Wearable sensor for continuous personalized dosimetry for targeted radionuclide therapy

Abstract

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

Description

[0001] Cross-references to related applications

[0002] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 538,174, filed September 13, 2023, which is incorporated herein by reference in its entirety. Background Technology

[0003] Radiation therapy is highly effective in treating cancer. However, the delivery of radiation using conventional external beam radiotherapy (EBRT) to treat widespread metastatic disease is limited by the dosage delivered to normal tissues and the logistic issues of treating many sites of disease. Furthermore, treating all sites of metastatic disease with EBRT is challenging because tiny pockets of disease are not visible on diagnostic imaging. Recent advances in the treatment of metastatic neuroendocrine carcinoma and prostate cancer have generated considerable interest in both the development of targeted radionuclide therapy (TRT) to maximize therapeutic benefit and in extending these therapies to other cancers. Molecularly targeted radionuclide therapy enables systemic delivery of radiation through the chelation of a radioisotope with tumor-specific ligands, including small molecules, antibodies, and their derivatives. The radioligand is administered intravenously and circulates in the body, attaching to cancer cells and emitting localized radiation that selectively destroys nearby cells (in the micrometer to millimeter range, depending on the radioisotope used). The goal of radiotherapy (TRT) is to deliver a sufficient dose to the tumor over multiple treatment cycles to ablate cancer cells, while minimizing unintended dose deposition in radiosensitive organs at risk (OARs), such as the kidneys, salivary glands, liver, spleen, and bone marrow. Furthermore, radiotherapy (RPT) has recently shown promise in the treatment of metastatic castrate-resistant prostate cancer (mCRPC) and has redefined the treatment of metastatic cancer. Despite significant progress in androgen inhibitors (de Bono et al., (2011) New England Journal of Medicine 364(21):1995-2005, Scher et al., (2012) New England Journal of Medicine 367(13):1187-1197), mCRPC is almost incurable and currently accounts for 20% of all prostate cancer deaths (Scher et al., (2015) PLoS One 10(10):e0139440), and effective treatment remains an unmet need (Nussbaum et al., (2016) Prostate Cancer Prostatic Dis. 19(2):111-21).Although significant progress has been made in recent years in the treatment of locally and newly diagnosed metastatic prostate cancer using new androgen blockade agents, improved imaging, surgical, and radiological techniques, the number of men developing mCRPC is increasing (Scher et al., (2015), ibid.). In the United States, the incidence of mCRPC is increasing at a rate of approximately 1.7% per year, estimated at 36,100 cases in 2009 and increasing to 42,970 cases in 2020 (Scher et al., (2015), ibid.). With limited treatment options, patients with mCRPC continue to have significantly poor survival (approximately 13–30 months (Halabi et al., (2016) Journal of Clinical Oncology 34(14):1652–1659)) and there is an urgent need for additional treatment options to overcome mechanisms of resistance. Current strategies, such as androgen suppression, chemotherapy (median survival of 18-19 months) (Tannock et al., (2004) *New England Journal of Medicine* 351(15):1502-1512, Petrylak et al., (2004) *New England Journal of Medicine* 351(15):1513-1520) or T-cell therapy (Higano et al., (2009) *Cancer* 115(16):3670-3679), offer only incremental benefits (median survival of 26 months) but inevitably fail (Hotte et al., (2010) *Curr Oncol* 17 Supplement 2:S72-9). Patients who fail first-line chemotherapy survive only 12-16 months. Although radiation therapy is highly effective for prostate cancer, it cannot be delivered to widespread metastatic disease using conventional external beam techniques due to the toxicity of irradiating significant amounts of normal tissue, as discussed. The Food and Drug Administration (FDA) recently approved it. 177 Lu-PSMA-617, a beta-particle-emitting radioligand therapy, is used to treat mCRPC (Sartor et al., (2021) The New England Journal of Medicine). New England Journal of Medicine(See references: 385:1091-1103, “Study of 177Lu-PSMA-617 In Metastatic Castrate-Resistant Prostate Cancer (VISION)”, identifier NCT03511664 (May 9, 2022 – August 11, 2022), Aghdam et al., (2019) World Journal of Nuclear Medicine 18(3):258-265, Kratochwil et al., (2016) Journal of Nuclear Medicine 57(8):1170-1176). Prostate-specific membrane antigen (PSMA) is a type II transmembrane glutamate carboxypeptidase that is highly expressed in mCRPC lesions. Elevated PSMA expression is an independent biomarker for poor prognosis, with its expression increasing in high-grade or metastatic tumors and typically absent in benign prostatic tissue (Sartor et al., ibid.).

[0004] Similar to the goal of stereotactic ablation radiotherapy, where the radiation dose to the tumor of interest is maximized while the dose to surrounding tissues is minimized, therapeutic radioligand therapy aims to maximize tumor uptake of radionuclides while minimizing unwanted dose deposition and toxicity to organs at risk (OARs) such as the kidneys, bladder, and bone marrow. In current clinical trials and practice, 177Lu-PSMA-617 is administered using standard dosing or a “one-size-fits-all” strategy. This treatment strategy ignores common patient-to-patient heterogeneity, including (1) varying tumor grades and therefore varying PSMA expression levels, (2) anatomical and physiological variations, including those of the tumor vascular system, radionuclide retention and excretion rates, (3) daily variations, including heart rate, blood pressure and blood flow rate, and (4) on-target but off-tumor toxicity from the binding of radionuclides to PSMA-expressing OARs (Aghdam et al., (2019) World Journal of Nuclear Medicine 18(3):258-265, Ling et al., (2022) Pharmaceutics 14(10):2166, Membreno et al., (2019) Mol Pharm 16(5):2259-2263). This approach undermines key dosing and triage modalities that could have improved 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, long-term biodistribution measurements for each patient over several half-lives and across all grades are extremely important in assessing and optimizing treatment response (Kratochwil et al., (2016) Journal of Nuclear Medicine 57(8):1170-1176, Nautiyal et al., (2022) Nucl Med Commun. 43(4):369-377, Kabasakal et al., (2017) Molecular Imaging Radionucl Ther. 26(2):62-68).

[0005] Single-photon emission computed tomography (SPECT) is currently the most advanced dosimetry technique in radioligand therapy. Despite advances in SPECT imaging and reconstruction algorithms, this dosimetry method provides a whole-body snapshot at only a single time point, leaving patient-specific long-term dosimetry an unmet need. Due to the lack of universal availability of SPECT, its long acquisition time, and high cost, performing multiple scans on each patient during treatment is logically impractical. At most one SPECT scan is acquired per treatment cycle, if any. The total dose is usually 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 point. However, this is insufficient, as the time to maximum uptake (tmax) and the effective half-life (Teff, the time required for the dose to become half) of metastatic lesions can vary by 50% and 30%, respectively. This uncertainty in dose estimation translates into dose variations exceeding 70% during treatment (Peters et al., (2022) Eur J Nucl Med Mol Imaging 8;49(4):1101-1112).

[0006] There is still a need for improved platforms for real-time, long-term in vivo dose determination to complement current medical imaging modalities. Summary of the Invention

[0007] Devices, systems, software, and methods are provided for calculating the percentage injected activity per milliliter of tissue (%IA / mL) delivered to tumors and organs at risk in subjects receiving radiopharmaceutical therapy (RTP). The method utilizes fiber-optic or chip-based gamma sensors or counters capable of real-time monitoring of radiopharmaceutical uptake by tumors or organs at risk (OARs) during and between all stages of treatment. Medical imaging is used to identify the location of tumors and OARs in the subject to position the counters on a wearable structure or the subject's skin to monitor radiopharmaceutical uptake. Furthermore, an algorithm is provided that automatically calculates the %IA / mL for tumors and OARs based on prior knowledge of the gamma count rate recorded by a sparse set of gamma counters, as well as the locations of the tumors, OARs, and gamma counters. The systems and methods disclosed herein can be used for non-invasive, continuous, real-time dosimetry of multiple tumors and OARs with high accessibility.

[0008] Fundamentally, the platform's uniqueness lies in its synergistic integration of algorithmic approaches to significantly reduce the amount of data required (and thus spatial coverage) for accurately reconstructing TRT dosimetry and SPECT images. The platform leverages prior knowledge of the tumor and OAR location, combined with strategically placed or sparsely placed sensors. Secondly, the platform uses integrated circuit technology to implement sensors with asynchronously operating pixels, enabling the determination of the energy and direction of incident photons, and allowing for highly reusable sensor arrays on the patient. The sensor area is scalable yet remains thin (< 300 micrometers). In some implementations, sensors are stacked to achieve energy resolution and acquire directional photon information, further enhancing the spatial resolution and accuracy of radionuclide distribution detection. The sensors have extremely small thickness and weight, allowing multiple sensors to be used simultaneously as wearable devices. The platform is capable of performing single-photon sensing for image reconstruction, similar to SPECT, unlike positron emission tomography-based imaging, where two time-coincident photons must be detected. No collimator is required. Instead, the flux of single-photon (γ) emission is captured at different known locations on the patient's surface to reconstruct the distribution of γ emission in vivo, and thus reconstruct dosimetry for tumors and organs at risk. The platform also utilizes the angle of the incident photon (in contrast to a collimator, which eliminates all angles except a narrow window of the incident angle) to inversely calculate the distribution of γ-emitted radionuclides. This approach allows for the measurement of a greater number of γ photons at a single spatial point, potentially increasing the signal-to-noise ratio and reducing the time required to collect the amount of data needed for accurate image reconstruction. In some embodiments, a chip-based platform is provided that is capable of a highly scalable architecture, allowing numerous 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 achieve energy resolution and / or incident direction resolution within a shape parameter of < 5 mm thickness. Furthermore, the use of SPECT emitters allows for greater selection of radionuclides to be imaged, and importantly, allows for imaging of the distribution of TRT.

[0009] In one aspect, a gamma photon counter is provided, comprising: a Y₂O₃-Eu-doped phosphor, wherein gamma photons incident on the surface of the Y₂O₃-Eu-doped phosphor generate scintillation light in the visible spectrum, the scintillation light being suitable for solid-state photon detection; a detector including a photodiode; an optical fiber guiding the scintillation light generated by the Y₂O₃-Eu-doped phosphor to the detector, wherein the detector generates a voltage pulse in response to detecting the scintillation light generated by the gamma photons; a digital counter coupled to the detector, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to a voltage pulse generated by the detector in response to detecting scintillation light generated from each gamma photon incident on the surface of the Y₂O₃-Eu-doped phosphor; and an opaque material covering the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y₂O₃-Eu-doped phosphor.

[0010] In some implementations, the photodiode is an avalanche photodiode (APD). In other implementations, the APD is a silicon APD.

[0011] In some implementations, the photodiode is a single photon avalanche diode (SPAD).

[0012] In some implementations, the detector further includes multiple power supplies to control circuit cooling, quenching and reset, as well as high-voltage bias.

[0013] In some implementations, the detector further includes a high-voltage regulator.

[0014] In some 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.

[0015] In some implementations, the incident gamma photons arriving at the detector surface are uncollimated.

[0016] In some implementations, the digital counter is configured in a field-programmable gate array (FPGA).

[0017] In some implementations, the gamma photon counter further includes a clock configured to generate a clock signal, wherein the digital counter uses the clock signal to count the number of gamma photon detection events within each time period.

[0018] In some implementations, the gamma photon counter further includes a level shifter configured in the circuit to ensure logic level compatibility with the digital counter.

[0019] In some implementations, the gamma photon counter further includes a data storage unit in communication with a digital counter, wherein the data storage unit is configured to store multiple gamma photon count records of multiple gamma photon detection events.

[0020] In some embodiments, the gamma photon counter further includes a data processing unit in communication with the data storage unit, wherein the data processing unit is programmed to calculate the total percentage of injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in the subject from multiple gamma photon count records.

[0021] In some embodiments, the gamma photon counter is attached to a wearable structure. In some embodiments, the gamma photon counter is attached to fabric or an adhesive patch. In some embodiments, the gamma photon counter is attached to clothing, such as, but not limited to, vests, shirts, shorts, trousers, hats, shoes, gloves, or body sleeves.

[0022] In some implementations, the gamma photon counter has a diameter of less than or equal to 2.5 mm.

[0023] On the other hand, a gamma photon counter is provided, comprising: a detector implemented as an application-specific integrated circuit (ASIC) on a chip, wherein the detector includes at least one reverse-biased diode, wherein gamma photons incident on the surface of the reverse-biased diode generate voltage pulses across the reverse-biased diode. In some embodiments, the reverse-biased diode is connected to an amplifier and then to a digital counter. In other embodiments, the reverse-biased diode is connected to a voltage buffer before being connected to a voltage amplifier and subsequently to the digital counter. The digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to a voltage pulse generated across the reverse-biased diode by each gamma photon incident on the surface. In some embodiments, the chip further includes an on-chip memory configured to store a plurality of gamma photon count records of a plurality of gamma photon detection events. In some embodiments, the chip further includes a digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period. In some implementations, the chip further includes custom digital logic circuitry configured to control voltage and supply power to detectors, digital counters, and digital clocks from on-chip or off-chip energy storage devices.

[0024] On the other hand, a gamma photon counter is provided, comprising: a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma sensing element. In some embodiments, each pixel in the array includes a silicon diode connected to an amplifier. In some embodiments, each pixel operates asynchronously, meaning that each pixel can register gamma interactions without reading out the entire array. This allows for greater temporal resolution and enables near-single-particle sensitivity on the array. This feature makes it possible to determine the incident direction of gamma photons, which then allows for improved image reconstruction using fewer incident gamma photons (compared to pure gamma counting without directional information). Regarding the diodes, in some embodiments, the diodes are reverse-biased. In other embodiments, the diodes have a zero-voltage bias. Regarding the pixel architecture, in some embodiments, this is a differential structure, where two diodes are connected to the input of a differential amplifier. Utilizing the sparsity of photon strikes, the most likely event is that only a single diode is struck at any given time, thereby generating a differential pulse at the output of the amplifier. This structure has the advantage of mitigating offsets associated with diode characteristics, reset, or other circuitry that affect the baseline voltage (signal) across the diodes. Any mismatch between the two diodes manifests as an input offset in the amplifier and can cause the amplifier to operate in the low-gain region or "rail" (saturation) to the point where it is not activated at all. Therefore, the differential structure enables the amplifier to maintain operation despite some inherent variations in the sensing diodes across the chip. Pulses from each diode are generated by the following process: incident gamma photons break bonds in the silicon, generating electron-hole pairs, which in turn generate a charge pulse (Q) in the silicon diode. p ), the charge pulse (Q p In parasitic diode capacitor (C) 二极管 This accumulates on the diode. This generates a small voltage pulse (V) across the diode. p = Q p / C 二极管 The use of integrated circuit technology enables ultra-small diode capacitance, increasing VC. pThis allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity-gain voltage amplifier. Each of these buffered outputs is connected to an input of a differential amplifier. In some implementations, to mitigate DC voltage offsets at the output due to manufacturing variability from inter-pixel and inter-chip sources, which can cause variability in detector sensitivity, a voltage integrator is configured with negative feedback to bootstrap from the amplifier's output to one of the amplifier's inputs. The voltage integrator also accepts a desired DC voltage that sets the voltage at the amplifier's output. This ensures that the sensitivity of each pixel across the chip is approximately the same. To tune each diode in each pixel to the desired sensitivity, the amplifier's output is connected to two level shifters: one level shifter shifts the DC level at the amplifier output upwards to amplify only the voltage pulse from the first diode, and the other level shifter shifts the DC level at the amplifier output downwards to amplify only the voltage pulse from the second diode. The amount by which these DC levels are offset is set using on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) to convert the stored bits into an analog voltage offset. These shifted and amplified voltage pulses are then digitized using a series of inverters. A capacitor at the input of the last inverter improves signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, where the digital counter counts gamma-photon detection events, where each gamma-photon detection event corresponds to a voltage pulse across the diode generated by each gamma photon incident on the surface of any silicon diode. The chip also includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate an on-chip clock signal, which the digital counter uses to count the number of gamma-photon detection events for each time period; and custom digital logic configured to control the voltage and supply power to the detector, digital counter, and digital clock from on-chip or off-chip power storage devices.

[0025] On the other hand, a gamma photon counter is provided, comprising: a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma sensing element, wherein each pixel includes a single reverse-biased silicon diode connected to a unity-gain voltage buffer. A buffered voltage output from a unity-gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed-loop amplifier can be preset or configured using in-pixel memory and a DAC. Gamma photons incident on the surface of the silicon diode generate voltage pulses across the diode and are subsequently buffered and amplified with a fixed, process-invariant gain. These voltage pulses are then digitized using a series of inverters connected to a digital counter to quantify the total number of gamma photons detected within a specific time frame. Each gamma photon detection event corresponds to a voltage pulse across the diode generated by each gamma photon incident on the surface of the silicon diode. The chip further includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events for each time period; and custom digital logic circuitry configured to control voltage and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0026] In some embodiments, detector sensitivity is optimized by reducing diode capacitance. In some embodiments, the diode size is 0.1 µm to 0.5 µm × 0.1 µm to 0.5 µm. In some embodiments, the diode size is 0.5 µm to 1 µm × 0.5 µm to 1 µm. In some embodiments, the diode size is the smallest available for complementary metal-oxide-semiconductor (CMOS) processes (and continues to decrease in size).

[0027] In some implementations, the detector is optimized to strike a tradeoff between pixel fill factor and sensitivity, wherein the diode size is 1 µm to 1.5 µm x 1 µm to 1.5 µm.

[0028] In some implementations, the detector is optimized to improve the fill factor with a trade-off in sensitivity, wherein the diode size is 1.5 µm to 3 µm x 1.5 µm to 3 µm.

[0029] In some implementations, the detector is optimized to improve the fill factor with a trade-off in sensitivity, wherein the diode size is 3 µm to 10 µm x 3 µm to 10 µm.

[0030] In some implementations, the detector is optimized to improve the fill factor with a trade-off in sensitivity, wherein the diode size is 10 µm to 50 µm x 10 µm to 50 µm.

[0031] The detector can have any suitable shape, such as a curved shape or a polygonal shape. In some embodiments, the detector is circular, elliptical, semi-circular, spherical, cylindrical, triangular, square, rectangular, pentagonal, hexagonal, octagonal, rhomboid, or parallelogram. In some embodiments, the detector has sides ranging in length from 0.1 µm to 50 µm.

[0032] In some implementations, the on-chip memory is static random-access memory (SRAM).

[0033] In some implementations, the chip has a diameter of less than or equal to 1 mm. 2 Surface area.

[0034] In some implementations, the chip has a thickness of less than or equal to 0.5 mm.

[0035] In some implementations, the chip has a diameter of less than or equal to 10 mm. 2 The surface area (e.g., to increase the measured gamma photon flux incident on the sensor).

[0036] In some implementations, the chip has a diameter of less than or equal to 1 cm. 2 The surface area (e.g., to increase the measured gamma photon flux incident on the sensor).

[0037] In some implementations, the chip has a 1 cm 2 Up to 5 cm 2 The surface area (e.g., to increase the measured gamma photon flux incident on the sensor).

[0038] In some implementations, the chip includes multiple detectors. In some implementations, the multiple detectors are organized into a detector array.

[0039] In some implementations, multiple sensors are integrated together to create a larger sensing array.

[0040] In some embodiments, the chip-based sensor has a shape parameter with a thickness 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 shape parameter has a thickness in the range of 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.

[0041] In some embodiments, the chip is covered with a material capable of Compton scattering gamma photons. Compton scattering materials can include, but are not limited to, lead, tungsten, or bismuth. Compton scattering of gamma photons colliding with the material generates lower-energy photons (typically < 100 keV) that have a high probability of interacting with the detector due to the photoelectric effect, and additionally generates secondary electrons from collisions with primary gamma photons, which also have a high probability of interacting with the detector. In some embodiments, these secondary electrons generated by the gamma photons are detected by the detector. Both energy conversions can be achieved by using a thin, high-density layer of Compton scattering material on top of or on the back of the detector (e.g., covering bulk silicon), which can enhance the detector signal, increase its sensitivity, and minimize data acquisition time.

[0042] In some implementations, the energy of an incident photon can be determined by measuring the ratio of detector counts using multiple detectors with attenuating materials of varying thicknesses. The attenuating material can include lead, tungsten, bismuth, or other high-density materials. For example, lower-energy photons have an exponentially higher probability of interacting with lead and can be detected without a lead layer, or in some cases, with only a very thin lead layer. Higher-energy photons are selectively measured by creating a subsequently thicker lead layer on top of other detectors to completely attenuate lower-energy photons and allow only high-energy photons to pass through. This process can be repeated with layers of different thicknesses to allow for determining the energy resolution of the incident gamma photon flux, which consists of multiple primary energy emissions. Because the energy of the gamma photons will be distributed across lead of varying thicknesses, multiphysics simulations can be used to determine the probability of detecting a certain energy photon with a detector of a given lead thickness and can be used to separate the detection counts for each energy.

[0043] In some embodiments, a chip-based gamma detector is provided that has energy resolution capable of determining the incident flux of gamma photons. In some embodiments, the chip-based gamma detectors are arranged in a vertically stacked configuration, wherein each detector is separated from another detector by a thin layer of attenuating material (see [link to relevant documentation]). Figure 33A The attenuation material may include lead, tungsten, bismuth or other high-density materials.

[0044] In some implementations, multiple chip-based gamma detectors are stacked with a stacking thickness of 3 mm or more and less than 5 mm, or 1 mm or more and less than 3 mm, or 0.1 mm or more and less than 1 mm.

[0045] In some embodiments, multiple chip-based gamma detectors are stacked with shape parameters 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 shape parameters have a thickness in the range of 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.

[0046] In some implementations, chip-based gamma detectors capable of determining the energy resolution of the incident flux of gamma photons are placed in the same plane to provide energy resolution over substantially the same spatial region. In some implementations, each detector has an attenuating material of varying thickness, such as lead, tungsten, bismuth, or other high-density material, which is placed on the surface of the detector or over the bulk silicon.

[0047] In some implementations, the on-chip circuitry is tuned to respond to a range of linear energy transfer (LET) such that the combination and distribution of signals from various pixels with known LET responsivity can determine the incident energy of the gamma photon. For example, low-energy photons have a high LET and can be detected by a pixel with low gain that only detects low-energy photons and does not detect higher-energy photons with higher LET, which do not generate a signal. On the same chip or adjacent chips, pixels with higher gain are included to amplify the low LET from higher-energy photons. Pixels with higher gain respond to both lower-energy and higher-energy photons. By combining statistics from the set of pixels with lower gain and the set of pixels with higher gain, the energy distribution of the incident gamma photon can be determined.

[0048] In some implementations, a combination of all the above-described energy resolution methods is used to determine the energy distribution of the incident γ photons.

[0049] In some embodiments, the pixel sensor may also respond to electrons generated by gamma photons. For example, electrons can be generated by gamma photons via the photoelectric effect, where a gamma ray transfers all its energy to the electron, causing it to be ejected from an atom. Alternatively, electrons can be generated by gamma photons via Compton scattering, which similarly causes electrons to be ejected from atoms, where the gamma ray retains some of its energy and scatters in different directions. In some embodiments, electrons are generated by gamma photons in a patient receiving a radiopharmaceutical containing a gamma-emitting radionuclide, in a layer of material placed between the patient and the pixel sensor, or in the silicon of a diode after a collision with a gamma photon. The electrons bombarding the silicon diode create electron-hole pairs in the silicon, which generate voltage pulses across the silicon diode. These voltage pulses can be detected using the chip-based devices described herein, similar to those generated by gamma photons. In some embodiments, the pixel sensor detects both gamma photons and electrons generated by gamma photons.

[0050] In some implementations, gamma photon sensors are stacked on top of each other to enable measurement of the incident angle of the photon. In some implementations, the stacked sensors are equipped with fast readout circuitry for an array of gamma sensing elements to allow near-instantaneous detection of the same incident gamma photon passing between two sensors in the stack. In some implementations, this near-instantaneous detection of the incident gamma photon is achieved through asynchronous pixel operation, such that each pixel samples the gamma hit and transmits the time of hit, pixel position, and a signal from the gamma hit, which is correlated with the LET of the gamma counter. The angular offset of the gamma photon transmitted from the top sensor to the sensor below can be used to calculate the incident gamma photon angle on the sensor stack by evaluating the numerical equations governing the physics of Compton scattering. Measurement of the incident gamma photon angle provides an additional dimension of information when reconstructing dose information in the tumor and OAR during therapy and allows for the use of a smaller number of sensors around the patient.

[0051] In some implementations, the clock signal is generated by a frequency-locked loop (FLL) oscillator. The clock beacon of the FLL is generated by an off-chip crystal oscillator.

[0052] In some implementations, the clock signal is generated directly by an off-chip crystal oscillator.

[0053] In some implementations, clock and control signals are generated by an external computer, FPGA, mobile phone, or other control device.

[0054] In some implementations, the on-chip or off-chip energy storage device includes a battery, a capacitor, or a photovoltaic system. In some implementations, the battery is rechargeable.

[0055] In some implementations, the gamma photon counter is connected via wires to a power supply, a control source (FGPA, computer, laptop, telephone), and a data collection unit. In some implementations, the data is wirelessly uploaded to the cloud.

[0056] In some implementations, the gamma photon counter is wireless and communicates with a central computer.

[0057] In some embodiments, the gamma photon counter further includes a data processing unit in communication with an on-chip memory, wherein the data processing unit is programmed to calculate the total percentage of injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in the subject from multiple gamma photon count records.

[0058] In some embodiments, the sensors will be organized into small arrays and interconnected to allow 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. It also achieves low power consumption by avoiding the need for additional readout and communication circuitry for each additional chip. Interconnecting the sensors in the small arrays allows for higher count recording, which directly reduces the required recording time to achieve a sufficient signal-to-noise ratio (SNR) for dose reconstruction in tumors and OARs. In some embodiments, many arrays of these small interconnected arrays of sensors can be used simultaneously. In this embodiment, each small interconnected array will be connected to each other and used with a single common communication and readout circuitry to prevent excessive wiring, reduce power consumption, and reduce the complexity of data collection during the therapy process. In some embodiments, the gamma photon counter is attached to a wearable structure. In some embodiments, the gamma photon counter is attached to fabric or adhesive patches. In some embodiments, the gamma photon counter is attached to clothing, such as, but not limited to, vests, shirts, shorts, trousers, hats, shoes, gloves, or body armor.

[0059] On the other hand, a wearable system is provided that includes a plurality of gamma photon counters (e.g., fiber-optic gamma photon counters or chip-based gamma photon counters) as described herein, which are attached to a wearable structure.

[0060] In some implementations, the wearable structure is clothing or adhesive patch.

[0061] In some embodiments, multiple gamma photon counters are positioned on a patient (or subject), on a garment (which is relatively fixed in position relative to the patient), on a strap, or with an adhesive tag, or on any other device, such that the position of the sensor is relatively fixed relative to the patient or subject. A first subset of these gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject; and a second subset of the multiple gamma photon counters is positioned on the garment such that, when the garment is worn by the subject, the second subset of the gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by an organ at risk in the subject.

[0062] In some implementations, medical imaging is used to determine the location of each gamma photon counter on the garment relative to all tumors and organs at risk in the patient. In some implementations, the medical imaging of the subject is performed using positron emission tomography (PET), computed tomography (CT), or single-photon emission computed tomography (SPECT).

[0063] In some implementations, multiple gamma photon counters are arranged in an array on the garment.

[0064] In some implementations, adhesive patches are used to attach each of the multiple gamma photon counters to the subject's skin.

[0065] In some embodiments, multiple gamma photon counters are attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's arm or leg. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's head.

[0066] On the other hand, a computer-implemented method is provided for calculating the total injection activity percentage (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject. The computer-executed steps include: a) receiving gamma photon count data from a plurality of gamma photon counters, each gamma photon counter having a known location; b) receiving an image of the subject showing the locations of one or more tumors and one or more organs at risk in the subject, and the locations of the plurality of gamma photon counters relative to the one or more tumors and one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) using the image to measure the volume of the one or more tumors and organs at risk; e) mapping the centroid location of each gamma photon counter on the image; f) performing distributed point source (DPS) modeling to generate a distribution of gamma photon emission point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) decay based on counts per second (CPS) and 1 / (the distance between the centroid location of the gamma photon counter and the gamma photon emission point source). 2The relevant assumptions include: calculating the probability of receiving gamma photons counted by the gamma photon counter from a gamma photon emission source within the boundary of a specific tumor or organ at risk for each gamma photon counter; and the CPS value being decayed by an empirically derived factor Ω, which takes into account the attenuation and scattering of gamma photons in the tissue; and ii) estimating the possible fraction of counts corresponding to a specific tumor or organ at risk for each gamma photon counter; g) estimating the total count for each tumor and organ at risk using a Monte Carlo Chain (MCMC) algorithm based on gamma photon count data from multiple counters and parameter estimates of the possible fraction of counts corresponding to a specific tumor or organ at risk for each gamma photon counter, modeled from DPS; h) calculating the total %IA / mL of one or more tumors and organs at risk in the subject based on the estimated total count for each tumor and organ at risk, divided by the volume of one or more tumors and organs at risk measured from the image; and i) displaying the total %IA / mL of one or more tumors and organs at risk in the subject.

[0067] In some implementations, performing DPS modeling includes creating a DPS model matrix ( W ), which represents the counts per second (CPS) contributed by each tumor or at-risk organ to each of the multiple gamma photon counters, where the CPS per μC is multiplied by the unknown activity in μC of the total tumor or at-risk organ activity, where the DPS model matrix ( W The values ​​in ) are estimated based on knowledge of the location of each tumor and each organ at risk from the image, as well as the known location of each γ-photon counter; and the DPS model matrix ( W Decompose into a matrix ( β ) and vectors ( α ), where the matrix ( β ) represents the score of CPS from a specific tumor or at-risk organ in each gamma photon counter, where the score is represented by a vector ( α ) scaled up proportionally, where the vector ( α ) is the CPS of μCi activity per injection for each γ-photon counter.

[0068] In some implementations, vectors are estimated by performing DPS titration simulations. α .

[0069] In some implementations, the matrix ( βThe initial estimation was made by: i) assuming that each tumor and each at-risk organ takes up an equal amount of radionuclide, where the total amount of radionuclide administered to the subject is known; and ii) allocating the same activity to all tumors and at-risk organs for the estimated possible fraction of the count per μCi of activity corresponding to a specific tumor or at-risk organ, counted by each counter. This estimation is based on acquiring each point source in the DPS model and utilizing 1 / (the distance between the centroid position of the gamma photon counter and the gamma photon emission point source) of the point source. 2 The relationship is used to estimate the count probability per μCi of activity. This value is also attenuated by an empirically derived factor Ω, which takes into account the attenuation and scattering of γ photons in the tissue, when the distance between the detector and the point source is large in the tissue.

[0070] In some implementations, the factor Ω is derived empirically by employing each gamma counter and performing fine sweeps at various depths in water at a point source 1 mm (2 μL) away from the utilized radioligand, characterizing the counts per second (CPS) detected. This sweep is repeated in air. The factor difference between the two curves at each distance is estimated, and this represents the nonlinear factor contributing to the scattering and attenuation of each point source. A unique factor Ω is assigned to each source based on the distance from each detector to each point source in the DPS model within the tissue.

[0071] In some implementations, the computer-implemented method further includes using adaptive Metropolis AM optimization, where information accumulated during chain generation using the MCMC algorithm is used to update the Gaussian proposal distribution.

[0072] In some implementations, the computer-implemented method further includes iterative optimization techniques, including but not limited to gradient descent, least squares minimization, and brute-force global minimization.

[0073] In some implementations, the computer-implemented method further includes segmenting the image, wherein the boundaries of each tumor and organ at risk are segmented, as well as the centroid location of each gamma photon counter.

[0074] In some embodiments, the plurality of gamma photon counters include on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from incident gamma photons, wherein the computer-implemented method further includes calculating the incident energy of the gamma photons based on combinations and distributions of signals from pixels having known LET responsivity. In some embodiments, the array of pixels includes a first subset and a second subset of pixels having 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 with higher LET but not higher-energy gamma photons with lower LET, and wherein the second set of pixels detects both lower-energy gamma photons with higher LET and higher-energy gamma photons with lower LET.

[0075] In some embodiments, multiple detectors are arranged in a vertically stacked configuration. In some embodiments, each detector is separated from adjacent detectors in the vertical stack by a layer of attenuating material. In some embodiments, each detector has fast readout circuitry connected to an array of pixels to allow near-instantaneous detection of the same incident gamma photon passing between two detectors in the vertical stack. In some embodiments, each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits the time when the incident gamma photon hits the pixel, the pixel position on the detector, and the signal generated by the gamma photon hitting the pixel. In some embodiments, the computer-implemented method further includes calculating the angle of the incident gamma photon relative to the vertical stack by measuring the angular offset of the incident gamma photon from the detector at the top of the stack to the detector located below in the stack (e.g., due to Compton scattering).

[0076] In some implementations, multiple detectors are arranged in a planar layout in a space region, wherein the computer-implemented method further includes determining the energy of incident gamma photons in the space region.

[0077] On the other hand, a non-transitory computer-readable medium is provided, comprising program instructions that, when executed by a processor in a computer, cause the processor to perform the methods described herein for calculating the total percentage of total injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject.

[0078] On the other hand, a kit is provided that includes the non-transitory computer-readable medium described herein and instructions for calculating the percentage of total injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject.

[0079] In another aspect, a system is provided comprising: a) a plurality of gamma photon counters (e.g., fiber-optic gamma photon counters or chip-based gamma photon counters) as described herein, attached to a wearable structure; b) a power supply; c) a processor, wherein the processor is programmed to calculate the total percentage of injection activity (%IA / mL) per milliliter of tissue 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 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.

[0080] In some implementations, multiple gamma photon counters are attached to clothing or adhesive patches.

[0081] In some embodiments, a first subset of multiple gamma photon counters is arranged on clothing such that, when the clothing is worn by a subject, the first subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset on the clothing is determined based on medical imaging of the subject to determine the location of the tumor in the subject; and a second subset of multiple gamma photon counters is arranged on clothing such that, when the wearable material is worn by a subject, the second subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset on the clothing is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

[0082] In some implementations, multiple gamma photon counters are arranged in an array on the garment.

[0083] In some implementations, adhesive patches are used to attach each of the multiple gamma photon counters to the subject's skin.

[0084] In some embodiments, multiple gamma photon counters are attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's arm or leg. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's head.

[0085] In some embodiments, a first subset of multiple gamma photon counters is attached to the subject's skin via an adhesive patch, such that the first subset of gamma photon counters can monitor the uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset is determined based on medical imaging of the subject to determine the location of the tumor in the subject; and a second subset of multiple gamma photon counters is attached to the subject's skin via an adhesive patch, such that the second subset of gamma photon counters can monitor the uptake of a radiopharmaceutical comprising a gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

[0086] In some 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 ultrasonic transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radio frequency (RF) transducer. In some embodiments, the internal power source includes a battery, a radionuclide, or a photovoltaic system.

[0087] In some implementations, the power source is used to provide power to the detector.

[0088] In some implementations, the external power supply is portable.

[0089] In some implementations, the external data receiving device includes a wireless communication unit. In some implementations, the wireless communication unit utilizes a wireless communication protocol that uses electromagnetic carrier waves (e.g., radio waves, microwaves, or infrared carrier waves) or ultrasonic waves to receive data from the internal data storage unit.

[0090] In some implementations, the processor is provided by a computer or a handheld device (e.g., a mobile phone or tablet).

[0091] In some implementations, connections for the sensors are made via wiring on the patient's body, or embedded in their clothing or other support devices, 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 for output, allowing many sensors to be multiplexed together using a small set of shareable connections. In some cases, nodes in a FIFO memory are used to buffer a subset of information from the sensors and output them when the common data line is idle.

[0092] In some implementations, the display further shows images of tumors and organs at risk obtained through medical imaging of the subject.

[0093] In some implementations, the display further shows the centroid position of each gamma photon counter superimposed on the image.

[0094] In some implementations, the display further shows the boundary lines around each tumor and at-risk organ superimposed on the image.

[0095] In some implementations, the display further models the distribution of gamma photon emission point sources based on distributed point sources (DPS) superimposed on the image.

[0096] In some implementations, the display further shows labels with information about tumors and organs at risk superimposed on the image.

[0097] On another aspect, a method is provided for measuring tumor uptake of a radiopharmaceutical containing a gamma-emitting radionuclide in a subject using the system described herein, the method comprising: performing medical imaging to identify the location of one or more tumors and one or more organs at risk in the subject; positioning a first subset of a plurality of gamma photon counters on a wearable structure such that the first subset of gamma photon counters can monitor uptake of the radiopharmaceutical containing a gamma-emitting radionuclide by one or more tumors in the subject; positioning a second subset of a plurality of gamma photon counters on the wearable structure such that the second subset of gamma photon counters can monitor uptake of the radiopharmaceutical containing a gamma-emitting radionuclide by one or more organs at risk in the subject; and calculating, according to a computer-implemented method, the total percentage of injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in the subject.

[0098] In some implementations, positron emission tomography (PET), computed tomography (CT), or single-photon emission computed tomography (SPECT) is used to perform medical imaging on the subject.

[0099] In some embodiments, the method further includes placing a fiducial sticker on the subject's skin at the planned location for the positioning of multiple gamma photon counters.

[0100] In some embodiments, multiple gamma photon counters are attached to a wearable structure, wherein reference markers are used for positioning a first subset and a second subset of the multiple gamma photon counters on the wearable structure. In some embodiments, the wearable structure is clothing or an adhesive patch.

[0101] In some implementations, a reference marker is used to locate a first subset and a second subset of the multiple gamma photon counters by adhering multiple adhesive patches to the subject's skin.

[0102] In some embodiments, multiple gamma photon counters are attached to a first wearable structure and a second wearable structure. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's arm or leg. In some embodiments, the first wearable structure can be worn on the subject's torso, and the second wearable structure can be worn on the subject's head.

[0103] In some embodiments, gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging. In some embodiments, the gamma-emitting radionuclides are... 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

[0104] In some embodiments, gamma photons are emitted from radionuclides emitted by alpha particles or beta particles. In some embodiments, the alpha-emitting radionuclides are... 149 Tb, 223 Ra, or 225 Ac. In some implementations, the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

[0105] In some implementations, radionuclides are conjugated with small molecules, peptides, or antibodies.

[0106] In some implementations, the method is performed during or after administration of targeted radionuclide therapy to the subject.

[0107] In some implementations, radiopharmaceutical therapy includes administering radiopharmaceuticals, radioimmunotherapy agents, or radiopeptides to the subject.

[0108] In some implementations, targeted radionuclide therapy includes administering [the treatment] to the subject. 177 Lu-PSMA-617 or 225 Ac-PSMA-617 is used to treat prostate cancer. Attached Figure Description

[0109] Figure 1A-1D Sparse gamma sensing network and real-time %IA / g reconstruction. Figure 4A Pre-treatment PET / CT scans were performed to identify which tumors and OARs would respond to SUV-based [treatment]. 177 Lu-PSMA-617 therapy. CT baseline markers are placed on the skin to mark the location where the probe will be placed. Figure 4B Following RPT administration, frequent gamma recordings are performed using a sparse probe sensing network. (Figure 4C) Structure of the gamma probe optical sensing front end. (Figure 4D) Using the novel reconstruction algorithm of this invention, the raw, uncollimated gamma recordings are converted into %IA / mL data for both the tumor and the OAR. This information can be used to assess whether the dose administered to the tumor is sufficient and to ensure that no toxicity to the OAR occurs.

[0110] Figure 2A-2C The conceptual workflow of the reconstruction algorithm. Figure 2A Sparse gamma sensing network devices and circuits (top) Figure 2A The recorded γCPS distribution (bottom) is decomposed into unknown total tumor and OAR activity multiplied by matrix W. Matrix W can be further decomposed into matrix β and vector β. . ( Figure 2B The matrix β (at the top) can be derived from annotated CT scans using the DPS model. Figure 2B (bottom) vector This can be derived from a comparison between experimental and simulated titration experiments. Figure 2C MCMC is used to create probabilistic estimates of tumor / OAR activity that, when transformed by matrix W, give the γCPS distribution that is most similar to experimental measurements.

[0111] Figures 3A-3F Experimental setup and reconstruction of the phantom. Figure 3A The experimental setup for the phantom experiment. Figure 3B The sensors used and the location of the vials. Figure 3C A convergent DPS model for phantom experiments. Figure 3D The convergence plot of reconstructed activity as more sensors are added to the phantom. Figure 3E The convergence of MCMC γCPS compared to experimental γCPS. Figure 3FThe probability distribution of the activity guesses for four vials, where N=4, N=10 and N=16 sensors were added to the phantom.

[0112] Figures 4A-4B Experimental and reconstruction workflows for gamma-sensing networks applied to in vivo models. Figure 4A The overall experimental workflow included SQ-injection of human prostate cancer cell lines to create four different mouse models, placing the mice in custom scaffolds, injecting radionuclides, measurement setup, SPECT / CT setup and reconstruction, ( Figure 4B Experimental γCPS measurements were performed on mice by placing a scaffold in a SPECT / CT scanner and in a SPECT / CT scanner with a visible probe location.

[0113] Figures 5A-5D Evolution of the DPS model across time points. Figure 5A SPECT / CT scans of the same mouse (M4) at 0, 6, 12, 24, and 48 hours post-injection. The %IA / mL color bar scale ranges from 0 to 6%. Figure 5B Annotated CT scan at 6 hours post-M4 injection. Tumor, kidney, and bladder are annotated. Body and probe annotations are not shown for clarity. Figure 5C From equal activity in each segmented volume to convergence of the DPS model to the true predicted value. Figure 5D The convergent DPS model solution for M4 was obtained at 0, 6, 12, 24, and 48 hours post-injection. The figure showed a good qualitative match with SPECT / CT.

[0114] Figure 6A-6I %IA / g reconstruction of all tumors, kidneys, and bladders across time points. Figure 6A M1 has a PC3-pip tumor in the left flank. Figure 6B M2 has PC3-pip tumors in the right and left flanks. Figure 6C M3 PC3-pip tumors on the left flank and right back, ( Figure 6D M4 has PC3-pip tumors in the right flank, left flank, and right back. Figure 6E PC3-flu tumors of M1 and M3, Figure 6F The kidneys of all four mice, and ( Figure 6G Radiopharmaceutical uptake in the bladders of all four mice. Figure 6H Linearity and 1:1 mapping of reconstructed %IA / mL and %IA / mL from SPECT / CT. Figure 6I The linearity and 1:1 mapping between the total tumor activity reconstructed and the total tumor activity from SPECT / CT.

[0115] Figures 7A-7C A custom-designed gamma counter with optimized linearity and dynamic range of activity. Figure 7A An experimental setup for measuring the linearity and dynamic range of a custom-designed gamma counter. Figure 7B The developed counter has a range of 0.5 µCi to 3 mCi. 177 The linearity of Lu activity, ( Figure 7C The absolute error between the linear fit and the recorded γCPS.

[0116] Figures 8A-8B Taking into account the differences in sensitivity between different counters. Figure 8A Experimental setup and support to ensure sensitivity across all sensing probes. 177 A fair comparison of Lu activity, ( Figure 8B Titration results and sensitivity plots for each of the eight sensors used in the in vivo experiments.

[0117] Figures 9A-9D Used to derive quantities Simulated titration. Figure 9A ) Experimental apparatus for titrating gamma sensitivity, ( Figure 9B ) Use segmented VOI CT scans to create DPS models, Figure 9C DPS titration model, ( Figure 9D The sensitivity plot of the DPS model titration is used to compare with the actual experimental sensitivity to deduce the titration. .

[0118] Figures 10A-10C Accuracy of the DPS model with trade-offs between CPS and distance, and nonlinearity. Figure 10A ) Experimental apparatus for distance sweeping, ( Figure 10B A comparison of the experimental trade-off between γCPS and distance with the experimental trade-off derived from the DPS model. Figure 10C The relative error of γCPS between the DPS model and experimental measurements.

[0119] Figure 11A-11D Reconstitution of ex vivo tumor activity. Figure 11A An experimental setup for measuring ex vivo tumors using a custom-designed gamma counter. Figure 11B SPECT / CT of ex vivo tumors using annotated CT, ( Figure 1C The DPS model of the experiment, Figure 11D The accuracy of the DPS model compared to in vitro gamma counting and SPECT / CT.

[0120] Figures 12A-12C Using the DPS model on the matrixW The accuracy of the modeling. Figure 12A This is used to derive the mapping matrix between activity and γCPS. W The vial configuration. Vial 1 was moved to all four locations of interest, and the counts received from each gamma counter from a specific tumor / OAR could be experimentally derived. Figure 12B The weight matrix derived experimentally. Figure 12C The weight matrix derived from the DPS model.

[0121] Figures 13A-13E Real-time relay of γCPS from each component of a sparse γ-counting network. (After injection) Figure 13A 0 hours, ( Figure 13B 6 hours, ( Figure 13C 12 hours, ( Figure 13D ) 24 hours and ( Figure 13E The 48-hour recording period consists of 10-minute intervals, with real-time gamma CPS from all 8 counters. The placement of each probe is also shown.

[0122] Figures 14A-14D Conceptual workflow and fiber optic gamma probe design. Figure 14A The investigated RPT was applied to a customized dual-tumor in vivo model derived from two cancer cell lines, and ( Figure 14B The proposed gamma counting system was used to perform measurements at very fine intervals with short acquisition times. Figure 14C At the last time point, a single SPECT / CT scan or ex vivo gamma count was performed to convert the gamma count to %IA / mL. Figure 14D (Left) A fiber optic interface with a compacted Y2O3-Eu-doped phosphor and optically insulating tape is connected to the readout circuit. Figure 14D (Right), the readout circuit includes single-photon detection of flashing γ, voltage level shifting, digital counter and data readout.

[0123] Figure 15A-15F Characterization and optimization of gamma-photon detectors. Figure 15A ) 177 Lu titration phantom experimental setup. Figure 15B γ-CPS with activity ranging from 0.5 µCi / mL to 0.5 mCi / mL 177 Real-time transient results of Lu titration. Figure 15C The Poisson fit of the recorded γCPS distribution is used because the count variation can be attributed to the Poisson nature of radioactive decay. Figure 15D For activities ranging from 0.1 µCi to 0.5 mCi, the average CPS from the proposed system is highly linear with the activity. Figure 15EFor the active range of interest, the absolute error of CPS ( Figure 15F Two handheld probes were used in this study, and the settings in (c) were also used to perform sensitivity calibration.

[0124] Figures 16A-16E In vivo experimental workflow. Figure 16A PC3-pip and PC3-flu cells (SQ) were injected into the flanks of mice M1-M16. Figure 16B Fourteen days later, both tumors had grown to a palpable size, and 600 µCi of [a specific drug / treatment] was administered via tail vein injection. 177 Lu-PSMA-617 was administered to mice M1-M16. Figure 16C Under anesthesia, a gamma probe was placed behind each tumor of mice M1-M16 for 2 hours. M1-M15 were monitored at a single time point post-injection (pi), but M16 was monitored long-term at five time points post-injection. M16 was also equipped with two additional probes, which were placed vertically above the left and right kidneys to track renal uptake and clearance (OAR). Figure 16D Mice M1-M15 were immediately euthanized and SPECT / CT scans were performed 2 hours after their respective measurements. M16 was not euthanized but was monitored long-term, with SPECT / CT scans performed after each gamma probe acquisition. Figure 16E Dissect the tumors of mice M1-M15 and obtain small tumor samples for in vitro dose determination.

[0125] Figures 17A-17E Representative SPECT scans and gamma probe counts of PC3-pip and PC3-flu tumors in M1-M15. Figure 17A SPECT scans show five time points acquired at the end of each customized gamma probe recording, in PC3-pip and PC3-flu tumors. 177 Progress in the accumulation of Lu-PSMA-617 activity. Figure 17B Real-time gamma probe recordings were taken during a two-hour recording period prior to acquiring the corresponding SPECT scan. Figure 17C The average slope of the instantaneous waveform per hour, 6-50 hours after injection. Figure 17D The long-term biodistribution curves derived from the proposed system within 50 hours after injection. Figure 17E Treatment ratio between PC3-pip tumor count and PC3-flu tumor count within 50 hours after injection.

[0126] Figures 18A-18F The accuracy of long-term surveillance was evaluated using SPECT / CT and biodistribution of M1-M15. (Source: [Source information missing]) Figure 18A SPECT / CT and ( Figure 18B Long-term biodistribution curves of isolated gamma counts. Figure 18C Comparison of CPS with tumor viability / tumor volume extracted from SPECT. Figure 18D Histogram of %IA / mL error between the system and SPECT / CT. Figure 18E Comparison of CPS with tumor activity normalized relative to tumor volume extracted from ex vivo gamma counts. Figure 18F Histogram of %IA / mL error between the system and in vitro γ counts.

[0127] Figure 19A-19G Monitoring of individual mouse M16 at multiple time points. (Source: [Insert Source Here]) Figure 19A The system proposed by ) and ( Figure 19B Biological distribution curves of the tumor and kidney on SPECT / CT. Figure 19C Comparison of CPS activity with that derived from SPECT. Figure 19D Histogram of %IA / mL error between the system and SPECT / CT. Figure 19E Average %IA / mL error, ( Figure 19F R 2 , ( Figure 19G The linear fitting slope converges with the measurement time before SPECT / CT.

[0128] Figure 20 (Left) Generated 133 IVIS image of a Ba point source (integration time 180 s) embedded in a disk with a 3D-printed fiber cap featuring an optimized 500 µm thick Y₂O₃-Eu-doped phosphor. The process was repeated for eight different thicknesses. (Right) Normalized total count from IVIS versus scintillator thickness over a 180-second integration time.

[0129] Figures 21A-21B For those used in in vivo experiments ( Figure 21A Probe 1 and ( Figure 21B Probe 2, dark counts of each APD before the complete titration experiment with 30 minutes of exposure per vial, compared with dark counts after the complete titration experiment.

[0130] Figures 22A-22B For those used in in vivo experiments ( Figure 22A Probe 1 and ( Figure 22B The dark count of each APD in probe 2 in the light-sealed box is compared with the dark count in a well-lit room.

[0131] Figures 23A-23D ( Figure 23AThe experimental setup was used to test the transfer function of the developed system with respect to distance and to test whether the lead thickness was sufficient to prevent cross-contamination of the recorded γCPS. 365 µCi 177 The Lu vial was swept from a distance of 0 to 3 cm from the sensor surface and from 0 to 6 cm laterally. Figure 23B The transfer function between the recorded γCPS and the distance from the sensor surface. Figure 23C For lead of various thicknesses, from 177 The detection probability of Lu-weighted average energy gamma photons. Figure 23D Measurement of the lateral distance transfer function with and without a 1 mm thick lead strip.

[0132] Figures 24A-24B Using the proposed system from 225 CPS measured externally from a 2-fold dilution of Ac. Measured for 30 minutes per vial. Figure 24A For activities ranging from 7 nCi to 500 nCi in 1 ml, the average CPS from the proposed system was compared with... 225 Ac activity is highly linear. Figure 24B The absolute error of CPS for the active range of interest.

[0133] Figure 25 Overview. Wearable, scalable gamma counter networks are needed to optimize treatment ratios.

[0134] Figure 26 Custom-designed single-gamma photon counter setup. Avalanche photodiode coupled to the scintillator via fiber optic cable. Two counters in the counter are measuring a solution diluted in 1 mL of saline solution. 177 Lu and 225 Ac activity.

[0135] Figure 27 Within the scope of treatment 177 Lu titration is a measurement of the count.

[0136] Figure 28 Within the scope of treatment 225 Ac titration is a measurement of the count.

[0137] Figure 29 Phantom vial experimental setup. (a) Eight gamma probe sensors are inserted into the side of a custom-designed tank. (b) A removable cap is used to secure the vial containing the variable activity of Lu-177. (c) The tank has five slots on each side for placing the gamma sensors.

[0138] Figures 30A-30D Distributed point source modeling. Figure 30A 4 small bottles 177The 3D volume of Lu is represented as a distributed point source in a computer associated with eight gamma-counting sensors surrounding them. Figure 30B Top view: Predicted signals on vials and sparse gamma detectors. In the computer, the activity in each vial is changed, the simulation is rerun, and a new set of detector values ​​is obtained. This process is repeated to build a library of sensor network values ​​corresponding to a specific activity layout. Figure 30C , Figure 30D The accuracy of the MCMC activity map reconstruction algorithm using sparse gamma counters. Using phantoms (e.g.) Figure 29 As shown) Measurement ( Figure 30A The simulation data is from ) and records were taken using 14 uncollimated gamma counters placed in 4 cells filled with varying values. 177 The activity of Lu is around the vial. The known (true) activity is determined by ( Figure 30D The horizontal line in the diagram is shown. Figure 30C The MCMC algorithm predicts the activity of the four vials, ensuring that the average γ counts per second predicted by the model match the actual records. Figure 30D This invention incrementally adds sensors until sufficient information is obtained, causing the algorithm to converge to the correct activity indicated by the horizontal dashed line. This provides a proof of concept that a sparse set of sensitive gamma counters can correctly identify activity at a priori known location.

[0139] Figure 31 A prototype of the SENTRI chip sensor shows the array of central pixels, on-chip memory (SRAM controlled), digital clock (FLL), and digital control circuitry (master digital). This chip was custom-designed at Anwar Labs and measures <1 mm. 2 It is manufactured by TSMC (Taiwan Semiconductor Manufacturing Company) using a 65-nanometer process.

[0140] Figure 32 Using SENTRI chips 111 Compared to gamma probes, In titration uses a chip-based solution to record counts per minute over a wide specific activity range, and a custom-developed gamma counter to record counts per second.

[0141] Figures 33A-33B Using sensor stacking to resolve the energy of incident gamma photons ( Figure 33A (Left) A stack of sensors was placed at various locations on the patient's skin and detected incident gamma photons ( Figure 33A (Right) A view of a sensor stack exposed to fluxes of different gamma photon energies. The sensor stack distinguishes incident energy based on the tunable LET sensitivity of the attenuation material between each chip and / or between chips. Figure 33BThe actual gamma photon energy distribution and the energy distribution resolved from the counts detected by each sensor in the stack.

[0142] Figure 34 System architecture and pixel timing diagram.

[0143] Figure 35 Pixel architecture and photon energy binning scheme.

[0144] Figures 36A-36E Experimental results of SRT. Figure 36A Transient counting; Figure 36B Linearity with cumulative dose; Figure 36C () Beam energy distribution boxes; ( Figure 36D The measured dose varies with depth in the tissue; Figure 36E Errors in ASIC dosing compared to existing technologies.

[0145] Figure 37 ASIC Summary: Die Micrographs. Detailed Implementation

[0146] Devices, systems, software, and methods are provided for calculating the percentage of total injection activity (%IA / mL) delivered to tumors and orifices (OARs) per milliliter of tissue in subjects receiving radiopharmaceutical therapy. The method utilizes fiber-optic or chip-based gamma counters capable of real-time monitoring of radiopharmaceutical uptake by tumors or OARs during treatment. Medical imaging is used to identify the location of tumors and OARs in the subject for positioning the counters on a wearable structure or the subject's skin to monitor radiopharmaceutical uptake. Furthermore, an algorithm is provided that automatically calculates the %IA / mL of tumors and OARs from prior knowledge of gamma count rates recorded by a sparse set of gamma counters, as well as the locations of tumors, OARs, and gamma counters. The systems and methods disclosed herein can be used for non-invasive, continuous, real-time dosimetry of multiple tumors and OARs.

[0147] Before describing the apparatus, system, software, and method of the present invention, it should be understood that the invention is not limited to the specific apparatus, system, software, and method described, and therefore they can certainly be varied. It should also be understood that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting, as the scope of the invention will be defined only by the appended claims.

[0148] Where a range of values ​​is provided, it should be understood that, unless the context explicitly specifies otherwise, every intermediate value between the upper and lower limits of the range, up to one-tenth of the lower limit unit, is also specifically disclosed. Every smaller range between any stated value or intermediate value within the stated range and any other stated value or intermediate value within the stated range is covered by this invention. The upper and lower limits of these smaller ranges may be independently included or excluded from the range, and for each smaller range, whether it includes one limit, excludes neither limit, or includes both limits, the range is covered by this invention, except for any limit explicitly excluded from the stated range. Where a stated range includes one or two limits, the range excluding any one or both of these included limits is also included in this invention.

[0149] Unless otherwise defined, 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 pertains. While any methods and materials similar to or equivalent to those described herein may be used in the practice or testing of this invention, some potential and preferred methods and materials are described hereafter. All publications mentioned herein are incorporated herein by reference to disclose and describe methods and / or materials associated with the cited publications. It should be understood that, to the extent contradictory, this disclosure supersedes any disclosure in the incorporated publications.

[0150] As will be readily apparent to those skilled in the art upon reading this disclosure, each of the individual embodiments described and illustrated herein has discrete components and features that can be readily separated from or combined with features of any of the other several embodiments without departing from the scope or spirit of the invention. Any described method may be performed in the order of the described events or in any other logically possible order.

[0151] It is important to note that, as used herein and in the appended claims, the singular forms “a,” “an,” and “the” include plural references unless the context clearly specifies otherwise. Thus, for example, reference to “photon” includes a plurality of such photons, and reference to “radionium” includes reference to one or more radionuclides and their equivalents, such as radionuclides, radioisotopes, or radioactive isotopes known to those skilled in the art.

[0152] The publications discussed herein are provided only for their disclosure prior to the filing date of this application. Nothing herein should be construed as an admission that the invention is not entitled to precedence over such publications by virtue of a prior invention. Furthermore, the publication dates provided may differ from the actual publication dates, which may require independent verification.

[0153] definition

[0154] The term “about,” especially when referring to a given quantity, is intended to cover a deviation of plus or minus five percent.

[0155] The terms “tumor,” “cancer,” and “neoplasia” are used interchangeably and refer to cells or groups of cells that grow, proliferate, or survive greater than the normal corresponding cells, such as proliferative disorders, hyperproliferative disorders, or differentiation disorders. Typically, the growth is uncontrolled. The term “malignant” refers to invasion of nearby tissues. The terms “metastatic” or secondary, recurrent, or recurrent tumor, cancer, or neoplasm refer to the spread or dissemination of a tumor, cancer, or neoplasm to other sites, locations, or regions within the subject’s body that are different from the primary tumor or cancer. Neoplasm, tumor, and cancer include benign, malignant, metastatic, and non-metastatic types, and include neoplasm, tumor, or cancer at any stage (I, II, III, IV, or V) or grade (G1, G2, G3, etc.), or neoplasm, tumor, cancer, or metastasis that is progressing, worsening, stable, or in remission. Specifically, the terms "tumor," "cancer," and "tumor formation" include carcinomas such as squamous cell carcinoma, adenocarcinoma, adenosquamous cell carcinoma, anaplastic carcinoma, large cell carcinoma, and small cell carcinoma, and include cancers such as, but 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, bile duct cancer, 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 disorder, colon cancer, endometrial cancer, ependymoma, esophageal cancer, Ewing sarcoma, extracranial germ cell tumor, extrahepatic bile duct cancer, gallbladder cancer, gastrointestinal carcinoid tumors, gestational trophoblastoma, hairy cell leukemia, Hodgkin lymphoma, non-Hodgkin lymphoma, and lower abdominal cancer. Pharyngeal cancer, pancreatic islet cell carcinoma, Kaposi's sarcoma, laryngeal cancer, leukemia, lip cancer, oral cancer, liver cancer, malignant mesothelioma, medulloblastoma, Merkel cell carcinoma, metastatic squamous cell carcinoma of the neck, multiple myeloma and other plasma cell tumors, mycosis fungoides and Cezari syndrome, myelodysplastic syndrome, nasopharyngeal carcinoma, neuroblastoma, oropharyngeal cancer, bone cancer, including osteosarcoma and malignant fibrous histiocytoma of bone, paranasal sinus cancer, parathyroid carcinoma, penile cancer, pheochromocytoma, pituitary adenoma, prostate cancer, rectal cancer, renal cell carcinoma, retinoblastoma, rhabdomyosarcoma, salivary gland cancer, small bowel cancer, soft tissue sarcoma, supratentorial primitive neuroectodermal tumor, pineal blastoma, testicular cancer, thymoma, thymic carcinoma, thyroid cancer, transitional cell carcinoma of the renal pelvis and ureter, urethral cancer, uterine sarcoma, vaginal cancer, vulvar cancer and nephroblastoma, and other pediatric kidney tumors.

[0156] The terms "radionuclide," "radioisotope," "radioactive nuclide," and "radioactive isotope" are used interchangeably and refer to atoms with unstable nuclei that emit ionizing radiation or particles. Radionuclides can emit gamma radiation, alpha particles, beta particles, or positrons. In particular, the term includes positron-emitting radionuclides suitable for positron emission tomography (PET) imaging, such as, but not limited to, those that emit positron emission tomography (PET). 64 Cu、 89 Zr、 68 Ga、 177 Lu、 82 Rb、 86 Y、 11 C 13 N、 15 O and 18 F; and gamma-emitting radionuclides suitable for single-photon emission computed tomography (SPECT) imaging or gamma camera (planar imaging), such as, but not limited to, those that are suitable for single-photon emission computed tomography (SPECT) imaging or gamma camera (planar imaging). 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb and 177 Lu. The term may also include alpha-emitting radionuclides suitable for radionuclide therapy, such as, but not limited to, those that are not part of radionuclide therapy. 149 Tb, 223 Ra, or 225 Ac, and beta-emitting radionuclides, such as but not limited to 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho and 177 Lu. Furthermore, the term further includes radionuclides used in therapeutic agents that can be used for both therapy and imaging. Such therapeutic agents may include radionuclides that can be used for both imaging and radiotherapy (e.g., iodine-131 and lutetium-177 are gamma emitters and beta emitters, respectively, which can be used for both imaging and therapy), or therapeutic agents that include both diagnostic and therapeutic radionuclides. Alternatively, therapeutic agents may include radionuclides linked to non-radiotherapeutic agents (e.g., radiopharmaceuticals, radioimmunotherapy agents, and radiopeptides).

[0157] The terms “individual,” “subject,” “recipient,” and “patient” are used interchangeably herein and refer to any mammalian subject, particularly a human, who requires diagnosis, treatment, or therapy. “Mammalian” for therapeutic purposes means any animal classified as a mammal, including both human and non-human mammals such as non-human primates, including chimpanzees and other ape and monkey species; laboratory animals such as mice, rats, rabbits, hamsters, guinea pigs, and chinchillas; domesticated animals such as dogs and cats; and farm animals such as sheep, goats, pigs, horses, and cattle.

[0158] As used herein, the term "user" means a person who interacts with the devices and / or systems disclosed herein to perform one or more steps of the methods disclosed herein. A user may be a patient receiving treatment. A user may be a healthcare practitioner, such as the patient's doctor.

[0159] A “therapeutic effective dose” or “therapeutic dose” is a quantity sufficient to achieve the desired clinical outcome (i.e., to achieve therapeutic efficacy). A therapeutic effective dose may be administered in one or more administrations.

[0160] "Pharmaceutical acceptable excipients or carriers" means excipients that can be optionally included in the compositions of the present invention and will not cause significant adverse toxicological effects on patients.

[0161] "Pharmaceutically acceptable salts" include, but are not limited to, amino acid salts, salts prepared with inorganic acids such as chlorides, sulfates, phosphates, hydrogen phosphates, bromides, and nitrates, or salts prepared from any of the aforementioned corresponding inorganic acid forms, such as hydrochlorides, or salts prepared with organic acids such as malates, maleates, fumarates, tartrates, succinates, ethylsuccinates, citrates, acetates, lactates, methanesulfonates, benzoates, ascorbic acid salts, p-toluenesulfonates, palmitates, salicylates, and stearates, as well as etolates, glucono-p-ethylates, and lacturonates. Similarly, salts containing pharmaceutically acceptable cations include, but are not limited to, sodium, potassium, calcium, aluminum, lithium, and ammonium (including substituted ammonium) salts.

[0162] "Separated" refers to an entity of interest situated in an environment different from that in which it might naturally exist. "Separated" also means including entities within a sample that is substantially enriched with the entity of interest and / or in which the entity of interest is partially or substantially purified.

[0163] The term “conjugation” refers to the connection of two compounds or agents by covalent or non-covalent means (e.g., a binding agent that is specific to a tumor marker conjugated to a radionuclide).

[0164] A "ligand" or "binding agent" is any molecule that can be used to target a radionuclide to cells, tissues, or other targets. In some embodiments, the ligand is a molecule that selectively binds to the target analyte of interest (e.g., a cancer antigen) with high binding affinity. High binding affinity means at least about 10. -4 M, usually at least about 10 -6 M or higher, such as 10 -9 M or higher binding affinity. The ligand can be any of a variety of different types of molecules, as long as it exhibits the necessary binding affinity to the target analyte when conjugated with a radionuclide. In some embodiments, the ligand has moderate or even low affinity to its target analyte, for example, less than about 10. -4 M. Therefore, ligands can be small molecule ligands or large molecule ligands. Small molecule ligands are defined as ligands with a molecular weight of less than 10,000 Daltons, typically ranging from about 50 Daltons to about 5,000 Daltons, and more typically in the range of about 100 Daltons to about 1,000 Daltons. Large molecule ligands are defined as ligands with a molecular weight greater than 10,000 Daltons.

[0165] Small molecule ligands can be any molecule and its binding portion or fragment capable of binding to a target analyte of interest (e.g., a cell marker) with the necessary affinity. Typically, small molecules are small organic molecules capable of binding to a target analyte of interest. The small molecule will include one or more functional groups necessary for interaction with the target analyte structure, such as groups necessary for hydrophobic, hydrophilic, electrostatic, or even covalent interactions. In the case of a protein, the pharmaceutical portion will include functional groups necessary for interaction with the protein structure, such as hydrogen bonding, hydrophobic-hydrophobic interactions, electrostatic interactions, etc., and will typically include at least one amine, amide, thiol, carbonyl, hydroxyl, or carboxyl group, preferably at least two of the functional chemical groups. The small molecule may also contain regions that can be modified and / or involved in conjugation to a radionuclide without substantially adversely affecting its ability to bind to its target analyte.

[0166] Small molecule ligands may comprise cyclic carbon or heterocyclic structures and / or aromatic or polyaromatic structures substituted with one or more of the aforementioned functional groups. Small molecule ligands may also comprise organic compounds containing alkyl groups (including alkanes, alkenes, alkynes, and heteroalkyl groups), aryl groups (including aromatics and heteroaryl groups), alcohols, ethers, amines, aldehydes, ketones, acids, esters, amides, cyclic compounds, heterocyclic compounds (including purines, pyrimidines, benzodiazepines, β-lactams, tetracyclines, cephalosporins, and carbohydrates), steroids (including estrogens, androgens, cortisone, ecdysone, etc.), alkaloids (including ergot, periwinkle, curare, pyrrolizidine, and mitomycin), organometallic compounds, compounds with heteroatoms, amino acids, and nucleosides. Small molecules may include structures found in biomolecules, including peptides, carbohydrates, fatty acids, vitamins, steroids, purines, pyrimidines, derivatives, structural analogs, or combinations thereof.

[0167] Small molecules can be derived from naturally occurring or synthetic compounds and can be obtained from a wide variety of sources, including libraries of synthetic or natural compounds. For example, numerous methods are available for the random and directed synthesis of a wide range of organic compounds and biomolecules, including the preparation of random oligonucleotides and oligopeptides. Alternatively, libraries of natural compounds in the form of bacterial, fungal, plant, and animal extracts are available or readily generated. Furthermore, naturally or synthetically generated libraries and compounds are readily modified using conventional chemical, physical, and biochemical methods and can be used to generate combinatorial libraries. Known small molecules can undergo directed or random chemical modifications, such as acylation, alkylation, esterification, and amidation, to produce structural analogs.

[0168] Therefore, small molecules can be obtained from libraries of naturally occurring or synthetic molecules, including libraries of compounds generated through combinatorial methods, i.e., combinatorial libraries of compound diversity. When obtained from such libraries, the small molecules employed will exhibit some desired affinity for protein targets in a convenient binding affinity assay. Combinatorial libraries and methods for their production and screening are known in the art and described in U.S. Patent 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, The public information in references 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; 5,438,119; and 5,223,409 is incorporated herein by reference.

[0169] Small molecule ligands may also include known pharmaceutical products that selectively bind to receptors on cells, including but not limited to growth factor receptors, receptor tyrosine kinases, receptor protein serine / threonine kinases, G protein-coupled receptors, cytokine receptors, lectin receptors, and folic acid receptors. For example, anticancer drugs that bind to such cellular receptors can be used as ligands to target radionuclides to cancer cells. Exemplary drugs that can be used as ligands to target cancer cells include, but are not limited to, acitinib, afatinib, axitinib, erlotinib, cabozantinib, crizotinib, gefitinib, imatinib, ibrutinib, lapatinib, neovastat, nilotinib, pazopanib, perifosine, ponatinib, regorafenib, sorafenib, sunitinib, trametinib, and vandetenib.

[0170] As noted, ligands can also be macromolecules. Of particular interest as macromolecular ligands are antibodies, as well as their binding fragments and mimics. Peptides and aptamers are also suitable as binding agents. Ligands or binding agents may include domains or portions that can be covalently attached to radionuclides without substantially eliminating their binding affinity to their target analytes (e.g., cell markers).

[0171] The term "antibody" encompasses monoclonal antibodies as well as hybrid antibodies, engineered antibodies, chimeric antibodies, and humanized antibodies. The term antibody includes: hybrid (chimeric) antibody molecules (see, for example, Winter et al., (1991) Nature). Nature )》349:293-299; and US Patent No. 4,816,567); F(ab′)2 and F(ab) fragments; F v Molecules (non-covalent heterodimers, see, for example, Inbar et al., (1972) Proceedings of the National Academy of Sciences) Proc Natl Acad Sci USA )》69:2659-2662; and Ehrlich et al., (1980) Biochemistry ( Biochem )》19:4091-4096); single-chain Fv molecules (scFv) (see, for example, Huston et al., (1988) Proceedings of the National Academy of Sciences 85:5879-5883); nanobodies or single-domain antibodies (sdAb) (see, for example, Wang et al., (2016) International Journal of Nanomedicine ( Int J Nanomedicine )》11:3287-3303, Vincke et al., (2012) Molecular Biology Methods ( Methods Mol Biol )》911:15-26; Dimeric and trimer antibody fragment constructs; Microantibodies (see, for example, Pack et al., (1992) Biochemistry 31:1579-1584; Cumber et al., (1992) Journal of Immunology ( J Immunology (149B:120-126); biantibodies, tetraantibodies, affinity molecules, camel antibodies, humanized antibody molecules (see, for example, Riechmann et al., (1988) Nature 332:323-327; Verhoeyan et al., (1988) Science ( Science (see GB 2,276,169, published on 21 September 1994); and any functional fragment obtained from such molecules, wherein such fragment retains the specific binding properties of the parent antibody molecule.

[0172] "Fv" is an antibody fragment containing antigen recognition and binding sites. This region consists of a heavy chain variable domain and a light chain variable domain in a tightly bound, non-covalently associated dimer. It is in this configuration that the three CDRs of each variable domain interact to achieve the binding site at V. H -V L Antigen-binding sites are defined on the surface of the dimer. In general, the six CDRs confer antigen-binding specificity to the antibody. However, even a single variable domain (or half of the Fv containing only the three CDRs that are specific to the antigen) has the ability to recognize and bind to the antigen, although usually with a lower affinity than the entire binding site.

[0173] The "single-chain Fv" or "scFv" antibody fragment contains the antibody's V. H Domain and V L Domains, wherein these domains are present within a single polypeptide chain. Typically, Fv polypeptides are further contained within V H Domain and V L The polypeptide linker between the domains enables scFv to form the desired structure for antigen binding. For a review of scFv, see, for example, Pluckthun, A. Pharmacology of Monoclonal Antibodies, Vol. 113, edited by Rosenburg and Moore, Springer-Verlag, New York, pp. 269–315 (1994).

[0174] The term "dual antibody" refers to a small antibody fragment having two antigen-binding sites, which contains components linked to the same polypeptide chain (V). H -V L The light-chain variable domain V on ) L The heavy-chain variable domain V H By using a linker that is too short to allow pairing between two domains on the same strand, the domain is forced to pair with a complementary domain on another strand, creating two antigen-binding sites. Biantibodies are described more fully in, for example, EP 404,097; WO 93 / 11161; and Holliger et al., (1993) Proceedings of the National Academy of Sciences 90: 6444-6448.

[0175] The term "affinity molecule" refers to a molecule consisting of three α-helices with 58 amino acids and a molar mass of approximately 6 kDa. For comparison, monoclonal antibodies are 150 kDa, and single-domain antibodies, the smallest type of antigen-binding antibody fragment, are 12–15 kDa. For exemplary details on the structure and uses of affinity molecules, see Orlova, A; Magnusson, M; Eriksson, TL; 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. An exemplary affinity molecule is shown. The molecule is commercially available from Abcam, Massachusetts.

[0176] The phrase “specifically (or selectively) binds” to the binding of antibodies or other binding agents to antigens or analytes (e.g., cellular markers, such as tumor markers) refers to a binding reaction that determines the presence of an antigen or analyte in a heterogeneous population of proteins and other biological products. Thus, under specified assay conditions, the stated antibody or other binding agent binds to a specific antigen or analyte at least twice the background amount and substantially not to other molecules present in the sample in significant amounts. Specific binding to an antigen or analyte under such conditions may require antibodies or other binding agents selected for their specificity to that particular antigen or analyte. For example, antibodies produced against antigens from a specific species such as rats, mice, or humans can be selected to obtain only those antibodies that specifically respond to that antigen and not to other proteins that specifically respond to it, except for polymorphic variants and alleles. This selection can be achieved by subtracting antibodies that cross-react with molecules from other species. Various immunoassay formats can be used to select antibodies that specifically respond to a particular antigen. For example, solid-phase ELISA immunoassays are commonly used to select antibodies that specifically react with proteins (see, for example, Harlow & Lane, *Antibodies, A Laboratory Manual* (1988), “for adescription of immunoassay formats and conditions that can be used to determine specific immunoreactivity”). Typically, the specific or selective reaction will be at least twice the background signal or noise, and more typically 10 to 100 times higher than the background.

[0177] Fiber-optic gamma photon counter

[0178] In one aspect, an optical fiber-based gamma photon counter is provided, which can be used in real time to monitor the uptake of radiopharmaceuticals containing gamma-emitting radionuclides in tumors and organs at risk in subjects undergoing radioligand therapy. The fiber-optic gamma-photon counter comprises i) a Y₂O₃-Eu-doped phosphor, wherein gamma photons incident on the surface of the Y₂O₃-Eu-doped phosphor generate scintillation light in the visible spectrum suitable for solid-state photon detection; ii) a detector comprising a photodiode; iii) an optical fiber guiding the scintillation light generated by the Y₂O₃-Eu-doped phosphor to the detector, wherein the detector generates a voltage pulse in response to detecting the scintillation light generated by the gamma photons; iv) a digital counter coupled to the detector, wherein the digital counter counts gamma-photon detection events, wherein each gamma-photon detection event corresponds to a voltage pulse generated by the detector in response to detecting scintillation light generated from each gamma photon incident on the surface of the Y₂O₃-Eu-doped phosphor; and v) an opaque material cladding 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 incident gamma photons reaching the surface of the detector are uncollimated. Figure 1C and Figure 2A Schematic diagrams of exemplary fiber-optic-based gamma-photon counters and their circuits are shown.

[0179] Any photodiode suitable for detecting flickering light can be used in the detector. Examples include avalanche photodiodes (APDs) and single-photon avalanche diodes (SPADs). The detector will typically include multiple power supplies to control circuit cooling, quenching and reset, and high-voltage bias. For example, an APD may be used with a 2-volt power supply to control circuit cooling, with a 5-volt power supply to control quenching and reset, and with a 30-volt power supply to control high-voltage bias (see Example 1). In some embodiments, the detector further includes a high-voltage regulator.

[0180] The optical fiber is clad in an opaque material to shield it from visible light emitted by phosphors not doped with Y₂O₃-Eu. 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.

[0181] A digital counter is used to count the number of gamma photon detection events, specifically counting the voltage pulses generated by a semiconductor photodiode detector in response to the detection of flickering light incident on the surface of a Y₂O₃-Eu-doped phosphor. In some embodiments, the digital counter is configured in a field-programmable gate array (FPGA). In some embodiments, the gamma photon counter further includes a clock configured to generate a clock signal representing time, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each set time period (e.g., counts per second (CPS)). In some embodiments, the gamma photon counter further includes a level shifter configured in the circuit to ensure logic level compatibility with the digital counter (see, e.g., Figure 2A and Figure 14D ).

[0182] 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 connected to the digital counter via wired or wireless communication can be configured to store multiple gamma photon count records of multiple gamma photon detection events. The data storage component can be any type capable of storing information and can utilize, for example, 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 writable memory.

[0183] In some embodiments, the fiber-optic gamma-photon counter further includes a first wireless communication unit communicating with the data storage unit and an external data receiving device including a second wireless communication unit. In some embodiments, the first wireless communication unit utilizes a wireless communication protocol using electromagnetic carrier waves (e.g., radio waves, microwaves, or infrared light) or ultrasound to transmit data from the data storage unit to the external data receiving device including the second wireless communication unit. For example, the first wireless communication unit may utilize a radio frequency communication protocol or an ultrasonic communication protocol to transmit data from the data storage unit to the external data receiving device including the second wireless communication unit. The data receiving device may include, but is not limited to, a computer or handheld device, such as a mobile phone or tablet. In some embodiments, the data is wirelessly uploaded to the cloud.

[0184] In some 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 includes an internal power supply or energy storage device, such as a capacitor or battery, to supply power to the chip, for example, for the operation of the digital counter, detector, and clock. The on-chip power supply or energy storage device may include, but is not limited to, lithium-ion batteries, silver oxide batteries, or sheet-type electric double-layer capacitors. In some embodiments, the battery is rechargeable.

[0185] In some embodiments, the fiber-optic gamma-photon counter further includes an edge computing device connected to the data storage unit, wherein the edge computing device receives gamma-photon counting data. In some embodiments, the on-chip edge computing device is programmed to partially process the counting data, which is then transmitted to an external data processing unit for further data processing. In some embodiments, the data storage unit communicates with the external data processing unit, wherein the data processing unit is programmed to calculate the total %IA / ml of one or more tumors and one or more organs at risk in a subject from multiple gamma-photon count records from multiple gamma-photon counters, as further described below.

[0186] Chip-based gamma photon counter

[0187] On the other hand, a chip-based gamma photon counter is provided, which can also be used for real-time monitoring of the uptake of radiopharmaceuticals containing gamma-emitting radionuclides in tumors and organs at risk in subjects. Fundamentally, the platform is unique in that it synergistically integrates algorithmic approaches to significantly reduce the amount of data required to accurately reconstruct TRT dosimetry and SPECT images (and thus reduce spatial coverage). The platform leverages prior knowledge of the location of the tumor and OAR, combined with strategically placed or sparsely placed sensors. Secondly, the platform uses integrated circuit technology to implement sensors with asynchronously operating pixels, enabling the determination of the energy and direction of incident photons, and allowing for highly multiplexed sensor arrays on the patient. The sensor area is scalable yet remains thin (< 300 micrometers). In some implementations, the sensors are stacked to achieve energy resolution and acquire directional photon information, which further enhances the spatial resolution and accuracy of radionuclide distribution detection. The sensors have extremely small thickness and weight, allowing multiple sensors to be used simultaneously as wearable devices. This platform is capable of performing single-photon sensing for image reconstruction, similar to SPECT, unlike positron emission tomography-based imaging, where two time-coincident photons must be detected. Not only does it eliminate the need for a collimator, but it also captures the flux of single-photon (γ) emissions at different known locations on the patient's surface to reconstruct the distribution of γ emission in vivo, and thus reconstruct dosimetry for tumors and organs at risk. The platform also utilizes the angle of the incident photon (in contrast to a collimator, which eliminates all angles except a narrow window of the incident angle) to inversely calculate the distribution of γ-emitted radionuclides. This approach allows for the measurement of a greater number of γ photons at a single spatial point, potentially increasing the signal-to-noise ratio and reducing the time required to collect the amount of data needed for accurate image reconstruction. In some embodiments, a chip-based platform is provided that can have a highly scalable architecture, allowing numerous chip-based sensors to be placed on the body. In some embodiments, asynchronous pixel operation is used within each sensor. In some embodiments, as described below, sensor stacking is used to achieve energy resolution and / or incident direction resolution in a shape parameter of < 5 mm thickness. Furthermore, the use of SPECT emitters allows for greater selection of radionuclides to be imaged, and importantly, allows for imaging of the distribution of TRT.

[0188] In some embodiments, a chip-based gamma-photon counter includes a detector comprising at least one silicon diode, wherein gamma photons are detected by voltage pulses generated when they strike the silicon of the diode. Unbound from theoretical constraints, gamma photons break bonds in the silicon of the diode, generating electron-hole pairs that produce charge pulses in the diode. These charge pulses accumulate on a capacitor to generate voltage pulses across the diode. In some embodiments, the chip-based gamma-photon counter includes an array of pixels, where each pixel is a gamma-sensing element. Figure 31 An exemplary chip-based gamma photon counter with an array of pixels is shown.

[0189] The detector can have any suitable shape, such as a curved shape or a polygonal shape. In some embodiments, the detector is shaped as a circle, ellipse, semicircle, sphere, cylinder, triangle, square, rectangle, pentagon, hexagon, octagon, rhombus, or parallelogram. In some implementations, the detector has sides ranging in length from 0.1 µm to 50 µm, including any length within this range, such as 0.1 µm, 0.2 µm, 0.3 µm, 0.4 µm, 0.5 µm, 0.6 µm, 0.7 µm, 0.8 µm, 0.9 µm, 1.0 µm, 1.5 µm, 2.0 µm, 2.5 µm, 3.0 µm, 3.5 µm, 4.0 µm, 4.5 µm, 5.0 µm, 5.5 µm, 6.0 µm, 6.5 µm, 7.0 µm, 8.5 µm, 9.0 µm, 10 µm, 11 µm, 12 µm, 13 µm, 14 µm, 15 µm, 16 µm, 17 µm, 18 µm, 19 µm, 20 µm, 21 µm, 22 µm, 23 µm, 24 µm. µm, 25 µm, 26 µm, 27µm, 28 µm, 29 µm, 30 µm, 31 µm, 32 µm, 33 µm, 34 µm, 35 µm, 36 µm, 37 µm, 38 µm, 39 µm, 40µm, 41 µm, 42 µm, 43 µm, 44 µm, 45 µm, 46 µm, 47 µm, 48 µm, 49 µm or 50 µm.

[0190] In some embodiments, the chip-based gamma photon counter has a shape parameter with a thickness 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 shape parameter has a thickness in the range of 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.

[0191] In some embodiments, a chip-based gamma-photon counter includes: a detector implemented as an application-specific integrated circuit (ASIC) on the chip, wherein the detector includes at least one reverse-biased diode. Gamma photons incident on the surface of the reverse-biased diode generate voltage pulses across the reverse-biased diode. In some embodiments, the reverse-biased diode is connected to an amplifier and then to a digital counter. In other embodiments, the reverse-biased diode is connected to a voltage buffer before being connected to a voltage amplifier and subsequently to the digital counter. The digital counter counts gamma-photon detection events, wherein each gamma-photon detection event corresponds to a voltage pulse generated across the reverse-biased diode by each gamma photon incident on the surface. The chip also includes on-chip memory configured to store multiple gamma-photon count records of multiple gamma-photon detection events. A digital clock is configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events for each time period. Custom digital logic circuitry is provided on the chip, wherein the digital logic circuitry is configured to control voltages and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0192] In some implementations, a chip-based gamma-photon counter includes: a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma-photon sensing element. Each pixel includes a reverse-biased silicon diode connected to a unity-gain voltage buffer. A buffered voltage output from a unity-gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed-loop amplifier can be preset or configured using in-pixel memory and a DAC. Gamma photons incident on the surface of the silicon diode generate voltage pulses across the diode and are subsequently buffered and amplified with a fixed, process-invariant gain. These voltage pulses are then digitized using a series of inverters connected to a digital counter to quantify the total number of gamma photons detected within a specific time frame. Each gamma-photon detection event corresponds to a voltage pulse across the diode generated by each gamma photon incident on the surface of the silicon diode. The chip further includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events for each time period; and custom digital logic circuitry configured to control voltage and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0193] In some implementations, the chip-based gamma-photon counter includes a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma-sensing element. In some implementations, each pixel in the array includes two silicon diodes connected to an amplifier. Incident gamma photons break bonds in the silicon, generating electron-hole pairs, which in turn generate charge pulses (Q) in the silicon diodes. p ), the charge pulse (Q p In parasitic diode capacitor (C) 二极管 This accumulates on the diode. This generates a small voltage pulse (V) across the diode. p = Q p / C 二极管 The use of integrated circuit technology enables ultra-small diode capacitance, increasing VC. pThis allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity-gain voltage amplifier. Each of these buffered outputs is connected to the input of a differential amplifier. To mitigate DC voltage offsets at the output due to manufacturing variability from inter-pixel and inter-chip sources, which can cause variations in detector sensitivity, a voltage integrator is configured with negative feedback to bootstrap from the amplifier's output to one of the amplifier's inputs. The voltage integrator also accepts a desired DC voltage that sets the voltage at the amplifier's output. This ensures that the sensitivity of each pixel across the entire chip is approximately the same. To tune each diode in each pixel to the desired sensitivity, the amplifier's output is connected to two level shifters: one shifts the DC level at the amplifier's output up to amplify only voltage pulses from the first diode, and the other shifts the DC level down to amplify only voltage pulses from the second diode. The amount by which these DC levels are offset is set using on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) to convert the stored bits into an analog voltage offset. These shifted and amplified voltage pulses are then digitized using a series of inverters. A capacitor at the input of the last inverter improves signal fidelity before subsequent pulse counting. A digital counter is coupled to the inverter chain, where the digital counter counts gamma-photon detection events, each corresponding to a voltage pulse across the diode generated by each gamma photon incident on the surface of any silicon diode. The chip also includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate an on-chip clock signal, which the digital counter uses to count the number of gamma-photon detection events for each time period; and custom digital logic configured to control voltages and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0194] On the other hand, a gamma photon counter is provided, comprising: a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma sensing element. In some embodiments, each pixel in the array includes a silicon diode connected to an amplifier. In some embodiments, each pixel operates asynchronously, meaning that each pixel can register gamma interactions without reading out the entire array. This allows for higher temporal resolution and enables near-single-particle sensitivity on the array. This feature makes it possible to determine the incident direction of gamma photons, which then allows for improved image reconstruction using fewer incident gamma photons (compared to pure gamma counting without directional information). Regarding the diodes, in some embodiments, the diodes are reverse-biased. In other embodiments, the diodes have a zero-voltage bias. Regarding the pixel architecture, in some embodiments, this is a differential structure, where two diodes are connected to the input of a differential amplifier. Utilizing the sparsity of photon strikes, the most likely event is that only a single diode is struck at any given time, thereby generating a differential pulse at the output of the amplifier. This structure has the advantage of mitigating offsets associated with diode characteristics, reset, or other circuitry that affect the baseline voltage (signal) across the diodes. Any mismatch between the two diodes manifests as an input offset in the amplifier and can cause the amplifier to operate in the low-gain region or "rail" (saturation) to the point where it is not activated at all. Therefore, the differential structure enables the amplifier to maintain operation despite some inherent variations in the sensing diodes across the chip. Pulses from each diode are generated by the following process: incident gamma photons break bonds in the silicon, generating electron-hole pairs, which in turn generate charge pulses (Q) in the silicon diode. p ), the charge pulse (Q p In parasitic diode capacitor (C) 二极管 This accumulates on the diode. This generates a small voltage pulse (V) across the diode. p = Q p / C 二极管 The use of integrated circuit technology enables ultra-small diode capacitance, increasing VC. pThis allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity-gain voltage amplifier. Each of these buffered outputs is connected to an input of a differential amplifier. In some implementations, to mitigate DC voltage offsets at the output due to manufacturing variability from inter-pixel and inter-chip sources, which can cause variability in detector sensitivity, a voltage integrator is configured with negative feedback to bootstrap from the amplifier's output to one of the amplifier's inputs. The voltage integrator also accepts a desired DC voltage that sets the voltage at the amplifier's output. This ensures that the sensitivity of each pixel across the chip is approximately the same. To tune each diode in each pixel to the desired sensitivity, the amplifier's output is connected to two level shifters: one shifts the DC level at the amplifier output up to amplify only the voltage pulse from the first diode, and the other shifts the DC level at the amplifier output down to amplify only the voltage pulse from the second diode. The amount by which these DC levels are offset is set using on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) to convert the stored bits into an analog voltage offset. These shifted and amplified voltage pulses are then digitized using a series of inverters. A capacitor at the input of the last inverter improves signal fidelity before subsequent pulse counting. A digital counter is coupled to the inverter chain, where the digital counter counts gamma-photon detection events, each corresponding to a voltage pulse across the diode generated by each gamma photon incident on the surface of any silicon diode. The chip also includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate an on-chip clock signal, which the digital counter uses to count the number of gamma-photon detection events for each time period; and custom digital logic configured to control voltages and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0195] In some embodiments, the chip is covered with a material capable of Compton scattering gamma photons. Compton scattering materials can include, but are not limited to, lead, tungsten, or bismuth. Compton scattering of gamma photons colliding with the material generates lower-energy photons (typically < 100 keV), which have a high probability of interacting with the detector due to the photoelectric effect, and additionally generate secondary electrons from inelastic collisions with primary gamma photons, which have a high probability of interacting with the detector. In some embodiments, these secondary electrons generated by the gamma photons are detected by the detector. Both energy conversions can be achieved by using a thin, high-density layer of Compton scattering material on top of or on the back of the detector (e.g., covering bulk silicon), which can enhance the detector signal, increase its sensitivity, and minimize data acquisition time.

[0196] In some implementations, the energy of an incident photon can be determined by measuring the ratio of detector counts using multiple detectors with attenuating materials of varying thicknesses. The attenuating material can include lead, tungsten, bismuth, or other high-density materials. For example, lower-energy photons have an exponentially higher probability of interacting with lead and can be detected without a lead layer, or in some cases, with only a very thin lead layer. Higher-energy photons are selectively measured by creating a subsequently thicker lead layer on top of other detectors to completely attenuate lower-energy photons and allow only high-energy photons to pass through. This process can be repeated with layers of different thicknesses to allow for determining the energy resolution of the incident gamma photon flux, which consists of multiple primary energy emissions. Because the energy of the gamma photons will be distributed across lead of varying thicknesses, multiphysics simulations can be used to determine the probability of detecting a certain energy photon with a detector of a given lead thickness and can be used to separate the detection counts for each energy.

[0197] In some embodiments, a chip-based gamma detector is provided, capable of energy-resolved and / or incident direction-resolved analysis of the incident flux of gamma photons. In some embodiments, the chip-based gamma detectors are arranged in a vertically stacked configuration, wherein each detector is separated from another detector by a thin layer of attenuating material, which may include lead, tungsten, bismuth, or other high-density materials. Figure 33A An exemplary implementation is shown, which depicts multiple chip-based gamma detectors arranged in a vertically stacked manner.

[0198] In some implementations, chip-based gamma detectors are stacked on top of each other (i.e., to create a gamma sensor stack), enabling measurement of the incident angle of incident photons. In some implementations, each of the stacked chip-based gamma detectors is equipped with fast readout circuitry for its array of pixels (i.e., gamma sensing elements) to allow near-instantaneous detection of the same incident gamma photon passing between two chip-based gamma detectors in the stack. In some implementations, this near-instantaneous detection of the incident gamma photon is achieved through asynchronous pixel operation, such that each pixel samples the gamma photon and transmits the time when the gamma photon hits the detector, the pixel position on the detector, and a signal associated with the LET of the gamma detector. The angular offset of the gamma photon transmitted from the chip-based gamma detector at the top of the stack to the chip-based gamma detector below can be used to calculate the incident gamma photon angle on the gamma sensor stack by evaluating the numerical equations governing the physics of Compton scattering. Measurement of the incident gamma photon angle provides an additional dimension of information when reconstructing dose information in the tumor and OAR during therapy and enables the use of a smaller number of sensors around the patient.

[0199] In some embodiments, the chip-based gamma detectors are stacked with a thickness greater than or equal to 3 mm and less than 5 mm. In some embodiments, the chip-based gamma detectors are stacked with a thickness greater than or equal to 1 mm and less than 3 mm. In some embodiments, the chip-based gamma detectors are stacked with a thickness greater than or equal to 0.1 mm and less than 1 mm.

[0200] In some embodiments, the chip-based gamma detectors are stacked with shape parameters 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 shape parameters have a thickness in the range of 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.

[0201] In some implementations, chip-based gamma detectors capable of determining the energy resolution of the incident flux of gamma photons are placed in the same plane to provide energy resolution over substantially the same spatial region. In some implementations, each detector has an attenuating material of varying thickness, such as lead, tungsten, bismuth, or other high-density material, which is placed on the surface of the detector or over the bulk silicon.

[0202] In some implementations, the on-chip circuitry is tuned to respond to a range of linear energy transfer (LET) such that the combination and distribution of signals from various pixels with known LET responsivity can determine the incident energy of the gamma photon. For example, lower-energy photons have higher LET and can be detected by a pixel with low gain that only detects low-energy photons and does not detect higher-energy photons with higher LET, which do not generate a signal. Pixels with higher gain are included on the same or adjacent chips to amplify the low LET from higher-energy photons. Pixels with higher gain respond to both lower-energy and higher-energy photons. By combining statistics from the set of pixels with lower gain and the set of pixels with higher gain, the energy distribution of the incident gamma photon can be determined.

[0203] In some implementations, a combination of two or more or all of the above-described energy-resolving methods is used to determine the energy distribution of the incident γ photons.

[0204] In some implementations, the pixel sensor may also respond to electrons generated by gamma photons. Electrons can be generated by gamma photons via the photoelectric effect, where gamma rays transfer all their energy to the electrons, causing them to be ejected from atoms. Alternatively, electrons can be generated by gamma photons via Compton scattering, which similarly causes electrons to be ejected from atoms, where gamma rays retain some of their energy and scatter in different directions. In some cases, electrons are generated by gamma photons in patients receiving radiopharmaceuticals containing gamma-emitting radionuclides, in a layer of material placed between the patient and the pixel sensor, or in the silicon of a diode after a collision with a gamma photon. Electrons bombarding the silicon diode create electron-hole pairs in the silicon, which generate voltage pulses across the silicon diode. These voltage pulses can be detected using the chip-based devices described herein, similar to those generated by gamma photons.

[0205] The number of diodes included in the pixel array (e.g., for detecting gamma photons or electrons generated by gamma photons) can vary. In some embodiments, the 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, for example, about 2 to 10 diodes, about 10 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... The number of diodes may range from 2 to 4,000, or approximately 4,000 to 5,000, including any number within 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. 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 a spacing of approximately 1 µm to 10 µm between diodes), or without a pattern. Such arrays can utilize ultra-small, micron-sized photodiodes with high sensitivity for detecting individual gamma photons. For example, micron-sized photodiodes are commercially available from companies such as X-FAB Silicon Foundries (Erfurt, Germany) and Taiwan Semiconductor Manufacturing Company (Hsinchu Science Park, Taiwan). These diodes can be used in massively parallel arrays for high-sensitivity gamma photon detection. In some implementations, thousands of these micron-sized gamma-ray sensitive photodiodes are included in a pixel array on a millimeter-sized chip.

[0206] In some implementations, the sensitivity of the pixel array is optimized by reducing the diode capacitance. In some implementations, the diode size is the smallest available size for CMOS processes (and it continues to decrease in size). In some implementations, the diode size is 0.1 µm to 0.5 µm x 0.1 µm to 0.5 µm. In some implementations, the diode size is 0.5 µm to 1 µm x 0.5 µm to 1 µm.

[0207] In some implementations, the pixel array is optimized to provide a trade-off between pixel fill factor and sensitivity by setting the diode size to 1 µm to 1.5 µm x 1 µm to 1.5 µm.

[0208] In some implementations, the detector is optimized to improve the fill factor with a trade-off between sensitivity and diode size by setting the diode size to 1.5 µm to 3 µm x 1.5 µm to 3 µm.

[0209] In some implementations, the detector is optimized to improve the fill factor while compromising sensitivity by setting the diode size to 3 µm to 10 µm x 3 µm to 10 µm.

[0210] In some implementations, the detector is optimized to improve the fill factor while compromising sensitivity by setting the diode size to 10 µm to 50 µm x 10 µm to 50 µm.

[0211] In some implementations, the diode is connected to the amplifier to improve the sensitivity of gamma photon detection. For a description of suitable amplifiers and amplification circuitry, see, for example, Lee et al., (2020) International Journal of Particle Therapy (Int J PartTher) 6(3):35-109; Lee et al., (2020), “A 64×64 Implantable Real-Time Single-Charged-Particle Radiation Detector for Cancer Therapy”, IEEE International Solid-State Circuits Conference (ISSCC), IEEE, pp. 506-508 (ieeexplore.ieee.org / document / 9063125); which are incorporated herein by reference in their entirety.

[0212] A digital counter is used to count the number of gamma-photon detection events, i.e., to count the voltage pulses generated by gamma photons incident on the surface of a silicon diode. In some embodiments, the chip-based gamma-photon counter further includes a clock configured to generate a clock signal representing time, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events per set time interval (e.g., counts per second (CPS)). In some embodiments, the clock signal is generated by a frequency-locked loop (FLL) oscillator (e.g., see [link to relevant documentation]). Figure 31 The clock beacon to the FLL can be generated from an off-chip crystal oscillator. In other implementations, the clock signal is generated directly from an off-chip crystal oscillator. In some implementations, the clock and control signals are generated by an external computer, FPGA, mobile phone, or other control device.

[0213] The digital output of the digital counter can be stored in an internal data storage unit (memory) or an external data storage unit connected to the digital counter via wired or wireless communication. The data storage unit can be configured to store multiple gamma photon count records of multiple gamma photon detection events. The data storage component can be of any type capable of storing information and can utilize, for example, 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 writable memory. In some embodiments, the gamma photon counter includes on-chip memory in the form of static random access memory (SRAM).

[0214] In some embodiments, the chip-based gamma photon counter further includes a first wireless communication unit communicating with an internal data storage unit (memory) and an external data receiving device including a second wireless communication unit. In some embodiments, the first wireless communication unit utilizes a wireless communication protocol using electromagnetic carrier waves (e.g., radio waves, microwaves, or infrared light) or ultrasound to transmit data from the data storage unit to the external data receiving device including the second wireless communication unit. For example, the first wireless communication unit may utilize a radio frequency communication protocol or an ultrasonic communication protocol to transmit data from the data storage unit to the external data receiving device including the second wireless communication unit. The data receiving device may include, but is not limited to, a computer or handheld device, such as a mobile phone or tablet. In some embodiments, the data is wirelessly uploaded to the cloud.

[0215] In some embodiments, the chip-based gamma photon counter further includes an edge computing device connected to an internal data storage unit (memory), wherein the edge computing device receives gamma photon counting data. In some embodiments, the on-chip edge computing device is programmed to partially process the counting data, which is then transmitted to an external data processing unit for further data processing. In some embodiments, the data storage unit communicates with the external data processing unit, wherein the data processing unit is programmed to calculate the total %IA / ml of one or more tumors and one or more organs at risk in a subject from multiple gamma photon counting records from multiple gamma photon counters, as further described below.

[0216] In some implementations, the chip includes an internal power supply or energy storage device, such as a capacitor or battery, to supply power to the chip, for example, for operating digital counters, detectors, and clocks. The on-chip power supply or energy storage device may include, but is not limited to, lithium-ion batteries, silver oxide batteries, or chip-type double-layer capacitors. In some implementations, the battery is rechargeable.

[0217] In some embodiments, power is transferred to the chip from an external transducer. Examples of external transducers include ultrasonic transducers, electromagnetic (EM) transducers, inductive transducers, and radio frequency (RF) transducers. In some embodiments, the chip further includes an energy storage device, such as a capacitor or rechargeable battery, to store electrical energy output from a piezoelectric substrate in response to receiving ultrasonic power, or to store electrical energy output from an antenna in response to receiving RF or electromagnetic power, wherein the capacitor or rechargeable battery supplies power to the chip for its operation. In some embodiments, the piezoelectric substrate and / or the battery or storage capacitor are assembled on a solid support (e.g., a plate) containing the chip. In some embodiments, the gamma photon counter includes a pre-charged battery that does not receive external power or is not recharged; in this case, after discharge, the battery remains until it is removed.

[0218] Several voltage regulators can be used to generate an on-chip voltage for circuit operation and on-chip clock generation. In an implementation where power is transferred from an external transducer, the gamma photon counter further includes a voltage rectifier and several voltage regulators to generate the on-chip voltage for circuit operation. Multiple voltage sources at various levels can be generated on-chip to power the on-chip circuitry. In some implementations, the clock signal is derived from the transducer signal. An analog-to-digital converter (ADC) can also be included on-chip. Examples of ADCs include an 8-bit differential SAR ADC with a maximum range of 0.5 V or 1 V and a 10-bit SAR ADC with a maximum range of 0.5 V or 1 V.

[0219] Wearable systems

[0220] A wearable system is provided comprising multiple gamma-photon counters (e.g., fiber-optic or chip-based gamma-photon counters) attached to a wearable structure for monitoring radiation delivered to a subject's tumors and organs at risk. The counters are positioned based on each patient's unique tumor distribution. By placing the counters at desired locations on a wearable material, patients can be monitored continuously or at set time intervals. This wearable material can be continuously worn or removed, or worn only for the time (e.g., 10 minutes) required to acquire counting data in a home, clinic, or hospital setting. The wearable system avoids the need for large-volume scintillation crystals and collimators by utilizing the longer image acquisition time enabled by the wearable counters.

[0221] Medical imaging of the subject (e.g., SPECT, PET, or CT) provides information about the location of the gamma photon counter relative to tumors and at-risk organs in the subject and limits the patient surface area that needs to be imaged. In some embodiments, images of the subject are used to position the gamma photon counter on a wearable structure to monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by specific tumors and at-risk organs in the subject. Count data from multiple wearable counters can be uploaded to a computer for calculating the dose distribution of the radiopharmaceutical containing a gamma-emitting radionuclide in the subject's tumors and at-risk organs using computer-implemented methods described further below. Such wearable systems can provide convenient continuous dosimetry for patients and reduce the need for hospital-based medical imaging.

[0222] The term "wearable" includes any structure that can be worn or carried on the body of a subject, similar to clothing or an article of clothing. The multiple gamma photon counters described herein can be attached to any suitable type of wearable material that allows the counters to monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor or organ at risk in the subject. In some cases, multiple gamma photon counters are attached to any number of different structures for wearing on different parts of the body. For example, wearable structures can take the form of adhesive patches or clothing, such as vests, shirts, shorts, trousers, hats, shoes, gloves, and body armor, and can include any combination of two or more of the foregoing. In some embodiments, different sizes of wearable systems can be made to accommodate individuals of different body types. For example, a range of sizes for a particular wearable system can be provided to accommodate different body types ranging from adults to children, from short to tall individuals, from slim to overweight or obese individuals, or any other range of body types. In some cases, adjustability can be provided by the elasticity of structures associated with body parts, adjustable components such as straps and fasteners, adjustable detector positions, and / or any other suitable layout or feature. In some cases, wearable structures can be attached to associated body parts using any suitable method, including, for example, the inherent elasticity of materials, straps, elastic bands, snaps, ties, hook and loop fasteners, clips, tapes, or adhesives, and / or any other applicable method of attaching and / or fitting the structure to the associated body part. In some embodiments, multiple gamma photon counters are attached to clothing belonging to the subject to be monitored.

[0223] In some implementations, the wearable structure provides the subject wearing the system with degrees of freedom of movement by using wireless connectivity, visual indicators, power sources (e.g., batteries, capacitors, wireless power transmission, etc.), and / or storage devices for later downloading gamma photon count data. In other implementations, the wearable structure has a wired connection to a processor and / or data storage device, or otherwise restricts the subject's movement.

[0224] In some embodiments, the wearable system includes 10 to 1000 gamma photon counters attached to the wearable structure. The exact number of counters attached to the wearable structure (e.g., for counting uptake of a radiopharmaceutical containing a gamma-emitting radionuclide from a tumor or at-risk organ) can vary and will depend on the patient's unique tumor distribution and the number required to provide the sensitivity and resolution needed to monitor the uptake of the radiopharmaceutical containing a gamma-emitting radionuclide. In some 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 1000 or more counters, such as 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, etc. 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 a spacing of about 1 cm to 10 cm between counters), or without a pattern. In some implementations, the location of each counter is determined based on medical imaging of the subject (e.g., PET, CT, or SPECT) to determine the location of tumors and at-risk organs within the subject, such that when the wearable structure is worn by the subject, the counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by the tumor or at-risk organ.

[0225] In some embodiments, a first subset of multiple counters is arranged on the garment such that, when the garment is worn by the subject, the first subset of counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject; and a second subset of multiple counters is arranged on the garment such that, when the garment is worn by the subject, the second subset of counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by an organ at risk in the subject. In some embodiments, the positioning of each counter in the first subset on the garment is determined based on medical imaging of the subject to determine the location of the tumor in the subject, and the positioning of each counter in the second subset on the garment is determined based on medical imaging of the subject to determine the location of an organ at risk in the subject.

[0226] The garment, including multiple counters attached thereto, can be any suitable type of clothing for this purpose, such as vests, shirts, shorts, trousers, hats, shoes, gloves, and body armor. The choice of garment type will depend on the location of the tumor in the subject and the organs at risk. For example, a vest or shirt including multiple counters may be suitable for detecting the uptake of radiopharmaceuticals containing gamma-emitting radionuclides by tumors in the lungs, stomach, intestines, bladder, prostate, etc. In another example, shorts or trousers including multiple counters may be suitable for detecting the uptake of radiopharmaceuticals containing gamma-emitting radionuclides by tumors in the legs or thighs. In yet another example, a hat including multiple counters may be suitable for detecting the uptake of radiopharmaceuticals containing gamma-emitting radionuclides by tumors in the brain.

[0227] In other embodiments, multiple counters are attached to the subject's skin via adhesive patches. The counters may be arranged in a regular, repeating pattern (e.g., a grid, such as a grid with spacing of approximately 1 cm to 10 cm between counters), or without a pattern. Alternatively, the location of each counter on the skin may be determined based on the subject's medical imaging (e.g., PET, CT, or SPECT) to determine the location of tumors and at-risk organs within the subject, such that when the counters are attached to the skin via adhesive patches, they can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by the tumor or at-risk organ.

[0228] In some implementations, a first subset of multiple counters is attached to the skin via an adhesive patch, such that the first subset of counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each counter in the first subset via the adhesive patch is determined based on medical imaging of the subject to determine the location of the tumor within the subject; and a second subset of multiple counters is attached to the skin via an adhesive patch, such that the second subset of counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each counter in the second subset via the adhesive patch is determined based on medical imaging of the subject to determine the location of the organ at risk within the subject.

[0229] Wearable systems can be used, for example, to monitor the uptake of radiopharmaceuticals containing gamma-emitting radionuclides during or after administration to a subject. In some embodiments, the radiopharmaceutical is a radioactive drug, a radioimmunotherapy agent, or a radiopeptide. In some embodiments, the wearable system is used to monitor the uptake of gamma-emitting radionuclides used in SPECT imaging by tumors and OARs, such as, but not limited to, radionuclides. 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe and 201 Tl. In some embodiments, the wearable system is used to monitor the uptake of a radiopharmaceutical containing an alpha-emitting radionuclide by tumors and OARs, such as, but not limited to, alpha-emitting radionuclides. 149 Tb, 223 Ra and 225 Ac. In some embodiments, the wearable system is used to monitor the uptake of a radiopharmaceutical containing a beta-emitting radionuclide by tumors and OARs, such as, but not limited to, [other radionuclides]. 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho and 177 Lu.

[0230] Wearable systems can be used to monitor subjects treated with a theotherapy agent for cancer treatment. In some embodiments, the theotherapy agent comprises a gamma-emitting radionuclide conjugated to a binder that specifically binds to a cancer biomarker. The radionuclide can be conjugated to any agent that specifically binds to a cancer biomarker of interest (e.g., a tumor-specific antigen or a tumor-associated antigen). In some embodiments, the binder binds to the cancer biomarker of interest with high affinity. Examples of binders include, but are not limited to, antibodies, antibody fragments, antibody mimics and aptamers, and small molecules, peptides, peptide-like molecules, or ligands that selectively bind to cell biomarkers. Conjugates used in the subject method comprise at least one radionuclide attached to a binder. In some embodiments, radionuclide conjugates are used that comprise a binder that selectively binds to cancer cell-specific biomarkers. In some embodiments, multiple radionuclide conjugates are used, wherein different radionuclide conjugates bind to different biomarkers on cancer cells of the same or different cell types.

[0231] In some embodiments, the conjugate comprises an antibody that specifically binds to the marker of interest. Any type of antibody can be used for radionuclide conjugates, including but not limited to monoclonal antibodies, polyclonal antibodies, and hybrid antibodies, engineered 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. Patent No. 4,816,567); F(ab′)2 and F(ab) fragments; F… vMolecules (non-covalent heterodimers, see, e.g., Inbar et al., (1972) Proceedings of the National Academy of Sciences 69:2659-2662; and Ehrlich et al., (1980) Biochemistry 19:4091-4096); single-chain Fv molecules (scFv) (see, e.g., Huston et al., (1988) Proceedings of the National Academy of Sciences 85:5879-5883); nanobodies or single-domain antibodies (sdAbs) (see, e.g., Wang et al., (2016) International Journal of Nanomedicine 11:3287-3303, Vincke et al., (2012) Molecular Biology Methods of Immunology 911:15-26; constructs of dimer and trimer antibody fragments; microantibodies (see, for example, Pack et al., (1992) Biochemistry 31:1579-1584; Cumber et al., (1992) Journal of Immunology 149B:120-126); biantibodies, tetraantibodies, affinity antibodies, camel antibodies, humanized antibody molecules (see, for example, Riechmann et al., (1988) Nature 332:323-327; Verhoeyan et al., (1988) Science 239:1534-1536; and UK Patent Publication No. GB ​​2,276,169, published on 21 September 1994; and any functional fragments derived from such molecules in which such fragments retain the specific binding properties of the parent antibody molecule).

[0232] In other embodiments, the binder comprises an aptamer that specifically binds to a biomarker of interest. Any type of aptamer can be used, including DNA, RNA, xeno-nucleic acid (XNA), or peptide aptamers that specifically bind to tumor antigens. Such aptamers can be identified, for example, by screening combinatorial libraries. Nucleic acid aptamers (e.g., DNA or RNA aptamers) that selectively bind to target tumor antigens can be generated by repeated rounds of in vitro selection or by systematic evolution of ligands by exponential enrichment (SELEX). Peptide aptamers that bind to biomarkers of interest can be isolated from combinatorial libraries and improved by directed mutagenesis or repeated rounds of mutagenesis and selection. For a description of methods for generating aptamers, see, for example, "Adaptamers: Tools for Nanotherapy and Molecular Imaging" (…). Aptamers: Tools for Nanotherapy and Molecular Imaging (RN Veedu, edited, Pan Stanford, 2016), Nucleic Acids and Peptide Aptamers: Methods and Protocols ( Nucleic Acid and Peptide Aptamers: Methods and Protocols(Methods in Molecular Biology, edited by G. Mayer, Humana Publishing, 2009), Nucleic Acid Aptamers: Selection, Characterization, and Applications (…) Nucleic Acid Aptamers: Selection, Characterization, and Application (Methods in Molecular Biology, edited by G. Mayer, Humana Publishing, 2016), Aptamers for Therapeutic Integration Selected by Cellular SELEX ( Aptamers Selected by Cell-SELEX for Theranostics (W. 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 16 Nov pii: S0304-4165(16)30447-0; and Lyu et al., (2016) Theranostics 6(9):1440-1452; all are incorporated herein by reference in their entirety.

[0233] In other embodiments, the binder comprises an antibody mimic. Any type of antibody mimic can be used, including but not limited to affinity molecules (Nygren (2008) FEBS J. 275 (11):2668-2676), affiliates (Ebersbach et al., (2007) J. Mol. Biol. 372 (1):172-185), affiliates (Johnson et al., (2012) Anal. Chem. 84 (15):6553-6560), affiliates (Krehenbrink et al., (2008) J. Mol. Biol. 383 (5):1058-1068), alpha antibodies (Desmet et al., (2014) Nature Communications 5:5237), and anticalins (Skerra (2008) FEBS J. 275). (11):2677-2683), avimers (Silverman et al., (2005) Nature Biotechnol. 23 (12):1556-1561), darpins (Stumpp et al., (2008) DrugDiscov. Today 13 (15-16):695-701), fynomers (Grabulovski et al., (2007) Journal of Biochemistry 282 (5):3196-3204) and monoclonal antibodies (Koide et al., (2007) Methods Mol. Biol. 352:95-109).

[0234] In other embodiments, the binder comprises a small molecule ligand. Small molecule ligands encompass a wide range of chemical classes, such as small organic compounds having molecular weights 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 interaction with the target analyte structure, such as groups necessary for hydrophobic, hydrophilic, electrostatic, or even covalent interactions. In the case where the target analyte is a protein (e.g., a cell marker), the ligand will include functional groups necessary for interaction with the protein structure, such as hydrogen bonding, hydrophobic-hydrophobic interactions, electrostatic interactions, etc., and will typically include at least one amine, amide, thiol, carbonyl, hydroxyl, or carboxyl group, or preferably at least two of the functional chemical groups. The small molecule may also contain regions that can be modified and / or involved in conjugation to a radionuclide without substantially adversely affecting the small molecule's ability to bind to its target analyte.

[0235] Small molecule ligands may comprise cyclic carbon or heterocyclic structures and / or aromatic or polyaromatic structures substituted with one or more of the aforementioned functional groups. Small molecule ligands may also comprise organic compounds containing alkyl groups (including alkanes, alkenes, alkynes, and heteroalkyl groups), aryl groups (including aromatics and heteroaryl groups), alcohols, ethers, amines, aldehydes, ketones, acids, esters, amides, cyclic compounds, heterocyclic compounds (including purines, pyrimidines, benzodiazepines, β-lactams, tetracyclines, cephalosporins, and carbohydrates), steroids (including estrogens, androgens, cortisone, ecdysone, etc.), alkaloids (including ergot, periwinkle, curare, pyrrolizidine, and mitomycin), organometallic compounds, compounds with heteroatoms, amino acids, and nucleosides. Small molecule ligands are also found in biomolecules, including peptides, carbohydrates, fatty acids, steroids, purines, pyrimidines, derivatives, structural analogs, or combinations thereof. Small molecules can be derived from naturally occurring or synthetic compounds and can be obtained from a wide variety of sources, including libraries of synthetic or natural compounds. For example, numerous methods are available for the random and directed synthesis of a wide range of organic compounds and biomolecules, including the preparation of random oligonucleotides and oligopeptides. Alternatively, libraries of natural compounds in the form of bacterial, fungal, plant, and animal extracts are available or readily generated. Furthermore, naturally or synthetically generated libraries and compounds are readily modified using conventional chemical, physical, and biochemical methods and can be used to generate combinatorial libraries. Known small molecules can undergo directed or random chemical modifications, such as acylation, alkylation, esterification, and amidation, to produce structural analogs.

[0236] Therefore, small molecules can be obtained from libraries of naturally occurring or synthetic molecules, including libraries of compounds generated through combinatorial methods, i.e., combinatorial libraries of compound diversity. When obtained from such libraries, the small molecules employed will exhibit some desired affinity for protein targets in a convenient binding affinity assay. Combinatorial libraries and methods for their production and screening are known in the art and described in U.S. Patent 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, The public information in references 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; 5,438,119; and 5,223,409 is incorporated herein by reference.

[0237] Small molecule ligands may also include known pharmaceutical products that selectively bind to receptors on cells, including but not limited to growth factor receptors, receptor tyrosine kinases, receptor protein serine / threonine kinases, G protein-coupled receptors, cytokine receptors, lectin receptors, folic acid receptors, prostate-specific membrane antigen (PSMA), carbonic anhydrase IX receptors, and biotin receptors. For example, anticancer drugs that bind to such cellular receptors can be used as ligands to target radionuclides to cancer cells. Exemplary pharmaceutical products that can be used as ligands to target cancer cells include, but are not limited to, axitinib, afatinib, axitinib, erlotinib, cabozantinib, crizotinib, gefitinib, imatinib, ibrutinib, lapatinib, neovastatin, nilotinib, pazopanib, perifoxine, ponatinib, regorafenib, sorafenib, sunitinib, trametinib, and vandetanib.

[0238] Exemplary tumor-specific antigens and tumor-associated antigens include, but are not limited to, oncogene protein products, mutated or dysregulated tumor suppressor proteins, tumor virus proteins, cancer-fetal antigens, mutated or dysregulated differentiation antigens, overexpressed or aberrantly expressed cellular proteins (e.g., mutated or aberrantly expressed growth factors, mitogens, receptor tyrosine kinases, cytosine tyrosine kinases, serine / threonine kinases and their regulatory subunits, G proteins and transcription factors), and altered cell surface glycolipids and glycoproteins on cancer cells. For example, tumor-specific antigens and tumor-associated antigens may include, but are not limited to, dysregulated or mutated RAS, WNT, MYC, ERK, TRK, CTAG1B, 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 tyrosine kinases, Abl, Raf kinase, cyclin-dependent kinases, alpha-fetoprotein (AFP), carcinoembryonic antigen (CEA), CA-125, MUC-1, epithelial tumor antigen (ETA), tyrosinases, melanoma-associated antigen (MAGE), and other abnormal or dysregulated proteins expressed on cancer cells. In some implementations, cancer-targeting binders bind to tumor antigens of interest with high affinity.

[0239] In some implementations, the tumor marker targeted by the binder is urokinase plasminogen activator receptor (uPAR) or urokinase plasminogen activator (uPA). Many anti-uPAR antibodies are available, including the 2G10 antibody, which inhibits the interaction between uPAR and urokinase plasminogen activator; and the anti-uPAR antibody 3C6, which inhibits the association of uPAR with β1 integrin (see, for example, LeBeau et al., (2013) Cancer Res. 73(7):2070-2081). Anti-PAR and anti-uPA antibodies can be conjugated to radionuclides for imaging or radioligand therapy to treat cancer cells expressing uPAR or uPA, respectively, including, but not limited to, those cancer cells in breast cancer (including triple-negative breast cancer), pancreatic cancer, prostate cancer, and melanoma.

[0240] In some implementations, the tumor marker targeted by the binder is PD-L1. Many anti-PD-L1 antibodies are commercially available, including durvalumab, pembrolizumab, atezolizumab, and avelumab. Other anti-PD-L1 antibodies include C4 and DFO-C4 (see, for example, Truillet C et al., (2018) Bioconjug. Chem. 29(1):96-103). These anti-PD-L1 antibodies can be conjugated with radionuclides for imaging or radioligand therapy to treat PD-L1-expressing cancer cells, including but not limited to: melanoma; lung cancer, including non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC); head and neck cancer; Hodgkin's lymphoma; gastric 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.

[0241] In some implementations, the tumor marker targeted by the binder is the epidermal growth factor receptor (EGFR). Many anti-EGFR antibodies are available, including panitumumab, cetuximab, zalumab, nimotuzumab, and mateuzumab, which can be conjugated with radionuclides for imaging or radioligand therapy to treat EGFR-expressing cancer cells, including but not limited to those cancer cells of the head and neck, colorectal, lung, ovarian, breast, endometrial, cervical, bladder, gastric, and esophageal types. Many small molecule drugs targeting EGFR are also available according to the methods described herein, including but not limited to gefitinib, erlotinib, lapatinib, sorafenib, and vandetanib, which can be conjugated with radionuclides for imaging or radioligand therapy to treat EGFR-expressing cancer cells.

[0242] In other embodiments, the tumor marker targeted by the binder is HER2. Many anti-HER2 antibodies are also available, including trastuzumab, pertuzumab, and margetuximab, which can be conjugated with radionuclides for imaging or radioligand therapy to treat HER2-expressing cancer cells, including but not limited to those cancer cells of the following types: breast cancer, ovarian cancer, stomach cancer, lung cancer, uterine cancer, gastric cancer, colon cancer, head and neck cancer, and salivary gland duct carcinoma. Many small molecule drugs targeting HER2 are also available according to the methods described herein, including but not limited to lapatinib and neratinib, which can be conjugated with radionuclides for imaging or radioligand therapy to treat HER2-expressing cancer cells.

[0243] In other embodiments, the tumor marker targeted by the binder is epithelial cell adhesion molecule (EpCAM) 17-1A. Many anti-EpCAM 17-1A antibodies are also available, including edrecolomab, catumaxomab, and nofetumomab, which can be conjugated radionuclides for imaging or radioligand therapy to treat cancer cells expressing EpCAM 17-1A, to detect cancer cells in epithelial tumors and various cancers such as lung cancer, gastrointestinal cancer, breast cancer, ovarian cancer, pancreatic cancer, kidney cancer, cervical cancer, colorectal cancer, and bladder cancer.

[0244] In other implementations, the tumor marker targeted by the binder is CD20. Many anti-CD20 antibodies are also available, including rituximab, tositumomab, ocrelizumab, oxcartuzumab, oflamumab, ibritumomab tiuxetan, utrituximab, and veltuzumab, which can be conjugated with radionuclides for imaging or radioligand therapy to treat CD20-expressing cancer cells, including but not limited to: lymphomas such as, but not limited to, marginal zone lymphoma, Hodgkin lymphoma, and non-Hodgkin lymphoma; leukemias such as, but not limited to, chronic lymphocytic leukemia, acute lymphoblastic leukemia, myeloid leukemia, and chemotherapy-resistant hairy cell leukemia; and thyroid cancer.

[0245] In other embodiments, the tumor marker targeted by the binder is CD52. Many anti-CD52 antibodies are also available, including alemtuzumab, which may be a conjugated radionuclide for imaging or radioligand therapy to treat CD52-expressing cancer cells, including but not limited to those cancer cells such as lymphomas, such as, but not limited to, cutaneous T-cell lymphoma (CTCL) and T-cell lymphomas, and chronic lymphocytic leukemia (CLL).

[0246] In other implementations, the tumor marker targeted by the binder is CD22. Many anti-CD22 antibodies are also available, including itutuzumab, which can be conjugated with radionuclides for imaging or radioligand therapy to treat CD22-expressing cancer cells, including but not limited to those cancer cells such as: leukemia, such as, but not limited to, lymphoblastic leukemia and hairy cell leukemia; lymphoma and lung cancer.

[0247] In other implementations, the tumor antigen targeted by the binder is CD19. Many anti-C19 antibodies are also available, including blinatumomab, MEDI-551, and MOR-208, which can be conjugated with radionuclides for imaging or radioligand therapy to treat CD19-expressing cancer cells, including but not limited to those cancer cells such as B-cell tumors, non-Hodgkin lymphoma (NHL), chronic lymphocytic leukemia (CLL), acute lymphoblastic leukemia (ALL), and multiple myeloma (MM).

[0248] In some implementations, the tumor marker targeted by the binder is carcinoembryonic antigen (CEA). Many anti-CEA antibodies are available, including acitumomab, which can be conjugated with a radionuclide for imaging or radioligand therapy to treat CEA-expressing cancer cells, including but not limited to those of colorectal cancer, gastric cancer, pancreatic cancer, lung cancer, breast cancer, and medullary thyroid carcinoma.

[0249] In some implementations, the tumor marker targeted by the binder is prostate-specific membrane antigen (PSMA). Many anti-PSMA antibodies are available, including capromab, PSMA30 nanobodies, and IAB2M microbodies, which can be conjugated to radionuclides for imaging or radioligand therapy to treat PSMA-expressing cancer cells, including but not limited to those in prostate cancer. Many small molecule drugs targeting PSMA are also available according to the methods described herein, including but not limited to zinc-bound compounds linked to isosteres or glutamates, phosphonates, phosphates, and aminophosphates and ureas; flucyclovir (Axumin); MIP-1072; MIP-1095; and N-(N-((S)-1,3-dicarboxypropyl)carbamoyl)-4-(18F)fluorobenzyl-L-cysteine ​​(18F-DCFBC), which can be conjugated to radionuclides for imaging or radioligand therapy to treat PSMA-expressing cancer cells.

[0250] In some implementations, the tumor marker targeted by the binder is the folate receptor (FR). Many anti-FR antibodies are available, including farletuzumab and m909, which can be conjugated with radionuclides for imaging or radioligand therapy to treat FR-expressing cancer cells, including but not limited to those expressing FR in ovarian, breast, lung, pleural, cervical, endometrial, renal, bladder, and brain cancers. Small molecule folate can also be conjugated with radionuclides for imaging or radioligand therapy to treat FR-expressing cancer cells, according to the methods described herein.

[0251] In some implementations, the tumor marker targeted by the binder is matrix metalloproteinase (MMP), including but not limited to MMP1, MMP3, MMP7, MMP9, MMP10, MMP11, MMP12, MMP13, and MMP14. Many anti-MMP antibodies are available and can be conjugated with radionuclides for imaging or radioligand therapy to treat MMP-expressing cancer cells, including but not limited to those cancer cells of the following types: ovarian cancer, breast cancer, lung cancer, prostate cancer, gastric cancer, thyroid cancer, skin cancer, brain cancer, kidney cancer, colon cancer, bladder cancer, esophageal cancer, endometrial cancer, hepatocellular carcinoma, and head and neck cancer. According to the methods described herein, endogenous glycoprotein inhibitors, such as tissue inhibitors of metalloproteinases (TIMPs), including TIMP-1, TIMP-2, TIMP-3, and TIMP-4, as well as many small molecule drugs targeting MMPs, are available, including but not limited to doxycycline, marimastat (BB-2516), and cipremasatal, which can be conjugated with radionuclides for imaging or radioligand therapy to treat cancer cells expressing MMPs.

[0252] Chelating agents can be included in therapeutic agents to impart metal-binding capabilities. In some embodiments, therapeutic agents include chelating agents that form complexes with radioactive nuclide metal ions. Exemplary chelating agents include, but are not limited to, 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-(biscarboxymethylamino)-ethyl]-7-carboxymethyl-[1,4,7]triazacyclononane-1-yl}acetic acid (NETA), and p-bromoacetamidobenzoyl-tetraethylaminetetraacetic acid (TETA), porphyrins, polyamines, crown ethers, thiourea diammonium ethers, polyoximes, and other groups known to be suitable for this purpose.

[0253] System and computer implementation methods

[0254] This disclosure provides systems and computer-implemented methods for practicing the subject methods. In some embodiments, the system may include: a processor programmed to calculate the total percentage of injected activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject; and a display unit for displaying the total %IA / mL for one or more tumors and one or more organs at risk. The system may also include one or more graphics cards for processing graphical information and outputting it to the display unit. For example, a display may be used to display images of the subject's tumors and organs at risk obtained through medical imaging. In some embodiments, a computer-implemented method is used to calculate the total %IA / mL for one or more tumors and one or more organs at risk in a subject. The injected activity may be derived from a radiopharmaceutical containing a gamma-emitting radionuclide, which may also emit particles such as alpha or beta particles. The processor can be programmed to perform the steps of a computer-implemented method, including: a) receiving gamma photon counting data from a plurality of gamma photon counters, wherein each gamma photon counter has a known location; b) receiving an image of a subject, wherein the image shows the location of one or more tumors and one or more organs at risk in the subject, and the location of the plurality of gamma photon counters relative to the one or more tumors and one or more organs at risk; c) defining boundaries around each tumor and each organ at risk on the image; d) using the image to measure the volume of the one or more tumors and organs at risk; e) mapping the centroid location of each gamma photon counter on the image; f) performing distributed point source (DPS) modeling to generate a distribution of gamma photon emission point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) decay based on counts per second (CPS) and 1 / (the distance between the centroid location of the gamma photon counter and the gamma photon emission point source). 2The related assumptions include: calculating the probability of receiving gamma photons counted by the gamma photon counter from a gamma photon emission source within the boundary of a specific tumor or organ at risk for each gamma photon counter; and the CPS value being decayed by an empirically derived factor Ω, which takes into account the attenuation and scattering of gamma photons in the tissue; and ii) estimating the possible fraction of counts corresponding to a specific tumor or organ at risk for each gamma photon counter; g) estimating the total count for each tumor and organ at risk using a Markov Chain Monte Carlo (MCMC) algorithm based on gamma photon count data from multiple counters and parameter estimates of the possible fraction of counts corresponding to a specific tumor or organ at risk for each gamma photon counter, modeled from DPS; h) calculating the total %IA / mL of one or more tumors and organs at risk in the subject based on the estimated total count for each tumor and organ at risk, divided by the volume of one or more tumors and organs at risk measured from the image; and i) displaying the total %IA / mL of one or more tumors and organs at risk in the subject.

[0255] In some implementations, performing DPS modeling includes creating a DPS model matrix ( W ), which represents the counts per second (CPS) contributed by each tumor or at-risk organ to each of the multiple gamma photon counters, where the CPS per μC is multiplied by the unknown activity in μC of the total tumor or at-risk organ, where the DPS model matrix ( W The values ​​in ) are estimated based on knowledge of the location of each tumor and each organ at risk from the image, as well as the known location of each γ-photon counter; and the DPS model matrix ( W Decompose into a matrix ( β ) and vectors ( α ), where the matrix ( β ) represents the score of CPS from a specific tumor or at-risk organ in each gamma photon counter, where the score is represented by a vector ( α ) scaled up proportionally, where the vector ( α The vector is the CPS of μCi activity per injection for each γ-photon counter. In some implementations, the vector is estimated by performing DPS titration simulations. α In some implementations, the matrix ( βThe initial estimation was made by: i) assuming that each tumor and each organ at risk takes up an equal amount of radionuclide, wherein the total amount of radionuclide administered to the subject is known, and ii) assigning the same activity to all tumors and organs at risk for the estimated possible fraction of the counts corresponding to a particular tumor or organ at risk, counted by each counter.

[0256] In some implementations, the empirically derived factor Ω is determined by a method comprising the following steps: measuring the detected CPS of each gamma photon counter at different distances from the gamma photon emission point source in water; measuring the detected CPS of each gamma photon counter at different distances from the gamma photon emission point source in air; deriving a nonlinear factor representing the scattering and attenuation of each gamma photon emission point source based on the difference between the CPS detected in water and air at each distance; and using the nonlinear factor to calculate a unique factor Ω for each gamma photon emission point source in the subject based on the distance in the tissue between each gamma photon counter and each gamma photon emission point source.

[0257] In some implementations, the computer-implemented method further includes using adaptive Metropolis (AM) optimization, wherein the Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm. In some implementations, the computer-implemented method further includes performing iterative optimization by including methods such as gradient descent, least squares minimization, or brute-force global minimization, or combinations thereof.

[0258] In some embodiments, the multiple gamma photon counters include on-chip circuitry tuned to respond to a range of LET (Light Emission Time) from incident gamma photons. The computer-implemented method further includes calculating the incident energy of the gamma photons based on combinations and distributions of signals from pixels having known LET responsivity. In some embodiments, the multiple gamma photon counters include multiple detectors, each of which includes attenuating material of varying thicknesses to allow resolution of incident gamma photons with different energies. The computer-implemented method further includes using multiphysics simulations to calculate the probability of detecting gamma photons of specific energies using each of the multiple detectors, thereby separating the detection counts of each detector by gamma photon energy.

[0259] In some embodiments, the plurality of gamma photon counters include on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from incident gamma photons, wherein the computer-implemented method further includes calculating the incident energy of the gamma photons based on combinations and distributions of signals from pixels having known LET responsivity. In some embodiments, the array of pixels includes a first subset and a second subset of pixels having 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 with higher LET but not higher-energy gamma photons with lower LET, and wherein the second set of pixels detects both lower-energy gamma photons with higher LET and higher-energy gamma photons with lower LET.

[0260] In some embodiments, the computer-implemented method uses gamma photon counting data from a chip-based gamma photon counter comprising a plurality of detectors arranged in a vertical stack. In some embodiments, each detector is spaced apart from adjacent detectors in the vertical stack by a layer of attenuating material. In some embodiments, each detector has fast readout circuitry connected to an array of pixels to allow near-instantaneous detection of the same incident gamma photon passing between two detectors in the vertical stack. In some embodiments, each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits the time when the incident gamma photon hits the pixel, the pixel position on the detector, and the signal generated by the gamma photon hitting the pixel. In some embodiments, the computer-implemented method further includes calculating the angle of the incident gamma photon relative to the vertical stack by measuring the angular offset (e.g., due to Compton scattering) of the incident gamma photon traveling from a detector at the top of the stack to a detector located below in the stack.

[0261] In some implementations, the computer-implemented method uses gamma photon counting data from a chip-based gamma photon counter, which includes multiple detectors arranged in a planar layout in a spatial region, wherein the computer-implemented method further includes determining the energy of incident gamma photons in the spatial region.

[0262] In some implementations, the computer-implemented method further includes segmenting the image, wherein the boundaries of each tumor and organ at risk, as well as the centroid location 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, IlastikToolkit, which uses a random forest classifier for cell segmentation; DeepCell, which uses a deep learning algorithm to leverage a deep convolutional neural network for cell segmentation; the Open Segmentation Framework OpSeF, which uses a deep learning convolutional neural network to semi-automate image segmentation, where the user manually provides some training data; CellSeg, which uses a region-convolutional neural network (R-CNN) for image segmentation; the CODEX image processing pipeline software, which uses reference cell markers, reference cell nuclear staining, and reference membrane staining to assist image segmentation; and CellProfiler, which uses conventional thresholding, classifying pixels as foreground if they are brighter than a certain “threshold” intensity value, and uses illumination correction, declustering, and watershed segmentation to identify cells in the image. For descriptions of image segmentation techniques and software, see, for example, Kreshuk et al., (2019) Methods in Molecular Biology 2040:449-463; Kreshuk et al., (2014) PLoS One 9(2):e87351; David A. Van Valen et al., (2016) PLOS ONE Computational Biology (PLoS Comput.Biol.) 12(11):e1005177; Dobson et al., (2021) Modern Experimental Methods (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) Nature Methodology (Nat. Methods) 14:873-876; Ljosa et al., (2009) PLOS ONE Computational Biology 5(12):e1000603 and Lee et al., (2022) BMC Bioinformatics 23(1):46; incorporated herein by reference. Images of tumors and organs at risk in subjects can be obtained by any suitable medical imaging technique, including but not limited to positron emission tomography (PET), computed tomography (CT) and single-photon emission computed tomography (SPECT).

[0263] This method can be implemented in digital electronic circuits or in computer software, firmware, or hardware. The disclosed embodiments 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 a data processing device or for controlling the operation of a data processing device. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, a composition of substances that realize machine-readable propagation signals, or any combination thereof.

[0264] Computer programs (also known as programs, software, software applications, scripts, or code) can be written in any programming language, including compiled or interpreted languages; and they can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suited to a computing environment. A computer program does not necessarily correspond to a file in a file system. A program can be stored as a portion of a file containing other programs or data (e.g., one or more scripts stored in a markup language document), as a single file dedicated to the program in question, or as multiple collaborative files (e.g., files storing portions of one or more modules, subroutines, or code). A computer program can be deployed to execute on a single computer or on multiple computers located in one place or distributed across multiple locations and interconnected by a communication network.

[0265] In another aspect, as described, the system for performing the computer-implemented method may include a processor, storage components (i.e., memory), display components, and other components typically found in general-purpose computers. In some embodiments, the various steps, components, and computing systems described in conjunction with the embodiments disclosed herein are implemented or performed by a machine such as a general-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), 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. The general-purpose processor may be a microprocessor, but alternatively, the processor may be a controller, microcontroller, or state machine, a combination thereof, etc. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration. The processor may primarily comprise digital or analog components. The computing environment may include any type of computer system, including but not limited to microprocessor-based computer systems, graphics processing units, mainframe computers, digital signal processors, portable computing devices, personal managers, device controllers, and computing engines within appliances, etc.

[0266] The steps of the methods, processes, or algorithms described in conjunction with the embodiments disclosed herein can be directly embodied in hardware, software modules executed by a processor, or a combination of both. Software modules, engines, and associated databases can reside in memory resources such as RAM memory, FRAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other form of non-transitory computer-readable storage medium, media, or physical computer storage device known in the art. An exemplary storage medium can be coupled to a processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be integrated into the processor. The processor and storage medium can reside in an ASIC. The ASIC can reside in a user terminal. Alternatively, the processor and storage medium can reside as discrete components in the user terminal.

[0267] The storage unit stores information accessible to the processor, including instructions executable by the processor and data that can be retrieved, processed, or stored by the processor. The storage unit includes instructions, including instructions for calculating the total percentage of total injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject. A computer processor is coupled to the storage unit and configured to execute the instructions stored in the storage unit to receive count data from multiple counters and images of one or more tumors and organs at risk in the subject, and to analyze the data and images according to one or more algorithms, as described herein.

[0268] The display component shows the total %IA / ml of one or more tumors and organs at risk in the subject. In some embodiments, the display further shows images of the tumors and organs at risk, as well as the centroid location of the boundary lines surrounding each tumor and organ at risk and the mapping of each counter superimposed on the image. In some embodiments, the display further shows the distribution of radionuclide point sources (e.g., gamma-photon emission or particle emission radionuclide point sources) within the boundaries of each tumor and organ at risk, as determined by distributed point source (DPS) modeling. Furthermore, the display may further display labels with information about the tumors and organs at risk superimposed on the image. In some embodiments, the labels are color-coded to distinguish different tumors and / or organs at risk.

[0269] Instructions can be any set of instructions to be executed directly by the processor (such as machine code) or indirectly (such as scripts). In this regard, the terms "instruction," "step," and "program" are used interchangeably. Instructions can be stored as object code for direct processing by the processor, or stored in any other computer language, including scripts or collections of independent source code modules that are interpreted or pre-compiled as needed.

[0270] Data can be retrieved, stored, or modified by the processor according to instructions. For example, although the system is not limited to any particular data structure, data can be stored in computer registers, tables with multiple different fields and records in a relational database, XML documents, or flat files. Data can also be formatted in any computer-readable format, such as, but not limited to, binary values, ASCII, or Unicode. Furthermore, data can include any information sufficient to identify the relevant information, such as numbers, descriptive text, proprietary code, pointers, references to data stored in other memory (including other network locations), or information used by functions to calculate the relevant data.

[0271] In some implementations, the processor and storage components may include multiple processors and storage components, which may or may not be stored in the same physical housing. For example, some instructions and data may be stored on a removable CD-ROM, while other instructions and data may be stored in a read-only computer chip. Some or all of the instructions and data may be stored in a location physically remote from the processor but still accessible to the processor. Similarly, the processor may include a collection of processors that can operate in parallel or not.

[0272] In some implementations, a cloud computing system can be used to perform the method. In these implementations, gamma photon counting data files, patient images obtained through medical imaging, and programming can be uploaded to a cloud computer, which runs the program and returns the output to the user.

[0273] The components of the system for implementing the methods disclosed herein are further described in the following embodiments.

[0274] Reagent test kit

[0275] A kit is also provided that includes a wearable gamma photon counter system comprising multiple counters (e.g., fiber-optic gamma photon counters or chip-based gamma photon counters) for monitoring radioactivity in tumors and organs at risk from radiopharmaceutical therapy or imaging delivery to a subject, as described herein. In some embodiments, the kit includes software for implementing the computer-implemented methods described herein for calculating the total percentage of injected activity (%IA / mL) per milliliter of tissue for one or more tumors and organs at risk in the subject. In some embodiments, the kit includes a non-transitory computer-readable medium and instructions for calculating the total %IA / mL for one or more tumors and organs at risk in the subject, as described herein. In some embodiments, the kit includes a system comprising a processor programmed to calculate the total %IA / mL for one or more tumors and organs at risk in the subject according to the computer-implemented methods described herein; and a display component for displaying the %IA / mL for one or more tumors and organs at risk in the subject.

[0276] In some embodiments, the kit includes a fiber-optic gamma-photon counter comprising: a Y₂O₃-Eu-doped phosphor, wherein gamma photons incident on the surface of the Y₂O₃-Eu-doped phosphor generate scintillation light in the visible spectrum suitable for solid-state photon detection; a detector including a photodiode; an optical fiber guiding the scintillation light generated by the Y₂O₃-Eu-doped phosphor to the detector, wherein the detector generates a voltage pulse in response to detecting the scintillation light generated by gamma photons; a digital counter coupled to the detector, wherein the digital counter counts gamma-photon detection events, wherein each gamma-photon detection event corresponds to a voltage pulse generated by the detector in response to detecting scintillation light generated from each gamma photon incident on the surface of the Y₂O₃-Eu-doped phosphor; and an opaque material covering the optical fiber, wherein the opaque material shields the optical fiber from visible light not emitted by the Y₂O₃-Eu-doped phosphor.

[0277] In some embodiments, the kit includes a chip-based gamma-photon counter comprising: a detector implemented as an application-specific integrated circuit (ASIC) on a chip, wherein the detector includes at least one reverse-biased diode, wherein gamma photons incident on the surface of the reverse-biased diode generate voltage pulses across the reverse-biased diode. In some embodiments, the reverse-biased diode is connected to an amplifier and then to a digital counter. In other embodiments, the reverse-biased diode is connected to a voltage buffer before being connected to a voltage amplifier and subsequently to the digital counter. The digital counter counts gamma-photon detection events, wherein each gamma-photon detection event corresponds to a voltage pulse generated across the reverse-biased diode by each gamma photon incident on the surface. In some embodiments, the chip further includes an on-chip memory configured to store multiple gamma-photon count records of multiple gamma-photon detection events. In some embodiments, the chip further includes a digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events for each time period. In some implementations, the chip further includes custom digital logic circuitry configured to control voltage and supply power to detectors, digital counters, and digital clocks from on-chip or off-chip energy storage devices.

[0278] In some embodiments, the kit includes a chip-based gamma-photon counter comprising a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma-sensing element. In some embodiments, each pixel in the array includes two silicon diodes connected to an amplifier, wherein incident gamma photons break bonds in the silicon, generating electron-hole pairs, which in turn generate charge pulses (Q) in the silicon diodes. p ), the charge pulse (Q p In parasitic diode capacitor (C) 二极管 This accumulates on the diode. This generates a small voltage pulse (V) across the diode. p = Q p / C 二极管 The use of integrated circuit technology enables ultra-small diode capacitance, increasing VC. pThis allows for in-pixel amplification. Each voltage pulse is individually buffered using a unity-gain voltage amplifier. Each of these buffered outputs is connected to the input of a differential amplifier. To mitigate DC voltage offsets at the output due to manufacturing variability from inter-pixel and inter-chip sources, which can cause variations in detector sensitivity, a voltage integrator is configured with negative feedback to bootstrap from the amplifier's output to one of the amplifier's inputs. The voltage integrator also accepts a desired DC voltage that sets the voltage at the amplifier's output. This ensures that the sensitivity of each pixel across the entire chip is approximately the same. To tune each diode in each pixel to the desired sensitivity, the amplifier's output is connected to two level shifters: one shifts the DC level at the amplifier's output up to amplify only the voltage pulse from the first diode, and the other shifts the DC level down to amplify only the voltage pulse from the second diode. The amount by which these DC levels are offset is set using on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) to convert the stored bits into an analog voltage offset. These shifted and amplified voltage pulses are then digitized using a series of inverters. A capacitor at the input of the last inverter improves signal fidelity before the pulses are subsequently counted. A digital counter is coupled to the inverter chain, where the digital counter counts gamma-photon detection events, each corresponding to a voltage pulse across the diode generated by each gamma photon incident on the surface of any silicon diode. The chip also includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate an on-chip clock signal, which the digital counter uses to count the number of gamma-photon detection events for each time period; and custom digital logic configured to control the voltage and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0279] In some embodiments, the kit includes a chip-based gamma-photon counter comprising: a detector implemented as an on-chip ASIC, wherein the detector comprises an array of pixels, each pixel being a gamma-sensing element, and each pixel containing a reverse-biased silicon diode connected to a unity-gain voltage buffer. A buffered voltage output from a unity-gain voltage amplifier is fed into a differential closed-loop amplifier. The gain of the differential closed-loop amplifier may be preset or configured using in-pixel memory and a DAC. Gamma photons incident on the surface of the silicon diode generate voltage pulses across the diode and are subsequently buffered and amplified with a fixed, process-invariant gain. These voltage pulses are then digitized using a series of inverters connected to a digital counter to quantify the total number of gamma photons detected within a specific time frame. Each gamma-photon detection event corresponds to a voltage pulse across the diode generated by each gamma photon incident on the surface of the silicon diode. The chip further includes an on-chip data buffer configured to store multiple gamma-photon count records of multiple gamma-photon detection events; a digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma-photon detection events for each time period; and custom digital logic circuitry configured to control voltage and supply power to the detector, digital counter, and digital clock from on-chip or off-chip energy storage devices.

[0280] In some embodiments, the kit includes a wearable structure comprising multiple gamma photon counters (e.g., fiber-optic gamma photon counters or chip-based gamma photon counters). In some embodiments, the wearable structure is clothing, such as a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor. The type of clothing chosen will depend on the location of the tumor in the subject. For example, a vest or shirt including multiple counters may be suitable for detecting the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by tumors in the lungs, stomach, intestines, bladder, prostate, etc. Trousers including multiple counters may be suitable for detecting the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by tumors in the legs. A hat including multiple counters may be suitable for detecting the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by tumors in the brain. In some embodiments, a first subset of multiple gamma photon counters is arranged on a wearable structure such that, when the wearable structure is worn by a subject, the first subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject; and a second subset of multiple gamma photon counters is arranged on the wearable structure such that, when the wearable structure is worn by a subject, the second subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by an organ at risk in the subject. In some embodiments, the positioning of each gamma photon counter in the first subset on the wearable structure is determined based on medical imaging of the subject to determine the location of the tumor in the subject, and the positioning of each gamma photon counter in the second subset on the wearable structure is determined based on medical imaging of the subject to determine the location of an organ at risk 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 some embodiments, the multiple gamma photon counters are arranged in an array on the wearable structure.

[0281] In some embodiments, the kit further includes a plurality of adhesive patches for attaching a plurality of counters (e.g., fiber-based gamma photon counters or chip-based gamma photon counters) to the skin.

[0282] In addition to the components described above, the subject kit may further include (in some embodiments) instructions for practicing the subject method. These instructions may exist in the subject kit in a variety of forms, one or more of these forms. One form of these instructions may be as printed information on a suitable medium or substrate, such as one or more sheets of paper with information printed on them, in the kit packaging, in a packaging insert, etc. Another form of these instructions is as computer-readable media, such as a disk, optical disc (CD), flash drive, etc., on which the information has been recorded. Yet another possible form of these instructions is a website address, which can be used via the Internet to access information at a remote site.

[0283] Examples of non-limiting aspects of this disclosure

[0284] The aspects of the subject matter of the invention described above, including embodiments, can be beneficial individually or in combination with one or more other aspects or embodiments. Without limiting the foregoing description, certain non-limiting aspects of this disclosure, numbered 1-177, are provided below. As will be apparent to those skilled in the art upon reading this disclosure, each of the individually numbered aspects can be used or combined with any preceding or following individually numbered aspects. This is intended to support all such combinations of aspects and is not limited to the combinations of aspects explicitly provided below.

[0285] 1. A gamma photon counter, comprising:

[0286] Y2O3-Eu doped phosphors, wherein γ photons incident on the surface of the Y2O3-Eu doped phosphor generate scintillation light in the visible spectrum;

[0287] The detector includes a photodiode;

[0288] An optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3-Eu-doped phosphor to the detector, wherein the detector generates a voltage pulse in response to detecting the scintillation light generated by the γ photons;

[0289] A digital counter, coupled to the detector, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to a voltage pulse generated by the detector in response to detecting the scintillation light generated from each gamma photon incident on the surface of the Y₂O₃-Eu-doped phosphor; and

[0290] An opaque material is used to cover the optical fiber, wherein the opaque material shields the optical fiber from visible light emitted by the phosphor other than that doped by the Y2O3-Eu.

[0291] 2. The gamma photon counter according to aspect 1, wherein the photodiode is an avalanche photodiode (APD).

[0292] 3. The γ-photon counter according to aspect 2, wherein the APD is a silicon APD.

[0293] 4. The gamma photon counter according to aspect 1, wherein the photodiode is a single-photon avalanche diode (SPAD).

[0294] 5. The gamma photon counter according to any one of aspects 1-4, wherein the detector further comprises a plurality of power supplies to control circuit cooling, quenching and reset, and high-voltage bias.

[0295] 6. The gamma photon counter according to aspect 5, wherein the plurality of power supplies includes a 2-volt power supply for controlling the cooling of the circuit, a 5-volt power supply for controlling the quenching and reset, and a 30-volt power supply for controlling the high-voltage bias.

[0296] 7. The γ-photon counter according to any one of aspects 1-6, wherein the detector further comprises a high-voltage regulator.

[0297] 8. The γ-photon counter according to any one of aspects 1-7, wherein the opaque material has an optical density (OD) of at least 4.

[0298] 9. The gamma photon counter according to aspect 8, wherein the opaque material is a black light-absorbing material.

[0299] 10. The γ-photon counter according to aspect 9, wherein the black light-absorbing material is black optical tape.

[0300] 11. The γ-photon counter according to any one of aspects 1-10, wherein the flashing light is red visible light.

[0301] 12. The γ-photon counter according to aspect 11, wherein the red visible light has a wavelength of about 610 nm.

[0302] 13. A γ-photon counter according to any one of aspects 1-12, wherein the incident γ-photons arriving at the surface of the detector are uncollimated.

[0303] 14. The gamma photon counter according to any one of aspects 1-13, wherein the digital counter is configured in a field-programmable gate array (FPGA).

[0304] 15. A gamma photon counter according to any one of aspects 1-14, wherein the digital counter has a sampling frequency of at least 150 MHz.

[0305] 16. The gamma photon counter according to any one of aspects 1-16, further comprising a clock configured to generate a clock signal, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period.

[0306] 17. The gamma photon counter according to aspect 16, wherein the time period is one second.

[0307] 18. The gamma photon counter according to any one of aspects 1-17, further comprising a level shifter, wherein the level shifter is configured in a circuit to ensure logic level compatibility with the digital counter.

[0308] 19. The gamma photon counter according to aspect 18, wherein the level shifter is a 1-bit level shifter.

[0309] 20. The gamma photon counter according to 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 of a plurality of gamma photon detection events.

[0310] 21. The gamma photon counter according to aspect 20, further comprising a data processing unit in communication with the data storage unit, wherein the data processing unit is programmed to calculate, from the plurality of gamma photon count records, the total percentage of total injection activity (%IA / mL) of one or more tumors and one or more organs at risk in the subject per milliliter of tissue.

[0311] 22. A gamma photon counter according to any one of aspects 1-21, wherein the gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging.

[0312] 23. The gamma photon counter according to aspect 22, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

[0313] 24. A γ-photon counter according to any one of aspects 1-23, wherein the γ-photons are emitted from α-particle-emitting radionuclides or β-particle-emitting radionuclides.

[0314] 25. The gamma photon counter according to aspect 24, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

[0315] 26. The gamma photon counter according to aspect 24, wherein the beta-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

[0316] 27. The gamma photon counter according to any one of aspects 1-26, wherein the radionuclide is conjugated with a small molecule, peptide, or antibody.

[0317] 28. The gamma photon counter according to aspect 28, wherein the gamma photon counter is attached to a fabric or adhesive patch.

[0318] 29. The gamma photon counter according to any one of aspects 1-28, wherein the gamma photon counter is attached to a wearable structure.

[0319] 30. The gamma photon counter according to aspect 29, wherein the wearable structure is clothing.

[0320] 31. The gamma photon counter according to aspect 30, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

[0321] 32. The γ-photon counter according to any one of aspects 1-31, wherein the γ-photon counter has a diameter of less than or equal to 2.5 mm.

[0322] 33. A gamma photon counter, comprising:

[0323] A detector configured in an application-specific integrated circuit (ASIC) on a chip, wherein the detector includes a reverse-biased diode, wherein gamma photons incident on the surface of the reverse-biased diode generate voltage pulses across the reverse-biased diode;

[0324] A digital counter coupled to the detector, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse across the diode generated by each gamma photon incident on the surface of the reverse bias diode;

[0325] An on-chip memory configured to store multiple γ-photon count records of multiple γ-photon detection events;

[0326] A digital clock configured to generate a clock signal on the chip, wherein a digital counter uses the clock signal to count the number of gamma photon detection events for each time period; and

[0327] A custom digital logic circuit is provided on the chip, wherein the custom digital logic circuit is configured to control voltage and supply power to the detector, the digital counter, and the digital clock from on-chip or off-chip energy storage devices.

[0328] 34. The gamma photon counter according to aspect 33 further includes a voltage amplifier disposed in the circuit between the reverse bias diode and the digital counter.

[0329] 35. The gamma photon counter according to aspect 34, further comprising a voltage buffer disposed in the circuit between the reverse bias diode and the voltage amplifier.

[0330] 36. The γ-photon counter according to any one of aspects 33-35, wherein the on-chip memory is a static random access memory (SRAM).

[0331] 37. A gamma photon counter, comprising:

[0332] A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel comprising a silicon diode, wherein gamma photons incident on the surface of the silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses.

[0333] A unity-gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by the gamma photon is individually buffered by the unity-gain voltage amplifier;

[0334] A differential closed-loop amplifier, wherein a buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential closed-loop amplifier, wherein the voltage gain is preset or can be configured using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified with a fixed, process-invariant gain;

[0335] An inverter chain comprising multiple inverters connected to the amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon;

[0336] A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the silicon diode;

[0337] An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events;

[0338] A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period;

[0339] On-chip or off-chip energy storage devices; and

[0340] A custom digital logic circuit is configured to control voltage and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0341] 38. A gamma photon counter, comprising:

[0342] A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel including a pair of silicon diodes, the pair of silicon diodes including a first silicon diode and a second silicon diode, wherein gamma photons incident on the surface of the first silicon diode or the second silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses.

[0343] A unity-gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a gamma photon is individually buffered by the unity-gain voltage amplifier;

[0344] A differential amplifier, wherein the buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential amplifier;

[0345] A voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets the voltage output of the differential amplifier, wherein the voltage integrator is configured with negative feedback to bootstrap from the output of the differential amplifier to the input of the differential amplifier;

[0346] A pair of level shifters connected to the output of the differential amplifier, wherein the pair of level shifters comprises two level shifters, including a first level shifter that shifts the direct current DC level at the output of the differential amplifier upward to amplify only the voltage pulse from the first diode; and a second level shifter that shifts the DC level at the output of the differential amplifier downward to amplify only the voltage pulse from the second diode, wherein an on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) are used to set the amount by which the DC level is shifted to convert the stored bits into an analog voltage shift;

[0347] An inverter chain comprising a plurality of inverters connected to the amplified and shifted voltage outputs from the pair of level shifters, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon;

[0348] A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the first silicon diode or the second silicon diode;

[0349] An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events;

[0350] A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period;

[0351] On-chip or off-chip energy storage devices; and

[0352] A custom digital logic circuit is configured to control voltage and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0353] 39. The gamma photon counter according to aspect 37 or 38, wherein the silicon diode is reverse biased or has zero voltage bias.

[0354] 40. The gamma photon counter according to any one of aspects 37-39, wherein the sensitivity of the detector is optimized by reducing the capacitance of the silicon diode.

[0355] 41. The gamma photon counter according to any one of aspects 33-40, wherein the diode size is 0.1 µm to 0.5 µm x 0.1 µm to 0.5 µm or 0.5 µm to 1 µm x 0.5 µm to 1 µm.

[0356] 42. The γ-photon counter according to any one of aspects 33-41, wherein the diode size is the smallest size that can be used in a complementary metal-oxide-semiconductor (CMOS) process.

[0357] 43. A γ-photon counter according to any one of aspects 37-42, wherein the detector is optimized by a trade-off between pixel fill factor and sensitivity.

[0358] 44. The gamma photon counter according to aspect 43, wherein the diode size is 1 µm to 1.5 µm x 1 µm to 1.5 µm.

[0359] 45. A γ-photon counter according to any one of aspects 37-42, wherein the detector is optimized to improve the fill factor with a compromise in sensitivity.

[0360] 46. ​​The gamma photon counter according to aspect 45, wherein the diode size is 1.5 µm to 3 µm x 1.5 µm to 3 µm, 3 µm to 10 µm x 3 µm to 10 µm, or 10 µm to 50 µm x 10 µm to 50 µm.

[0361] 47. A γ-photon counter according to any one of aspects 33-46, wherein the detector has a curved shape or a polygonal shape.

[0362] 48. The gamma photon counter according to aspect 47, wherein the polygon shape is a triangle, square, rectangle, pentagon, hexagon, octagon, rhombus, or parallelogram.

[0363] 49. The gamma photon counter according to aspect 47, wherein the curved shape is circular, semi-circular, elliptical, spherical or cylindrical.

[0364] 50. A γ-photon counter according to any one of aspects 47-49, wherein the detector has an edge with a length ranging from 0.1 µm to 50 µm.

[0365] 51. A γ-photon counter according to any one of aspects 37-50, wherein the pixels in the array of pixels operate asynchronously.

[0366] 52. The γ-photon counter according to any one of aspects 33-51, wherein the chip is covered with a Compton scattering material.

[0367] 53. The gamma photon counter according to aspect 52, wherein the Compton scattering material comprises lead, tungsten, or bismuth.

[0368] 54. The γ-photon counter according to aspect 52 or 53, wherein the Compton scattering material is in a layer on top of the detector or on the back side of the detector.

[0369] 55. The γ-photon counter according to any one of aspects 37-54, further comprising on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from the incident γ-photon, such that the combination and distribution of signals from a pixel having a known LET responsivity can determine the incident energy of the incident γ-photon.

[0370] 56. A gamma photon counter according to aspect 55, wherein the array of pixels comprises a first subset of pixels having a known LET responsivity and a second subset of pixels, 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 with higher LET but does not detect higher-energy gamma photons with lower LET, wherein the second set of pixels detects both the lower-energy gamma photons with higher LET and the higher-energy gamma photons with lower LET.

[0371] 57. The gamma photon counter according to any one of aspects 33-56, wherein the chip includes a plurality of detectors.

[0372] 58. The gamma photon counter according to aspect 57, wherein each of the plurality of detectors comprises an attenuating material of different thicknesses to allow resolution of incident gamma photons with different energies.

[0373] 59. The gamma photon counter according to aspect 58, wherein the attenuation material is lead, tungsten, bismuth, or iron.

[0374] 60. The gamma photon counter according to aspect 58 or 59, wherein the plurality of detectors are arranged in a vertically stacked manner.

[0375] 61. The γ-photon counter according to aspect 60, wherein each detector is separated from the adjacent detector in the vertical stack by a layer of the attenuating material.

[0376] 62. A γ-photon counter according to aspect 60 or 61, wherein each detector has a fast readout circuit connected to an array of the pixels to allow near-instantaneous detection of the same incident γ-photon passing between two of the plurality of detectors in the vertical stack.

[0377] 63. The gamma photon counter according to aspect 62, wherein each pixel operates asynchronously, wherein each pixel samples the incident gamma photon and transmits the time when the incident gamma photon hits the pixel, the pixel position on the detector, and the signal generated by the gamma photon hitting the pixel.

[0378] 64. The γ-photon counter according to aspect 63, wherein the angular offset of the incident γ-photon transmitted from the detector at the top of the stack to the detector located below in the stack due to Compton scattering can be used to calculate the angle of the incident γ-photon relative to the vertical stack.

[0379] 65. A γ-photon counter according to any one of aspects 60-64, wherein the plurality of detectors are stacked with a stacking 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.

[0380] 66. A γ-photon counter according to any one of aspects 60-65, wherein the vertical stack has a shape parameter 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.

[0381] 67. A gamma photon counter according to aspect 57 or 58, wherein the plurality of detectors are in a planar arrangement in a spatial region to allow for the resolution of incident gamma photons with different energies in the spatial region.

[0382] 68. A gamma photon counter according to any one of aspects 33-67, wherein the chip has a diameter of less than or equal to 1 mm. 2 Surface area.

[0383] 69. A γ-photon counter according to 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.

[0384] 70. The gamma photon counter according to 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 computer, mobile phone or other control device.

[0385] 71. The gamma photon counter according to 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.

[0386] 72. The γ-photon counter according to any one of aspects 33-69, further comprising an off-chip crystal oscillator, wherein the clock signal is directly generated by the off-chip crystal oscillator.

[0387] 73. The gamma photon counter according to 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.

[0388] 74. The gamma photon counter according to aspect 73, wherein the battery is rechargeable.

[0389] 75. The gamma photon counter according to 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, from the plurality of gamma photon count records, the total percentage of total injection activity (%IA / mL) of one or more tumors and one or more organs at risk in a subject per milliliter of tissue.

[0390] 76. A γ-photon counter according to any one of aspects 33-75, wherein the detector further detects electrons generated by γ-photons.

[0391] 77. The gamma photon counter according to aspect 76, wherein the electrons are generated in a subject administering a radiopharmaceutical containing a gamma-emitting radionuclide, in a layer of material positioned between the detector and the subject administering the radiopharmaceutical containing the gamma-emitting radionuclide, or in the silicon of the diode of the detector.

[0392] 78. A gamma photon counter according to any one of aspects 1-77, wherein the gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging.

[0393] 79. The gamma photon counter according to aspect 78, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

[0394] 80. A gamma photon counter according to any one of aspects 1-79, wherein the gamma photons are emitted from alpha particles or beta particles.

[0395] 81. The gamma photon counter according to aspect 80, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

[0396] 82. The gamma photon counter according to aspect 80, wherein the beta-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

[0397] 83. The gamma photon counter according to any one of aspects 1-82, wherein the radionuclide is conjugated with a small molecule, peptide, or antibody.

[0398] 84. A gamma photon counter according to any one of aspects 1-83, wherein the gamma photon counter is attached to a fabric or adhesive patch.

[0399] 85. A gamma photon counter according to any one of aspects 1-84, wherein the gamma photon counter is attached to a wearable structure.

[0400] 86. The gamma photon counter according to aspect 85, wherein the wearable structure is clothing.

[0401] 87. The gamma photon counter according to aspect 86, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves or body armor.

[0402] 88. A gamma photon counter according to any one of aspects 1-87, wherein the gamma photon counter is connected via wires to a power supply, a control source, and a data collection unit.

[0403] 89. The gamma photon counter according to aspect 88, wherein the control source is a field-programmable gate array (FGPA), a computer, a laptop, or a smartphone.

[0404] 90. A gamma photon counter according to any one of aspects 1-89, wherein the gamma photon counting data is wirelessly uploaded to a computer or cloud server.

[0405] 91. A wearable system comprising a plurality of gamma photon counters according to any one of aspects 1-90, the plurality of gamma photon counters being attached to a wearable structure.

[0406] 92. The wearable system according to aspect 91, wherein the wearable structure is clothing or adhesive patch.

[0407] 93. The wearable system according to aspect 92, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

[0408] 94. The wearable system according to aspect 92 or 93, wherein

[0409] A first subset of the plurality of gamma photon counters is arranged on the garment such that, when the garment is worn by a subject, the first subset of the gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject; and

[0410] A second subset of the plurality of gamma photon counters is arranged on the garment such that, when the garment is worn by the subject, the second subset of the gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by organs at risk in the subject.

[0411] 95. The wearable system according to aspect 94, wherein the positioning of each gamma photon counter on the garment is determined based on medical imaging of the subject to determine the location of the tumor in the subject, and the positioning of each gamma photon counter of the second subset on the garment is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

[0412] 96. The wearable system according to 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).

[0413] 97. The wearable system according to any one of aspects 92-96, wherein the plurality of gamma photon counters are arranged in an array on the garment.

[0414] 98. The wearable system according to aspect 92, wherein each of the plurality of gamma photon counters is attached to the subject's skin using the adhesive patch.

[0415] 99. The wearable system according to any one of aspects 91-98, wherein the plurality of gamma photon counters are attached to a first wearable structure and a second wearable structure.

[0416] 100. The wearable system according to aspect 99, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

[0417] 101. The wearable system according to aspect 99, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the head of the subject.

[0418] 102. A computer-implemented method for calculating the total percentage of injected activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject, the computer-implemented steps comprising:

[0419] a) Receive γ-photon counting data from multiple γ-photon counters, wherein each γ-photon counter has a known position;

[0420] b) Receive images of the subject, the images showing the location of the one or more tumors and the one or more organs at risk in the subject, and the location of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk;

[0421] c) Define the boundaries around each tumor and each organ at risk on the image;

[0422] d) Use the images to measure the volume of the one or more tumors and organs at risk;

[0423] e) Map the centroid position of each γ-photon counter onto the image;

[0424] f) Perform distributed point source (DPS) modeling to generate a distribution of gamma photon emission point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) decay based on counts per second (CPS) and 1 / (the distance between the centroid location of the gamma photon counter and the gamma photon emission point source). 2 The related assumptions are as follows: calculating the probability of receiving the γ photons counted by the γ photon counter from a γ photon emission source within the boundary of a specific tumor or organ at risk for each γ photon counter, and the CPS value is attenuated by an empirically derived factor Ω, which takes into account the attenuation and scattering of γ photons in the tissue, and ii) estimating the possible fraction of the counts counted by each γ photon counter corresponding to a specific tumor or organ at risk;

[0425] g) Based on the γ-photon count data from the plurality of counters and the parameter estimates of the possible fractions of the counts corresponding to a specific tumor or organ at risk modeled by the DPS, the Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the total count for each tumor and organ at risk.

[0426] h) Based on the estimated total count of each tumor and at-risk organ, and divided by the volume of the one or more tumors and at-risk organs measured from the image, calculate the total %IA / ml of the one or more tumors and at-risk organs in the subject; and

[0427] i) Display the total %IA / mL of the one or more tumors and the one or more organs at risk in the subject.

[0428] 103. The computer-implemented method according to aspect 102, wherein performing DPS modeling comprises:

[0429] Create DPS model matrix ( W ), which represents the counts per second (CPS) contributed by each tumor or at-risk organ to each of the plurality of gamma photon counters, where the CPS per μC is multiplied by the unknown activity in μC of the total tumor or at-risk organ activity, wherein the DPS model matrix ( W The values ​​in ) are estimated based on knowledge of the location of each tumor and each organ at risk from the images, as well as the known location of each gamma photon counter; and

[0430] The DPS model matrix ( W Decompose into a matrix (β ) and vectors ( α ), wherein the matrix ( β ) represents the score of CPS from a specific tumor or at-risk organ in each gamma photon counter, wherein the score is determined by the vector ( α ) scaled up proportionally, wherein the vector ( α ) is the CPS of μCi activity per injection for each γ-photon counter.

[0431] 104. The computer-implemented method according to aspect 103, wherein the vector α is estimated by performing a DPS titration simulation.

[0432] 105. The computer-implemented method according to aspect 103 or 104, wherein the matrix ( β The initial estimation was made by: i) assuming that each tumor and each organ at risk ingests an equal amount of the radionuclide, wherein the total amount of the radionuclide administered to the subject is known, and ii) allocating the same activity to all the tumors and organs at risk for the estimated possible fraction of the counts corresponding to a particular tumor or organ at risk, counted by each counter.

[0433] 106. The computer-implemented method according to any one of aspects 102-105, further comprising using adaptive Metropolis (AM) optimization, wherein the Gaussian proposal distribution is updated using information accumulated during chain generation using the MCMC algorithm.

[0434] 107. The computer-implemented method according to any one of aspects 102-106 further includes performing iterative optimization by means of methods including gradient descent, least squares minimization, or brute-force global minimization, or combinations thereof.

[0435] 108. A computer-implemented method according to any one of aspects 102-107, wherein the empirical derivation factor Ω is determined by a method comprising the following steps:

[0436] The detected CPS of each gamma photon counter was measured in water at different distances from the gamma photon emission point source;

[0437] The detected CPS of each γ-photon counter was measured in air at different distances from the γ-photon emission point source;

[0438] Based on the differences in CPS detected in water and air at each distance, a nonlinear factor representing the scattering and attenuation of each γ-photon emission point source is derived; and

[0439] The nonlinear factor is used to calculate a unique factor Ω for each gamma photon emission point in the subject based on the distance in the tissue between each gamma photon counter and each gamma photon emission point.

[0440] 109. The computer-implemented method according to any one of aspects 102-108, further comprising segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid location of each gamma photon counter are segmented.

[0441] 110. A computer-implemented method according to any one of aspects 102-109, wherein each of the plurality of gamma photon counters comprises:

[0442] Y2O3-Eu doped phosphors, wherein γ photons incident on the surface of the Y2O3-Eu doped phosphor generate scintillation light in the visible spectrum;

[0443] The detector includes a photodiode;

[0444] An optical fiber, wherein the optical fiber guides the scintillation light generated by the Y2O3-Eu-doped phosphor to the detector, wherein the detector generates a voltage pulse in response to detecting the scintillation light generated by the γ photons;

[0445] A digital counter, coupled to the detector, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to a voltage pulse generated by the detector in response to detecting the scintillation light generated from each gamma photon incident on the surface of the Y₂O₃-Eu-doped phosphor; and

[0446] An opaque material is used to cover the optical fiber, wherein the opaque material shields the optical fiber from visible light emitted by the phosphor other than that doped by the Y2O3-Eu.

[0447] 111. A computer-implemented method according to any one of aspects 102-109, wherein each of the plurality of gamma photon counters comprises:

[0448] A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel comprising a silicon diode, wherein gamma photons incident on the surface of the silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses.

[0449] A unity-gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by the gamma photon is individually buffered by the unity-gain voltage amplifier;

[0450] A differential closed-loop amplifier, wherein a buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential closed-loop amplifier, wherein the voltage gain is preset or can be configured using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified with a fixed, process-invariant gain;

[0451] An inverter chain comprising multiple inverters connected to the amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon;

[0452] A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the silicon diode;

[0453] An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events;

[0454] A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period;

[0455] On-chip or off-chip energy storage devices; and

[0456] A custom digital logic circuit is configured to control voltage and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0457] 112. A computer-implemented method according to any one of aspects 102-109, wherein each of the plurality of gamma photon counters comprises:

[0458] A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel including a pair of silicon diodes, the pair of silicon diodes including a first silicon diode and a second silicon diode, wherein gamma photons incident on the surface of the first silicon diode or the second silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q).p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses.

[0459] A unity-gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a gamma photon is individually buffered by the unity-gain voltage amplifier;

[0460] A differential amplifier, wherein the buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential amplifier;

[0461] A voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets the voltage output of the differential amplifier, wherein the voltage integrator is configured with negative feedback to bootstrap from the output of the differential amplifier to the input of the differential amplifier;

[0462] A pair of level shifters connected to the output of the differential amplifier, wherein the pair of level shifters comprises two level shifters, including a first level shifter that shifts the DC level at the output of the differential amplifier upward to amplify only the voltage pulse from the first diode; and a second level shifter that shifts the DC level at the output of the differential amplifier downward to amplify only the voltage pulse from the second diode, wherein an on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) are used to set the amount by which the DC level is shifted to convert the stored bits into an analog voltage shift;

[0463] An inverter chain comprising a plurality of inverters connected to the amplified and shifted voltage outputs from the pair of level shifters, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon;

[0464] A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the first silicon diode or the second silicon diode;

[0465] An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events;

[0466] A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period;

[0467] On-chip or off-chip energy storage devices; and

[0468] A custom digital logic circuit is configured to control voltage and supply power from the on-chip or off-chip energy storage device to the detector, the digital counter, and the digital clock.

[0469] 113. The computer-implemented method according to aspect 111 or 112, wherein the plurality of gamma photon counters include on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from incident gamma photons, wherein the computer-implemented method further includes calculating the incident energy of the incident gamma photons based on a combination and distribution of signals from pixels having known LET responsivity.

[0470] 114. The computer-implemented method according to aspect 113, wherein the array of pixels comprises a first subset of pixels having a known LET responsivity and a second subset of pixels, 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 with higher LET but does not detect higher-energy gamma photons with lower LET, wherein the second set of pixels detects both the lower-energy gamma photons with higher LET and the higher-energy gamma photons with lower LET.

[0471] 115. A computer-implemented method according to any one of aspects 102-114, wherein the plurality of gamma photon counters comprises a plurality of detectors, wherein each of the plurality of detectors comprises an attenuating material of different thicknesses to allow resolution of incident gamma photons of different energies, wherein the computer-implemented method further comprises using multiphysics simulation to calculate the probability of detecting gamma photons of a specific energy using each of the plurality of detectors to separate the detection counts of each detector by gamma photon energy.

[0472] 116. The computer-implemented method according to aspect 115, wherein the attenuating material is lead, tungsten, bismuth, or iron, wherein the multiphysics simulation is used to calculate the probability of detecting a photon of a certain energy with a detector of a certain thickness of lead, tungsten, or iron.

[0473] 117. The computer-implemented method according to aspect 115 or 116, wherein the plurality of detectors are arranged in a vertically stacked manner.

[0474] 118. The computer-implemented method according to aspect 117, wherein each detector is separated from adjacent detectors in the vertical stack by a layer of the attenuating material.

[0475] 119. A computer-implemented method according to aspect 117 or 118, wherein each detector has a fast readout circuit connected to an array of the pixels to allow near-instantaneous detection of the same incident γ photon passing between two of the plurality of detectors in the vertical stack.

[0476] 120. The computer-implemented method according to aspect 119, wherein each pixel operates asynchronously, wherein each pixel samples the incident γ photon and transmits the time when the incident γ photon hits the pixel, the pixel position on the detector, and the signal generated by the γ photon hitting the pixel.

[0477] 121. The computer-implemented method according to aspect 120 further includes calculating the angle of the incident γ-photon relative to the vertical stack by measuring the angular offset of the incident γ-photon transmitted from the detector at the top of the stack to the detector located below in the stack due to Compton scattering.

[0478] 122. A computer-implemented method according to any one of aspects 117-121, wherein the plurality of detectors are stacked with a stacking 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.

[0479] 123. A computer-implemented method according to any one of aspects 117-122, wherein the vertical stack has a shape parameter 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.

[0480] 124. The computer-implemented method according to aspect 115, wherein the plurality of detectors are in a planar arrangement in a spatial region, wherein the computer-implemented method further includes determining the energy of incident gamma photons in the spatial region.

[0481] 125. A non-transitory computer-readable medium comprising program instructions that, when executed by a processor in a computer, cause the processor to perform the method according to any one of aspects 102-124.

[0482] 126. A kit comprising a non-transitory computer-readable medium as described in aspect 125 and instructions for calculating the percentage of total injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject.

[0483] 127. A system comprising:

[0484] a) A plurality of gamma photon counters, said plurality of gamma photon counters being attached to a wearable structure;

[0485] b) Power supply;

[0486] c) A processor, wherein the processor is programmed to calculate, according to any one of aspects 102-124, the total percentage of injection activity (%IA / mL) of one or more tumors and one or more organs at risk in a subject per milliliter of tissue.

[0487] d) An external data receiving device connected to the processor, wherein the external data receiving device receives the gamma photon counting data from the plurality of gamma photon counters and transmits the gamma photon counting data to the processor; and

[0488] e) A display component that displays %IA / mL of one or more tumors and one or more organs at risk in the subject.

[0489] 128. The system according to aspect 127, wherein the plurality of gamma photon counters are attached to clothing or adhesive patches.

[0490] 129. The system according to aspect 128, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves or body armor.

[0491] 130. The system according to aspect 128 or 129, wherein

[0492] A first subset of the plurality of gamma photon counters is arranged on the garment such that, when the garment is worn by a subject, the first subset of gamma photon counters is capable of monitoring the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset on the garment is determined based on medical imaging of the subject to determine the location of the tumor within the subject; and

[0493] A second subset of the plurality of gamma photon counters is arranged on the garment such that, when the wearable material is worn by the subject, the second subset of the gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset on the garment is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

[0494] 131. The system according to aspect 128, wherein the plurality of gamma photon counters are arranged in an array on the garment.

[0495] 132. The system according to aspect 128, wherein each of the plurality of gamma photon counters is capable of being attached to the skin of a subject using the adhesive patch.

[0496] 133. The system according to aspect 132, wherein

[0497] A first subset of the plurality of gamma photon counters can be attached to the skin of the subject using an adhesive patch, such that the first subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset is determined based on medical imaging of the subject to determine the location of the tumor within the subject; and

[0498] A second subset of the plurality of gamma photon counters is capable of being attached to the subject's skin with an adhesive patch, such that the second subset of gamma photon counters is capable of monitoring the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

[0499] 134. The system according to any one of aspects 127-133, wherein the plurality of gamma photon counters are attached to the first wearable structure and the second wearable structure.

[0500] 135. The system according to aspect 134, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

[0501] 136. The system according to aspect 134, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the head of the subject.

[0502] 137. The system according to 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).

[0503] 138. The system according to any one of aspects 127-137, wherein the power source is an external power source, an internal power source, or a combination thereof.

[0504] 139. The system according to aspect 138, wherein the external power source is an ultrasonic transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radio frequency (RF) transducer.

[0505] 140. The system according to aspect 138, wherein the internal power source comprises a battery, a radioactive nuclide, or a photovoltaic system.

[0506] 141. The system according to any one of aspects 127-140, wherein the power source is used to provide power to the detector.

[0507] 142. The system according to any one of aspects 138 or 139, wherein the external power supply is portable.

[0508] 143. The system according to any one of aspects 127-142, wherein the external data receiving device includes a wireless communication unit.

[0509] 144. The system according to aspect 143, wherein the wireless communication unit utilizes a wireless communication protocol using electromagnetic carrier or ultrasonic waves to receive data from the internal data storage unit.

[0510] 145. The system according to aspect 144, wherein the electromagnetic carrier wave is a radio wave, microwave, or infrared carrier wave.

[0511] 146. The system according to any one of aspects 127-145, wherein the processor is provided by a computer or a handheld device.

[0512] 147. The system according to aspect 146, wherein the handheld device is a mobile phone or a tablet computer.

[0513] 148. The system according to any one of aspects 127-147, wherein the display further displays images of the tumor and organs at risk obtained through medical imaging of the subject.

[0514] 149. The system according to any one of aspects 127-148, wherein the display further displays the centroid position of each γ-photon counter superimposed on the image.

[0515] 150. The system according to any one of aspects 127-149, wherein the display further displays, superimposed on the image, boundary lines surrounding each tumor and organ at risk.

[0516] 151. The system according to any one of aspects 127-150, wherein the display further displays the distribution of gamma photon emission point sources based on the distributed point sources (DPS) superimposed on the image.

[0517] 152. The system according to any one of aspects 127-151, wherein the display further displays labels having information about the tumor and organs at risk superimposed on the image.

[0518] 153. The system according to any one of aspects 127-152, wherein the gamma photon is emitted from a gamma-ray emitted radionuclide suitable for single-photon emission computed tomography (SPECT) imaging.

[0519] 154. The system according to aspect 153, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

[0520] 155. The system according to any one of aspects 127-154, wherein the γ photon is emitted from an alpha particle-emitting radionuclide or a beta particle-emitting radionuclide.

[0521] 156. The system according to aspect 155, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

[0522] 157. The system according to aspect 155, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

[0523] 158. The system according to any one of aspects 127-157, wherein the radionuclide is conjugated with a small molecule, peptide, or antibody.

[0524] 159. A method for measuring tumor uptake of a radiopharmaceutical containing a gamma-emitting radionuclide in a subject using the system according to any one of aspects 127-158, the method comprising:

[0525] Perform medical imaging to identify the location of one or more tumors and one or more organs at risk in the subject;

[0526] A first subset of the plurality of gamma photon counters is positioned on the wearable structure such that the first subset of gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by one or more tumors in the subject;

[0527] A second subset of the plurality of gamma photon counters is positioned on the wearable structure such that the second subset of gamma photon counters can monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by one or more organs in the subject at risk; and

[0528] The total percentage of injected activity (%IA / mL) of the one or more tumors and one or more organs at risk in the subject is calculated per milliliter of tissue according to the computer-implemented method.

[0529] 160. The method according to 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).

[0530] 161. The method according to aspect 159 or 160, wherein the gamma photon is emitted from a gamma-ray emission radionuclide suitable for single-photon emission computed tomography (SPECT) imaging.

[0531] 162. The method according to aspect 161, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

[0532] 163. The method according to any one of aspects 159-162, wherein the γ photon is emitted from an α particle emitting radionuclide or a β particle emitting radionuclide.

[0533] 164. The method according to aspect 163, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

[0534] 165. The method according to aspect 163, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

[0535] 166. The method according to any one of aspects 159-165, wherein the radionuclide is conjugated with a small molecule, peptide, or antibody.

[0536] 167. The method according to any one of aspects 159-166 further includes placing a reference marker on the subject's skin at the planned location for positioning the plurality of gamma photon counters.

[0537] 168. The method according to aspect 167, wherein the reference marker is used for positioning the first subset and the second subset of the plurality of gamma photon counters on the wearable structure.

[0538] 169. The method according to any one of aspects 159-168, wherein the wearable structure is clothing or an adhesive patch.

[0539] 170. The method according to aspect 169, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

[0540] 171. The method according to aspect 169, wherein the reference marker patch is used to locate the first subset and the second subset of the plurality of gamma photon counters by adhering the plurality of gamma photon counters to the skin of the subject using a plurality of adhesive patches.

[0541] 172. The method according to any one of aspects 159-171, wherein the plurality of γ-photon counters are attached to the first wearable structure and the second wearable structure.

[0542] 173. The method according to aspect 172, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

[0543] 174. The method according to aspect 172, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the head of the subject.

[0544] 175. The method according to any one of aspects 159-174, wherein the method is performed during or after administration of the radiopharmaceutical to the subject.

[0545] 176. The method according to aspect 175, wherein the radiopharmaceutical is a radiopharmaceutical, a radioimmunotherapy agent, or a radiopeptide.

[0546] 177. The method according to aspect 176, wherein the radiopharmaceutical is administered to the subject for the treatment of prostate cancer. 177 Lu-PSMA-617 or 225 Ac-PSMA-617.

[0547] It will be apparent to those skilled in the art that various changes and modifications can be made without departing from the spirit or scope of the invention.

[0548] Experimental

[0549] The following embodiments are provided to provide a complete disclosure and description of how to make and use the invention to those skilled in the art, and are not intended to limit the scope of what the inventors consider to be their invention, nor to represent that the following experiments are all or only the experiments performed. Efforts have been made to ensure the accuracy of the figures used (e.g., quantities, temperatures, etc.), but some experimental errors and biases should be taken into account. Unless otherwise stated, parts are parts by weight, molecular weights are weight-average molecular weights, temperatures are in degrees Celsius, and pressures are at or near atmospheric pressure.

[0550] All publications and patent applications cited in this specification are incorporated herein by reference, as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference.

[0551] The invention has been described according to specific embodiments discovered or proposed by the inventors, including preferred modes for practicing the invention. Those skilled in the art will understand that many modifications and alterations can be made to the specific embodiments illustrated in this disclosure without departing from the intended scope of the invention. For example, changes can be made to the underlying DNA sequence without affecting the protein sequence due to codon redundancy. Furthermore, changes can be made to the protein structure without affecting the type or amount of biological action due to considerations of biological functional equivalence. All such modifications are intended to be included within the scope of the appended claims.

[0552] Example 1

[0553] Sparse, uncollimated gamma counting networks for continuous real-time dose reconstruction in radiopharmaceutical therapy

[0554] introduction

[0555] Treatment of widespread metastatic disease in cancer remains an unmet need. Radiation therapy is widely effective when targeted at tumors with adequate doses, ablating them or inhibiting their growth. However, conventional external beam-based methods of delivering radiation therapy to many sites throughout the body can result in excessive doses to normal tissues, ruling out its use in widespread metastatic disease. Radiopharmaceutical therapy (RPT) offers a radically different approach to radiation delivery by attaching a radioactive isotope to a molecule that targets the tumor, selectively irradiating cancer cells throughout the body while protecting most normal tissues. Recently, this has shown promise in metastatic castration-resistant prostate cancer (mCRPC).

[0556] Despite significant progress in androgen inhibitors 2,3 However, mCRPC is almost incurable, and currently accounts for 20% of all prostate cancer deaths. 1 And effective treatment remains an unmet need. 4 In the United States, the incidence of mCPRC is increasing, estimated at 36,100 cases in 2009 and rising to 42,970 cases in 2020. 1 With limited treatment options, patients with mCRPC continue to have significantly poorer survival (approximately 13–30 months). 5 Furthermore, there is an urgent need for additional treatment options to overcome drug resistance mechanisms. Prostate cancer is the best disease to use RPT because the vast majority of patients (85%-90%)... 1 The prostate tissue exhibits elevated levels of prostate-specific membrane antigen (PSMA), a type II transmembrane glutamate carboxypeptidase that is typically absent or weakly expressed in benign prostate tissue. 10 Recently, the FDA approved... 177 Lu-PSMA-617, a beta-particle emission radioligand therapy, is used to treat mCRPC. 10,11,12,13 Subsequent trials showed that, compared to 11.3 months and 3.4 months using current standard of care, [the following treatment was effective]: 177Participants treated with Lu-PSMA-617 experienced improved overall survival of 15.3 months and improved progression-free survival of 8.7 months, respectively. Despite these promising results, patients eventually progressed. Given the known radiation dose and locally controlled dose response from external beam radiotherapy, knowledge of the dose delivered to the tumor is extremely important for tailoring optimal treatment to each patient. However, this remains an unresolved necessity for managing the quality and safety of RPT.

[0557] Similar to the goal of stereotactic ablation radiotherapy, where the radiation dose to the tumor of interest is maximized while the dose to surrounding tissues is minimized, therapeutic RPT aims to maximize tumor uptake of radionuclides while minimizing unwanted dose deposition and toxicity to organs at risk (OARs). For example, in the case of prostate cancer, the OAR consists of: excretory organs (e.g., for small molecules, the kidneys and bladder; for antibodies, the liver), organs that inherently express target receptors (e.g., the kidneys expressing PSMA), and organs expressing target receptors. 1-4 (e.g., bone marrow), or organs temporarily exposed due to activity in the blood. In practice, RPT is administered using standard dosing or a "one-size-fits-all" strategy, such as in... 177 As demonstrated in the Lu-PSMA-617 RPT, 200 mCi is administered every 6 weeks. 177 Lu-PSMA-617, for up to 6 cycles. This treatment strategy ignores the total integral dose delivered to each tumor, as well as the common patient-to-patient heterogeneity that ultimately governs the dose delivered, including (1) varying PSMA expression levels, (2) changes in tumor uptake and ligand retention, (3) daily variations including heart rate, blood flow, and excretion dynamics, and (4) on-target but detumescent toxicity due to the binding of radionuclides to PSMA-expressing OARs. 12,14,15 Furthermore, due to tumor preservation, ligand circulating half-life, and radionuclide half-life, accurate dosing methods benefit from measuring the total integral dose over multiple half-lives of the selected radionuclide. Given these patient-to-patient variability, a uniform dosing approach may deliver suboptimal doses to tumors in some patients and provide greater than acceptable doses to OARs in others. This lack of continuous dosing excludes crucial patient-specific dosing and grading adjustments that could improve clinical outcomes. 48,49 Therefore, continuous dosing over several half-lives and across all grades is extremely important for assessing and optimizing treatment response for each patient (across multiple tumors and OARs). 13,16,17 .

[0558] Single-photon emission computed tomography (SPECT) is currently the most advanced dosimetry technique in radioligand therapy. Despite advancements in SPECT imaging and reconstruction algorithms, this dosimetry method provides only a whole-body snapshot at a single time point, leaving patient-specific continuous dosimetry an unmet need. Due to the lack of widespread availability of SPECT, its long acquisition time, and high cost, performing multiple scans on each patient during treatment is logically impractical. At most one SPECT scan is acquired per treatment cycle due to reimbursement, logistical, and availability challenges, but most commonly, SPECT dosimetry is not performed. For patients utilizing a single scan, the total dose is typically calculated by simply plotting a representative biodistribution curve. 18,19 This is fitted to that point for calculation. However, this is insufficient because the maximum uptake time (t) of metastatic lesions is not considered. max ) and effective half-life (T eff The time required for the dose to become half can change by 50% and 30%, respectively. This uncertainty in dose estimation translates to dose changes exceeding 70% during treatment. 20 .

[0559] Given the limitations and practical constraints of modern dosimetry, a platform for real-time continuous dosimetry is needed to complement current state-of-the-art imaging modalities. Such a platform must meet the following requirements: 1) the ability to reconstruct the percentage of injection activity (%IA / mL) per milliliter of tissue for all tumors and OARs of interest with high accuracy (within 1%IA / mL of the true value); 2) the ability to reconstruct %IA / mL for all tumors and OARs with short acquisition times (relative to biodistribution kinetics); 3) high sensitivity and dynamic range in terms of radioligand activity; 4) non-invasiveness; 5) seamless integration into patients' existing workflows; and 6) easy accessibility and cost-effectiveness for hospitals, patients, and clinicians. Despite efforts to realize such a platform for continuous monitoring of radiopharmaceutical uptake in RPT, previous work has not met all of these requirements, as discussed. 21,22,23,25,26,27,28,29,30 .

[0560] To meet these requirements, this invention proposes a sparse gamma-sensing network and reconstruction algorithm for real-time %IA / mL reconstruction in tumors and OARs, utilizing prior knowledge of patient anatomy (e.g., tumor and OAR locations) relative to the sensor location. The proposed workflow involves using pre-treatment CT (from PET / CT in clinical practice) to identify lesions and OARs that will take up RPT. CT baseline markers are used to annotate the placement of the gamma-sensing probe on the skin. Figure 1AThis allows for prior knowledge of the location and size of all tumors of interest and OARs relative to the probe position. Following RPT administration, the patient is continuously monitored at fine time intervals by placing the gamma photon probe at the desired location. Figure 1B One implementation involves placing the probe tip in a wearable vest worn for 10 minutes per acquisition session. These uncollimated, continuous gamma-photon recordings need to be converted to %IA / mL in all tumors and OARs using a developed model. Biodistribution curves for all tumors and OARs were created, and a comprehensive plot of the total integral dose for each organ was obtained to make further clinical decisions regarding grading schedules, the amount of injection activity, and the use of other cancer treatment options. Figure 1D ).

[0561] This invention uses 177 Lu-PSMA-617 demonstrated a preclinical proof-of-concept for the system, algorithm, and workflow. Initially, it used four vials containing varying amounts of active ingredients. 177 A custom-designed water phantom of Lu-PSMA-617 was used to validate the proposed system. The system was then validated in four different mouse models carrying two or three tumors at varying locations, and derived from the administration of Lu-PSMA-617. 177 Lu-PSMA-617 PC3-pip or PC3-flu prostate cancer cell lines. Activity was successfully reconstructed for each tumor, kidney, and bladder at 10 min, 6 h, 12 h, 24 h, and 48 h post-injection. The %IA / mL reconstruction of all tumors and OAR at each time point was highly linear with activity from small animal SPECT / CT.

[0562] result

[0563] The developed uncollimated fiber-optic-based gamma-photon sensor and 177 Lu-PSMA-617 exhibits highly linear activity. A custom gamma-photon counter was developed by coupling a high-quantum-efficiency Y₂O₃-Eu-doped phosphor to an avalanche photodiode (APD) using optical fiber. The APD (Excelitas, SPCM-AQ4C) demonstrates high-efficiency detection at the phosphor's peak scintillation wavelength (610 nm), enabling a large dynamic range and a detection sensitivity of counts per second (CPS). Since optical fibers are susceptible to visible light not emitted by the phosphor, a length of 500 μm black optical adhesive tape with an optical density (OD) of 4 was used to cover the fiber. No lead was used on these fibers, ensuring that the incident gamma rays incident on the sensor surface were completely uncollimated. Figure 1CThe γ incident on the phosphor surface is scintillated into 610 nm red light, which generates an exponentially decaying voltage pulse at the APD sensing node. This pulse is buffered, fed through a comparator, and is now fed into a 1-bit 4.5 V to 3.3 V level shifter with a 50 ohm input impedance. The 3.3 V voltage pulse is then counted at a sampling frequency of 150 MHz using a field-programmable gate array (Opal Kelly XEM6010) with multiple digital counters. Figure 2A Using a custom Python interface, the accumulated incoming count is relayed to the PC every second. Eight probes were developed for this study.

[0564] The recommended usage is 0.5g in 1 mL. Ci to 3 mCi 177 A 2-fold dilution of Lu-PSMA-617 was used to evaluate the sensitivity and dynamic range of each developed probe. The developed system exhibited high linearity within this range, with the average CPS varying from 1.38 CPS to 11,055 CPS, and R... 2 The value is 0.999 (Figure 7). Because there can be variations in sensitivity to γ ​​between probes, a custom-made 3D-printed scaffold is manufactured. Figure 8A ) to keep the probe and the housing 177 The Lu-PSMA-617 vials were used to assist in probe calibration. The response of each probe to 50 µCi, 100 µCi, and 200 µCi vials was recorded, and a linear fit without intercept was applied to the resulting CPS. The change in slope or sensitivity (CPS / µCi) for each probe was recorded at [data missing]. Figure 8B As shown in the figure, the sensitivity of each probe is normalized relative to probe 1.

[0565] Modeling the tumor and OAR as a bounded, uniform distribution of gamma-photon emission point sources allows for the reconstruction of their %IA / mL. Given prior knowledge of the tumor and OAR locations, N Recordings from uncollimated gamma counting probes and the positions of these probes relative to the tumor and OAR ( Figure 2A A mathematical framework for %IA / mL reconstruction was developed. The CPS recorded by each counter was decomposed into an unknown matrix ( W Multiply by a vector containing the unknown total tumor or OAR activity in µCi, i.e., the quantity of interest ( Figure 2B ).matrix W Indicates from M Each tumor or OAR contributes to N CPS per µCi for each of the γ-photon counting probes. Due to WSince both tumor and OAR activity are unknown, an approximation of one is needed to estimate the other. Furthermore, prior knowledge of the tumor, OAR, and sensor location is required to estimate the matrix. W .matrix W It can be further decomposed into matrices β sum vector α .matrix β This indicates the probability that the probe's CPS originates from a specific tumor or OAR. β It has the capability to "unmix" uncollimated gamma counts. Once the CPS fraction for each probe contributed by each tumor or OAR is known, a vector is used. α These probabilities are scaled down to the CPS per μCi seen at each detector in each tumor and OAR.

[0566] Estimated matrix W Involves estimating the matrix separately β sum vector α Matrix estimation was performed using pre-therapeutic CT scans (from PET / CT scans within the clinical workflow). β From CT scans, all tumor and OAR boundaries, as well as sensor locations, can be segmented. These boundaries serve as input to a custom-developed simulation framework. The tumor and OAR boundaries are used to uniformly distribute gamma emission point sources within them, creating a distributed point source (DPS) model for each tumor and OAR. Tumors and OARs are initialized to have the same activity encoded by the number of point sources. This is based on a typical 1 / d... 2 The CPS decays with distance (d), and the probability of a specific γ-photon counting probe receiving a count from a specific tumor or OAR is calculated by tracking how many photons are detected from each of the tumor and OAR by a specific probe and dividing that value by the total number of photons detected by that specific probe. Figure 2C In clinical proportional models, both attenuation and scattering play significant roles in the counts detected at each probe location. With this in mind, the aforementioned probability can be scaled using attenuation and scattering factors that are functions of the depth of the point source in the tissue. These attenuation and scattering factors can be empirically derived by acquiring each gamma counter and characterizing its counts per second (CPS) detected at depths far from the point source of the utilized radioligand in water. This sweep is repeated in air, and the factor difference between the two curves at each distance is estimated, representing a nonlinear function of the attenuation and scattering factors as a function of distance. Based on the distance in the tissue from each detector to each point source in the DPS model, a unique attenuation and scattering factor can be assigned to each source. αThe sensitivity was estimated using titration simulations using a DPS model. Due to variations in the manufacturing process, each probe exhibits slightly different sensitivities in CPS / µCi, which were measured using the experimental titration shown in Figure 8. The DPS model for the titration experiment was created by extracting the vial boundaries from the CT and distributing point sources within these boundaries. Figures 9A-9C The DPS model also provides certain CPS / in the simulation. Ci ( Figure 9D The ratio between the experimental and DPS model probe sensitivities was used to scale the simulated CPS to the experimental CPS. This is a linear scaling factor because the nonlinearity of the system stems from the relationship between flux and distance, as well as the shape of the tumor and the OAR, and both of these factors are... β The probability is considered in the definition.

[0567] Given α and β And therefore given matrix W Approximate values ​​are obtained using a Bayesian method to approximate total tumor and OAR activity. Due to the sparsity of the inverse problem, the matrix... W Some weight estimates may contain inaccuracies. The optimization technique used here employs a Markov Chain Monte Carlo (MCMC) method to explore the solution space of activity, which gives the best representation of the distribution of γCPS of the experimentally measured records, rather than simply minimizing the error between the predicted CPS and the recorded CPS. All tumor and OAR activity guesses are initialized to the same activity, and MCMC runs for 100,000 iterations or until convergence. MCMC provides the probability density distribution of the total tumor activity guesses, allowing visualization of the most probable solution space and uncertainties in the estimation. 51 .

[0568] The proposed system allows for the reactivation of spatially approximate 1 mL phantoms with a wide range of activities. To initially validate the workflow shown in Figure 2, a water phantom experiment was conducted. A custom-designed 3D-printed ABS tank was constructed with slots on the side for gamma probes and filled with water. A sealing cap was placed on top of the tank, which had features for filling with varying concentrations of [unspecified substance / material]. 177 The hole in a 1 mL eppendorf vial of Lu-PSMA-617. Figure 3A An experimental water tank with eight gamma probes surrounding its perimeter is shown. To test the ability of the developed sensing network and algorithm to reconstruct the activity in each vial, two-minute recordings were obtained from 14 different locations spaced apart around the perimeter of the water tank containing four different activity vials, as shown. Figure 3B As shown.

[0569] The convergence solution of the DPS model after recording with all 14 gamma photon probes and the simulated CPS at each sensor surface. Figure 3C As shown in the figure. The predicted activity is compared with the convergence of each sensor added to the periphery. Figure 3D As shown in the diagram, after adding sensors 1-3 around the periphery (e.g., the YZ plane), the predicted activities of vials 1 and 2 converge to the correct solution. In contrast, the predicted activities of vials 3 and 4 are close, but more information about the regional γ flux is needed for a more accurate estimate. Because vials 3 and 4 are closely spaced, the algorithm benefits from counters whose faces point in different plane directions to distinguish which of the two vials has higher activity uptake. When counters 4-8 are added in the same plane, the predicted activities of both vials 1 and 2 oscillate between the two true values ​​of the vials because the inverse problem has multiple solutions. When counters 9-14 are added in different planes (e.g., the XZ plane), the activity converges.

[0570] When MCMC converges to a solution 177 The input probability distribution of Lu-PSMA-617 activity was modulated until the predicted CPS distribution matched well with the actual experimental CPS distribution. N The probability density functions for updating the vial activity of vials with 4, 10, and 14 sensors are in Figure 3F As shown in the figure, and the trends discussed are reflected in these distributions, where vials 3 and 4 are only added when the γ sensor facing the other plane is added ( N >8) Only then did it converge to the true solution. The predicted CPS matched well with the experimental average CPS from each of the 14 counter positions, such as Figure 3E As shown, the ability of the developed system to reconstruct the average activity of a 1 mL phantom in water at centimeter-level depth intervals and in sub-centimeter-level spatial separation was successfully demonstrated.

[0571] The designed network and algorithm can be seamlessly adapted to predict %IA / mL of tumors and OAR in in vivo models. To demonstrate the effectiveness of the proposed system in monitoring the biodistribution of radiopharmaceuticals, the sparse gamma counter dose reconstruction method was validated in four different mouse models of PSMA+PC3-pip and PSMA-PC3-flu human prostate cancer cell lines with varying locations. M1 had a PC3-pip tumor on its left flank and a PC3-flu tumor on its right flank. M2 had PC3-pip tumors on both its left and right flanks. M3 had PC3-pip tumors on its left flank and right back, and a PC3-flu tumor on its right flank. M4 had PC3-pip tumors on its left flank, right flank, and right back. Each of the four mouse models was placed on a custom-designed 3D-printed scaffold with grooves to maintain the fixed and consistent placement of the gamma counter. Each mouse was injected with approximately 650 μCi of gamma counters. 177 Lu-PSMA-617 was used, with γ-ray counting recorded for 10 minutes at 0, 6, 12, 24, and 48 hours post-injection. Approximately 1 hour before each γ-ray recording, each mouse was injected with 200 µL of CT contrast agent (Medilumine Fenestra LC) to allow SPECT / CT imaging and tumor and OAR delineation. After each recording, the mice were held in a custom-designed 3D-printed scaffold for SPECT / CT imaging. CT scans using the contrast agent enabled segmentation of the tumor, kidney, and bladder across time points, as well as annotation of γ-ray probe locations, since the pores in the scaffold were visible on the CT scan. Tumor and OAR boundaries were delineated on CT and converted to a DPS model. MCMC was run on this model to predict the probability density distribution of each of the tumor, kidney, and bladder activities until they converged with CPS measurements. The mouse model, sensor locations, and overall workflow are summarized in [details omitted]. Figure 4A middle.

[0572] Experimental setup for mouse placement and anesthesia, sensor placement, anesthesia in SPECT / CT, and the resulting SPECT scan with visible probe placement. Figure 4B As shown in the diagram, the peripheral gamma probe is not placed directly on the tumor. Instead, the probe is positioned between the tumor and the OAR to obtain... β A good approximation of β is the crosstalk count between multiple organs. Taking advantage of recording in three dimensions, the probe, with its sensing surface on the top plane in a top-down view, is suspended above the flank tumor and kidney / bladder, allowing for the separation of activity between tumors or OARs that are spatially difficult to distinguish or are very close in %IA / mL.

[0573] The in vivo DPS model solution qualitatively matches well with changes in SPECT / CT scans across time points. As an example, in mouse 4 (M4), changes in SPECT / CT scans at all time points... 177 The true activity distribution of Lu-PSMA-617 is shown in Figure 5A In order to estimate activity at each time point, CT scans were used to segment sensor locations across all mouse models, as well as tumors, kidneys, bladders, and the remainder of the body (or background uptake) (e.g., Figure 5B CT scan of M4 6 hours post-injection. From these boundaries, a DPS model was generated, in which all segmented tumors and organs were initialized to the same activity ( Figure 5C As MCMC optimization converged, the activity distribution reached its true value, primarily in the three PC3-pip tumors at the 6-hour post-injection timepoint of M4. The convergent DPS model for all timepoints... Figure 5C As shown, and qualitatively well matched with the %IA / mL intensity from SPECT / CT.

[0574] If the raw, uncollimated gamma recordings are used alone without applying the unmixing and scaling procedures outlined in Figures 2 and 5, convergence to the correct solution is not observed due to significant crosstalk between probes. Real-time trends in the CPS of each probe monitoring M4 are shown in Figure 13 for reference. The temporal CPS of each probe varies considerably due to crosstalk from the CPS of various tumors and OARs. For example, probe 4, closest to the right posterior PC3-pip tumor of M4, maintains the second-highest CPS reading over time, while probe 8, similarly hovering above the right posterior PC3-pip tumor, is one of the highest CPS records initially but becomes one of the lowest over time. This is likely due to cross-contamination with the kidneys and bladder at very early time points, which, if measured without this consideration, would lead to an overestimation of activity in the right posterior tumor at the earliest time points. Similarly, all CPS traces are higher than those if a probe were to measure only its closest tumor or OAR.

[0575] The proposed system accurately tracks the biodistribution of tumors and extensively varied OARs in mice with different tumor locations and PSMA expression levels, where %IA / mL and total tumor activity predictions are highly linear with state-of-the-art SPECT / CT across time points. Figure 7AThe %IA / mL of PSMA+ PC3-pip tumor reconstruction in all mice (M1-M4) is shown in -7D. It is evident that even among genetically identical mice with tumors derived from the same cell culture, there were significant differences in both the absolute magnitude of tumor radioligand uptake and the relative trend of radioligand uptake over time. M1 had only one PC3-pip tumor, which peaked at approximately 6 hours post-injection and then plateaued at subsequent time points. The two PC3-pip tumors in M2 showed similar absolute uptake, but the tumor on the right flank peaked at approximately 12 hours, while the tumor on the left flank peaked at approximately 6 hours. The two PC3-pip tumors in M3 showed similar absolute uptake during the first three time points, but after peak uptake at 12 hours post-injection, radiopharmaceutical clearance occurred much faster in the left flank tumor than in the right back tumor. M4 had three PC3-pip tumors, all of which showed peak uptake immediately post-injection. Although the percentage of tumors in the right back stabilized quickly after peaking, the percentage of tumors in the right flank decreased significantly before stabilizing, and the percentage of tumors in the left flank decreased monotonically.

[0576] The %IA / mL reconstructed values ​​of the two PSMA-PC3-flu tumors on the right flank of M1 and M3 peaked immediately after injection. Both tumors exhibited uptake slightly above 1%IA / mL, followed by an exponential decline thereafter. Figure 6E The kidneys of M1-M4 showed variable uptake immediately after injection, ranging between 7% and 12% IA / mL, but similar to PC3-flu tumors, the %IA / mL index decreased to very small absolute values ​​for the remaining time points. Figure 6F The bladders of M1-M4 mice immediately after injection had a large %IA / mL, varying between 50% and 160% %IA / mL. Subsequently, the bladder %IA / mL of all mice also decreased exponentially. Figure 6G ).

[0577] The %IA / mL of reconstructed PC3-pip tumors, PC3-flu tumors, kidneys, and bladders was compared with the %IA / mL from SPECT / CT at 10 minutes, 6 hours, 12 hours, 24 hours, and 48 hours post-injection. This involved %IA / mL of 90 individual tumors or OARs reconstructed at different time points. The relationship between these two quantities was highly linear, with R0... 2=0.994. The linear relationship between the proposed model and SPECT / CT is given by the predicted %IA / mL = 0.91 (%IA / mL SPECT / CT), where the Pearson correlation coefficient r is 0.9975, indicating that the mapping from the proposed model to SPECT / CT is close to 1:1. This linear relationship applies to a large dynamic range in vivo from 0.1% to 160% in %IA / mL (Figure 7H). Similarly, the total tumor activity reconstructed from the proposed model and SPECT / CT is highly linear, where R 2 =0.991. Since this is the value initially reconstructed in the mathematical formula for the inverse problem, the linear relationship is even closer to a 1:1 mapping from SPECT / CT, described by the predicted total tumor activity = 0.96 (total tumor activity SPECT / CT), where the Pearson correlation coefficient r is 0.9982. This mapping applies to in vivo ranges from <1 C to 400 Total tumor and OAR activity of Ci (Figure 7I).

[0578] When bladder %IA / g <1%, the relative error in %IA / mL for bladder estimation is slightly higher, but this is due to small inaccuracies in low-activity uptake in a very small volume organ in mice. According to Figure 7I, the total bladder tumor activity at these %IA / mL levels is <3. Ci, where model predictions <5 However, since the volume of a mouse bladder is approximately 0.3 mL, the error is amplified when estimating %IA / mL. Within this range of %IA / mL, the absolute error is between 1 and 3. The difference is on the order of Ci, and therefore not clinically significant.

[0579] 4. Discussion

[0580] Molecularly targeted reactive tumor therapy (RPT) against PSMA offers a novel approach for patients with mCRPC, but RPT is ultimately limited by detumescent toxicity due to the inability to predict dose distribution a priori. The key to successful RPT lies in a relatively simple proposition: deliver a high dose to the tumor and a low dose to the ozone layer (OAR). 177 Lu's RPT is transforming prostate cancer, particularly in VISION, a recent finding in metastatic patients. 42 and TheraP 12,13 Positive results from the trial demonstrated a survival benefit, and trials are currently underway in non-metastatic patients. 14 .

[0581] Currently, application 177Patients receiving Lu-PSMA-617 therapy receive at most a single SPECT / CT image within approximately 24 hours post-injection. Multi-timepoint SPECT for continuous dosimetry is necessary to observe the full dose distribution and total integrated dose measurement of TRT. 45 However, this remains a major logistical challenge and is almost universally infeasible outside of trials. Compared to conventional systems, modern SPECT / CT machines, including the Veriton multi-CZT detector... 46 and GE StarGuide SPECT / CT 47 The system demonstrates higher spatial resolution and reduced acquisition time. Such systems show promise, but challenges remain regarding cost and the complex logistics involved in scanning patients at multiple optimal post-injection time points. Furthermore, the ultimate goal of RPT is widespread distribution to communities where specialized SPECT / CT services may not be available.

[0582] In addition to being state-of-the-art, Cerenkov luminescence imaging CLI has been used in recent preclinical and clinical studies for long-term monitoring of uptake due to its short acquisition time and accessibility. Cerenkov luminescence has a limited range in tissues because it images for visible light, which can lead to increased scattering, low localization specificity, poor sensitivity to less active lesions, and suboptimal detection of deeper lesions commonly found in RPT. 21,22,23,24 The "MD PHD" platform based on a vest 29 SPECT / CT is still required and has only been demonstrated in Monte Carlo simulations. WIDMApp has been used recently. 30 Measurement 131 The work on thyroid treatment showed promise, but this work was again demonstrated only in Monte Carlo simulations without phantoms or in vivo validation. 131 I-type thyroid treatment also utilizes photon detection with greater gamma flux and higher energy. Other fiber-optic dosimetry-based methods focus on external beam radiotherapy (EBRT), where significantly higher gamma flux, larger detection areas are preferred, and the developed counters have much lower sensitivity. 31,32,33,34,35,36 MOSFET 37,38 Calorimeter 39,41 And competing scintillator-based detection methods also need to be more... 177The Lu-PSMA-617 therapy exhibits a much higher gamma flux, but also suffers from voltage offset drift, sensitivity drift over time, low sensitivity, and scintillator afterglow in the case of scintillator-based detectors. To date, existing work on portable counting systems has not enabled long-term monitoring platforms for tumors and OARs, nor has it demonstrated experimental versatility in phantoms and in vivo. 25,26,27,28 .

[0583] In this work, the present invention demonstrates a best-in-class sparse gamma counting method for non-invasive reconstruction of %IA / mL of multiple tumors and OARs in vivo without requiring a single SPECT / CT measurement. The system was validated at different levels and as a complete unit. (1) To verify the ability of the gamma counter to linearly track radiopharmaceutical activity, titration was performed using a probe, demonstrating a range from 0.5 in a 5-minute acquisition time. A wide linear dynamic range of Ci to 3 mCi (Fig. 7). (2) The probe shows an appropriate trade-off with distance, demonstrating performance even at distances of... 177 Significant CPS records were also observed at 3 cm from the Lu source (Fig. 10). (3) The ability of the developed DPS model to simulate distance trade-offs for small bottle-shaped objects was tested by running this distance sweep in the simulation. The relative decrease in CPS with distance matched very well between the DPS model and the experimental records (Fig. 10). (4) The ability of the algorithm to reconstruct activity in tumors of arbitrary shapes was tested by dissecting PC3-pip tumors with low uptake and measuring their activity with a single γ-photon counting probe. The predicted values ​​based on the DPS model and reconstruction method were in good agreement with both ex vivo γ-count and SPECT / CT measurements (Fig. 11). (5) The proposed model reconstructs the hybrid matrix. W The capability was verified using a custom-made water model containing four small vials of unknown activity. Real-world experiments. W and reconstruction W The models were in good agreement with each other (Fig. 12). (6) The proposed model then showed a high degree of linearity with both %IA / mL and total tumor activity, as demonstrated in both the custom-designed aquatic model (Fig. 3) and four different in vivo human prostate cancer mouse models (Fig. 6).

[0584] This allows clinicians to create numerous patient-specific snapshots of radioligand uptake in tumors and OARs, along with associated probability density functions. The probability density function helps characterize uncertainties in reconstruction, enabling informed decisions to balance tumor ablation and OAR toxicity levels (Figure 6). Because a sparse gamma-sensing network relays real-time gamma counts from each probe, these counts can be used for real-time reconstruction at %IA / mL if closer monitoring of biodistribution at earlier time points is desired (Figure 5). It should be noted that tissue attenuation is negligible for the depth of water and tissue used in phantoms and in vivo experiments. During full-scale procedures in patients, mass attenuation factors must be considered based on CT scans, and the detection of isotopic emissions from each probe as a function of distance within the tissue must be characterized. Both factors will slightly adjust for the probability in the beta used in reconstruction.

[0585] Besides their accuracy, current sparse gamma counting networks and algorithms represent a significant advancement in... 177 Lu-PSMA-617 is an affordable alternative for lower-cost, more readily available, and faster acquisition of %IA / mL reconstruction during treatment (approximately $20,000, compared to SPECT / CT systems). 50 (Prices range from $500,000 to $3,000,000). This significantly cheaper imaging modality will allow hospitals and clinics to expand their therapeutic capabilities for mCRPC, where previously installing conventional SPECT / CT systems might have been unavailable and prohibitively expensive. The ease of repeating measurements using the developed sparse gamma counting system can open up new imaging workflows that track patient therapy when conventional imaging may be impractical or too costly, and provide sufficient clinical information for high-end SPECT / CT scanners.

[0586] This invention successfully demonstrated the functionality of the proposed system in a small animal model of human prostate cancer. It is foreseeable that the proposed system can be used for personalized RPT, significantly improving the overall safety and efficacy of treatment through safe dose management. The system's low cost, high accessibility, accuracy, and rapid acquisition time allow for its use... 177 Continuous dose determination measurements were performed over multiple half-lives of Lu-PSMA-617 radioligand therapy and between fractionated treatments.

[0587] method

[0588] Optical front-end design

[0589] Y₂O₃-Eu-doped phosphors (Sigma Aldrich, 756490) were used to convert incident γ-photon scintillation into 610 nm red light. 0.25 g of the phosphor was compacted to a thickness of 500 µm to eliminate air gaps and increase density, thereby increasing the mass decay coefficient. 28 The phosphor is compacted within a cylindrical housing with an inner diameter of 2.5 mm, which is 3D printed. The probe utilizes a 200 µm core optogenetic patch cable (THORLABS, M104L01) with a 2.5 mm ceramic ferrule and a length of 1 meter to facilitate movement around the lesion of interest. Figure 1C The image shows a custom-designed probe based on a...

Claims

1. A gamma photon counter, comprising: Y2O3-Eu doped phosphors, wherein γ photons incident on the surface of the Y2O3-Eu doped phosphor generate scintillation light in the visible spectrum; The detector includes 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 generates a voltage pulse in response to detecting the scintillation light generated by the γ photons; A digital counter coupled to the detector, wherein the digital counter counts γ-photon detection events, wherein each γ-photon detection event corresponds to a voltage pulse generated by the detector in response to detecting the scintillation light generated from each γ-photon incident on the surface of the Y2O3-Eu-doped phosphor; and An opaque material is used to cover the optical fiber, wherein the opaque material shields the optical fiber from visible light emitted by the phosphor other than that doped by the Y2O3-Eu.

2. The γ-photon counter according to claim 1, wherein the photodiode is an avalanche photodiode (APD).

3. The γ-photon counter according to claim 2, wherein the APD is a silicon APD.

4. The γ-photon counter according to claim 1, wherein the photodiode is a single-photon avalanche diode (SPAD).

5. The γ-photon counter according to any one of claims 1-4, wherein the detector further comprises a plurality of power supplies to control circuit cooling, quenching and reset, and high-voltage bias.

6. The gamma photon counter of claim 5, wherein the plurality of power supplies includes a 2-volt power supply for controlling the cooling of the circuit, a 5-volt power supply for controlling the quenching and reset, and a 30-volt power supply for controlling the high-voltage bias.

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

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

9. The γ-photon counter according to claim 8, wherein the opaque material is a black light-absorbing material.

10. The γ-photon counter according to claim 9, wherein the black light-absorbing material is black optical tape.

11. The γ-photon counter according to any one of claims 1-10, wherein the flashing light is red visible light.

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

13. The γ-photon counter according to any one of claims 1-12, wherein the incident γ-photons arriving at the surface of the detector are uncollimated.

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

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

16. The gamma photon counter according to any one of claims 1-16, further comprising a clock configured to generate a clock signal, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period.

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

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

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

20. The gamma photon counter according to 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 of a plurality of gamma 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, from the plurality of gamma photon count records, the total percentage of total injection activity (%IA / mL) of one or more tumors and one or more organs at risk in the subject per milliliter of tissue.

22. The gamma photon counter according to any one of claims 1-21, wherein the gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging.

23. The gamma photon counter according to claim 22, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

24. The γ-photon counter according to any one of claims 1-23, wherein the γ-photons are emitted from α-particle-emitting radionuclides or β-particle-emitting radionuclides.

25. The gamma photon counter according to claim 24, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

26. The γ-photon counter according to claim 24, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

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

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

29. The gamma photon counter according to 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, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

32. The γ-photon counter according to any one of claims 1-31, wherein the γ-photon counter has a diameter of 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 includes a reverse-biased diode, wherein gamma photons incident on the surface of the reverse-biased diode generate voltage pulses across the reverse-biased diode; A digital counter coupled to the detector, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse across the diode generated by each gamma photon incident on the surface of the reverse bias diode; An on-chip memory configured to store multiple γ-photon count records of multiple γ-photon detection events; A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period; and A custom digital logic circuit is provided on the chip, wherein the custom digital logic circuit is configured to control voltage and supply power to the detector, the digital counter, and the digital clock from on-chip or off-chip energy storage devices.

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

35. The gamma photon counter of claim 34, further comprising a voltage buffer disposed in the circuit between the reverse bias diode and the voltage amplifier.

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

37. A gamma photon counter, comprising: A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel comprising a silicon diode, wherein gamma photons incident on the surface of the silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses. A unity-gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by the gamma photon is individually buffered by the unity-gain voltage amplifier; A differential closed-loop amplifier, wherein a buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential closed-loop amplifier, wherein the voltage gain is preset or can be configured using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified with a fixed, process-invariant gain; An inverter chain comprising multiple inverters connected to the amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon; A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the silicon diode; An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events; A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period; On-chip or off-chip energy storage devices; and A custom digital logic circuit is configured to control voltage 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, comprising an array of pixels, each pixel including a pair of silicon diodes, the pair of silicon diodes including a first silicon diode and a second silicon diode, wherein gamma photons incident on the surface of the first silicon diode or the second silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses. A unity-gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a gamma photon is individually buffered by the unity-gain voltage amplifier; A differential amplifier, wherein the buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential amplifier; A voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets the voltage output of the differential amplifier, wherein the voltage integrator is configured with negative feedback to bootstrap from the output of the differential amplifier to the input of the differential amplifier; A pair of level shifters connected to the output of the differential amplifier, wherein the pair of level shifters includes two level shifters, the two level shifters including a first level shifter that shifts the DC level at the output of the differential amplifier upward to amplify only the voltage pulse from the first diode; A second level shifter shifts the DC level at the output of the differential amplifier down to amplify only the voltage pulse from the second diode, wherein an on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) are used to set the amount by which the DC level is shifted to convert the stored bits into an analog voltage shift. An inverter chain comprising a plurality of inverters connected to the amplified and shifted voltage outputs from the pair of level shifters, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon; A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the first silicon diode or the second silicon diode; An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events; A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period; On-chip or off-chip energy storage devices; and A custom digital logic circuit is configured to control voltage 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 according to claim 37 or 38, wherein the silicon diode is reverse biased or has zero voltage bias.

40. The γ-photon counter according to any one of claims 37-39, wherein the sensitivity of the detector is optimized by reducing the capacitance of the silicon diode.

41. The γ-photon counter according to any one of claims 33-40, wherein the diode size is 0.1 µm to 0.5 µm x 0.1 µm to 0.5 µm or 0.5 µm to 1 µm x 0.5 µm to 1 µm.

42. The γ-photon counter according to any one of claims 33-41, wherein the diode size is the smallest size that can be used in a complementary metal-oxide-semiconductor (CMOS) process.

43. The γ-photon counter according to any one of claims 37-42, wherein the detector is optimized by a trade-off between pixel fill factor and sensitivity.

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

45. The γ-photon counter according to any one of claims 37-42, wherein the detector is optimized to improve the fill factor with a compromise in sensitivity.

46. ​​The gamma photon counter of claim 45, wherein the diode size is 1.5 µm to 3 µm x 1.5 µm to 3 µm, 3 µm to 10 µm x 3 µm to 10 µm, or 10 µm to 50 µm x 10 µm to 50 µm.

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

48. The gamma photon counter according to claim 47, wherein the polygon shape is a triangle, square, rectangle, pentagon, hexagon, octagon, rhombus or parallelogram.

49. The γ-photon counter according to claim 47, wherein the curved shape is circular, semi-circular, elliptical, spherical or cylindrical.

50. The γ-photon counter according to any one of claims 47-49, wherein the detector has a side with a length ranging from 0.1 µm to 50 µm.

51. The γ-photon counter according to any one of claims 37-50, wherein the pixels in the array of pixels operate asynchronously.

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

53. The γ-photon counter according to claim 52, wherein the Compton scattering material comprises lead, tungsten, or bismuth.

54. The γ-photon counter according to 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 γ-photon counter according to any one of claims 37-54, further comprising on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from the incident γ-photon, such that the combination and distribution of signals from pixels having a known LET responsivity can determine the incident energy of the incident γ-photon.

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

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

58. The gamma photon counter of claim 57, wherein each of the plurality of detectors comprises an attenuating material of different thicknesses to allow resolution of incident gamma photons with different energies.

59. The gamma photon counter according to claim 58, wherein the attenuation material is lead, tungsten, bismuth, or iron.

60. The gamma photon counter according to claim 58 or 59, wherein the plurality of detectors are arranged in a vertically stacked configuration.

61. The γ-photon counter of claim 60, wherein each detector is separated from the adjacent detector in the vertical stack by a layer of the attenuating material.

62. The γ-photon counter of claim 60 or 61, wherein each detector has a fast readout circuit connected to an array of the pixels to allow near-instantaneous detection of the same incident γ-photon passing between two detectors of the plurality of detectors 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 the time when the incident gamma photon hits the pixel, the pixel position on the detector, and the signal generated by the gamma photon hitting the pixel.

64. The γ-photon counter of claim 63, wherein the angular offset of the incident γ-photon transmitted from the detector at the top of the stack to the detector located below in the stack due to Compton scattering can be used to calculate the angle of the incident γ-photon relative to the vertical stack.

65. The γ-photon counter according to any one of claims 60-64, wherein the plurality of detectors are stacked with a stacking 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 γ-photon counter according to any one of claims 60-65, wherein the vertical stack has a shape parameter 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 according to claim 57 or 58, wherein the plurality of detectors are in a planar arrangement in a spatial region to allow for the resolution of incident gamma photons with different energies in the spatial region.

68. The γ-photon counter according to any one of claims 33-67, wherein the chip has a diameter of less than or equal to 1 mm. 2 Surface area.

69. The γ-photon counter according to 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 γ-photon counter according to 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 computer, mobile 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 γ-photon counter according to any one of claims 33-69, further comprising an off-chip crystal oscillator, wherein the clock signal is directly generated by the off-chip crystal oscillator.

73. The gamma photon counter according to 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 according to 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, from the plurality of gamma photon count records, the total injection activity percentage (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in the subject.

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

77. The gamma photon counter of claim 76, wherein the electrons are generated in a subject administering a radiopharmaceutical containing a gamma-emitting radionuclide, in a layer of material positioned between the detector and the subject administering the radiopharmaceutical containing the gamma-emitting radionuclide, or in silicon of the diode of the detector.

78. The gamma photon counter according to any one of claims 1-77, wherein the gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging.

79. The gamma photon counter according to claim 78, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

80. The γ-photon counter according to any one of claims 1-79, wherein the γ-photons are emitted from α-particle-emitting radionuclides or β-particle-emitting radionuclides.

81. The gamma photon counter according to claim 80, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

82. The γ-photon counter according to claim 80, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

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

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

85. The gamma photon counter according to 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, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

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

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

90. The gamma photon counter according to any one of claims 1-89, wherein the gamma photon counting data is wirelessly uploaded to a computer or cloud server.

91. A wearable system comprising a plurality of gamma photon counters according to any one of claims 1-90, the plurality of gamma photon counters being attached to a wearable structure.

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

93. The wearable system of claim 92, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

94. The wearable system according to claim 92 or 93, wherein A first subset of the plurality of gamma photon counters is arranged on the garment such that, when the garment is worn by a subject, the first subset of the gamma photon counters can monitor the uptake of a radiopharmaceutical containing 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 garment such that, when the garment is worn by the subject, the second subset of the gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by organs at risk in the subject.

95. The wearable system of claim 94, wherein the positioning of each gamma photon counter on the garment is determined based on medical imaging of the subject to determine the location of the tumor in the subject, and the positioning of each gamma photon counter of the second subset on the garment is determined based on medical imaging of the subject to determine the location of the organ at risk 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 according to any one of claims 92-96, wherein the plurality of γ-photon counters are arranged in an array on the garment.

98. The wearable system of claim 92, wherein each of the plurality of gamma photon counters is attached to the subject's skin using the adhesive patch.

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

100. The wearable system of claim 99, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

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

102. A computer-implemented method for calculating the total percentage of injected activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject, the computer-implemented steps comprising: a) Receive γ-photon counting data from multiple γ-photon counters, wherein each γ-photon counter has a known position; b) Receive images of the subject, the images showing the location of the one or more tumors and the one or more organs at risk in the subject, and the location of the plurality of gamma photon counters relative to the one or more tumors and the one or more organs at risk; c) Define the boundaries around each tumor and each organ at risk on the image; d) Use the images to measure the volume of the one or more tumors and organs at risk; e) Map the centroid position of each γ-photon counter onto the image; f) Perform distributed point source (DPS) modeling to generate a distribution of gamma photon emission point sources within the boundaries of each tumor and each organ at risk, wherein the DPS modeling is used to i) decay based on counts per second (CPS) and 1 / (the distance between the centroid location of the gamma photon counter and the gamma photon emission point source). 2 The related assumptions are as follows: calculating the probability of receiving the γ photons counted by the γ photon counter from a γ photon emission source within the boundary of a specific tumor or organ at risk for each γ photon counter, and the CPS value is attenuated by an empirically derived factor Ω, which takes into account the attenuation and scattering of γ photons in the tissue, and ii) estimating the possible fraction of the counts counted by each γ photon counter corresponding to a specific tumor or organ at risk; g) Based on the γ-photon count data from the plurality of counters and the parameter estimates of the possible fractions of the counts corresponding to a specific tumor or organ at risk modeled by the DPS, the Markov Chain Monte Carlo (MCMC) algorithm is used to estimate the total count for each tumor and organ at risk. h) Based on the estimated total count of each tumor and at-risk organ, and divided by the volume of the one or more tumors and at-risk organs measured from the image, calculate the total %IA / ml of the one or more tumors and at-risk organs in the subject; and i) Display the total %IA / mL of 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 performing DPS modeling comprises: A DPS model matrix (W) is created, representing the counts per second (CPS) per μCi contributed by each tumor or at-risk organ to each of the plurality of gamma photon counters, wherein the CPS per μCi is multiplied by the unknown activity in μCi of the total tumor or at-risk organ activity, wherein the values ​​in the DPS model matrix (W) are estimated based on knowledge of the location of each tumor and each at-risk organ from the image and the known location of each gamma photon counter; as well as The DPS model matrix (W) is decomposed into a matrix (β) and a vector (α), wherein the matrix (β) represents the fraction of CPS from a specific tumor or organ at risk in each γ-photon counter, wherein the fraction is scaled by the vector (α), wherein the vector (α) is the CPS of μCi activity per injection for each γ-photon counter.

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

105. The computer-implemented method according to claim 103 or 104, wherein the matrix (β) is initially estimated by: i) assuming that each tumor and each organ at risk takes up 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 the tumors and organs at risk for the estimated possible fraction of the counts corresponding to a particular tumor or organ at risk, counted by each counter.

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

107. The computer-implemented method according to any one of claims 102-106, further comprising performing iterative optimization by means of methods including gradient descent, least squares minimization, or brute-force global minimization, or combinations thereof.

108. The computer-implemented method according to any one of claims 102-107, wherein the empirical derivation factor Ω is determined by a method comprising the following steps: The detected CPS of each gamma photon counter was measured in water at different distances from the gamma photon emission point source; The detected CPS of each γ-photon counter was measured in air at different distances from the γ-photon emission point source; Based on the differences in CPS detected in water and air at each distance, a nonlinear factor representing the scattering and attenuation of each γ-photon emission point source is derived; and The nonlinear factor is used to calculate a unique factor Ω for each gamma photon emission point in the subject based on the distance in the tissue between each gamma photon counter and each gamma photon emission point.

109. The computer-implemented method according to any one of claims 102-108, further comprising segmenting the image, wherein the boundaries of each tumor and organ at risk and the centroid location of each gamma photon counter are segmented.

110. The computer-implemented method according to any one of claims 102-109, wherein each of the plurality of gamma photon counters comprises: Y2O3-Eu doped phosphors, wherein γ photons incident on the surface of the Y2O3-Eu doped phosphor generate scintillation light in the visible spectrum; The detector includes 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 generates a voltage pulse in response to detecting the scintillation light generated by the γ photons; A digital counter coupled to the detector, wherein the digital counter counts γ-photon detection events, wherein each γ-photon detection event corresponds to a voltage pulse generated by the detector in response to detecting the scintillation light generated from each γ-photon incident on the surface of the Y2O3-Eu-doped phosphor; and An opaque material is used to cover the optical fiber, wherein the opaque material shields the optical fiber from visible light emitted by the phosphor other than that doped by the Y2O3-Eu.

111. The computer-implemented method according to any one of claims 102-109, wherein each of the plurality of gamma photon counters comprises: A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel comprising a silicon diode, wherein gamma photons incident on the surface of the silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses. A unity-gain voltage amplifier connected to the silicon diode, wherein each voltage pulse generated by the gamma photon is individually buffered by the unity-gain voltage amplifier; A differential closed-loop amplifier, wherein a buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential closed-loop amplifier, wherein the voltage gain is preset or can be configured using in-pixel memory and a digital-to-analog converter (DAC), wherein the voltage pulse generated across the silicon diode is buffered and amplified with a fixed, process-invariant gain; An inverter chain comprising multiple inverters connected to the amplified voltage output from the differential closed-loop amplifier, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon; A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the silicon diode; An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events; A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period; On-chip or off-chip energy storage devices; and A custom digital logic circuit is configured to control voltage 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 according to any one of claims 102-109, wherein each of the plurality of gamma photon counters comprises: A detector, configured in an application-specific integrated circuit (ASIC) on a chip, comprising an array of pixels, each pixel including a pair of silicon diodes, the pair of silicon diodes including a first silicon diode and a second silicon diode, wherein gamma photons incident on the surface of the first silicon diode or the second silicon diode break silicon bonds to generate electron-hole pairs, thereby generating a charge pulse (Q). p The charge pulse (Q) p The accumulation of voltage pulses due to diode capacitors leads to the generation of voltage pulses. A unity-gain voltage amplifier connected to each silicon diode, wherein each voltage pulse generated by a gamma photon is individually buffered by the unity-gain voltage amplifier; A differential amplifier, wherein the buffered voltage output from the unity-gain voltage amplifier is connected to the input of the differential amplifier; A voltage integrator, wherein the voltage integrator accepts a selected DC voltage and sets the voltage output of the differential amplifier, wherein the voltage integrator is configured with negative feedback to bootstrap from the output of the differential amplifier to the input of the differential amplifier; A pair of level shifters connected to the output of the differential amplifier, wherein the pair of level shifters includes two level shifters, the two level shifters including a first level shifter that shifts the DC level at the output of the differential amplifier upward to amplify only the voltage pulse from the first diode; A second level shifter shifts the DC level at the output of the differential amplifier down to amplify only the voltage pulse from the second diode, wherein an on-chip configurable memory and an in-pixel digital-to-analog converter (DAC) are used to set the amount by which the DC level is shifted to convert the stored bits into an analog voltage shift. An inverter chain comprising a plurality of inverters connected to the amplified and shifted voltage outputs from the pair of level shifters, wherein the inverter chain generates a digital output corresponding to each voltage pulse generated by a gamma photon; A digital counter coupled to the digitized output of the inverter chain, wherein the digital counter counts gamma photon detection events, wherein each gamma photon detection event corresponds to the voltage pulse generated by each gamma photon incident on the surface of the first silicon diode or the second silicon diode; An on-chip data buffer, configured to store multiple γ-photon count records of multiple γ-photon detection events; A digital clock configured to generate a clock signal on the chip, wherein the digital counter uses the clock signal to count the number of gamma photon detection events for each time period; On-chip or off-chip energy storage devices; and A custom digital logic circuit is configured to control voltage 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 claim 111 or 112, wherein the plurality of gamma photon counters include on-chip circuitry tuned to respond to a range of linear energy transfer (LET) from incident gamma photons, wherein the computer-implemented method further comprises calculating the incident energy of the incident gamma photons based on a combination and distribution of signals from pixels having known LET responsivity.

114. The computer-implemented method of claim 113, wherein the array of pixels comprises a first subset of pixels having a known LET responsivity and a second subset of pixels, 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 with higher LET but does not detect higher-energy gamma photons with lower LET, wherein the second set of pixels detects both the lower-energy gamma photons with higher LET and the higher-energy gamma photons with lower LET.

115. The computer-implemented method according to any one of claims 102-114, wherein the plurality of gamma photon counters comprises a plurality of detectors, wherein each of the plurality of detectors comprises an attenuating material of different thicknesses to allow resolution of incident gamma photons of different energies, wherein the computer-implemented method further comprises using multiphysics simulation to calculate the probability of detecting gamma photons of a specific energy using each of the plurality of detectors to separate the detection 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 multiphysics simulation is used to calculate the probability of detecting a photon of a certain energy with a detector of a certain thickness of lead, tungsten, or iron.

117. The computer-implemented method of claim 115 or 116, wherein the plurality of detectors are arranged in a vertically stacked configuration.

118. The computer-implemented method of claim 117, wherein each detector is separated from adjacent detectors 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 a fast readout circuit connected to an array of the pixels to allow near-instantaneous detection of the same incident γ photon passing between two of the plurality of detectors 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 the time when the incident gamma photon hits the pixel, the pixel position on the detector, and the signal generated by the gamma photon hitting the pixel.

121. The computer-implemented method of claim 120, further comprising calculating the angle of the incident γ-photon relative to the vertical stack by measuring the angular offset of the incident γ-photon transmitted from the detector at the top of the stack to the detector located below in the stack due to Compton scattering.

122. The computer-implemented method according to any one of claims 117-121, wherein the plurality of detectors are stacked with a stacking 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 according to any one of claims 117-122, wherein the vertical stack has a shape parameter 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 are in a planar arrangement in a spatial region, wherein the computer-implemented method further comprises determining the energy of incident gamma photons in the spatial region.

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

126. A kit comprising the non-transitory computer-readable medium of claim 125 and instructions for calculating the percentage of total injection activity (%IA / mL) per milliliter of tissue 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, said plurality of gamma photon counters being attached to a wearable structure; b) Power supply; c) A processor, wherein the processor is programmed to use a computer-implemented method according to any one of claims 102-124 to calculate the total percentage of injection activity (%IA / mL) per milliliter of tissue for one or more tumors and one or more organs at risk in a subject. d) An external data receiving device connected to the processor, wherein the external data receiving device receives the gamma photon counting data from the plurality of gamma photon counters and transmits the gamma photon counting data to the processor; and e) A display component that displays %IA / mL of one or more tumors and one or more organs at risk in the subject.

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

129. The system of claim 128, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

130. The system according to claim 128 or 129, wherein A first subset of the plurality of gamma photon counters is arranged on the garment such that, when the garment is worn by a subject, the first subset of gamma photon counters is capable of monitoring the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset on the garment is determined based on medical imaging of the subject to determine the location of the tumor within the subject; and A second subset of the plurality of gamma photon counters is arranged on the garment such that, when the wearable material is worn by the subject, the second subset of the gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset on the garment is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

131. The system of claim 128, wherein the plurality of γ-photon counters are arranged in an array on the garment.

132. The system of claim 128, wherein each of the plurality of gamma photon counters is capable of being attached to the subject's skin using the adhesive patch.

133. The system according to claim 132, wherein A first subset of the plurality of gamma photon counters can be attached to the skin of the subject using an adhesive patch, such that the first subset of gamma photon counters can monitor the uptake of a radiopharmaceutical containing a gamma-emitting radionuclide by a tumor in the subject, wherein the positioning of each gamma photon counter in the first subset is determined based on medical imaging of the subject to determine the location of the tumor within the subject; and A second subset of the plurality of gamma photon counters is capable of being attached to the subject's skin with an adhesive patch, such that the second subset of gamma photon counters is capable of monitoring the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by an organ at risk in the subject, wherein the positioning of each gamma photon counter in the second subset is determined based on medical imaging of the subject to determine the location of the organ at risk in the subject.

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

135. The system of claim 134, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

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

137. The system according to 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 according to 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 ultrasonic transducer, an electromagnetic (EM) transducer, an inductive transducer, or a radio frequency (RF) transducer.

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

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

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

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

144. The system of claim 143, wherein the wireless communication unit utilizes a wireless communication protocol using electromagnetic carrier or ultrasonic waves 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 infrared carrier wave.

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

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

148. The system according to any one of claims 127-147, wherein the display further displays images of the tumor and organs at risk obtained through medical imaging of the subject.

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

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

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

152. The system according to any one of claims 127-151, wherein the display further displays labels having information about the tumor and organs at risk superimposed on the image.

153. The system according to any one of claims 127-152, wherein the gamma photons are emitted from gamma-ray emitted radionuclides suitable for single-photon emission computed tomography (SPECT) imaging.

154. The system of claim 153, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

155. The system according to any one of claims 127-154, wherein the γ 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 is 149 Tb, 223 Ra, or 225 Ac.

157. The system of claim 155, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

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

159. A method for measuring tumor uptake of a radiopharmaceutical containing a gamma-emitting radionuclide in a subject using the system according to any one of claims 127-158, the method comprising: Perform medical imaging to identify the location of one or more tumors and one or more organs at risk in the subject; A first subset of the plurality of gamma photon counters is positioned on the wearable structure such that the first subset of gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by one or more tumors in the subject; A second subset of the plurality of gamma photon counters is positioned on the wearable structure such that the second subset of the gamma photon counters is able to monitor the uptake of the radiopharmaceutical containing the gamma-emitting radionuclide by one or more organs in the subject that are at risk. as well as The total percentage of injected activity (%IA / mL) of the one or more tumors and one or more organs at risk in the subject is calculated per milliliter of tissue 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 gamma photon is emitted from a gamma-ray emitted radionuclide suitable for single-photon emission computed tomography (SPECT) imaging.

162. The method of claim 161, wherein the gamma-emitting radionuclide is 46 Sc、 67 Ga、 99m Tc, 111 In、 123 I, 131 I, 155 Tb, 177 Lu、 133 Xe or 201 Tl.

163. The method according to any one of claims 159-162, wherein the γ photon is emitted from an α particle emitting radionuclide or a β particle emitting radionuclide.

164. The method of claim 163, wherein the alpha-emitting radionuclide is 149 Tb, 223 Ra, or 225 Ac.

165. The method of claim 163, wherein the β-emitting radionuclide is 32 P, 90 Y、 131 I, 89 Sr、 152 Tb, 153 Sm、 161 Tb, 166 Ho, or 177 Lu.

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

167. The method according to any one of claims 159-166, further comprising placing a reference marker on the subject's skin at the planned location for positioning the plurality of gamma photon counters.

168. The method of claim 167, wherein the reference marker is used for the positioning of the first subset and the second subset of the plurality of gamma photon counters on the wearable structure.

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

170. The method of claim 169, wherein the clothing is a vest, shirt, shorts, trousers, hat, shoes, gloves, or body armor.

171. The method of claim 169, wherein the reference marker patch is used to locate the first subset and the second subset of the plurality of gamma photon counters by adhering the plurality of gamma photon counters to the subject's skin using a plurality of adhesive patches.

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

173. The method of claim 172, wherein the first wearable structure is wearable on the torso of the subject, and the second wearable structure is wearable on the arm or leg of the subject.

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

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

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

177. The method of claim 176, wherein the radiopharmaceutical is administered to the subject for the treatment of prostate cancer. 177 Lu-PSMA-617 or 225 Ac-PSMA-617.

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