and 2 oscillates between the two true values of the vials since there are multiple solutions to this inverse problem. As we add counters 9-14 which are in a different plane (e.g. X-Z plane), the activity converges.

[0295] As MCMC is converging to a solution, the input probability distributions ofl77Lu-PSMA-617 activity are modulated until the predicted CPS distribution matches well to the true experimental CPS distribution. The updated probability density functions of vial activity from / V=4, 10, and 14 sensorsis shown in FIG. 3F, and the trends discussed are reflected in these distributions with Vial 3 and 4 only converging to the true solution after y sensors facing in another plane are added ( / V>8). The predicted CPS matched well with the experimental average CPS from each of the 14 counter positions as shown in FIG. 3E. The ability of the developed system to reconstruct average activity of 1 mL phantoms spaced at cm-scale depths in water, spatially separated at sub-cm scales was successfully demonstrated.

[0296] The designed network and algorithm can be seamlessly adapted for %IA / mL prediction of tumors and OAR in an in vivo model. To demonstrate the effectiveness of the proposed system in monitoring the biodistribution of the radiopharmaceutical, the sparse y counting dose reconstruction approach was validated on 4 different mouse models with varying locations of PSMA+ PC3-pip and PSMA- PC3-flu human prostate cancer cell lines. M1 had a PC3-pip tumor on its left flank and PC3-flu tumor on its right flank. M2 had a PC3-pip tumor on both its left and right flank. M3 had a PC3-pip tumor on its left flank and right back, and a PC3-flu tumor on its right flank. M4 had a PC3-pip tumor on its left flank, right flank, and right back. Each of these four mouse models was placed in a custom 3D printed scaffold with slots for keeping y counter placement stationary and consistent. Each mouse was injected with approximately 650 piCi of177Lu-PSMA-617, with y counting recordings conducted for 10 minutes at 0 hour, 6 hours, 12 hours, 24 hours, and 48 hours postinjection. Approximately 1 hour before every y-photon recording, each mouse was injected with 200 iL of CT contrast (Medilumine Fenestra LC) to allow for SPECT / CT imaging with tumor and OAR delineation. After each recording the mouse is kept in the custom 3D printed scaffold and imaged with SPECT / CT. The CT scan with contrast enables segmentation of the tumors, kidneys, and bladders across time points, as well as annotation of y probe position, since the holes in the scaffold are visible in the CT scan. The tumor and OAR boundaries are delineated on CT and are converted into a DPS model. MCMC is run on this model to predict the probability density distributions of each of the tumors, kidneys, and bladder activities until they converge with the CPS measurements. The mouse models, sensor positions, and overarching workflow are summarized in FIG. 4A.

[0297] The experimental setup of mouse placement and anesthetization, sensor placement, anesthetization in SPECT / CT, and the resulting SPECT scan with visible probe locations are shown in FIG. 4B. y probe locations on the periphery are not placed directly on tumors. Instead, probes are placed in locations between tumors and OAR to get a good approximation of / 3, the cross talk of counts between multiple organs. Leveraging the advantage of recording in three dimensions, probes whose sensing face are on the top plane looking down are placed hovering over the flank tumorsand the kidneys / bladder, allowing for separation of activity between tumors or OAR that are hard to distinguish spatially or that are very close in %IA / mL.

[0298] The in vivo DPS model solution matches qualitatively well to changes in the SPECT / CT across time points. As an example, the true activity distribution of177Lu-PSMA-617 from SPECT / CT in mouse 4 (M4) for all time points is shown in FIG. 5A. To estimate the activity at each time point, the CT scan is used to segment the sensor positions as well as the tumors, kidneys, bladder, and rest of the body (or background uptake) of all mice models (e.g., M4’s 6 hours post-injection CT in FIG. 5B). From these boundaries, a DPS model was generated with all segmented tumors and organs initialized to the same activity (FIG. 5C). As the MCMC optimization converges, the activity distributes to its true values, which in the reconstructed activity of M4’s 6 hours post-injection time point, is mainly in its three PC3-pip tumors. The converged DPS models for all time points is shown in FIG. 5C and qualitatively matches well with the %IA / mL intensity from SPECT / CT.

[0299] If the raw uncollimated y recordings were used by themselves and the unmixing and scaling procedure outlined in FIG. 2 and FIG. 5 is not applied, convergence to the correct solution is not observed since there is significant crosstalk between probes. The real-time trends in CPS for each of the probes monitoring M4 are shown in FIG. 13 for reference. There is a large variation in temporal CPS for each of the probes due to cross-talk of CPS from various tumors and OARs. For instance, probe 4 that is in closest proximity to the right back PC3-pip tumor of M4 maintains the second- highest CPS reading over time, whereas probe 8 that also hovers over the top of the right back PC3- pip tumor is one of the highest CPS recordings at the beginning but becomes one of the smallest as time goes on. This may be due to cross-contamination with the kidneys and bladder at very early time points, which if measured without this consideration would lead to overestimating the activity in the right back tumor at the earliest time point. Similarly all of the CPS traces are higher than they would be if one probe was measuring only the tumor or OAR it was closest to.

[0300] The proposed system accurately tracks the widely varying biodistribution in tumors and OARs of mice with different tumor locations and PSMA expression levels, with %IA / mL and total tumor activity predictions that are highly linear with state-of-art SPECT / CT across time points. The reconstructed %IA / mL for the PSMA+ PC3-pip tumors for all mice (M1-M4) are shown in FIGS. 7A-7D respectively. It is evident that even between genetically identical mice with tumors derived from the same cell culture, there are large differences in both the absolute magnitude of tumor radioligand uptake as well as relative trends in radioligand uptake over time. M1 only has one PC3-pip tumor that peaks around 6 hours post-injection and plateaus for the subsequent time-points. The two PC3-pip tumors in M2 have similar absolute uptake, but the tumor on the right-flank peaks around the 12 hr time point while the tumor on the left-flank peaks around the 6 hr time point. The two PC3-pip tumors in M3 have similar absolute uptake during the first three time points but radiopharmaceutical clearance occurs much faster in the left flank tumor than in the right-back tumor after peak uptake occurs at 12 hours post-injection. M4 has three PC3-pip tumors with all three tumors having their peak uptake immediately post-injection. While the right-back tumor %IA / mL plateaus very quickly after the peak, the right-flank tumor %IA / mL decreases substantially before plateauing, and the left flank tumor %IA / mL monotonically decreases.

[0301] The reconstructed %IA / mL of the two PSMA- PC3-flu tumors on the right-flanks of M1 and M3 peak immediately post injection. Both tumors have an uptake slightly above 1 %IA / mL and exponentially decrease thereafter (FIG. 6E). The kidneys of M1 -M4 have varying uptake immediately after injection, ranging between 7 and 12 %IA / mL, but similar to the PC3-flu tumors the %IA / mL exponential decreases to very small absolute values for the remaining time-points (FIG. 6F). The bladders of M1 -M4 have large %IA / mL immediately after injection, varying between 50 and 160 %IA / mL. The bladder %IA / ml_ for all mice also exponentially decays thereafter (FIG. 6G).

[0302] The reconstructed PC3-pip tumors, PC3-flu tumors, kidneys, and bladder %IA / mL were compared to the %IA / mL from SPECT / CT at 10 minutes, 6 hours, 12 hours, 24 hours, and 48 hours post-injection. This involves the reconstruction of the %IA / mL of 90 separate tumors or OARs at different time points. The relationship between the two quantities is highly linear with an R2=0.994. The linear relationship between the proposed model and SPECT / CT is given by Predicted %IA / mL=0.91 (%IA / mL SPECT / CT) with a Pearson’s r of 0.9975, indicating the mapping from the proposed model to SPECT / CT is nearly 1 to 1. This linear relationship is held for a large dynamic range in %IA / mL from 0.1% to 160% in vivo (FIG. 7H). Likewise, the total tumor activity reconstructed from the proposed model and SPECT / CT are highly linear with an R2=0.991 . Since this is the value that is initially reconstructed in the mathematical formulation of this inverse problem, the linear relationship is even closer to a 1 to 1 mapping from SPECT / CT, described by Predicted Total Tumor Activity = 0.96(Total Tumor Activity SPECT / CT) with a Pearson’s r of 0.9982. This mapping holds for total tumor and OAR activities ranging from <1 Ci to 400 Ci in vivo (FIG. 7I).

[0303] The relative error in %IA / mL is slightly higher in bladder estimates when the bladder %IA / g <1%, but this is due to small inaccuracy in low activity uptake in a very small volume organ in a mouse. From FIG. 7I, the bladder total tumor activities at these %IA / mL are <3 iC\ with the model predicting but since the mouse bladder is ~0.3 mL in volume, the error is amplified when estimating %IA / mL. The absolute error is on the order of 1 -3 ^Ci in this range of %IA / mL, and is therefore clinically insignificant.4. Discussion

[0304] Molecularly targeted RPT to PSMA offers a novel approach for mCRPC patients, but RPT is ultimately limited by off-tumor toxicity caused by an inability to predict dose distribution a priori. The key to success of RPT is a relatively simple proposition: delivery of high doses to the tumors and low doses to OAR. RPT using177Lu is transforming prostate cancer, with recent positive results in the VISION42and TheraP12 13trials in metastatic patients showing survival benefits, and current trials underway in non-metastatic patients14.

[0305] Currently patients administered177Lu-PSMA-617 therapy receive at most a single SPECT / CT image around 24 hours post injection. Multi-time point SPECT for continuous dosimetry, is necessary to observe the full dose distribution and total integrated dosimetry of TRT45, but remains a major logistical challenge, and near universally infeasible off-trial. Modern SPECT / CT machines, including the Veriton Multi-CZT Detector46and GE StarGuide SPECT / CT47systems, demonstrate higher spatial resolution and reduced acquisition times in comparison to conventional systems. Such systems show promise, but face issues regarding cost, and challenges remain with the complex logistics involved in scanning patients at multiple, optimal, post-injection time points. Moreover, the eventual goal of RPT is to enable wide distribution to the community, where specialized SPECT / CT may not be available.

[0306] In addition to the state-of-the-art, recent preclinical studies and clinical trials have utilized Cerenkov luminescence imaging (CLI) for chronic monitoring of uptake due to short acquisition times and accessibility. Cerenkov luminescence has limited range in tissue because it images visible light, and this is prone to increased scattering, low localization specificity, poor sensitivity to lower activity lesions, and suboptimal detection of deeper lesions common in Rpj2i ,22,23,24puD’ vestbased platform29still requires a SPECT / CT and has only been demonstrated in monte-carlo simulation. Recent work measuring1311 thyroid treatment using WIDMApp30shows promise, but this work is again only demonstrated in Monte-Carlo simulation with no phantom or in vivo validation.1311 thyroid treatment also utilizes a larger y flux with higher energy photon detection. Other optical fiber dosimetry-based approaches, focus on external beam radiotherapy (EBRT) where y flux is much higher, large detection area is more preferable, and sensitivity of the developed counters is much lower31'32'33'3435’36. MOSFET37’38, calorimeter3941, and competing scintillator-based approaches to detection likewise require much larger y flux than what is present in177Lu-PSMA-617 therapy, and present with some voltage offset drift, drift in sensitivity with time, low sensitivity, and in the case of scintillator-based detectors, scintillator afterglow effects. Prior work with portable counting systems,has not, to date, achieved a chronic monitoring platform for tumors and OARs and shown experimental versatility in phantom and in vivo2526'27'28.

[0307] In this work, we demonstrate a first-in-class sparse y counting approach to reconstructing %IA / mL of multiple tumors and OAR non-invasively in vivo, without the need of a single SPECT / CT measurement. The system was validated at different levels and as one cohesive unit. (1 ) To validate the ability of y counters to track radiopharmaceutical activity linearly, a titration was performed with the probe demonstrating a wide linear dynamic range from 0.5 / zCi to 3 mCi with 5 minute acquisition times (FIG. 7). (2) The probe was shown to have a suitable tradeoff with distance, showing significant CPS recordings even 3 cm away from a177Lu source (FIG. 10). (3) The developed DPS model’s ability to mimic the distance tradeoff for a vial shaped object was tested by running this distance sweep in simulation as well. The relative drop in CPS with distance matches very well between the DPS model and experimental recordings (FIG. 10). (4) The ability of the algorithm to reconstruct the activity in an arbitrarily shaped tumor was tested by dissecting a PC3-pip tumor with a small amount of uptake and measuring its activity with a single y-photon counting probe. The predicted value based on the DPS model and reconstruction approach was in good agreement with both ex vivo y counting and SPECT / CT measurements (FIG. 11 ). (5) The proposed model’s ability to reconstruct the mixing matrix l / l / was validated using a custom water phantom with four vials of unknown activity. The true experimental W and reconstructed W are in good agreement with each other (FIG. 1 ). (6) The proposed model was then shown to be highly linear with both %IA / mL and total tumor activity as demonstrated in both a custom water phantom (FIG. 3) and 4 different in vivo human prostate cancer mouse models (FIG. 6).

[0308] This allows clinicians to create a large number of patient-specific, snap-shots of radioligand uptake in the tumors and OARs with associated probability density functions. The probability density functions help characterize uncertainty in the reconstruction, such that an informed decision can be made to balance both tumor ablation and OAR toxicity levels (FIG. 6). Since the sparse y sensing network relays real-time y counts from each probe, these can be used for real-time reconstruction of %IA / mL if biodistribution at earlier time-points want to be more closely monitored (FIG. 5). It should be noted that for the depths of water and tissue used during phantom and in vivo experiments, tissue attenuation is negligible. During full-scale operation in a patient, mass attenuation coefficients must be considered from the CT scan and each probe’s detection of emissions from the isotope as a function of distance in tissue has to be characterized. These two factors will slightly adjust the probabilities in p used in reconstruction.

[0309] In addition to its accuracy, the current sparse y counting network and algorithm represents an affordable alternative (approximately $20,000 compared with $500,000 to $3,000,000 forSPECT / CT systems50) modality for lower-cost, more accessible, and faster acquisition %IA / mL reconstruction during the course177Lu-PSMA-617 therapy. Such a significantly cheaper imaging modality will permit hospitals and clinics to expand their therapeutic treatment capabilities for mCRPC where previously, installation of conventional SPECT / CT systems could be unavailable and cost-prohibitive. The ease of repeated measurements with the developed sparse y counting system can open new imaging workflows that track patient therapy when conventional imaging may not be feasible or is cost-prohibitive, and provides sufficient clinical information to that of high-end SPECT / CT scanners.

[0310] We successfully demonstrated the functionality of our proposed system in human prostate cancer small animal models. It is envisioned that the proposed system can be utilized to personalize RPT, significantly improving the overall safety and efficacy of the treatment through safe dose management. The low-cost, high accessibility, accuracy, and rapid acquisition time of this system allows for continuous dosimetry measurements over multiple half-lives of and across fractionated treatments with177Lu-PSMA-617 radioligand therapy.MethodsOptical Front-End Design

[0311] Y2O3-EU doped phosphor (Sigma Aldrich, 756490) was used to scintillate incoming gamma photons into 610 nm red light. 0.25g of phosphor was compacted to a thickness of 500pm, in order to eliminate air gaps and increase density, and hence the mass attenuation coefficient28. The phosphor was compacted in a 2.5 mm inner diameter cylindrical casing that was 3D printed. The probe utilizes a 200pm core, optogenetics patch cable (THORLABS, M104L01 ) with a 2.5 mm ceramic ferrule, and is 1 meter long to enable ease of maneuvering around lesions of interest. The customized single-gamma photon sensitive optical fiber-based probe is shown in FIG. 1 C. Because patch cables are very light sensitive, five layers (500um) of black optical seal tape (THORLABS, T743-1.0) were placed on the outside of the fiber throughout its length to ensure no ambient light photons were mistaken as gamma photon events. Fibers are optically coupled to a silicon avalanche photodiode (Excelitas, SPCM-AQ4C) with a circular active area of 180 pm and peak photon detection efficiency of 60% at 650 nm.Mice

[0312] All mice were housed in a pathogen-free environment under protocols approved by the UCSF Institution of Animal Care and Use Committee (IACUC). All animal research follows the NationalINstitutes of Health (NIH) guidelines, described in the Guide for the Care and Use of Laboratory Animals. 4 4-week-old homozygous athymic nude male mice (NU / J 002019, Jackson Laboratory) are used for this study. Human prostate cancer PC3-pip and PC3-flu cell-lines are cultured according to the ATCC guideline. 2.5 million PC3-pip and PC3-flu cells are subcutaneously injected into the appropriate locations specified in FIG. 4A. The size of each tumor is monitored every week. Tumors were allowed to grow for 10 days after injection, before the mice were transferred to the UCSF Imaging Center at China Basin for experimentation (FIGS. 3A-3B). The 4 mice were monitored for 10 minutes starting at 0 hr, 6 hr, 12 hr, 24 hr, and 48 hr after177Lu-PSMA-617 is administered.Radiolabeling

[0313] 177LuC was purchased from Oak Ridge National Laboratory. A stock solution of PSMA-617 (Vipivotide tetraxetan, MedChemExpress) is prepared in dimethyl sulfoxide (DMSO) with a concentration of 1 mg / mL. 5mCi of177LuCl3 is transferred to a reaction vial, and the solution pH was adjusted to 6 by adding 100 pL 0.2M ammonium acetate. 25 pg of PSMA-617 is added to the vial before allowing the reaction to occur at 50°C with constant shaking for 45 minutes. Thin layer chromatography (TLC) is subsequently performed on a Whatman 41 paper as a stationary phase, 20 mM citric acid as the mobile phase, and an AR-2000 Bioscan TLC Reader in order to evaluate labeling efficiency.

[0314] 177Lu-PSMA-617 is purified using a SEP-PAK Plus C8 cartridge, which is preconditioned with5mL of 100% ethanol and 5 mL of water. The reaction solution is pushed through the cartridge and waste (unlabeled177Lu) is collected in a vial.177Lu-PSMA-617 is eluted with 2 mL ethanol solution (100%) and ethanol is evaporated under vacuum with a constant flush of N2at 40eC. Dried177Lu- PSMA-617 is reconstituted in a formulation of DMSO:Tween 80:saline (10%:10%:80% volume per volume) before preparing the mice injections.Measurement Setup

[0315] Mice were administered approximately 200 pL of CT contrast (Medilumine Fenestra LC) ~1 hour before injection. Mice were administered approximately 650pCi of177Lu-PSMA-617 via tail vein injection. All 4 mice were measured using the same configuration of gamma probe placement (FIG. 4A). Each mouse was measured for 10 minutes starting 0 hr, 6 hr, 12 hr, 24 hr, 48 hr post injection. During each measurement time, mice were administered light anesthesia using isoflurane. After each 10 minute acquisition, the mice were transferred to the SPECT / CT (VECTor4CT, MILabs) in the scaffold (FIGS. 4A-4B) and again administered light anesthesia using isoflurane for the duration of the scan.CT Annotation

[0316] CT annotation was done on the CT scans that were taken concurrently with the SPECT / CT after each measurement at a specific time point. Tumors and gamma counter locations were annotated using AMIDE, an open-source image viewing and segmentation software. Ellipsoid volumes of interest (VOIs) were used to bound the tumors, kidneys, and bladder of each of the mice at each time point. Cylindric VOIs were used to annotate the locations of the gamma counter faces. This was easily identifiable since the CT was taken with the mouse still in the measurement scaffold, so the holes in the scaffold where the sensors were placed are visible from the CT. For the 0 hr time points the mouse body outline is also taken as a VOI since there is a large amount of free-floating radioligand immediately after injection. These VOI bounds are exported into MATLAB for DPS model generation.SPECT / CT

[0317] The SPECT / CT (VECTor4CT, MILabs) utilized a 3.6 mm pinhole collimator (HE-GP-RM) and was taken with a 30 minute SPECT acquisition with an energy detection range of 0-1.2 MeV. This was followed by a CT scan with a tube current of 0.19 mA, tube voltage of 55 kV, and acquisition time of 5 minutes. To verify the %IA / g of the model, the SPECT / CT at a particular time point was used, with the activity extracted in the bounds denoted by the CT annotations used for activity reconstruction. The activity in these bounds was then compared to that reconstructed from our proposed model. %IA / g linearity between SPECT / CT and the proposed models was executed using the standard least-squares solution with one coefficient and with no intercept.Distributed Point Source (DPS) Model

[0318] Point sources with a 1 / d2distance (d) tradeoff were distributed in the bounds specified by the annotated SPECT / CT. To find an approximation of matrix / 3, all of the tumors and OARs are initialized to the same activity which is 50 pCi to understand how many CPS each probe will get if each lesion or organ has the same uptake. Activity is encoded by the number of point sources in the tumor or OAR. For all the phantom and in vivo simulations, 600 point sources are used to encode 50 pCi, meaning that each point source represents approximately 83 nCi of177Lu activity. The point sources are uniformly distributed since no prior knowledge of radioligand distribution in the tumor or OAR is taken into account.

[0319] The DPS model for the 0 hr time point takes into account radioligand distributed in the rest of the body as well. The CT annotation is of the whole mouse outline and point sources are uniformlydistributed in this volume. For the rest of the time points only the tumors and OAR are taken into account since most of the free-floating radioligand has been excreted from the body. In a larger in vivo model, if more tumors or OARs need to be added they can be seamlessly included into this workflow as they only need to be annotated in the CT scan and this boundary has to be incorporated into the existing DPS model.Model Reconstruction

[0320] For reconstruction only the last 2 minutes of the 10 minute recording was used. The CPS distribution over the 2 minutes was used for parameter estimation using monte carlo markov chain (MCMC), with the most probable CPS being the mean of the distribution.

[0321] MCMC provides a class of algorithms for systematic random sampling from high-dimensional probability distributions. Unlike a typical monte carlo simulation, MCMC draws samples where every sample is dependent on the existing samples, implicitly generating a Markov Chain. This makes this method favorable in the following use case as the number of sensors and tumors / OARs to be reconstructed will increase substantially depending on the cancer stage, so a probabilistic framework rather than a minimization solution is required to ensure proper tumor ablation and OAR safety. MCMC allows for the approximation of posterior distributions (tumor / OAR activities) based on random samples of the observed data distribution, which is the gamma CPS distribution in this case. These random samples are used to continually update a prior state of beliefs about the parameters as given by Bayes rule: p(Tumor & OAR Activities | Sampled y CPS)

[0322] The mapping from activity to the observed CPS is the estimated DPS model matrix W. MCMC parameter estimation was executed using adaptive Metropolis (AM) optimization, where the Gaussian proposal distribution is updated along the process using all the information accumulated during chain generation. The algorithm was run using 100,000 iterations for the phantom experiment and in vivo experiment to permit for sufficient burn-in and convergence to the desired solution. Larger number of iterations showed no change or metastability of values. Tumor / OAR activities were initialized to an identical value, which is also the same as the value that the DPS model (50 / zCi) was initialized to approximate matrix / 3. The result of the MCMC run is a distribution of the explored parameter space with a mean and standard deviation in total tumor activity. This total tumor activityis converted into %IA / mL by dividing by the known injected activity and dividing by the volume of the tumor or OAR derived from the CT scan during SPECT / CT.Activity Extraction from Ex Vivo Tumor

[0323] The PC3-pip tumor was removed from M’s flank a few days after the last sparse network acquisition. The tumor was placed into a test tube and placed in a HIDEX ex vivo gamma counting machine. The test tube was then measured with 1 custom y-photon counting probe flush against the test tube wall (FIG. 11 A). A CT fiducial sticker was placed on the outside surface of the test tube where the probe was flush against the test tube. The test tube was placed in the SPECT / CT machine and a 30 minute SPECT / CT was taken.

[0324] From the CT scan both the tumor shape and probe position (FIG. 11 B) were annotated. The boundaries...

Claims

What is claimed is:1 . A gamma photon counter comprising: a Y203-Eu-doped phosphor, wherein a y-photon incident on a surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3- Eu doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.

2. The gamma photon counter of claim 1 , wherein the photodiode is an avalanche photodiode (APD).

3. The gamma photon counter of claim 2, wherein the APD is a silicon APD.

4. The gamma photon counter of claim 1 , wherein the photodiode is a single photon avalanche diode (SPAD).

5. The gamma photon counter of any one of claims 1 -4, wherein the detector further comprises multiple power supplies to control circuit cooling, quenching and reset, and high voltage biasing.

6. The gamma photon counter of claim 5, wherein the multiple power supplies comprise a 2 volt power supply to control the circuit cooling, a 5 volt power supply to control the quenching and reset, and a 30 volt power supply to control the high voltage biasing.

7. The gamma photon counter of any one of claims 1 -6, wherein the detector further comprises a high voltage regulator.

8. The gamma photon counter of any one of claims 1-7, wherein the opaque material has an optical density (OD) of at least 4.

9. The gamma photon counter of claim 8, wherein the opaque material is a black lightabsorbing material.

10. The gamma photon counter of claim 9, wherein the black light-absorbing material is black optical tape.11 . The gamma photon counter of any one of claims 1 -10, wherein the scintillation light is red visible light.

12. The gamma photon counter of claim 11 , wherein the red visible light has a wavelength of about 610 nm.

13. The gamma photon counter of any one of claims 1 -12, wherein incoming gamma photons reaching the surface of the detector are uncollimated.

14. The gamma photon counter of any one of claims 1 -13, wherein the digital counter is configured in a field-programmable gate array (FPGA).

15. The gamma photon counter of any one of claims 1 -14, wherein the digital counter has a sampling frequency of at least 150 MHz.

16. The gamma photon counter of any one of claims 1 -16, further comprising a clock configured to produce a clock signal, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time.

17. The gamma photon counter of claim 16, wherein the period of time is one second.

18. The gamma photon counter of any one of claims 1 -17, further comprising a level shifter, wherein the level shifter is configured in circuitry to ensure logic level compatibility with the digital counter.

19. The gamma photon counter of claim 18, wherein the level shifter is a 1 -bit level shifter.

20. The gamma photon counter of any one of claims 1 -19, further comprising a data storage unit in communication with the digital counter, wherein the data storage unit is configured to store a plurality of gamma photon count records for a plurality of y-photon detection events.21 . The gamma photon counter of claim 20, further comprising a data processing unit in communication with the data storage unit, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.

22. The gamma photon counter of any one of claims 1 -21 , wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.

23. The gamma photon counter of claim 22, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TI.

24. The gamma photon counter of any one of claims 1 -23, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.

25. The gamma photon counter of claim 24, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.

26. The gamma photon counter of claim 24, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.

27. The gamma photon counter of any one of claims 1 -26, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.

28. The gamma photon counter of claim 28, wherein the gamma photon counter is attached to a fabric or an adhesive patch.

29. The gamma photon counter of any one of claims 1 -28, wherein the gamma photon counter is attached to a wearable structure.

30. The gamma photon counter of claim 29, wherein the wearable structure is clothing.31 . The gamma photon counter of claim 30, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

32. The gamma photon counter of any one of claims 1 -31 , wherein the gamma photon counter has a diameter less than or equal to 2.5 mm.

33. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises a reverse biased diode, wherein a y-photon incident on a surface of the reverse biased diode generates a voltage pulse across the reverse biased diode; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse across the diode produced by each y-photon incident on the surface of the reverse biased diode; an on-chip memory configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; and a custom digital logic circuitry on the chip, wherein the custom digital logic circuitry is configured to control voltages and supply power from an on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

34. The gamma photon counter of claim 33, further comprising a voltage amplifier configured in circuitry between the reverse biased diode and the digital counter.

35. The gamma photon counter of claim 34, further comprising a voltage buffer configured in circuitry between the reverse biased diode and the voltage amplifier.

36. The gamma photon counter of any one of claims 33-35, wherein the on-chip memory is static random-access memory (SRAM).

37. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a silicon diode, wherein a y-photon incident on a surface of the silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential closed-loop amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential closed-loop amplifier, wherein voltage gain is either pre-set or configurable using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified by a fixed process-invariant gain; an inverter chain comprising a plurality of inverters connected to amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of the silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

38. A gamma photon counter comprising: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a pair of silicon diodes comprising a first silicon diode and a second silicon diode, wherein a y-photon incident on a surface of either the first silicon diode or the second silicon diode breaks a silicon bond to produce anelectron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential amplifier; a voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets voltage output of the differential amplifier, wherein the voltage integrator is bootstrapped from the differential amplifier output to the differential amplifier input in a negative feedback configuration; a pair of level shifters connected to output of the differential amplifier, wherein the pair of level shifters comprises two level shifters comprising a first level shifter that shifts a direct current (DC) level of the output of the differential amplifier up to amplify only the voltage pulse from the first diode, and a second level shifter that shifts the DC level of the differential amplifier output down to only amplify the voltage pulse from the second diode, wherein an amount the DC level is shifted is set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert stored bits into an analog shift in voltage; an inverter chain comprising a plurality of inverters connected to amplified and shifted voltage output from the pair of level shifters, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of either the first silicon diode or the second silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

39. The gamma photon counter of claim 37 or 38, wherein the silicon diodes are reversed biased or have zero voltage bias.

40. The gamma photon counter of any one of claims 37-39, wherein the detector is optimized for sensitivity by decreasing the capacitance of the silicon diodes.41 . The gamma photon counter of any one of claims 33-40, wherein the diode size is 0.1 pm to 0.5 pm x 0.1 pm to 0.5 pm or 0.5 pm to 1 pm x 0.5 pm to 1 pm.

42. The gamma photon counter of any one of claims 33-41 , wherein the diode size is the smallest size available for use in a complementary metal-oxide-semiconductor (CMOS) process.

43. The gamma photon counter of any one of claims 37-42, wherein the detector is optimized with a tradeoff between pixel fill factor and sensitivity.

44. The gamma photon counter of claim 43, wherein the diode size is 1 pm to 1 .5 pm x 1 pm to 1.5 pm.

45. The gamma photon counter of any one of claims 37-42, wherein the detector is optimized to increase fill factor with a tradeoff in sensitivity.

46. The gamma photon counter of claim 45, wherein the diode size is 1 .5 pm to 3 pm x1 .5 pm to 3 pm, 3 pm to 10 pm x 3 pm to 10 pm, or 10 pm to 50 pm x 10 pm to 50 pm.

47. The gamma photon counter of any one of claims 33-46, wherein the detector has a curved shape or a polygonal shape.

48. The gamma photon counter of claim 47, wherein the polygonal shape is a triangular, square, rectangular, pentagonal, hexagonal, octagonal, diamond, or parallelogram shape.

49. The gamma photon counter of claim 47, wherein the curved shape is circular, semicircular, oval, spherical, or cylindrical.

50. The gamma photon counter of any one of claims 47-49, wherein the detector has sides ranging from 0.1 pm to 50 pm in length.51 . The gamma photon counter of any one of claims 37-50, wherein the pixels in the array of pixels operate asynchronously.

52. The gamma photon counter of any one of claims 33-51 , wherein the chip is covered with a Compton scattering material.

53. The gamma photon counter of claim 52, wherein the Compton scattering material comprises lead, tungsten, or bismuth.

54. The gamma photon counter of claim 52 or 53, wherein the Compton scattering material is in a layer on top of the detector or on the back of the detector.

55. The gamma photon counter of any one of claims 37-54, further comprising on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons such that combination and distribution of signals from pixels with known LET responsivity enables determination of incident energies of the incoming gamma photons.

56. The gamma photon counter of claim 55, wherein the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET.

57. The gamma photon counter of any one of claims 33-56, wherein the chip comprises a plurality of detectors.

58. The gamma photon counter of claim 57, wherein each detector of the plurality comprises an attenuating material of a different thickness to allow resolution of incoming gamma photons having different energies.

59. The gamma photon counter of claim 58, wherein the attenuating material is lead, tungsten, bismuth, or iron.

60. The gamma photon counter of claim 58 or 59, wherein the plurality of detectors is arranged in a vertical stack.61 . The gamma photon counter of claim 60, wherein each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material.

62. The gamma photon counter of claim 60 or 61 , wherein each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack.

63. The gamma photon counter of claim 62, wherein each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits a time that the incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel.

64. The gamma photon counter of claim 63, wherein an angle shift of the incident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack due to Compton scattering can be used to calculate the incident gamma photon angle with respect to the vertical stack.

65. The gamma photon counter of any one of claims 60-64, wherein the plurality of detectors is stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm, greater than or equal to 1 mm and less than 3 mm, or greater than or equal to 0.1 mm and less than 1 mm.

66. The gamma photon counter of any one of claims 60-65, wherein the vertical stack has a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm.

67. The gamma photon counter of claim 57 or 58, wherein the plurality of detectors is in a planar arrangement in a spatial area to allow said resolution of incoming gamma photons having different energies in the spatial area.

68. The gamma photon counter of any one of claims 33-67, wherein the chip has a surface area of less than or equal to 1 mm2.

69. The gamma photon counter of any one of claims 33-68, wherein the chip has a thickness of less than or equal to 1 cm, less than or equal to 5 mm, less than or equal to 3 mm, less than or equal to 1 mm, or less than or equal to 0.5 mm.

70. The gamma photon counter of any one of claims 33-69, wherein the clock signal is generated by a frequency locked loop (FLL) oscillator or an external computer, FPGA, tablet, cellular phone, or other control device.

71. The gamma photon counter of claim 70, further comprising an off-chip crystal oscillator, wherein a clock beacon to the FLL oscillator is generated by the off-chip crystal oscillator.

72. The gamma photon counter of any one of claims 33-69, further comprising an off-chip crystal oscillator, wherein the clock signal is generated directly from the off-chip crystal oscillator.

73. The gamma photon counter of any one of claims 33-72, wherein the on-chip energy storage device or the off-chip energy storage device comprises a battery, a capacitor, or a photovoltaic system.

74. The gamma photon counter of claim 73, wherein the battery is rechargeable.

75. The gamma photon counter of any one of claims 33-74, further comprising a data processing unit in communication with the on-chip memory or the on-chip data buffer, wherein the data processing unit is programmed to calculate a total percent injected activity per milliliter of tissue ( IA / mL) for one or more tumors and one or more organs at risk in a subject from the plurality of gamma photon count records.

76. The gamma photon counter of any one of claims 33-75, wherein the detector further detects electrons generated by gamma photons.

77. The gamma photon counter of claim 76, wherein the electrons are generated in a subject administered a radiopharmaceutical comprising a gamma-emitting radionuclide, in a layer ofmaterial positioned between the detector and the subject administered the radiopharmaceutical comprising the gamma-emitting radionuclide, or in silicon of the diodes of the detector.

78. The gamma photon counter of any one of claims 1 -77 , wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.

79. The gamma photon counter of claim 78, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL80. The gamma photon counter of any one of claims 1 -79, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.81 . The gamma photon counter of claim 80, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.

82. The gamma photon counter of claim 80, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,16lTb,166Ho, or177Lu.

83. The gamma photon counter of any one of claims 1 -82, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.

84. The gamma photon counter of any one of claims 1-83, wherein the gamma photon counter is attached to a fabric or an adhesive patch.

85. The gamma photon counter of any one of claims 1-84, wherein the gamma photon counter is attached to a wearable structure.

86. The gamma photon counter of claim 85, wherein the wearable structure is clothing.

87. The gamma photon counter of claim 86, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

88. The gamma photon counter of any one of claims 1 -87, wherein the gamma photon counter is connected by a wire to a power source, a control source, and a data collection unit.

89. The gamma photon counter of claim 88, wherein the control source is a field programmable gate array (FGPA), a computer, a laptop, or a smartphone.

90. The gamma photon counter of any one of claims 1 -89, wherein the gamma photon count data is uploaded wirelessly to a computer or a cloud server.91 . A wearable system comprising a plurality of gamma photon counters of any one of claims 1 -90 attached to a wearable structure.

92. The wearable system of claim 91 , wherein the wearable structure is clothing or adhesive patches.

93. The wearable system of claim 92, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

94. The wearable system of claim 92 or 93, wherein a first subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject; and wherein a second subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject.

95. The wearable system of claim 94, wherein positioning of each gamma photon counter on the clothing is determined based on medical imaging of the subject to determine where the tumor is located in the subject and positioning of each gamma photon counter of the second subset on the clothing is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

96. The wearable system of claim 95, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).

97. The wearable system of any one of claims 92-96, wherein the plurality of gamma photon counters is arranged in an array on the clothing.

98. The wearable system of claim 92, wherein each gamma photon counter of the plurality is attached to skin of the subject using the adhesive patches.

99. The wearable system of any one of claims 91 -98, wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.

100. The wearable system of claim 99, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.

101. The wearable system of claim 99, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

102. A computer implemented method for calculating total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject, the computer performing steps comprising: a) receiving gamma photon count data from a plurality of gamma photon counters, wherein each gamma photon counter has a known location; b) receiving an image of the subject, wherein the image shows locations of the one or more tumors and the one or more organs at risk in the subject, and locations of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) measuring volumes of the one or more tumors and organs at risk using the image; e) mapping centroid locations of each gamma photon counter on the image; f) performing distributed point source (DPS) modelling to generate a distribution of gamma photon-emitting point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) calculate probabilities for each gamma photon counterthat the gamma photons, counted by the gamma photon counter, were received from a gamma photon emitting point source within the boundaries of a particular tumor or organ at risk based on an assumption that counts per second (CPS) falloff correlates with 1 / (distance between the centroid location of the gamma photon counter and the gamma photon emitting point source)2and CPS values are attenuated by an empirically derived factor Q which accounts for attenuation and scattering of gamma photons in tissue, and ii) estimate probable fractions of counts counted by each gamma photon counter that correspond to a particular tumor or organ at risk; g) estimating total counts for each tumor and organ at risk using a Monte Carlo Markov Chain (MCMC) algorithm based on the gamma photon count data from the plurality of counters and parameter estimates of the probable fractions of counts counted by each gamma photo counter that correspond to a particular tumor or organ at risk from the DPS modelling; h) calculating the total %IA / ml for the one or more tumors and organs at risk in the subject based on said estimating the total counts for each tumor and organ at risk and dividing by the volumes of the one or more tumors and organs at risk measured from the image; and i) displaying the total %IA / mL for the one or more tumors and the one or more organs at risk in the subject.

103. The computer implemented method of claim 102, wherein said performing DPS modelling comprises: creating a DPS model matrix ( W) denoting the counts per second (CPS) per pCi contributed from each tumor or organ at risk to each gamma photon counter of the plurality, wherein the CPS per pCi are multiplied by an unknown activity in pCi of the total tumor or total organ at risk activity in pCi, wherein values in the DPS model matrix ( W) are estimated based on knowledge of the location of each tumor and each organ at risk from the image and the known locations of each gamma photon counter; and decomposing the DPS model matrix ( W) into a matrix ( / 3) and a vector (a), wherein the matrix ( / 3) denotes the fraction of each gamma photon counter’s CPS that comes from a certain tumor or organ at risk, wherein the fraction is scaled up by the vector (a), wherein the vector (a) is each gamma photon counter’s CPS per injected pCi of activity.

104. The computer implemented method of claim 103, wherein the vector a is estimated by conducting a DPS titration simulation.

105. The computer implemented method of claim 103 or 104, wherein the matrix (J3) is initially estimated by i) assuming each tumor and each organ at risk uptakes an equal amount of the radionuclide, wherein the total amount of the radionuclide administered to the subject is known, and ii) assigning the same activity to all of the tumors and organs at risk for said estimating the probable fractions of counts counted by each counter that correspond to a particular tumor or organ at risk.

106. The computer implemented method of any one of claims 102-105, further comprising using adaptive Metropolis (AM) optimization, wherein a Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm.

107. The computer implemented method of any one of claims 102-106, further comprising performing iterative optimization by a method comprising using gradient descent, least squares minimization, or brute force global minimization, or a combination thereof.

108. The computer implemented method of any one of claims 102-107, wherein the empirically derived factor Q is determined by a method comprising: measuring detected CPS for each gamma photon counter at different distances in water from a gamma photon emitting point source; measuring detected CPS for each gamma photon counter at different distances in air from the gamma photon emitting point source; deriving a non-linear factor representing scattering and attenuation for each gamma photon emitting point source based on differences between the CPS detected in water and air at each distance; and using the non-linear factor to calculate a unique factor O for each gamma photon emitting point source in the subject based on distances in tissue between each gamma photon counter and each gamma photon emitting point source.

109. The computer implemented method of any one of claims 102-108, further comprising segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid locations of each gamma photon counter are segmented.1 10. The computer implemented method of any one of claims 102-109, wherein each gamma photon counter of the plurality comprises:a Y203-Eu-doped phosphor, wherein a y-photon incident on a surface of the Y2O3-EU doped phosphor generates scintillation light in the visible light spectrum; a detector comprising a photodiode; an optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3- Eu doped phosphor to the detector, wherein the detector produces a voltage pulse in response to detecting the scintillation light generated from the y-photon; a digital counter coupled to the detector, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by the detector in response to detecting the scintillation light generated from each y-photon incident on the surface of the Y2O3-EU doped phosphor; and an opaque material enclosing the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y2O3-EU doped phosphor.11 1. The computer implemented method of any one of claims 102-109, wherein each gamma photon counter of the plurality comprises: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a silicon diode, wherein a Y-photon incident on a surface of the silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential closed-loop amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential closed-loop amplifier, wherein voltage gain is either pre-set or configurable using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified by a fixed process-invariant gain; an inverter chain comprising a plurality of inverters connected to amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon; a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of the silicon diode;an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

112. The computer implemented method of any one of claims 102-109, wherein each gamma photon counter of the plurality comprises: a detector configured in an application specific integrated circuit (ASIC) on a chip, wherein the detector comprises an array of pixels, wherein each pixel comprises a pair of silicon diodes comprising a first silicon diode and a second silicon diode, wherein a y-photon incident on a surface of either the first silicon diode or the second silicon diode breaks a silicon bond to produce an electron-hole pair, wherein a pulse of charge (Qp) is generated that is accumulated by a diode capacitor resulting in generation of a voltage pulse; a unity gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a y-photon is individually buffered by the unity gain voltage amplifier; a differential amplifier, wherein buffered voltage outputs from the unity gain voltage amplifier are connected to inputs of the differential amplifier; a voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets voltage output of the differential amplifier, wherein the voltage integrator is bootstrapped from the differential amplifier output to the differential amplifier input in a negative feedback configuration; a pair of level shifters connected to output of the differential amplifier, wherein the pair of level shifters comprises two level shifters comprising a first level shifter that shifts a direct current (DC) level of the output of the differential amplifier up to amplify only the voltage pulse from the first diode, and a second level shifter that shifts the DC level of the differential amplifier output down to only amplify the voltage pulse from the second diode, wherein an amount the DC level is shifted is set using on-chip configurable memory and an in-pixel digital to analog converter (DAC) to convert stored bits into an analog shift in voltage; an inverter chain comprising a plurality of inverters connected to amplified and shifted voltage output from the pair of level shifters, wherein the inverter chain generates digitized output corresponding to each voltage pulse generated by a y-photon;a digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts y-photon detection events, wherein each y-photon detection event corresponds to the voltage pulse produced by each y-photon incident on the surface of either the first silicon diode or the second silicon diode; an on-chip data buffer configured to store a plurality of gamma photon count records for a plurality of y-photon detection events; a digital clock configured to produce a clock signal on the chip, wherein the digital counter uses the clock signal to count numbers of y-photon detection events per a period of time; an on-chip or off-chip energy storage device; and a custom digital logic circuit configured to control voltages and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.1 13. The computer implemented method of claim 111 or 112, wherein the plurality of gamma photon counters comprises on-chip circuitry tuned to be responsive to a range of linear energy transfer (LET) from incoming gamma photons, wherein the computer implemented method further comprises calculating incident energies of the incoming gamma photons based on combination and distribution of signals from pixels with known LET responsivity.1 14. The computer implemented method of claim 113, wherein the array of pixels comprises a first subset of pixels and a second subset of pixels with known LET responsivity, wherein the first subset of pixels has a lower gain than the second subset of pixels, wherein the first subset of pixels detects lower energy photons having higher LET but not higher energy gamma photons having lower LET, wherein the second set of pixels detects both the lower energy gamma photons having higher LET and the higher energy gamma photons having lower LET.

115. The computer implemented method of any one of claims 102-114, wherein the plurality of gamma photon counters comprises a plurality of detectors, wherein each detector of the plurality comprises an attenuating material of a different thickness to allow resolution of incoming gamma photons having different energies, wherein the computer implemented method further comprises calculating likelihood of detecting a gamma photon of a certain energy with each detector of the plurality using a multiphysics simulation to separate detected counts of each detector by gamma photon energy.

116. The computer implemented method of claim 115, wherein the attenuating material is lead, tungsten, bismuth, or iron, wherein the likelihood of detecting a photon of a certain energy with a detector of a certain thickness of lead, tungsten, or iron is calcuated using the multiphysics simulation.

117. The computer implemented method of claim 115 or 116, wherein the plurality of detectors is arranged in a vertical stack.

118. The computer implemented method of claim 1 17, wherein each detector is separated from a neighboring detector in the vertical stack by a layer of the attenuating material.

119. The computer implemented method of claim 117 or 118, wherein each detector has fast readout circuitry connected to the array of pixels to allow for near instantaneous detection of the same incident gamma photon passing between two detectors of the plurality in the vertical stack.

120. The computer implemented method of claim 119, wherein each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits a time that the incident gamma photon hits the pixel, the pixel location on the detector, and a signal produced by the gamma photon hitting the pixel.

121. The computer implemented method of claim 120, further comprising calculating the incident gamma photon angle with respect to the vertical stack by measuring an angle shift of the incident gamma photon passing from the detector at the top of the stack to an underlying detector in the stack due to Compton scattering.

122. The computer implemented method of any one of claims 117-121 , wherein the plurality of detectors is stacked with a stack thickness of greater than or equal to 3 mm and less than 5 mm, or greater than or equal to 1 mm and less than 3 mm, or greater than or equal to 0.1 mm and less than 1 mm.

123. The computer implemented method of any one of claims 117-122, wherein the vertical stack has a form factor having a thickness of less than or equal to 1 cm, or less than or equal to 5 mm, or less than or equal to 3 mm, or less than or equal to 2 mm, or less than or equal to 1 mm.

124. The computer implemented method of claim 115, wherein the plurality of detectors is in a planar arrangement in a spatial area, wherein the computer implemented method further comprises determining energies of incoming gamma photons in the spatial area.

125. A non-transitory computer-readable medium comprising program instructions that, when executed by a processor in a computer, causes the processor to perform the method of any one of claims 102-124.

126. A kit comprising the non-transitory computer-readable medium of claim 125 and instructions for calculating the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject.

127. A system comprising : a) a plurality of gamma photon counters attached to a wearable structure; b) a power source; c) a processor, wherein the processor is programmed to calculate the total percent injected activity per milliliter of tissue (%IA / mL) for one or more tumors and one or more organs at risk in a subject according to the computer implemented method of any one of claims 102-124; d) an external data receiving device connected to the processor, wherein the external data receiving device receives the gamma photon count data from the plurality of gamma photon counters and transmits the gamma photon count data to the processor; and e) a display component that displays the %IA / mL for one or more tumors and one or more organs at risk in a subject.

128. The system of claim 127, wherein the plurality of gamma photon counters is attached to clothing or adhesive patches.

129. The system of claim 128, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

130. The system of claim 128 or 129, wherein a first subset of the plurality of gamma photon counters is arranged on the clothing such that when the clothing is worn by a subject, the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject,wherein positioning of each gamma photon counter of the first subset on the clothing is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters is arranged on the clothing such that when the wearable material is worn by the subject, the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset on the clothing is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

131. The system of claim 128, wherein the plurality of gamma photon counters is arranged in an array on the clothing.

132. The system of claim 128, wherein each gamma photon counter of the plurality can be attached to skin of a subject using the adhesive patches.

133. The system of claim 132, wherein a first subset of the plurality of gamma photon counters can be attached to the skin of the subject with adhesive patches such that the first subset of gamma photon counters can monitor uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein positioning of each gamma photon counter of the first subset with the adhesive patches is determined based on medical imaging of the subject to determine where the tumor is located in the subject; and wherein a second subset of the plurality of gamma photon counters can be attached to the skin of the subject with adhesive patches such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by an organ at risk in the subject, wherein positioning of each gamma photon counter of the second subset with the adhesive patches is determined based on medical imaging of the subject to determine where the organ at risk is located in the subject.

134. The system of any one of claims 127-133, wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.

135. The system of claim 134, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.

136. The system of claim 134, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

137. The system of any one of claims 130-136, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).

138. The system of any one of claims 127-137, wherein the power source is an external power source, an internal power source, or a combination thereof.

139. The system of claim 138, wherein the external power source is an ultrasound transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radiofrequency (RF) transducer.

140. The system of claim 138, wherein the internal power source comprises a battery, a radionuclide, or a photovoltaic system.

141. The system of any one of claims 127-140, wherein the power source is used to provide power to the detector.

142. The system of any one of claims 138 or 139, wherein the external power source is portable.

143. The system of any one of claims 127-142, wherein the external data receiving device comprises a wireless communication unit.

144. The system of claim 143, wherein the wireless communication unit utilizes a wireless communication protocol using an electromagnetic carrier wave or ultrasound to receive data from the internal data storage unit.

145. The system of claim 144, wherein the electromagnetic carrier wave is a radio wave, microwave, or an infrared carrier wave.

146. The system of any one of claims 127-145, wherein the processor is provided by a computer or handheld device.

147. The system of claim 146, wherein the handheld device is a cell phone or tablet.

148. The system of any one of claims 127-147, wherein the display further displays an image of the tumors and organs at risk obtained by medical imaging of the subject.

149. The system of any one of claims 127-148, wherein the display further displays the centroid locations of each gamma photon counter superimposed on the image.

150. The system of any one of claims 127-149, wherein the display further displays the boundary lines surrounding each tumor and organ at risk superimposed on the image.

151. The system of any one of claims 127-150, wherein the display further displays the distribution of gamma photon-emitting point sources according to the distributed point source (DPS) modelling superimposed on the image.

152. The system of any one of claims 127-151 , wherein the display further displays labels with information regarding the tumors and organs at risk superimposed on the image.

153. The system any one of claims 127-152, wherein the y-photon is emitted from a gamma ray-emitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.

154. The system of claim 153, wherein the gamma-emitting radionuclide is46Sc,67Ga,99mTc,111In,123l,1311,155Tb,177Lu,133Xe, or201TL155. The system of any one of claims 127-154, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.

156. The system of claim 155, wherein the alpha-emitting radionuclide is149Tb,223Ra, or157. The system of claim 155, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.

158. The system of any one of claims 127-157, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.

159. A method of using the system of any one of claims 127-158 for measuring tumor uptake of radiopharmaceutical comprising a gamma-emitting radionuclide in a subject, the method comprising: performing medical imaging to identify locations of one or more tumors and one or more organs at risk in the subject; positioning a first subset of the plurality of gamma photon counters on the wearable structure such that the first subset of gamma photon counters can monitor the uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by the one or more tumors in the subject; positioning a second subset of the plurality of gamma photon counters on the wearable structure such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical comprising the gamma-emitting radionuclide by the one or more organs at risk in the subject; and calculating the total percent injected activity per milliliter of tissue (%IA / mL) for the one or more tumors and the one or more organs at risk in the subject according to the computer implemented method.

160. The method of claim 159, wherein the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single photon emission computed tomography (SPECT).161 . The method of claim 159 or 160, wherein the y-photon is emitted from a gamma rayemitting radionuclide suitable for single photon emission computed tomography (SPECT) imaging.

162. The method of claim 161 , wherein the gamma-emitting radionuclide is46Sc,67Ga, "mTc, m In,123l,1311,155Tb,177Lu,133Xe, or201TL163. The method of any one of claims 159-162, wherein the y-photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.

164. The method of claim 163, wherein the alpha-emitting radionuclide is149Tb,223Ra, or225Ac.

165. The method of claim 163, wherein the beta-emitting radionuclide is32P,90Y,1311,89Sr,152Tb,153Sm,161Tb,166Ho, or177Lu.

166. The method of any one of claims 159-165, wherein the radionuclide is conjugated to a small molecule, a peptide, or an antibody.

167. The method of any one of claims 159-166, further comprising placing fiducial stickers on skin of the subject at planned locations for said positioning of the plurality of gamma photon counters.

168. The method of claim 167, wherein the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters on the wearable structure.

169. The method of any one of claims 159-168, wherein the wearable structure is clothing or adhesive patches.

170. The method of claim 169, wherein the clothing is a vest, a shirt, shorts, pants, a hat, a shoe, a glove, or a body sleeve.

171. The method of claim 169, wherein the fiducial stickers are used for said positioning of the first subset and second subset of the plurality of gamma photon counters using a plurality of adhesive patches to adhere the plurality of gamma photon counters to the skin of the subject.

172. The method of any one of claims 159-171 , wherein the plurality of gamma photon counters is attached to a first wearable structure and a second wearable structure.

173. The method of claim 172, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's arms or legs.

174. The method of claim 172, wherein the first wearable structure is wearable on the subject's torso and the second wearable structure is wearable on the subject's head.

175. The method of any one of claims 159-174, wherein the method is performed during or after administering the radiopharmaceutical to the subject.

176. The method of claim 175, wherein the radiopharmaceutical is a radioactive drug, a radioimmunotherapeutic agent, or a radiopeptide.

177. The method of claim 176, wherein the radiopharmaceutical is177Lu-PSMA-617 or225Ac-PSMA-617 administered to the subject for treatment of prostate cancer.

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