Photon absorption remote sensing system for histological evaluation of tissue

Abstract

The imaging device may be used for histological and / or molecular imaging of a tissue sample. An imaging device may include: one or more light sources that generate one or more excitation beams directed at an excitation location focused on the sample to generate a signal in the sample; and one or more interrogation beams directed at a detection location such that a portion of the one or more interrogation beams returned from the sample is indicative of at least some of the generated signals. An imaging device may include a photodetector configured to detect a radiation signal from the sample. An imaging device may generate an image of the sample using a pressure-only (photoacoustic) signal, a temperature-only (photothermal) signal, and / or both a photoacoustic signal and a photothermal signal from the generated signals.

Description

[0001] Cross Reference to Related Applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 483,854, filed February 8, 2023, which is incorporated by reference herein in its entirety. TECHNICAL FIELD

[0003] The present disclosure relates to the field of optical imaging, and in particular to a photon absorption remote sensing system and method for non-contact imaging of a sample, such as an in vivo, ex vivo, or in vitro biological tissue. BACKGROUND

[0004] In some imaging fields, traditional imaging techniques often require staining or coloring of a sample prior to imaging. For example, in histological imaging, traditional histopathology workflows require fixation, embedding, and then sectioning of a sample into thin, translucent samples prior to imaging. This process can take days or even weeks. Furthermore, samples prepared in this manner can only be stained once and / or use one set of stains, which results in these samples being generally useful for only one specific purpose. However, when several assessments must be made, multiple stained samples can be required, one for each specific assessment. This can complicate and delay the diagnostic process, especially in the case of small tissue samples.

[0005] Accordingly, there is a need for an imaging technique, architecture, system, or method that is capable of capturing sufficient detail to perform cellular and subcellular assessments of a tissue while reducing the need for sample processing and / or staining and circumventing many of the sample collection and preparation challenges associated with traditional pathology workflows, such as histopathology. SUMMARY

[0006] Aspects disclosed herein can be used with and / or receive or collect signals from any of the photoabsorption or photoacoustic remote sensing systems, methods, or signals disclosed in the following U.S. patent applications, which are incorporated by reference herein: U.S. Application Serial No. 16 / 847,182 (entitled “Photoacoustic Remote Sensing (PARS)”), filed April 13, 2020; U.S. Application Serial No. 17 / 091,856 (entitled “Non-Interferometric Photoacoustic Remote Sensing (NI-PARS)”), filed November 6, 2020; U.S. Application Serial No. 16 / 814,538 (now U.S. Patent No. 11,022,540) (entitled “Camera-Based Photoacoustic Remote Sensing (C-PARS)”), filed March 10, 2020; U.S. Application Serial No. 16 / 753,887 (entitled “Coherence Gated Photoacoustic Remote Sensing (CG-PARS)”), filed April 6, 2020; U.S. Application Serial No. 16 / 647,076 (entitled “Single Source Photoacoustic Remote Sensing (SS-PARS)”), filed March 13, 2020; U.S. Application Serial No. 16 / 629,371 (entitled “Photoacoustic Remote Sensing (PARS), and Related Methods Of Use”), filed January 8, 2020; U.S. Application Serial No. 17 / 394,919 (entitled “PARS Imaging Methods”), filed August 5, 2021; and U.S. Provisional Application No. 63 / 241,170 (entitled “Non-Linear PARS Methods”), filed September 7, 2021.The aspects disclosed herein can be used with any of the PARS systems described in the above-referenced applications, such as: time-domain PARS or TD-PARS, total absorption PARS or TA-PARS, multi-pass PARS or MP-PARS, multiphoton excitation PARS or multiphoton PARS, thermal enhancement PARS or TE-PARS, temperature sensing PARS or TS-PARS, super-resolution PARS or SR-PARS, spectral enhancement PARS or SE-PARS, smart detection PARS or SD-PARS, camera-based PARS or C-PARS, non-interferometric PARS or NI-PARS, coherence-gated PARS or CG-PARS, single-source PARS or SS-PARS, optical resolution PARS or OR-PARS, bimodal PARS combined with optical coherence tomography (PARS-OCT), and / or endoscopic PARS combined with optical coherence tomography (EPARS-OCT).

[0007] In some aspects, the technology described herein relates to an imaging device for histology and / or molecular imaging of a tissue sample, the device comprising: one or more light sources, wherein the one or more light sources are configured to generate: i) one or more excitation beams configured to be directed to an excitation location focused on the tissue sample to generate a signal in the tissue sample; and ii) one or more interrogation beams configured to be directed to a detection location, wherein a portion of the one or more interrogation beams returned from the tissue sample is indicative of at least some of the generated signal; a photodetector configured to detect a radiation signal from the tissue sample; and one or more processors configured to: generate an image of the tissue sample using only a photoacoustic signal from the generated signal; generate an image of the tissue sample using only a photothermal signal from the generated signal; and generate an image of the tissue sample using both a photoacoustic signal and a photothermal signal from the generated signal.

[0008] In some aspects, the technology described herein relates to a device, wherein a photoacoustic signal used to generate an image of a tissue sample is measured in a range of one picosecond to 500 milliseconds from an excitation event induced by the one or more excitation beams.

[0009] In some aspects, the technology described herein relates to a device, wherein a photothermal signal used to generate an image of a tissue sample is measured in a range of one microsecond to 500 milliseconds from an excitation event induced by the one or more excitation beams.

[0010] In some aspects, the technology described herein relates to an apparatus, wherein the one or more light sources comprise: a first excitation light source configured to emit light at a first wavelength; and a second excitation light source configured to emit light at a second wavelength different from the first wavelength.

[0011] In some aspects, the technology described herein relates to an apparatus, wherein the light at the first and second wavelengths is configured to target unique radiative and non-radiative absorption properties of local biomolecules in the tissue sample.

[0012] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to generate images based on photoacoustic and / or photothermal signals from: excitation using only the first wavelength; and excitation using only the second wavelength.

[0013] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to generate an absorption difference image based on relative differences between: 1) photoacoustic and photothermal signals from excitation using only the first wavelength, and 2) photoacoustic and photothermal signals from excitation using only the second wavelength.

[0014] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to generate transmission and reflectance attenuation maps via light scattering contrast images of one or more interrogating or excitation light beams.

[0015] In some aspects, the technology described herein relates to an apparatus, wherein the biomolecules or target of interest appear as relatively darker spots in the light scattering contrast images than the surrounding non-absorbing medium.

[0016] In some aspects, the technology described herein relates to an apparatus, wherein the tissue sample comprises one or more of a freshly excised tissue specimen, a preserved tissue specimen, a prepared tissue specimen, an extracted tissue specimen, or a live tissue.

[0017] In some aspects, the technology described herein relates to an apparatus, further comprising a temperature control device configured to adjust a temperature of the tissue sample.

[0018] In some aspects, the technology described herein relates to an apparatus, further comprising a glass slide for housing the tissue sample, wherein the glass slide comprises an ultraviolet transparent material configured to allow imaging through the glass slide.

[0019] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are further configured to: calculate the intensity of the signal generated before excitation; subtract the intensity calculated before excitation from the intensity of the signal generated after excitation to determine the residual modulation; integrate the residual modulation; and use the integration to estimate the total absorption level of the radiative or non-radiative signal.

[0020] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to apply de-noising or filtering prior to extracting the integration.

[0021] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to use all of the photoacoustic signal, the photothermal signal, and the radiative signal to generate the image.

[0022] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to use 1) the photoacoustic signal and the photothermal signal and 2) the QER ratio of the radiative signal to generate the image.

[0023] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are configured to use i) the QER ratio to define the color of the combined QER-total absorption image and ii) all of the photoacoustic signal, the photothermal signal, and the radiative signal to define the intensity of the combined QER-total absorption image to generate the combined QER-total absorption image.

[0024] In some aspects, the technology described herein relates to an apparatus, wherein the color provides information about the type of biomolecule in the combined QER-total absorption image and the intensity of the combined QER-total absorption image provides information about the concentration of the biomolecule.

[0025] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are further configured to extract the time domain characteristics to form a visualization that distinguishes different biomolecules with different colors.

[0026] In some aspects, the technology described herein relates to an apparatus, further comprising a secondary imaging head, wherein the secondary imaging head is a camera-based probe configured to perform wide-field, high-resolution imaging at a high rate.

[0027] In some aspects, the technology described herein relates to an apparatus, wherein the one or more light sources are one or more of: i) a white light source; and ii) a wavelength-isolated; wherein the one or more light sources are configured to provide one or more of: i) a brightfield image; ii) a measurement of light attenuation within the sample; and iii) a measurement of autofluorescence within the sample.

[0028] In some aspects, the technology described herein relates to an apparatus, wherein the one or more excitation beams and / or the one or more interrogation beams do not fill the objective used for histology and / or molecular imaging of the tissue sample.

[0029] In some aspects, the technology described herein relates to an apparatus, wherein the one or more excitation beams and / or the one or more interrogation beams exactly fill or overfill the objective used for histology and / or molecular imaging of the tissue sample.

[0030] In some aspects, the technology described herein relates to an apparatus, wherein the one or more processors are further configured to generate an image using the radiation signal detected by the photodetector, the radiation signal being autofluorescence.

[0031] In some aspects, the technology described herein relates to an apparatus, the photodetector is configured to detect a non-radiation signal dominated by a temperature (photothermal) signal.

[0032] In some aspects, the technology described herein relates to an apparatus, the photodetector is configured to detect a non-radiation signal dominated by a pressure (photoacoustic) signal.

[0033] In some aspects, the technology described herein relates to a method for configuring a scanning system to scan a sample at different pixels spaced at a determined distance from each other, the different pixels corresponding to different locations of excitation events, the method comprising: performing a first scan in an area of more than one pixel of the sample; determining a determined distance between each pixel from the first scan, wherein the determined distance corresponds to a minimum distance that enables extraction of a signal from a particular pixel such that the particular pixel is completely isolated and allows the sample to recover to thermal equilibrium before the sample is excited again; synchronizing a vibration frequency of the MEMS mirror with a pulse repetition frequency (PRF) of the laser source; and optically scanning, via the MEMS mirror, a beam generated by the laser source across the sample at each pixel in a sub-group, wherein the vibration frequency synchronized with the PRF enables the beam to be pulsed onto the sample at the determined distance.

[0034] In some aspects, the technology described herein relates to a method, the method further comprising: one or more additional beams generated by the laser source and / or one or more additional laser sources, wherein each beam of the one or more additional beams corresponds to a separate pixel sub-group; and optically scanning, via the MEMS mirror, each beam of the one or more additional beams across the sample at each pixel in the corresponding sub-group, wherein the synchronized scanning frequency and the PRF enable the one or more additional beams to be pulsed onto the sample at the determined distance.

[0035] In some aspects, the technology described herein relates to a method, wherein each of the light beam and one or more additional light beams are a determined distance apart from each other.

[0036] In some aspects, the technology described herein relates to a method for configuring a scanning system to scan a sample at different pixels spaced a determined distance apart from each other, the different pixels corresponding to different locations of excitation events, the method comprising: performing a first scan in a region of more than one pixel of the sample; determining a determined distance between each pixel from the first scan, wherein the determined distance corresponds to a minimum distance that enables extraction of a signal from a particular pixel such that the particular pixel is completely isolated and allows the sample to recover to thermal equilibrium before the sample is excited again; pulsing a plurality of light beams generated by one or more laser sources at a pulse repetition frequency (PRF), wherein each of the plurality of light beams corresponds to a separate subset of pixels; and optically scanning the plurality of light beams across the sample at each pixel in the corresponding separate subset via a MEMS mirror such that the plurality of light beams are pulsed onto the sample at the determined distance.

[0037] In some aspects, the technology described herein relates to a method, wherein the PRF is greater than a vibration frequency of the MEMS mirror. BRIEF DESCRIPTION OF DRAWINGS

[0038] In this patent document, the terms “comprises,” “comprising,” “includes,” “including,” and “having” are inclusive and specify the presence of stated features, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, steps, operations, elements, and / or components. The use of the articles “a,” “an,” and “the” to refer to an element does not, unless the context clearly indicates otherwise, require that the element be only one and not a plurality of elements. The use of terms such as “about,” “approximately,” “substantially” and the like are intended to describe a value + / - 10% of the value, unless otherwise indicated.

[0039] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the present disclosure and together with the description, serve to explain the principles of the present disclosure.

[0040] FIG. 1A A plot showing PARS signal in methylene blue at different temperatures is shown.

[0041] FIG. 1B An exemplary final pixel spacing and skip pixel architecture is shown.

[0042] FIG. 1C A plot showing the difference in radiative and non-radiative channels at different fast pitch and excitation pulse repetition rates.

[0043] FIG. 1D An exemplary sample slide with a barcode is shown.

[0044] FIG. 1E An exemplary PARS shuttle stage system is shown.

[0045] FIG. 1F An exemplary single-point scanning architecture employing single-point scanning is shown.

[0046] FIG. 1G An exemplary multi-point scanning architecture employing multi-point scanning is shown.

[0047] FIG. 1H An exemplary correlation process for image reconstruction is shown.

[0048] FIG. 1I An exemplary iterative process for image reconstruction is shown.

[0049] FIG. 1J An exemplary before-and-after comparison for images undergoing image reconstruction is shown.

[0050] FIG. 1K An etched silicon wafer is shown.

[0051] FIG. 1L An exemplary architecture for a multi-pass PARS detection system is shown.

[0052] FIG. 1M An exemplary multi-point scanning architecture to enable ultrafast single-point scanning is shown.

[0053] FIG. 1N An exemplary single detection source and single ultrafast excitation source to provide input beams for a sequential multi-point scanning embodiment is shown.

[0054] FIG. 1O Several exemplary detection sources and an exemplary excitation source to provide input beams for a sequential multi-point scanning embodiment is shown.

[0055] FIG. 1P An exemplary single detection source and exemplary single excitation source to provide input beams for a simultaneous multi-point scanning embodiment is shown.

[0056] FIG. 1Q Several exemplary detection sources and an exemplary single excitation source to provide input beams for a simultaneous multi-point scanning embodiment is shown.

[0057] FIG. 2AAnother example architecture of a multi-pass PARS detection system is shown.

[0058] FIG. 2B Another example architecture of a multi-pass PARS detection system is shown with additional measurements of scattered excitation light.

[0059] FIG. 2C Another example architecture of a multi-pass PARS detection system is shown with additional measurements of transmitted and reflected excitation light.

[0060] FIG. 2D Another example architecture of a multi-pass PARS detection system is shown using a camera-based detector.

[0061] FIG. 2E Another example architecture of a PARS detection system in reflectance mode is shown.

[0062] FIG. 2F Another example architecture of a PARS detection system in reflectance mode is shown.

[0063] FIG. 2G Another example architecture of a PARS detection system in reflectance mode is shown.

[0064] FIG. 2H Another example architecture of a PARS detection system is shown.

[0065] FIG. 2I Another example architecture of a PARS detection system is shown.

[0066] FIG. 2J Another example architecture of a PARS detection system is shown.

[0067] FIG. 2K Another example architecture of a PARS detection system is shown.

[0068] FIG. 2L Another example architecture of a multi-pass PARS detection system is shown using a camera-based detector with additional measurements of transmitted and reflected excitation light.

[0069] FIG. 2M Another example architecture of a PARS detection system using a camera-based detector with additional measurements of transmitted and reflected excitation light is shown.

[0070] FIG. 3 An example excitation source architecture for any of the PARS detection systems in FIG. 2A to FIG. 2M

[0071] FIG. 4 A plot of a signal energy measurement process is shown.​

[0072] FIG. 5 Total non-radiative absorption PARS images captured using a 266 nm excitation source and a 532 nm excitation source are shown.

[0073] FIG. 6 Total radiative absorption PARS images captured using a 266 nm excitation source and a 532 nm excitation source are shown.

[0074] FIG. 7 Total absorption PARS images captured using a 266 nm excitation source are shown.

[0075] FIG. 8 Total absorption PARS images captured using a 532 nm excitation source are shown.

[0076] FIG. 9 Total absorption PARS images captured using a 266 nm excitation source and a 532 nm excitation source are shown.

[0077] FIG. 10 Quantum efficiency ratio PARS images captured using a 266 nm excitation source are shown.

[0078] FIG. 11 Quantum efficiency ratio PARS images captured using a 532 nm excitation source are shown.

[0079] FIG. 12 Quantum efficiency ratio PARS images captured using a 266 nm excitation source and a 532 nm excitation source are shown.

[0080] FIG. 13 Quantum efficiency ratio PARS images captured using a 266 nm excitation source and a 532 nm excitation source are shown, with coloring based on total absorption.

[0081] FIG. 14 is an image showing the differential absorption contrast extracted from the non-radiative absorption PARS signals captured using a 266 nm excitation source and a 532 nm excitation source.

[0082] FIG. 15 is an image showing the differential absorption contrast extracted from the radiative absorption PARS signals captured using a 266 nm excitation source and a 532 nm excitation source.

[0083] FIG. 16A to FIG. 16D is a collection of images and accompanying plots showing the application of the K-means feature extraction method to saved thin sections of human breast tissue.

[0084] FIG. 17 is a collection of images and accompanying plots showing the application of the K-means feature extraction method to saved thin sections of human breast tissue. FIG. 16A to FIG. 16C is a collection of images and accompanying plots showing the application of the K-means feature extraction method to saved thin sections of human breast tissue.

[0085] FIG. 18 is an annotated image showing the use of two K-means features and one signal energy feature (extracted using the signal energy feature extraction method).

[0086] FIG. 19 shows a plot of the PARS non-radiative pressure (photoacoustic signal) and temperature (photothermal signal) induced modulations generated in the local optical properties of the sample.

[0087] FIG. 20A shows another plot of the PARS non-radiative pressure (photoacoustic signal) and temperature (photothermal signal) induced modulations generated in the local optical properties of the sample.

[0088] FIG. 20B shows another plot of the PARS non-radiative pressure (photoacoustic signal) and temperature (photothermal signal) induced modulations generated in the local optical properties of the sample.

[0089] FIG. 20C shows another plot of the PARS non-radiative pressure (photoacoustic signal) and temperature (photothermal signal) induced modulations generated in the local optical properties of the sample.

[0090] FIG. 21 is a schematic depiction of an axial depth scan performed in 500 nm steps over a range of + / - 2 pm.

[0091] FIG. 22 shows a plot of the focal curve generated by the axial depth scan.

[0092] FIG. 23 shows two annotated PARS images, one image showing tissue sample boundary detection / selection and the other image showing division of the tissue sample region into smaller sub-regions.

[0093] FIG. 24 is a full-slice PARS image containing contrast and brightness variations between adjacent tiles in the scattering channel.

[0094] FIG. 25 is a full-slice PARS image after applying the full-slice stitching and contrast equalization method. FIG. 24

[0095] FIG. 26 shows a plot of the local spatio-temporal filtering implementation.

[0096] FIG. 27 ​Two PARS images of a thin section of human skin tissue are shown, including an image before (pre-filtered) the application of a local statistical image smoothing method to the non-radiative contrast channel of the image and an image after (post-filtered) the application of a local statistical image smoothing method to the non-radiative contrast channel of the image.

[0097] FIG. 28 Two non-radiative contrast PARS images and two radiative contrast PARS images of a thin section of human skin tissue are shown, including images before (non-radiative contrast - original image; radiative contrast - original image) the application of a total absorption variance correction method and images after (non-radiative contrast - filtered image; radiative contrast - filtered image) the application of a total absorption variance correction method.

[0098] FIG. 29 A non-radiative contrast PARS image captured using a 266 nm excitation source is shown.

[0099] FIG. 30 A non-radiative contrast PARS image captured using a 532 nm excitation source is shown.

[0100] FIG. 31 A radiative contrast PARS image captured using a 266 nm excitation source is shown.

[0101] FIG. 32 A radiative contrast PARS image captured using a 532 nm excitation source is shown.

[0102] FIG. 33 A light scattering contrast PARS image captured from a 405 nm probe source is shown.

[0103] FIG. 34 An indirect absorption PARS image captured under light scattering contrast of a 405 nm probe source is shown.

[0104] FIG. 35 An excitation scattering contrast PARS image captured from a 266 nm excitation source is shown.

[0105] FIG. 36A to FIG. 36D Different exemplary embodiments of a collection unit are shown.

[0106] FIG. 37 An exemplary optical processing unit is shown. DETAILED DESCRIPTION

[0107] The present disclosure relates generally to photon absorption remote sensing (PARS) and to related architectures, systems, and methods.

[0108] As will be discussed in detail below, PARS (and related architectures, systems, and methods) can capture multiple direct light absorption (radiative and non-radiative), indirect light absorption, and light scattering signals from a biological sample, such as a biological (e.g., cellular or tissue) specimen. An excitation source can induce an excitation event, and then a relaxation process can be captured that subsequently evolves over time. Thereafter, multiple signal features (e.g., amplitude, frequency components, phase modulation) can be extracted by processing at least one of the multiple generated signals. These signal features can then be used to directly form visualizations, can be processed to form visualizations, and / or can be combined into a feature vector characteristic that can be used for further processing. In this case, the feature vector characteristic can be used for various applications, such as powering an AI diagnostic tool, or developing an AI-based coloring method.

[0109] PARS mechanism

[0110] PARS is an all-optical, non-contact absorption microscopy technique. PARS uses excitation and probe laser sources to generate and probe light absorption and scattering contrast in various samples.

[0111] As will be discussed further below, an excitation source, such as an excitation laser, is used to deposit optical energy into a sample. When light is absorbed by a chromophore, the energy causes the sample to enter an excited state. In some cases, such as inelastic scattering events (e.g., stimulated Raman or Brillouin scattering events), only a fraction of the energy of the incident photon is captured. Depending on how much of the absorbed light energy is captured, the sample can enter any of a variety of energy states, such as different vibrational, virtual, or electronic states. This absorbed energy can then be dissipated through optical radiation (radiative) or non-radiative relaxation.

[0112] During non-radiative relaxation, the absorbed optical energy is converted into heat. This heating causes a modulation of the local material properties of the specimen by affecting material density, stress, etc. These temperature changes and corresponding optical property changes are the basis of photothermal microscopy. In certain scenarios, the generation of heat can also produce additional effects within the heated region. In some cases, the rapid heating and subsequent thermal-elastic expansion can cause the generation of pressure. This is referred to as photoacoustic pressure, and this effect forms the basis of photoacoustic microscopy. The generated pressure causes an effect that results in a corresponding modulation of the local material properties of the sample by affecting material density, stress, etc. Additionally, the generated pressure can also cause additional effects, such as ultrasonic absorption, which can further modulate the material properties. In PARS, these local (non-radiative) temperature and pressure modulations are observed using a probe source. The perturbations of the optical and material properties of the sample can be captured as temporal evolution of backscattered intensity modulation in the probe laser.

[0113] During radiative relaxation, the absorbed optical energy is released through the emission of photons. In general, the emitted photons exhibit different energy levels compared to the absorbed photons. Modalities such as fluorescence microscopy, multiphoton fluorescence, or harmonic generation rely on the radiative relaxation effect to achieve contrast. In PARS, radiative contrast can be captured by measuring the non-excited photons emitted from the sample.

[0114] In inelastic scattering events, the photons exhibit different energy levels compared to the input photons. Modalities such as spontaneous or stimulated Brillouin scattering or spontaneous or stimulated Raman scattering rely on these events to achieve contrast. In PARS, inelastic scattering contrast can be captured by measuring the photons scattered from the sample that exhibit different energies compared to the input photons.

[0115] It should be appreciated that, in general, PARS can capture almost all optical properties of a chromophore simultaneously. This includes non-radiative and radiative direct light absorption contrast and their effects, in addition to indirect light absorption provided by the scattered signals of the excitation and probe beams. This can facilitate unique contrast and visualization effects. Furthermore, PARS can improve sensitivity to any range of chromophores (e.g., 100 nm to 16 pm) compared to other independent modalities. Unlike traditional methods that independently capture radiative or non-radiative absorption, PARS contrast can not be limited by common efficiency factors such as photo-thermal conversion efficiency or fluorescence quantum yield.

[0116] The PARS probing mechanism will now be discussed in detail. As previously mentioned, all optical interactions of the probe and excitation beams with the sample can be collected by PARS. This includes indirect and direct absorption effects, linear scattering, nonlinear scattering, etc. These features can then be used to generate a feature vector characteristic of the biomolecule or mixture of biomolecules located at the focal point of the beams.

[0117] In general, the optical interactions captured by PARS can be classified into two categories of optical scattering, elastic and inelastic, and light absorption contrast. According to their relaxation processes, the absorption effects are further divided into radiative events and non-radiative events. During non-radiative relaxation, the absorbed optical energy is converted into heat. During radiative relaxation, the absorbed optical energy is released through the emission of photons. In most cases, the optical interactions and subsequent effects are not isolated. That is, except for elastic scattering events, most interactions induce some radiative relaxation properties and some non-radiative relaxation properties. For example, stimulated Raman scattering, a non-elastic scattering effect, can induce some non-radiative relaxation.

[0118] With respect to absorption events, a variety of different absorption mechanisms can be at play in PARS. For example, linear (e.g., single-photon) absorption interactions and nonlinear (e.g., multiphoton such as two- or three-photon) absorption interactions can both induce and / or generate PARS signals. Other effects such as stimulated Raman absorption, vibrational absorption, electronic absorption, and surface plasmon resonance absorption can also be utilized. Any number of these or other effects can contribute to absorption in a single excitation event, inducing and / or generating PARS radiative and non-radiative signals.

[0119] PARS can use one or more probe sources to capture non-radiative contrast. All non-radiative relaxations cause perturbations in the local physical and optical properties of the sample. These are then captured by observing their effects on the interaction of the probe laser with the sample over time.

[0120] In some cases, the non-radiative relaxation processes captured by PARS can exhibit temperature-based (e.g., photothermal) effects. In these cases, the non-radiative signals can be considered to be dominated by photothermal signals. While the sample can generate pressure, the PARS probe mechanism can not be able to collect the pressure signal because the probe mechanism is not fast enough. Thus, the collected signal can be primarily photothermal (e.g., dominated by temperature-based signals). For example, in the case of a non-radiative relaxation event, the deposited energy will cause local heating and subsequent thermal-elastic expansion to be generated. This is a fundamental effect exploited by traditional modalities such as photothermal microscopy, time-domain photothermal microscopy, thermal lens, thermal lens microscopy, and photothermal deflection microscopy. The local heating causes changes in material properties such as density, birefringence, refractive index, absorption coefficient, or scattering behavior.

[0121] In some cases, the non-radiative relaxation processes captured by PARS can exhibit pressure-based (e.g., photoacoustic) effects. In these cases, the non-radiative signals can be considered to be dominated by photoacoustic signals. This is because the pressure-based signals can be more (e.g., stronger, larger, more dominant, etc.) than the temperature-based signals. PARS can collect pressure-based signals that are two, three, or even more times the temperature-based signals. For example, if the sample heats up fast enough, the material will be constrained from undergoing thermal-induced thermal-elastic expansion. The heated region then accumulates pressure as it overcomes this constraint. This results in the generation of photoacoustic pressure. In general, this initial pressure is generated if the rate of energy deposition is faster than the stress confinement time, which is the time it takes for the pressure to propagate away from the excited region. Thus, depending on the PARS architecture (e.g., device or system) and sample / specimen parameters, the pressure confinement time can range from femtoseconds to microseconds in magnitude.

[0122] The generation of initial pressure can induce a variety of effects. Dominant effects of initial pressure generation can include initial pressure optical modulation, stress, deformation / displacement, or cavitation. In the case where the dominant effect of initial pressure generation is initial pressure optical modulation, the megapascal-level initial high pressure generated during the excitation event can directly affect the local optical (e.g., refractive index, scattering cross-section) and material properties (e.g., density, heat capacity) of the sample. In the case where the dominant effect of initial pressure generation is stress, the generation of initial pressure can induce stress and strain fields inside the sample. These fields can cause changes in the optical properties (e.g., polarizability, reflectivity) of the sample. In the case where the dominant effect of initial pressure generation is deformation / displacement, the pressure generation can induce deformation and displacement of scatterers, surface, or subsurface features of the sample, resulting in distortion and changes in the scattering distribution. In the case where the dominant effect of initial pressure generation is cavitation, the large initial pressure generation and subsequent negative pressure can cause cavitation to occur. Cavitation can induce rapid modulation of local optical properties at the location of the probe laser source, resulting in an observable PARS signal.

[0123] Additional effects of initial pressure generation can include ultrasound absorption, resonance, secondary reflection, surface oscillation, or vibration. In the case where the additional effect of initial pressure generation is ultrasound absorption, the initial pressure induced by the excitation event will propagate away from the excitation location in the form of ultrasound waves. These high-frequency ultrasound waves will be attenuated by the surrounding sample, resulting in the generation of local heating. In the case where the additional effect of initial pressure generation is resonance, depending on the frequency of the generated pressure, the excitation event can induce resonant vibrations inside the sample, resulting in observable modulations. In the case where the additional effect of initial pressure generation is secondary reflection, after the initial pressure generation, the pressure wave can interact with interfaces inside the sample, resulting in secondary reflections of ultrasound waves. These secondary reflections can produce similar effects to the initial pressure interaction, but with a time delay. In the case where the additional effect of initial pressure generation is surface oscillation, the acoustic signal propagating to the surface of the sample can generate surface oscillations, which can also induce observable changes (e.g., phase modulation, intensity modulation) in the PARS signal. In the case where the additional effect of initial pressure generation is vibration, the generated pressure can also induce effects such as scatterer surface or subsurface location modulation / vibration.

[0124] In some cases, the non-radiative relaxation processes captured by PARS can exhibit effects based on temperature (i.e., photothermal) and pressure (i.e., photoacoustic). Many of the listed effects are not entirely independent phenomena, and thus, there can be interactions between these mechanisms and effects on the material and optical properties of the sample. The pressure and temperature induced by previous and current excitation events can produce measurable differences in the current PARS excitation and PARS time-domain signal excitation. This can be expressed through changes in the local material and optical properties such as density, birefringence, refractive index, absorption coefficient, scattering behavior, etc.

[0125] At the same time, differences in the sample and the scanning environment can also have an impact on the measured PARS signal. For example, since material properties depend on the ambient temperature, there is a corresponding temperature dependence in the PARS signal. Another example can involve introducing mechanical stress to the sample (such as bending), which in turn can affect the material properties of the sample (e.g., density or local optical properties such as birefringence, refractive index, absorption coefficient, scattering behavior). This can interfere with the generated PARS signal compared to the signal that would have been generated without the introduction of this mechanical stress.

[0126] Traditionally, non-radiative relaxation effects are observed in the probe source as amplitude modulations of the backscattered or transmitted light. These amplitude modulations can be caused by the effects described previously such as refractive index modulation, scatterer motion, surface deformation, etc. However, there are many other aspects of the probe beam that can be utilized. For example, other optical properties that can be utilized can include polarization, phase, or frequency.

[0127] The PARS non-radiative relaxation signal can also be dependent on some aspects of the probe laser such as wavelength, spectral linewidth, coherence length, beam size, or fluence, since the modulated signal is observed indirectly by the probe. In addition, the observed non-radiative signal can also depend on the interaction of the probe beam with the sample. This means that the signal can be dependent to some extent on properties such as sample temperature, scatterer size, sample morphology, electrical conductivity, or density. For example, some of the scattering, polarization, frequency, and phase content of the PARS signal can be attributed to the size, shape, features, and dimensions of the region that generates the signal. These details can be used to recover unique information that can be used to improve the final image fidelity, classify regions of the sample, determine the size of constituent chromophores, and classify constituent chromophores, etc.

[0128] In some cases, the probe source intensity is measured directly using a single intensity sensor such as a photodiode, avalanche photodiode, or photomultiplier tube. Other embodiments can use a multiplexed sensor to measure probe interactions at multiple locations simultaneously. This can include a line array sensor (e.g., linear photodiode), an array of avalanche photodiodes, or a two-dimensional sensor (e.g., CMOS, CCD, or SPAD sensor). Exemplary probe sources and methods are described in U.S. Patent No. 11,022,540 (C-PARS), which is incorporated herein by reference in its entirety.

[0129] In PARS, complementary techniques can also be used to simultaneously acquire non-radiative absorption measurements. In one example, a traditional acoustically-coupled ultrasound transducer such as a piezoelectric sensor, a capacitive micromachined ultrasound transducer (CMUT), or a Fabry-Perot sensor can be used to capture pressure-induced non-radiative relaxation effects. Additionally, other methods such as a gas-coupled ultrasound probe or an optical ultrasound probe (e.g., speckle decorrelation measurements) can also be used. In another alternative example, thermal relaxation can be captured by visualizing blackbody radiation emitted from a heated sample. A photodetector can be used to measure the infrared radiation, determine the local heating of the sample, and subsequently measure the thermal relaxation of the excitation event.

[0130] Radiative relaxation and inelastic scattering can be captured by measuring non-excited photons emitted from the sample. There are several primary effects and many related phenomena that can be characterized as radiative relaxation. The absorption of any light beam can induce some effects, examples of which include, but are not limited to: stimulated emission at the probe wavelength, stimulated Raman scattering, spontaneous Raman scattering, coherent anti-Stokes Raman scattering, harmonic generation microscopy (e.g., second or third harmonic), (spontaneous) fluorescence, and (spontaneous) fluorescence lifetime, or Brillouin scattering.

[0131] Radiative and inelastic scattering effects can be captured as a combined measurement encompassing all optical emissions from the sample, or as isolated measurements specifically targeting independent radiative and inelastic scattering effects. As described below, effects can be separated by methods such as timing, chromatic, or polarization-based filtering. Isolated contrasts can be observed on independent photodetectors, or can be captured with time delays on a single photodetector.

[0132] Various photodetectors can be used to measure the camera-based radiation and inelastic scattering signals, such as CMOS sensors, CCD sensors, photodiodes, avalanche photodiodes, or photomultiplier tubes. In some examples, the photodetectors can be arranged as a single sensor or as an array of sensors. Depending on the array of sensors, radiation and inelastic scattering emissions can be measured simultaneously at more than one location by using a spatially multiplexed detector. In some cases, the same radiation and inelastic scattering signals can be captured on several different or similar photodetectors to facilitate noise reduction methods that leverage measurement redundancy. In other cases, the radiation and inelastic scattering emissions can be separated by chromaticity, with each color band being measured on a single photodetector or different regions of a multiplexed photodetector. This can provide intensity measurements of the radiation and inelastic scattering emissions with respect to the wavelength of the emissions.

[0133] In addition to direct absorption measurements captured by radiation and non-radiation absorption contrast, PARS can also evaluate light absorption by indirect methods. For example, the scattering intensity of the excitation and probe beams will depend on the local absorption properties. Subsequently, PARS can also capture indirect absorption contrast by using the light scattering signals to estimate the absorption level at a given wavelength. The wavelength range can vary greatly. In some aspects, the wavelength can be between 100 nm and 500 nm. In other aspects, the wavelength can be between 500 nm and 1 pm. In further aspects, the wavelength can be between 1 pm and 10 pm. In some embodiments, the wavelength can be in the range between 10 pm and 16 pm. Generally, the wavelength can be in the range of 100 nm or about 100 nm to 16 pm or about 16 pm. Indirect absorption can be measured by measuring the transmitted or reflected light intensity using any type of photodetector to calculate the indirect light absorption. In some embodiments, this can be done using a photodiode, avalanche photodiode, or photomultiplier tube. In other cases, a multiplexed detector can be used, such as an array of photodiodes (linear or two-dimensional), an array of avalanche detectors (linear or two-dimensional), a CCD sensor, a CMOS sensor, or a SPAD sensor. FIG. 2D 、 FIG. 2G 、 FIG. 2K 、 FIG. 2L and FIG. 2M An exemplary architecture of a camera-based system is shown.

[0134] In addition to the light absorption effects described above, PARS can also capture light scattering contrast at each excitation and probe wavelength. In these embodiments, any number of different light scattering features can be evaluated for each wavelength. Some techniques can monitor the scattering intensity over any angular range, or scattering distribution / profile. Additional features within each of the scattering signals can also be evaluated, such as polarization, frequency, and phase content. Such evaluations can be made on transmitted or reflected light, or at any reasonable observation angle in a given architecture. This means that PARS can provide comparable contrast to conventional scattering modalities such as differential interference microscopy, optical coherence tomography, and laser interference microscopy. Scattering can be measured using any type of photodetector by measuring the transmitted or reflected light intensity. In some embodiments, this can be done using photodiodes, avalanche photodiodes, or photomultiplier tubes. In other cases, multiplexed detectors can be used, such as photodiode arrays (linear or two-dimensional), avalanche detector arrays (linear or two-dimensional), CCD sensors, CMOS sensors, or SPAD sensors. FIG. 2D 、 FIG. 2G 、 FIG. 2K 、 FIG. 2L and FIG. 2M An example architecture for a camera-based system is shown.

[0135] PARS architectures and systems

[0136] In some embodiments, PARS can be a point scanning microscope. That is, in forming a PARS image, it is necessary to move the measurement point with respect to the sample. This disclosure discusses two different methods of performing the task of moving the measurement point, which are mechanical scanning and optical scanning.

[0137] In mechanical scanning, the optical excitation point remains stationary, while the sample is physically moved over the light point. In this case, signal acquisition can be a simpler process, as all signals originate from a fixed location. The probe system can be focused on this location in order to collect all the light signals and map them to the probe. FIG. 2A to FIG. 2M An example of this is shown.

[0138] In optical scanning, optical scanning devices (e.g., microelectromechanical systems (MEMS) mirrors, galvanometer mirrors, and polygon mirrors) are used to scan the PARS interrogation point over the sample. FIG. 1F to FIG. 1G An example of optical scanning is shown. In these cases, collecting the PARS light signals can be less straightforward.

[0139] Since the PARS interrogation point is optically moved over the sample, additional consideration must be given to collecting signals from different locations. A collection unit can be added to collect optical signals from different locations on the sample and re-direct these signals for analysis. The collection unit can use any combination of optical components (e.g., mirrors, lenses, etc.) to collect optical signals from different physical locations and re-direct them to the appropriate measurement location. FIG. 36A to FIG. 36D An exemplary embodiment of a collection unit is shown.

[0140] FIG. 36A The shown collection unit 700 includes an input objective 710, a sample 708, a receiving objective 706, mirrors 704, and an optical fiber 702 (single mode or multi-mode). The input objective 710 optically scans the sample 708 and directs the scan to the receiving objective 706 to collect the optical signal. The receiving objective 706 then directs the signal through a series of mirrors 704. The signal is ultimately re-directed to the optical fiber 702, which can transport the light to a different location where an optical processing unit is used to separate and measure different PARS signal components. FIG. 37 An exemplary processing unit capable of performing this operation is shown in

[0141] FIG. 36B The shown collection unit 712 includes an input objective 722, a sample 720, a receiving objective 718, mirrors 716, and a photodetector 714. The input objective 722 optically scans the sample 720 and directs the scan to the receiving objective 718 to collect the optical signal. The receiving objective 718 then directs the signal through a series of mirrors 716. The signal is ultimately re-directed to the photodetector 714, which can directly measure the optical signal originating from the sample 720. In this case, different optical filters (e.g., wavelength filters, power filters, polarization filters, etc.) can be added in the beam path to separate different parts of the PARS optical signal for measurement.

[0142] FIG. 36C The shown collection unit 724 includes an input objective 734, a sample 732, a receiving objective 730, mirrors 728, and a camera (or other multiplexing array) 726. The input objective 734 optically scans the sample 732 and directs the scan to the receiving objective 730 to collect the optical signal. The receiving objective 730 then directs the signal through a series of mirrors 728. The signal is ultimately re-directed to the camera 726, which can perform substantially similar measurement functions as the FIG. 36B The camera 726 can help reveal the location on the sample 732 where the interrogation event occurred, while providing an additional dimension of spatial resolution. Thus, the camera 726 can help reveal the location on the sample 732 where the interrogation event occurred, while providing an additional dimension of spatial resolution.

[0143] FIG. 36DThe illustrated collection unit 736 includes an input objective 746, a sample 744, a receiving objective 742, mirrors 740, and an optical system 738. The input objective 746 optically scans the sample 744 and directs the scan to the receiving objective 742 to collect the optical signal. The receiving objective 742 then directs the signal through a series of mirrors 740. The signal is ultimately redirected to the optical system 738. In this case, the collection unit 736 can be designed to “pre-process” the light to make it compatible with multiple optical systems (such as the optical processing unit described below) for separating and measuring different PARS signal components. Thus, the optical system 738 can be any type of optical system configured to process the optical signal. FIG. 37 The optical processing unit described.

[0144] FIG. 37 The illustrated optical processing unit or PARS signal detection unit 800 includes spectral filters 802 and 806, one or more mirrors 804, a beam input 808, a photodetector 810, and a photodetector 812. The PARS signal detection unit 800 separates and measures the radiative and non-radiative signal strengths. The photodetector 810 can be configured to provide radiative detection, while the photodetector 812 can be configured to provide non-radiative detection. A collection unit (e.g., collection unit 700 or collection unit 736) can be configured to provide the beam input 808 to the PARS signal detection unit 800. Further, the PARS signal detection unit 800 can be compatible with the collection unit, the optical system, and / or the optical processing unit. FIG. 2A to FIG. 2D And FIG. 2H to FIG. 2M The transmission side of any of the illustrated architectures is substantially similar.

[0145] For transmission mode PARS imaging, the collection unit can be more important. This is because, in reflection mode imaging, the beams travel along the same path as they go to and from the sample. That is, the beams pass through the optical scanning system again as they reflect back from the sample. Since the beams pass through the optical scanning system in reverse, they can perform the same functions as the collection unit, effectively mapping the signal from the interrogation point on the sample back to the same detection location.

[0146] The present disclosure also provides PARS architectures and systems for sample imaging and, in some cases, histology and / or molecular imaging of any form of sample. For example, the PARS architectures and systems of the present disclosure can be used for label-free histology imaging of untreated and / or unstained / unlabeled samples. As used herein, the terms "label-free," "unlabeled" refer to tissue that has not been stained with a stain used in histology. For example, label-free tissue has not been stained with a stain such as hematoxylin, eosin, acid dye, basic dye, periodic acid-Schiff reagent, Masson's stain, Alcian blue stain, Van Gieson stain, reticulin stain, Giemsa stain, Toluidine blue stain, Gallein stain, hematoxylin stain, Eriochrome blue stain, osmic acid stain, PAS, T-Blue, Congo red, crystal violet, etc. In other examples, the sample can be unstained or substantially unstained and / or can not include any stain.

[0147] Suitable samples can include any biological specimen (liquid or solid), including any combination of histological or cytological specimens. Histological or cytological specimens include, but are not limited to, cellular tissue specimens, freshly excised tissue specimens (i.e., tissue smears, cytological samples, endoscopic tissue biopsies, needle core biopsies, liquid tissue biopsies, gross surgical resections), preserved tissue specimens (i.e., formalin-fixed tissue or cells, ethanol-fixed tissue or cells, acetic acid-fixed tissue or cells), prepared tissue specimens (i.e., formalin-fixed paraffin-embedded tissue or cells, formalin-fixed paraffin-embedded thin tissue sections, frozen sections), and / or extracted tissue specimens (i.e., purified protein samples, cell cultures). Thin tissue samples can be from thin tissue smears as thin as a single cell, standard frozen sections, standard paraffin-embedded sections, standard paraffin-embedded tissue blocks, or thick as any thickness of a gross tissue resection that is not treated. Additionally, the penetration depth of the optical system can determine the preferred tissue thickness.

[0148] In some examples, to further facilitate imaging, the sample can be mounted on a slide. The slide can be formed of any material configured to: allow imaging through the slide; allow the tissue to be planed on the slide to reduce or prevent surface undulations; allow imaging of liquid samples and / or samples that are not fully fixed on the slide; reduce or prevent sample dripping or spillage; and / or be compatible with fresh tissue and fixed sections. For example, the material can include various types of glass, such as ultraviolet transparent materials (e.g., quartz or ultraviolet fused silica). In particular cases, the slide can be configured to allow temperature control of the slide and / or stabilization of the direct current (DC) value of the signal. In these cases, the PARS architecture and system can include a heater or a thermoelectric cooler (TEC) (e.g., a Peltier device or chiller) to control the temperature of the slide such that the DC value of the signal is more stable, recoverable to the same DC value, and / or to facilitate stability of contrast over time. The temperature control device is configured to adjust the temperature of the slide. FIG. 1A A plot of PARS signal in methylene blue at different temperatures is shown, where the y-axis represents modulation and the x-axis represents time.

[0149] In some examples, the PARS system can be used for in vivo applications. For example, the histological sample can be replaced with any in vivo target. Accordingly, the present disclosure contemplates using an in vivo target in place of a histological sample in any of the embodiments described herein. An example in vivo application can include placing a patient’s hand under a microscope to perform the various functions mentioned in the present disclosure. Another example in vivo application can include placing a microscope on a surgical arm and then placing the surgical arm over a patient; again allowing the various functions mentioned in the present disclosure to be performed.

[0150] In some examples, the PARS system can feature a secondary imaging head that uses a camera-based detector to perform wide-field, high-resolution imaging at high rates. The system can have multiple illumination sources and multiple detection filter options to provide different contrast within the sample. For example, the illumination source can be selected as a white light source to provide “brightfield images,” as a wavelength-isolated (ultraviolet to infrared) to measure light attenuation within the sample, or as a wavelength-isolated (ultraviolet to infrared) to measure autofluorescence within the sample. These images can be used to guide PARS imaging or to enhance PARS contrast. For example, these images can be utilized to select only regions of interest for PARS scanning when combined with methods such as automated edge detection. Alternatively, fluorescence or attenuation measurements can be registered with PARS images and added to the PARS data vector collected at each pixel.

[0151] When using a secondary imaging head for edge assessment, the goal is to determine whether the extracted surface is cancer-free. More specifically, the goal is to determine the cancer-free status of the extracted surface as quickly as possible for edge assessment. In this design, the secondary imaging head displays areas with a high probability of cancer; the PARS imaging head can then scan these areas to assess positive or negative regions. The secondary imaging head is able to display areas with a high probability of cancer because it quickly provides an overall view of the tissue, and the user can automatically (or manually) select tissue edges that appear cancerous. Confirmation can then be received using the PARS primary imaging head (or a precision optical head). Additionally, the secondary imaging head can identify coarse features, such as densely packed tumor tissue and large tissue deformities, such as necrosis or inflammation. These assessments can be performed at a low resolution of approximately 10x to 15x magnification. This modality is particularly useful for samples with large areas, such as breast cancer edge assessment. In other applications with smaller samples (e.g., Mohs), scanning the entire tissue at the highest resolution of the PARS imaging head may be more efficient without using a secondary imaging head.

[0152] Based on the images and analysis from the secondary imaging head, the results can indicate which excitation wavelengths to use for scanning specific regions of tissue within the PARS unit to identify biomolecules of interest. By targeting the desired excitation wavelength, the scanning time of the PARS head can be shortened, allowing for greater focus on the required analysis.

[0153] As described below, the PARS architecture and system of this disclosure may include at least one excitation and probe beam. There may be two or more excitation points, and / or one or more probe points. The excitation and / or probe beams may originate from different laser sources, or they may originate from different portions of the same laser source, or from harmonics of the same laser source. Each beam in the excitation and probe beams may be a pulsed source or a continuous source, wherein the pulse width ranges from femtoseconds to microseconds, and in some cases even longer. It should be understood that the PARS architecture and system of this disclosure can be designed and / or optimized according to the desired imaging results. Therefore, the PARS architecture and system have several unique design features to significantly improve the sensitivity of histological samples.

[0154] A feature of PARS systems is the specific optimization of the non-radiative detection path to improve sensitivity. For example, it is possible to intentionally underfill the objective with the detection and / or excitation beam. This means that the beam is smaller than the intended input beam of the optical element. In this case, PARS detection can provide a looser forward focusing while achieving efficient collection of the backscattered intensity modulation. This design can make PARS detection more sensitive to non-radiative modulation compared to a full objective fill. Alternatively, it is possible to intentionally stretch or compress the length of the detection path, such as the distance path between the sample and the photodetector. If the path length is adjusted in this way, the sensitivity to deviations in the backscattered non-radiative modulation, which can change the detection beam path, can be enhanced. In particular cases, a longer path can provide higher sensitivity to smaller modulation in the beam. Furthermore, spatial filtering such as a pinhole can be added in the non-radiative detection path to enhance sensitivity to smaller non-radiative modulation in the detection beam.

[0155] In other embodiments, it is possible to intentionally overfill the objective with the detection and / or excitation beam. Conversely, this beam is larger than the intended input beam of the optical element. It is also possible to exactly fill the objective with the detection and / or excitation beam.

[0156] Some embodiments of the PARS systems of the present disclosure can utilize a multi-pass non-radiative detection architecture, such as the multi-pass PARS system described in International Application No. PCT / IB2022 / 054433, which is incorporated herein by reference.

[0157] Generally speaking, in a multi-pass detection architecture, the detection beam returned from the sample is captured and then redirected back to the sample. In some embodiments, the recaptured detection beam can be co- focal ly aligned with the initial detection and excitation points, although non- co- focal embodiments are contemplated by the present application. The result is that the detection beam repeatedly interacts with the excitation modulation point multiple times, each time the detection beam interacts with the sample, further information is acquired from the excitation point. Thus, in some cases, the non-radiative PARS signal can then be non-linearly expanded. In other words, in a multi-pass detection system, the detection can be redirected to interact with the sample any number of times, resulting in a corresponding degree of non-linear expansion of the non-radiative absorption contrast.

[0158] The fast scan "skip-pixel" architecture that enables high-speed PARS scanning will now be discussed in detail. The signal at each pixel in the PARS architecture and the resulting contrast (both radiative and non-radiative channels) is related to the excitation laser event and the corresponding light absorption from the tissue in the pixel of interest. To maximize image quality, it is desirable to be able to extract the PARS signal at each pixel based only on the local light absorption properties at the point of interest (e.g., the focal point of the excitation and probe beams) without contamination from the surrounding thermal environment. In addition to achieving high image quality, it is also desirable to be able to image tissue quickly, which can be achieved by increasing the repetition rate of the excitation laser.

[0159] For example, in an exemplary best case scenario, each pixel is completely isolated and the sample is allowed to fully recover to thermal equilibrium before being excited again. If the excitation events overlap spatially (e.g., overlap spatially within the excited region) and in time (e.g., occur before a long enough relaxation time), the non-radiative signal will "stack" on top of the previous excitation event and provide a false reading. That is, the signal will be influenced by the previous excitation event that it "stacks" on top of and will not be a true reading from the sample. Thus, the signal overlap is effectively 0% or close to 0%.

[0160] As an example of an exemplary worst case scenario with two overlapping excitation events, 50% of the signal measured in the second measurement is actually from the first event (e.g., two modulations of unity amplitude overlap completely, resulting in a measured amplitude of two, one from the first event and one from the second event).

[0161] The fast pitch described herein refers to the spatial separation required to ensure that the pixels do not overlap. Since a portion of the PARS signal is based on heat, increasing the repetition rate of the laser excitation significantly not only damages the tissue, but also interferes with the signal extraction of individual pixels and their associated PARS amplitudes and time-domain signal decay. Due to the energy flux of the excitation laser spot, heat will propagate to neighboring tissue regions outside of the intended target pixel region. The thermal influence region is related to the tissue type, thickness, and embedding paraffin technique (e.g., paraffin type).

[0162] To ensure that the “new pixel” is not affected by the thermal effects of a previous excitation event, it is often necessary to “skip pixels” between successive excitation pulse events. Skipping pixels can be necessary from both an image quality perspective and to protect the sample from irreversible thermal damage. The ideal distance to separate pixels along the fast axis is referred to as the “fast pitch”. In embodiments where the fast pitch is greater than the final pitch corresponding to the final desired resolution, the system must make multiple scans of the tissue to fill in the gaps of the fast pitch to ultimately achieve the final pixel pitch and resolution, which for PARS systems is nominally about 250 nm. Pixel pitch can range from a few (e.g., 1-4) nm to several (e.g., 3-7) microns depending on the desired resolution. Standard pathology systems can range from 25 nm pixels to 10 pm pixels. FIG. 1B An example of skipped pixels and the “fast pitch” axis is shown.

[0163] FIG. 1B A final pixel spacing 130 and a skipped pixel architecture 132 are shown. The final pixel spacing 130 includes sample pixels 134 distributed at Nyquist rate across a portion of a tile 136 with a spacing equal to half the resolution. The skipped pixel architecture 132 includes sample pixels 134 that form isolated spacing due to the presence of skipped pixels 138 between them. The space between sample pixels 134 can be the fast pitch. In this example, the fast pitch is 2 pm. FIG. 1B In the example embodiment shown, the tile 136 has a length of 500 pm in the x-axis (i.e., the “slow axis”) and a width of 200 pm in the y-axis (i.e., the “fast pitch” axis). For this example embodiment, eight scans are needed in the slow axis to completely fill the 250 nm final resolution pitch, which is illustrated on the tile 136 as eight sample pixels 134 with a fast pitch of 2 pm.

[0164] The ideal fast pitch is the minimum distance between two pixels (n and n+1) such that the SNR and signal waveform of pixel n+1 is not affected by the excitation event at pixel n. FIG. 1CThe difference between the radiative and non-radiative channels is shown in the following cases: in section 140, at a lower (e.g., 50 kHz) excitation pulse repetition rate or frequency (“PRR” and “PRF”, respectively), the fast pitch is equal to or higher than the ideal pitch rate; in section 142, at a faster (500 kHz) excitation pulse repetition rate (“PRR”), the fast pitch is lower than the ideal pitch rate; in section 144, at a slow (50 kHz) excitation pulse repetition rate or frequency (“PRR” and “PRF”, respectively), the fast pitch is significantly higher than the ideal pitch rate; in section 146, at a faster (500 kHz) excitation pulse repetition rate or frequency (“PRR” and “PRF”, respectively), the fast pitch is equal to or higher than the ideal pitch rate. The ideal pitch rate is related to the sample itself and will vary with the sample mechanical properties. Thus, there are different ways to determine the fast pitch. These ways can be combined or not combined and can be theoretical, empirical, or a combination of both.

[0165] One way to determine the fast pitch is to scan the barcode of the sample, which contains information such as the wax type (e.g., paraffin type) and the sample thickness. FIG. 1D An exemplary sample 148 with a barcode 150 is shown. Scanning the barcode 150 can provide information about the thermal properties of the tissue in advance. For example, the barcode 150 can contain information about sample preparation parameters, tissue thickness, paraffin type, tissue type, etc. The mechanical properties (e.g., density, conductivity, etc.) of the tissue sample 148 can be used to calculate the ideal point spacing. In other words, the correct fast pitch in the scanning direction can be calculated so as not to damage the sample 148 or negatively affect signal extraction.

[0166] Another way to determine the optical fast pitch is by experimentally measuring the time-domain signature of the sample being imaged. The thermal decay characteristics can be measured at one pixel and by correlating the time decay with a pre-calculated thermal model (e.g., thermal FEA model) to determine the ideal fast pitch between pixels. Another way to experimentally determine the optical fast pitch is to perform a full scan at different pitches in a small area and experimentally determine the pitch that does not cause thermal interference. This can be done in the sample area at the edge of the sample or in the sample clinical low value area determined by the overview camera so as not to damage critical aspects of the sample being measured.

[0167] FIG. 1E A PARS shuttle stage system 152 according to one or more embodiments of the present disclosure is shown. More specifically, FIG. 1E The status of the PARS shuttle stage system 152 when the sample slide 170 is located at the overview camera unit 154, light source-based camera scanner or secondary imaging head (as described herein) unit 156, and PARS unit 158 is shown. Additionally,FIG. 1E The shuttle stage 160 is depicted in isometric view. The PARS shuttle stage system 152 includes a sample loading area 162, an overview camera 164, a secondary imaging head 166, and a PARS system 168. The shuttle stage 160 can be configured to enable movement of a sample slide 170 between three different units. As shown, the sample loading area 162 and the overview camera 164 can be located at one end of the shuttle stage 160, the PARS system 168 can be located at the other end of the shuttle stage 160, and the secondary imaging head 166 can be located between the sample loading area 162 (and the overview camera 164) and the PARS system 168. If the sample thickness of a sample is unknown or not recorded in the barcode information, the overview camera 164 can determine the sample thickness by focusing on the top of the tissue and the bottom of the slide. The overview camera 164 can be fixed such that the sample slide 170 can be movably engaged with the overview camera 164 via a mechanical stage (e.g., the shuttle stage 160). If the depth of focus of the overview camera 164 is too large to distinguish tissue thickness, a different non-contact optical thickness measurement (e.g., laser triangulation, ultrasonic thickness measurement, time-of-flight camera, interferometry, etc.) can be implemented.

[0168] One method to implement a fast scanning architecture is to utilize a fast mechanical stage on one axis that is synchronized with the excitation repetition rate. An example of a fast scanning mechanical stage is a voice coil motor (VCM) or actuator. In this method, the speed of the stage must be synchronized with the excitation repetition rate to achieve the desired fast axis pitch. Another set of fast scanning methods creates multiple points simultaneously (i.e., at once) in a one- or two-dimensional array, rather than using only one point at a time as in the methods described above and further described below. As previously mentioned, due to signal contamination and sample damage thresholds, a minimum pitch in the fast axis direction must be maintained between synchronized points.

[0169] Additionally, a diffraction grating can be used to generate an array of points with a pitch that meets the fast pixel requirement. A one- or two-dimensional diffractive optical element (DOE) can be used to split the primary collimated beam into a multi-point array. A rotating motor can contain various diffraction gratings, and the diffractive element and corresponding fast pixel pitch can be selected based on the sample that is currently being interrogated. Alternatively, a focusing lens on a linear stage can be actuated and changed to achieve the desired fast pitch on the sample.

[0170] In general, skipping pixels in the x- and y-axes also allows a complete image (with lower resolution) to be scanned, processed, and displayed on the screen as the PARS head returns for multiple passes. The image on the screen can update its resolution as more data and pixels are completely filled. Different architectures can be utilized to enable skipping pixels and / or fast scanning.

[0171] One such architecture employs single point optical scanning.FIG. 1F An exemplary front view 400, top view 402, and isometric detailed view 404 of this scanning architecture are shown. The vibration frequency of the resonant microelectromechanical system ("MEMS") mirror (e.g., its scan frequency) is simultaneous (e.g., synchronized) with the excitation pulse repetition rate or frequency (respectively, "PRR" and "PRF") in order to rapidly optically scan the light beam across the sample slide 174 in one or two dimensions in the x-y plane of the sample slide 174. As FIG. 1F As shown, the scanning light beam can reach the entire width of the sample slide 174 in the y-axis direction through the MEMS mirror, while the width in the x-axis direction can be reached by mechanically moving the slow stage in the x-axis. The light beam path can be split into: a linear region that extends along the width of the sample slide 174 substantially parallel to the y-axis, and turnaround regions on both sides of the sample slide 174 that indicate a change in the light beam path direction as the sample slide 174 is mechanically moved in the x-axis. The fast pitch can be determined by the excitation laser PRR and the scan frequency of the MEMS mirror.

[0172] The scanning architecture 172 includes a sample slide 174, an objective lens 176, a telescope 178, a single incident collimated probe and excitation light beam 180, and a resonant MEMS mirror 182. In the scanning architecture 172, the collimated co-linear probe and excitation light beam 180 is optically scanned over the field of view ("FOV") of the objective lens 176 by using the resonant MEMS mirror 182. The resonant MEMS mirror 182 can optionally be replaced with a resonant galvanometer or a rotating polygon mirror, but the downstream architecture (e.g., the telescope 178 and the objective lens 176) remains unchanged. In slower systems, the MEMS mirror or galvanometer can operate in linear mode (e.g., non-resonant), with other design aspects remaining unchanged. To map the optical scan angle of the resonant MEMS mirror 182 to the entrance pupil of the objective lens 176, a Kepler telescope can be used to magnify the beam diameter on the resonant MEMS mirror 182 to fill the entrance pupil diameter of the objective lens 176. At the same time, the telescope 178 changes the pivot point of the optical angle range, which rotates around the entrance pupil and linearly decreases the optical scan angle by the magnification of the telescope 178. For example, in a typical system, the beam diameter at the MEMS mirror is 1 mm, and the MEMS mirror mechanically moves + / - 2.5 degrees to produce + / - 5 degrees of optical scan angle. A typical magnification of the telescope can be 3, which results in a beam diameter of 3 mm at the entrance pupil of the objective lens, and an optical scan angle of + / - 1.67 degrees rotating around the entrance pupil diameter (EPD).

[0173] Another architecture employs multi-point optical scanning. FIG. 1GExemplary front view 406, top view 408, and isometric detailed view 410 of the scan architecture are shown. Scan architecture 184 is similar in design to scan architecture 172, with the difference being that rather than sending a single collimated probe and excitation beam 180 to a scan mirror (e.g., resonant MEMS mirror 182, resonant galvanometer, linearly driven mirror, multi-faceted mirror, etc.), scan architecture 184 sends an array of multi-point spots to the scan mirror. As FIG. 1G shown, resonant MEMS mirror 182 can be used to scan multiple incident collimated probe and excitation beams 186. Scan architecture 184 reduces the overall scan time by increasing the number of spots in the non-scanned direction. A multi-point optical scan architecture can be very useful for systems that require a fast PRF. That is, since multiple beams can be pulsed alternately, the PRF can be faster, and in some cases, can be higher than the maximum vibration frequency of the MEMS mirror. For example, if two beams each have a PRF of 5 MHz, they can be pulsed alternately at an effective or equivalent PRF of 10 MHz to achieve a faster imaging time. Since the vibration frequency of the MEMS mirror is typically the upper limit of the PRF in an imaging system, pulsing the beams alternately allows for a higher PRF value without requiring the MEMS mirror to increase the vibration frequency. In other words, the MEMS mirror does not need to increase speed to maintain the minimum ideal (fast pitch) spacing.

[0174] Rather than having only one confocal beam spot at a given time, there are multiple confocal beams that can be scanned along the y-axis on sample slide 174 using a resonant scan mirror. As FIG. 1G shown, each beam can scan a separate subset of pixels, providing a faster scan speed than a single point scan architecture. One light source can provide each beam, or each beam can be provided by a different light source, or the present disclosure contemplates any other number of light sources to provide multiple beams. As FIG. 1GAs shown, multiple scan beams can reach the entire width of the sample slide 174 in the y-axis direction through the MEMS mirror, while the width in the x-axis direction can be reached by mechanically moving the slow stage in the x-axis. The beam path can be split into linear regions that extend along the width of the sample slide 174 substantially parallel to the y-axis, and turnaround regions on either side of the sample slide 174 indicating a change in the direction of the beam path as the sample slide 174 is mechanically moved in the x-axis. The scan beams can be configured such that each beam maintains the same y-value relative to each other as it moves from one side of the sample slide 174 to the other along the y-axis (e.g., the beams can only be offset relative to the x-axis such that each beam scans the same y-value at a different x-value). The most time-efficient configuration of the scan beams can be where the pitch between the simultaneous scan points (e.g., the distance between the scan beams in the x-axis direction at a certain moment in time) is equal to the height of the sample slide 174 (i.e., the x-dimension) divided by the number of scan beams. The fast pitch can be determined by the firing laser PRR and the scan frequency of the MEMS mirror. In the case of rate-limited, the number of scan beams divided by the height of the sample slide 174 is equal to the ideal fast pitch.

[0175] FIG. 1P One aspect of the disclosure as shown relates to delivering the excitation (and detection) points 640 to the sample. In the case of simultaneous delivery and detection of the beams on an array detector such as a line array or camera, the excitation and detection beams can be generated from a single detection (and excitation) source 634. A dichroic mirror (DM) 636 is used to combine the beams, which are then split into several different paths using a series of beam splitters (BS) 638. Standard turning mirrors can be used to aim the individual beams to the appropriate angles on the MEMS mirror.

[0176] FIG. 1Q Another aspect of the disclosure is shown in the case of simultaneous delivery and spectral separation of the detection beams. A single excitation source 642 can be used to provide multiple detection sources (DS) 650, 652, 654, 656, and 658 for the excitation points 644. A series of cascading beam splitters (BS) 646 can be used to split the excitation source 642, which is then combined with any number of different detection sources (DS) 650, 652, 654, 656, and 658 using a dichroic mirror (DM) 648, which have different wavelengths along independent beam paths. Standard turning mirrors can be used to aim the individual beams to the appropriate angles on the MEMS mirror.

[0177] Another variant of the multi-point optical scanning architecture allows for the use of ultra-high pulse repetition rate (PRR) lasers to effectively construct a "superfast" single-point scan. Even with the current hybrid scanning embodiment, the maximum available PRR is limited due to physical limitations associated with the MEMS scanning mirror. To overcome these challenges, a multi-point optical scanning design can be used to provide a virtual scan axis.

[0178] FIG. 1M An example of this is shown. Shown in the figure are an exemplary front view 406, top view 408, and isometric detailed view 410 of this scanning architecture. This scanning architecture is similar in design to the scanning architecture 172, with the difference being that instead of sending a single collimated probe and excitation beam 180 to a scanning mirror (e.g., resonant MEMS mirror 182, resonant galvanometer, linearly driven mirror, multi-faceted mirror, etc.), the scanning architecture 184 sends a multi-point array of light points to the scanning mirror. As shown, a resonant MEMS mirror 182 can be used to scan the multiple incident collimated probe and excitation beams 186. However, unlike the scanning architecture 184, the excitation points are not delivered simultaneously; rather, these events are separated in time. FIG. 1M

[0179] Only one excitation and probe beam point is active at a given time. However, since these points are already separated by a minimum point (i.e., fast-pitch) spacing in the alignment process, there is no need to wait for the system to adjust to a safe spacing before introducing another excitation event. Rather, another point of the multi-point array is activated, providing an excitation and probe point with the required spatial separation. This provides a "virtual" scan axis in line with the mechanical scan axis (i.e., x-axis) due to the multi-point excitation. The virtual scan axis, composed of multiple points, can be used to scan the sample slide 174 along the y-axis using a resonant scanning mirror.

[0180] As FIG. 1G ​As shown, multiple scan beams can reach the entire width of the sample slide 174 in the y-axis direction through the MEMS mirror, while the width in the x-axis direction can be reached by mechanically moving the slow stage in the x-axis. The beam path can be split into: a linear region, which extends along the width of the sample slide 174 substantially parallel to the y-axis; and a turnaround region, which is located on both sides of the sample slide 174, indicating a change in the direction of the beam path when the sample slide 174 is mechanically moved in the x-axis. The scan beams can be configured in such a way that each beam maintains the same y-value relative to each other as it moves from one side of the sample slide 174 to the other along the y-axis (e.g., the beams can only be offset relative to the x-axis such that each beam scans the same y-value at a different x-value). The most time-efficient configuration of the scan beams can be when the pitch between the simultaneous scan points (e.g., the distance between the scan beams in the x-axis direction at a certain moment in time) is equal to the height of the sample slide 174 (i.e., the x-dimension) divided by the number of scan beams. The fast pitch can be determined by the firing laser PRR and the scan frequency of the MEMS mirror. In the case of rate-limited, the number of scan beams divided by the height of the sample slide 174 is equal to the ideal fast pitch.

[0181] As FIG. 1N shown, one aspect of the present application involves delivering the excitation and probe spots 610 to the sample. In the case where multiple excitation and probe beams are not delivered simultaneously, but are introduced serially to provide "ultrafast" single-point scanning, a different approach is required. In this embodiment, multiple beams can be provided by a single excitation source 608 and probe source 600; however, this requires a different design, as FIG. 1N shown. In this design, much like FIG. 1P the design shown in FIG. 6A, a dichroic mirror (DM) 602 is used to combine the beams, which are then split into several different paths using a series of beam splitters (BS) 604. However, in this case, each path features a pulse picker (PP) 606, which is used to switch modulate the combined excitation and probe beam, resulting in a series of sequential excitation and probe "packets" that travel along independent beam paths. Standard turning mirrors can be used to aim the independent beams to the appropriate angles on the MEMS mirror. This design allows a single high-repetition-rate laser to operate like a low-repetition-rate laser array.

[0182] Alternatively, as FIG. 1OAs shown, multiple beams can be provided by multiple independent excitation sources 616, 620, 624, 628, and 632 and temporally synchronized multiple probe sources 612, 618, 622, 626, and 630. In this design, several low-repetition-rate excitation lasers are used together with several probe lasers. In each path, a dichroic mirror (DM) 614 is used to combine the excitation and probe beams. These sources are then electrically modulated to produce a series of sequential excitation and probe "packets" traveling along independent beam paths. Standard turning mirrors can be used on the MEMS mirror to aim the independent beams to the appropriate angles.

[0183] One aspect of the present disclosure relates to the ability to reconstruct high-resolution images that are not affected by mechanical or optical jitter that would cause loss of resolution in the reconstructed image. Each of the fast scanning architectures listed above has different causes of image artifacts, which makes image reconstruction challenging. The following design approaches to aid in reconstruction (both software and hardware) specifically relate to one-dimensional hybrid MEMS scanning, but aspects can also be applied to the other architectures listed above.

[0184] 1. Image Reconstruction Aid Method 1

[0185] In the current embodiment of the hybrid scanning architecture, the PARS system lacks position feedback from the MEMS positioning mirror used for optical scanning. Therefore, a series of processing steps are applied to reconstruct the image without position feedback. These methods rely heavily on structure correlation and data redundancy to iterate on the scattered data until a solution is generated that optimizes image quality.

[0186] One step in this process is to correlate each mirror scan. It is assumed that each scan of the mirror follows a sinusoidal path through the sample. The scattered data is then fit to the assumed sinusoidal position. This is observed in FIG. 1H In many cases, the direct fitting of the sinusoidal position does not work well because there is some jitter in the triggering. To correct for this jitter, the phase of the sinusoidal position is adjusted until the correlation between the scattered signals observed in the forward and backward scans of the mirror is maximized, resulting in an optimized mirror phase offset. This is observed in FIG. 1H Plot 188 shows the raw mirror scan scattered data fit to the assumed sinusoidal position, plot 190 shows the sinusoidal phase offset chosen to maximize the correlation, and plot 192 shows an example of the phase error calculated in the true image.

[0187] Another step in this process is to FIG. 1IThe iterative process is illustrated. First, all stage passes are aligned by structural correlation (e.g., step 1 in “Iteration 1” 412). Second, the aligned images are averaged to form a merged image (e.g., step 2 in “Iteration 1” 412). Third, each line (i.e., mirror scan) of each stage pass is independently repositioned to maximize correlation to the merged image (e.g., step 3 in “Iteration 1” 412). Fourth, the process is repeated until no positional offsets need to be applied (e.g., typically “Iteration 2” 414). FIG. 1J A figure is presented showing the image before correction 416 and the image after correction 418 using the image reconstruction process.

[0188] 2. Image Reconstruction Aid Method 2

[0189] When a MEMS mirror is driven in a resonant fashion, the voltage waveform is typically sinusoidal. Due to electrical instability of the waveform and mechanical instability of the mirror itself, the pixels cannot fall in the intended exact position, which results in a blurry edge of the resulting reconstructed image. One solution is to add a position sensitive detector (“PSD”) in the system that captures the entire optical run on the sensor surface. The PSD then outputs an analog voltage waveform that, after the signal is amplified and conditioned, linearly scales with position. Since the output of the PSD module is an analog signal, the signal can be converted to a digital signal via an A / D sampling card and can be synchronized with the detector channels using the same system clock or trigger. The probe beam itself can be picked up between the MEMS mirror and the telescope (e.g., using a beam sampler to sample some of the energy of the beam to capture 1% or about 1% of the beam intensity without significantly altering or affecting the original beam) and collected on a PSD or secondary (non-PARS related) collimated laser. Alternatively, an LED can be reflected from the MEMS and collected on the PSD independent of the PARS excitation and probe light paths.

[0190] 3. Image Reconstruction Aid Method 3

[0191] In one-dimensional hybrid scanning (as well as two-dimensional stage scanning), the position feedback of the stage via optical encoders, Hall sensors, or laser proximity sensors can be used and synchronized with the system trigger and clock to aid in reconstruction. The position of the stage is recorded directly in digital form.

[0192] 4. Image Reconstruction Aid Method 4

[0193] Another method that aids in image reconstruction is to use the scanning elements in the instrument to image a known spatial calibration target. In this way, the known target can act as a master reference image to reconstruct the unknown geometry, as is the case with histology samples. An example of a known spatial calibration target is an etched silicon wafer, as shown in FIG. 1K The etch depth of the silicon features (along the page depth direction) is designed to exceed the depth of focus of the main objective, so that the contrast with the focused non-etched surface can be measured. In the example aspect shown in FIG. 1K The etch depth is 5 pm. The calibration target can be mounted to the bottom surface of the histology sample carrier, which is fixed to the mechanical stage. By imaging the calibration target mounted to the same mechanical stage stack as the sample itself, the instabilities from both the MEMS mirror and the mechanical translation stage can be corrected. This method forms a design that does not require other sensor-based modalities (e.g., PSD) to aid in image reconstruction. In a typical design, the probe beam can be picked up between the last element of the telescope and the main objective. The picked-up beam can be sent to its own narrow-bandwidth, non-glass-corrected objective and focused onto the calibration target mounted on the bottom surface of the sample carrier plate. In this way, the instabilities of the mirror and stage can be calibrated.

[0194] Additionally, a silicon-based resolution target can act as a calibration target to standardize the power level and health check of the PARS system. A calibration target such as etched silicon is ideal because, since the sample is composed of pure crystalline silicon, it can produce a repeatable and uniform PARS contrast on the surface of the reference target.

[0195] 5. Image reconstruction aid method 5

[0196] In a one-dimensional hybrid scan, the radiative and non-radiative signals are acquired at each fast pixel pitch at a selected excitation laser repetition rate. The probe wavelength is continuous wave (CW) and can be continuously acquired at a higher sampling rate between radiative and non-radiative excitation events. These higher resolution data from the probe channel can be used to aid in the reconstruction of the image and supplement the reconstruction aids described above.

[0197] The multi-pass probe architecture will now be discussed in detail. In PARS, a secondary confocal detection laser is used to visualize the perturbations induced by non-radiative absorption in the optical properties. The detection laser is confocal with the excitation spot, such that the absorption-induced modulation can be captured as a change in the backscattered intensity of the detection laser. For a given probe intensity, the signal can be approximated as: PARS 激发前 ∝ I 探测 (R), where R is the unperturbed reflectivity of the sample.

[0198] Once the excitation pulse interacts with the sample, the signal can be approximated as: PARS 激发后a I 探测 (R + AR), where the pressure and temperature induced reflectivity change is denoted by AR. Then, the total PARS absorption contrast can be approximated as: PARS 信号 a PARS 激发后 -PARS 激发前 . Substituting the previous relationships for PARS 激发前 and PARS 激发后 can be obtained: PARS sig a I 探测 (R + AR) - I 探测 (R).

[0199] The backscattered signal of the multi-pass PARS (i.e., MPPARS) prior to the excitation pulse can then be approximated based on the following relationship: MPPARS 激发前 a (I 探测 (R)) n where R is the undisturbed reflectivity of the sample and n is the number of times the excitation interacts with the sample. Once the excitation pulse interacts with the sample,

[0200] the signal can be approximated as: MPPARS 激发后 a (I 探测 (R + AR)) n where the pressure and temperature induced reflectivity change is denoted by AR.

[0201] Then, the total multi-pass PARS absorption contrast can be approximated as: MPPARS 信号 a MPPARS 激发后 -MPPARS 激发前 . Substituting the previous relationships for MPPARS 激发前 and MPPARS 激发后 can be obtained: MPPARS 信号 a (I 探测 (R + AR)) n - (I 探测 (R)) n where n is the number of times the probe interacts with the sample. The PARS signal can be non-linearly extended by the backscattered detection of these repeated interactions with the sample. The detection can then be redirected to interact with the sample any number of times, thereby causing a corresponding degree of non-linear extension of the non-radiative absorption contrast.

[0202] As noted above, the multi-pass probing architecture can be oriented such that the passes consist of reflection or transmission events, which can be normal incidence to the sample or occur at some relevant transmission or reflection angle. For example, if the target is characterized by a particularly strong Mie scattering angle, it can be advantageous to orient multiple passes along this direction. The multiple passes can occur along a single (only one or exactly one) path, such as a normal incidence reflection, or along multiple paths, such as a normal incidence transmission architecture or even an architecture with additional (more than two) paths to exploit additional spatial nonlinearity.

[0203] Turning now to FIG. 1L In some cases, the multi-pass probing architecture 100 can include an excitation source 102 (e.g., a 266 nm excitation source or laser), one or more probing sources 104 (e.g., a 405 nm probing source or laser), one or more photodiodes or photodetectors 106, a circulator 108, a collimator 110, one or more mirrors 112 for directing the excitation and / or probing light, a prism 116, and a variable beam expander 118. In addition, the multi-pass probing architecture 100 can include a pair of alignment mirrors 120 for aligning the excitation and / or probing light, and one or more scanners or scan heads 122, 124 arranged on different sides of the sample. The one or more scanners can include a first scanner 122 for transmitting the excitation and probing light to the sample and a second scanner 124 arranged with a mirror 126 to allow multiple passes. A computer 128 can be used to analyze the received signals and / or control the excitation source 102 and detection source 104.

[0204] Turning to FIG. 2A In some cases, the multi-pass probing architecture 200 can be equipped with multi-pass non-radiative probing, which can simultaneously capture transmission and reflection signals (e.g., a transmission multi-pass probing architecture). It can also be equipped with a condenser lens for focusing the diverging light. At the same time, it features two independent radiation collection paths, one on each side of the sample, as shown in FIG. 2A That is, a first light beam is focused on the sample from a first side of the sample and a second light beam is focused on the sample from a second side of the sample, where the first side is opposite the second side. It will be appreciated that due to this design, the multi-pass probing architecture can facilitate imaging of certain samples, such as thin samples required for histological imaging, as the light beams are able to pass through the sample to enable imaging. For example, the sample thickness range can be from less than 1 pm to greater than 5 mm. More generally, the sample can be any thickness that light is able to penetrate.

[0205] In these examples, the multi-pass detection architecture 200 can include two excitation sources 202, 204 (e.g., a 266 nm excitation source or laser and a 532 nm excitation source or laser) with different excitation wavelengths, one or more detection sources 206 (e.g., a 405 nm detection source or laser), two objectives 208, 210, one or more photodiodes or photodetectors 212, 214, 216, 218, a collimator 220, one or more mirrors 222 for directing excitation and / or detection light, one or more dichroic mirrors 224 for directing excitation light, and one or more spectral filters 226.

[0206] In transmission, the multi-pass detection architecture 200 can use two objectives 208, 210, which are mounted on opposite sides of the sample, as shown. The excitation and detection beams from the excitation and detection sources 202-206 can be brought to a focus on the sample 228 using the lower objective 210. A portion of the modulated detection beam and / or a portion of the radiative absorption and inelastic scattering signals can be captured by the upper objective 208. In some cases, a portion of the modulated detection beam can return to the sample 228, and the returning detection beam can be captured by the lower objective 210. This portion of the returning modulated detection beam can be in the range of 1% to 100% of the light collected by the upper objective. In some cases, the lower objective 210 can also be used to capture a portion of the radiative absorption signal. The detection beam can be separated from the radiative relaxation signal via chromatic isolation. The isolated detection and radiative signals on the top and bottom of the sample are then directed to independent photodiodes, such as the photodiodes 212, 214, 216, 218.

[0207] As previously mentioned, with this architecture, both radiative and non-radiative signals can be collected on both sides of the sample. By collecting both linear and nonlinear representations of the non-radiative signal, the opportunity to capture additional unique contrast within the material is increased. As described below, this can aid in increasing the signal-to-noise ratio, or can be used in techniques such as super-resolution or super-localization.

[0208] It should be appreciated that, although the multi-pass detection architecture can be described as a transmission mode device in some cases (e.g., where the beams must pass through the sample to generate and capture signals), the multi-pass detection architecture can employ a reflection mode design. In such a design, all signals can be collected from one side of the sample (e.g., single-path, multi-pass detection architecture). This design can facilitate imaging of certain samples, such as thick samples, as the beams do not need to pass through the sample to image.

[0209] It should be understood that the above multi-pass probe architecture is not a requirement for PARS imaging. In some cases, a multi-pass architecture can not be required, and can not be used at all; in these cases, PARS can instead be described as a transmission mode or reflection mode device only. In such designs, the probe beam need only interact with the sample a single time.

[0210] FIG. 2H may be substantially similar to the architecture of FIG. 2A but does not include certain components. Specifically, FIG. 2H may not include the 50:50 beamsplitter between the spectral filter 226 and the objective lens 210. This exclusion removes the multi-pass capability.

[0211] FIG. 2B may be substantially similar to the architecture of FIG. 2A but includes additional components. Specifically, FIG. 2B may include a spectral filter 226 (with condenser lens) and photodetector 242 between the excitation source 204 and the one or more dichroic mirrors 224, and can include a spectral filter 226 (with condenser lens) and photodetector 244 between the excitation source 202 and the one or more dichroic mirrors 224. FIG. 2B These additional components in may enable excitation scattering. This is achieved due to the beam sampler redirecting a portion of the light returning from the sample to the spectral filter 226, condenser lens, and photodetector. The spectral filter isolates the excitation wavelength, and the photodetector measures the intensity, thereby measuring the scattered light intensity.

[0212] FIG. 2I may be substantially similar to the architecture of FIG. 2B but does not include certain components. Specifically, FIG. 2I may not include the 50:50 beamsplitter between the spectral filter 226 and the objective lens 210. This exclusion removes the multi-pass capability.

[0213] FIG. 2C may be substantially similar to the architecture of FIG. 2B but includes additional components. Specifically, FIG. 2C may include a beam sampler with a spectral filter 226 (with condenser lens) and photodetector 248, and can include a beam sampler with a spectral filter 226 (with condenser lens) and photodetector 246 between the mirror 222 and the photodetector 212. FIG. 2C These additional components shown can enable transmission measurements.

[0214] FIG. 2J may be substantially similar to the architecture of FIG. 2C but does not include certain components. Specifically, FIG. 2JThe 50:50 beam splitter located between the spectral filter 226 and the objective lens 210 may be excluded. This exclusion eliminates multipass capability.

[0215] FIG. 2D Can be with FIG. 2B The architecture is basically similar, but it includes additional components and removes some components. Specifically, FIG. 2D Photodetectors 216, 218, 242, and 244 can be replaced with cameras 250, 256, 258, and 260, respectively. Therefore, through these changes, FIG. 2D It could be a camera-based system.

[0216] FIG. 2K Can be with FIG. 2D The architecture is basically similar, but it does not include specific components. Specifically, FIG. 2K The 50:50 beam splitter located between the spectral filter 226 and the objective lens 210 may be excluded. This exclusion eliminates multipass capability.

[0217] FIG. 2L Can be with FIG. 2C The architecture is basically similar, but it includes additional components and removes some components. Specifically, FIG. 2L Photodetectors 212, 216, 218, 246, and 248 can be replaced with cameras 254, 250, 256, 258, and 260, respectively. Therefore, through these changes, FIG. 2L It could be a camera-based system.

[0218] FIG. 2M Can be with FIG. 2L The architecture is basically similar, but it does not include specific components. Specifically, FIG. 2M The 50:50 beam splitter located between the spectral filter 226 and the objective lens 210 may be excluded. This exclusion eliminates multipass capability.

[0219] FIG. 2E Can be with FIG. 2B The architecture is basically similar, but some components are removed. Specifically, FIG. 2E Removed from FIG. 2B All transmission components. Therefore, in reflection mode... FIG. 2E It can be FIG. 2B A reflection mode can be thought of as the pattern of an architecture when all light enters and is collected from the same side of the sample. Therefore, measurements or imaging can be performed without light penetrating the sample.

[0220] FIG. 2F Can be with FIG. 2C The architecture is basically similar, but some components are removed. Specifically, FIG. 2F Removed from FIG. 2CAll transmission components. Therefore, in reflection mode... FIG. 2F It can be FIG. 2C .

[0221] FIG. 2G Can be with FIG. 2D The architecture is basically similar, but some components are removed. Specifically, FIG. 2G Removed from FIG. 2D All transmission components. Therefore, in reflection mode... FIG. 2G It can be FIG. 2D .

[0222] FIG. 3 An excitation source architecture 300 is shown, which can be used to generate FIG. 2A to FIG. 2M Excitation sources 202 and 204 are among the excitation sources in the excitation source. The excitation source architecture 300 may include: a pump laser 302 that provides light of a specific wavelength (e.g., 1030 nm); one or more half-wave plates 304, 306; one or more optical crystals 308, 310 (e.g., lithium triborate (LBO) or barium β-borate (BBO)); one or more mirrors 312 for guiding light from the pump laser 302; one or more dichroic mirrors 314 for guiding light from the pump laser 302; a prism 316; and two variable beam expanders 318, 320.

[0223] PARS extraction method

[0224] Once an excitation event occurs at the excitation location (e.g., the location where the excitation beam is focused), the PARS system of this disclosure can collect all, substantially all, or a portion of the generated signals to extract information about the sample at that excitation location. For example, using one or more PARS signal extraction methods, the PARS system can extract information at the excitation location of the sample, such as one or more unique eigenvector characteristics. The extracted information (e.g., eigenvector characteristics) may include absorption and / or scattering properties at the excitation location, and more specifically, absorption and / or scattering properties at one or more pixel locations within the excitation location. Therefore, the extracted information (e.g., eigenvector characteristics) may contain detailed information about the sample composition, constituent biomolecules, etc. It should be understood that the PARS system of this disclosure can collect and / or extract multiple eigenvector characteristics at multiple excitation locations throughout the tissue sample / sample.

[0225] Each PARS data vector will contain 'n' PARS features, the specific number determined by the user or control algorithm. The feature vector can contain any number of extracted signals such as signal energy, total non-radiative or radiative energy, total absorption, quantum efficiency ratio, absorption difference, relative relaxation fraction, time domain signal features, blind clustering / dimensionality reduction, isolated non-radiative initial temperature and pressure signals, filter bank / frequency based extraction. These measurements can be extracted at any wavelength or combination of wavelengths. The feature vector can also contain any number of secondary measurements extracted in different combinations, calculations, or ratios of the primary features. An example of a secondary measurement can include the difference in quantum efficiency ratio (QER) at two different excitation wavelengths. In general, the PARS feature vector can contain any information collected and extracted from each PARS event.

[0226] The feature vector can then be used at the pixel level, as well as aggregated, to analyze aspects of the sample. In one example, the PARS feature vector can be correlated at the pixel level to ground truth (e.g., histochemical or immunohistochemical staining). This can provide a one-to-one mapping between the PARS data vector and different histochemical stains or their underlying biomolecular targets. This process allows for the calculation of a PARS "signature / fingerprint" for a given biomolecule or mixture of biomolecules or ground truth PARS data vector. Alternatively, the PARS vector can be analyzed aggregately, where the distribution of vectors within the sample can indicate potential diagnostic properties of the sample such as malignancy, tumor grade, molecular expression, etc.

[0227] The PARS system of the present disclosure can further process the extracted information to form a visualization such as an image. In examples where the visualization is an image, the image can be a digital image such as a raster image (e.g., JPEG, PNG, BMP, GIF, etc.) comprising a plurality of pixels or one or more pixel sets. As used herein, the term "pixel" refers to the smallest addressable element in an image. In these cases, the PARS system can assign a portion of the information extracted from the signals generated at a single excitation location, such as a feature vector property, to a pixel. In some cases, the location of the pixel, i.e., the pixel location, corresponds to a unique portion of the excitation location. If the visualization comprises one or more pixel sets, a single pixel set can correspond to all or substantially all of the information extracted from the signals generated at a single excitation location of the sample. That is, the visualization can comprise all or substantially all of the information extracted from the signals generated at a single excitation location or multiple excitation locations. In some cases, the visualization can comprise all or substantially all of the information extracted from the signals generated at multiple excitation locations, which can span the entire or substantially the entire sample.

[0228] In some examples, the visualization can then be used directly for histological diagnosis, or in conjunction with other tools such as AI to perform the diagnosis or generate more advanced colorization effects. For example, where the extracted information contains absorption and / or scattering properties, one or more values can be further assigned to the absorption and / or scattering properties at the pixel location, such as color and / or intensity values corresponding to a color space. The color space can be RGB, YCbCr, CIELAB, sRGB, YPbPr, scRGB, HSV, CMYK, or any other known color space. These color and / or intensity values can be computed using one or more PARS signal extraction methods. In some examples, the PARS system can include one or more processors configured to extract information from the generated signals, process the extracted information, and / or form visualizations as described above.

[0229] The PARS signal extraction methods of the present disclosure can be any of the signal extraction methods, signal processing methods, and / or signal collection methods described in U.S. Application Serial No. 17 / 010,500, filed August 5, 2021, entitled “Pars imaging methods,” and Patent Cooperation Treaty Application No. PCT / IB2021 / 055380, filed May 12, 2022, entitled “Photoabsorption remote sensing (pars) imaging methods,” which are incorporated by reference herein. The PARS signal extraction methods can be used for both radiative and non-radiative channels. It will be appreciated that each PARS signal can be extracted in several different ways to capture different salient details of the signal, or the signal can be used in its entirety as it evolves over time. The following PARS signal extraction methods can be used in a PARS system.

[0230] 1. Signal Energy

[0231] The PARS signal extraction method can be a signal energy measurement process. In this process, to determine the total absorption energy level at a given pixel location, the process determines the integral of the modulation of the time-domain signal FIG. 4 The DC value of the signal (intensity before excitation) is computed and subtracted from the signal. Then, the remaining modulation is integrated to compute FIG. 4 the highlighted region shown. That is, the integral of the modulation of the signal is extracted independent of the DC offset of the signal. The higher the absorption, the greater the integral of the modulation, the longer the duration, the greater the integral corresponds to. This is a simple and fast method and is robust to additive noise. This method can be applied directly to any generated radiative or non-radiative signal to capture an estimate of the total absorption level.

[0232] This approach can be further enhanced by applying de-noising / filtering prior to extracting the integrals. For example, matched filtering (e.g., based on K-means extraction) can be used to extract the total signal energy. This technique aims to optimally filter the signal based on the expected time-domain shape. This provides a robust anti-noise approach for determining the absorption amplitude or pixel “brightness”.

[0233] 2. Total non-radiative or radiative energy

[0234] In PARS architectures and systems using multiple excitation sources of different wavelengths, there are radiative and non-radiative absorption measurements (e.g., extractable information) for each wavelength. That is, by isolating the generated signals by wavelength, the PARS system can extract and / or collect radiative and non-radiative absorption measurements for each wavelength at the excitation location. Thus, it can be advantageous to view the radiative or non-radiative relaxation energy for a combination of all wavelengths. For example, FIG. 5 and FIG. 6 present exemplary images of total radiative and non-radiative energy, respectively.

[0235] 3. Total absorption

[0236] By capturing both radiative and non-radiative absorption fractions (e.g., extractable information) at the excitation location, PARS architectures and systems can facilitate enhanced visualization. Unlike traditional modalities that independently capture some radiative or non-radiative absorption, in PARS, the contrast can not be constrained by efficiency factors such as photo-thermal conversion efficiency or fluorescence quantum yield. Thus, PARS can enhance sensitivity to any range of chromophores. The total absorption TA( ) for any excitation wavelength can be calculated as the sum of the absorption amplitudes of all radiative absorption signals (P r ( )) and non-radiative absorption signals (P nr ( )).

[0237] TA( ) = P r ( ) + P nr ( )

[0238] FIG. 7 shows an exemplary total absorption rate image captured using a 266 nm excitation source, and FIG. 8 shows another exemplary total absorption rate image captured using a 532 nm excitation source.

[0239] Total absorption can also be calculated at several wavelengths. For example, similar total absorption can be calculated for 266 nm and 532 nm excitation. This amounts to the sum of the independent total absorption characteristics for each wavelength. FIG. 9 shows an exemplary image containing both 266 nm and 532 nm radiative and non-radiative relaxation effects. As shown, FIG. 7 to FIG. 9The total interaction is captured. In other words, this modality can capture the effect simultaneously.

[0240] 4. Quantum efficiency ratio

[0241] Once the information is extracted from the signal generated at the excitation location, the PARS system can extract / collect additional biomolecule-specific details from the extracted information. For example, additional biomolecule-specific details can be extracted based on the proportional radiative and non-radiative relaxation characteristics. Different biomolecules can exhibit a stronger tendency for radiative or non-radiative relaxation. This is determined by known unique material properties such as fluorescence quantum efficiency. Thus, additional biomolecule-specific details can be further extracted from the relative proportion of radiative and non-radiative absorption fractions. This is denoted as the quantum efficiency ratio or QER, which is calculated as follows:

[0242]

[0243] In the PARS system, this can be done at any given excitation wavelength. FIG. 10 An exemplary image of a PARS system using 266 nm excitation is shown, and FIG. 11 An exemplary image of a PARS system using 532 nm excitation is shown.

[0244] QER can also be calculated at several wavelengths. For example, similar QERs can be calculated for both 266 nm and 532 nm excitation. FIG. 12 An exemplary image generated by a PARS system using both 266 nm and 532 nm excitation is shown.

[0245] QER can then be used in combination with other aspects to produce useful visualizations, such as coloration. For example, in a PARS system using both 266 nm and 532 nm excitation. QER can be combined with total absorption as shown in FIG. 13 In this example, QER is used to define the color of the image, while total absorption is used to define the intensity. In this case, QER is scaled between [0, 1] and used to define the hue value of the HSV color space. At the same time, total absorption is scaled between [0, 1] and used to define the saturation and lightness. Thus, in this example, the color of each pixel (from QER) can provide details about the type of biomolecule at a given pixel, while the brightness (from total absorption) can provide some information about the concentration of the biomolecule. Similar approaches using any other color space (such as YCbCr, Lab, RGB, etc.) can be envisioned, where the intensity is defined by total absorption, while the color is defined by QER. The PARS system can be configured to generate a combined QER-total absorption image.

[0246] 5. Absorption difference

[0247] Once the information is extracted from the signal generated at the excitation location, the PARS system can further process the extracted information, such as by assigning a color value to the extracted information. For example, when using excitation sources with different wavelengths in the PARS system, the absorption difference visualization can be used to compare the observation of any two (or more) absorption properties. This visualization provides a method to assess the relative difference in absorption intensity at a given wavelength for each pixel location of the excitation location. The absorption difference for two wavelengths is calculated as follows:

[0248]

[0249] where A is the absorption signal (radiative or non-radiative) at a given wavelength, and A is the corresponding radiative or non-radiative absorption signal at a second wavelength. Assessing the absorption difference between two wavelengths can significantly enhance the separability of different biomolecules compared to the observation of either independently or in combination.

[0250] This method can be applied to images as shown in FIG. 14 to FIG. 15 where a color map is assigned according to the absorption difference values. Red indicates stronger absorption at 266 nm, while blue indicates stronger absorption at 532 nm. FIG. 14 shows a non-radiative difference contrast image, while FIG. 15 shows a radiative difference contrast image.

[0251] 6. Relative relaxation fraction

[0252] In some examples, the extracted radiative or non-radiative absorption properties, or different combinations thereof, can be expressed as a fraction of the total absorption. This enables the assessment of the proportional absorption at each wavelength independent of the biomolecule concentration in each region. Furthermore, this can also allow for easier comparison of signals captured at different wavelengths. For example, the non-radiative signal at a single wavelength can be expressed as a fraction or percentage of the total non-radiative relaxation. In another example, the non-radiative relaxation at a single wavelength can be expressed as a fraction or percentage of the total absorption (including radiative and non-radiative relaxation).

[0253] The radiative relaxation signal is an emission spectrum. This emission spectrum can have a unique correlation with the excited biomolecule. In other words, for a given excitation wavelength, two different biomolecules are expected to exhibit different spectral emissions. If the spectral difference is significant, this can help to better separate the two biomolecules.

[0254] 7. Time-domain signal features

[0255] Additional PARS contrast exists in the time evolution of the PARS signal. Important information about the biomolecular composition of the sample can be encoded into the various time domain signals. Unique signatures can be obtained in the signal frequency, rise time, fall time, amplitude, etc. That is, by measuring these signatures, the PARS system can then collect and / or extract further information (e.g., chromophore-specific information) from a single excitation event. This can enable, for example, chromophores to be unmixed (e.g., probed, separated, or otherwise made discrete in composition species and / or subspecies) from a limited number of excitation events.

[0256] In some examples, the shape of the non-radiative PARS signal depends on the evolution of pressure and temperature induced changes within the sample. In these examples, the shape of the modulation that evolves over time then captures details of the local material properties. On a short time scale, the signal decay rate can be related to the speed of sound of the material. On a longer time scale, the signal decay rate can be related to the speed of heat propagation. Additionally, if a shear wave is generated, the signal decay rate can be related to a different speed. The rise time of the signal can also provide additional information about mechanical properties (e.g., speed of sound). This means that the PARS time domain signal can capture properties such as thermal diffusivity, electrical conductivity, speed of sound, density, heat capacity, and acoustic impedance, which can be extracted and collected by the PARS system for further processing.

[0257] Similar material-specific signatures can also be encoded in the time evolution of the PARS radiation modulation. As with the non-radiative signal, the radiation signal time domain shape is determined by the material properties. For example, if a fluorescent signal is isolated from the radiation relaxation signal, the time-resolved fluorescence lifetime can be captured. The fluorescence lifetime is a biomolecule-specific property that can be used to directly identify the biomolecular composition.

[0258] These time-evolving signals can be decomposed into measurable unique (e.g., in amplitude or amplitude and / or evolution time) signature features. This rich information can then be used to improve the available contrast, provide additional multiplexing capability, and provide signature molecular markers of the constituent chromophores. Several methods can be used to capture features indicative of material properties from the time domain signals. Methods can include techniques such as principal component analysis, Fourier analysis, frequency decomposition, Fourier principal component analysis, fitting methods, K-means methods, or wavelet extraction methods. These methods can be applied to both the radiation and non-radiation time domain signals. Any information or signatures extracted from the time domain signals can be included as additional information in the PARS data vector for enhanced data for further analysis.

[0259] 8. Blind clustering / dimensionality reduction

[0260] In some examples, to collect or extract further information, the PARS system can use blind clustering and / or dimensionality reduction methods to compress the time domain signals into fewer representative features, such as to identify time domain features that are relevant to underlying sample properties. Examples of some underlying methods include K-means clustering, principal component analysis, principal linear component decomposition, or other signal decomposition methods. Alternatively, intelligent AI-based clustering methods can be used. These blind methods have the advantage that they do not require prior information about the signals. This can simplify processing when the sample (such as a specimen) is complex and can have a large number of available time domain features.

[0261] If properly implemented, clustering can identify signal features that capture material-specific information of the underlying sample, such as thermal diffusivity, electrical conductivity, sound velocity, density, heat capacity, and acoustic impedance. These feature intensities can then be extracted and used directly. Alternatively, the extracted feature intensities can be used with further processing to produce unique visualizations.

[0262] For example, a specialized K-means clustering method can be used to extract / collect signal features from the time domain signals generated at the excitation location, as shown in FIG. 16A to FIG. 16D . FIG. 16A to FIG. 16C K-means feature extraction applied to a saved thin section of human breast tissue is shown. In this example, the ultraviolet excitation (e.g., 266 nm) can target several biomolecules, such as collagen, elastin, myelin, DNA, and RNA, while FIG. 16D is a plot showing FIG. 16A to FIG. 16C feature extraction. As shown, the feature intensities present in each time domain are displayed along with the corresponding features within the time domain signal. Subsequently, clustering can be used to identify three unique time domain features. The intensity or prevalence of each feature can be extracted from the time domain and presented in a corresponding feature representation, such as feature 1 FIG. 16A , feature 2 FIG. 16B , and feature 3 FIG. 16C .

[0263] The extracted feature-specific images can then be used for further processing, or can be viewed directly. In one example, such as when further processing, color values can be assigned to each pixel based on the extracted feature intensities, as shown in FIG. 16A to FIG. 16C . In another example, each of the feature images in FIG. 16A to FIG. 16C can be assigned to one of the red, green, or blue (RGB) channels to generate a colorized image, as shown in FIG. 17As shown. Subsequently, the color and intensity of each pixel can be described by the proportional presence of these three features in the temporal signal. In this example, the cell nucleus (which may appear as the first color; in this example, it is green) blends with the surrounding connective tissue (which may appear as the second color; in this example, it is blue / purple).

[0264] In another example, the extracted temporal features can be combined with other PARS features to create visualizations such as coloring. FIG. 18 As shown. In these examples, two features can be further extracted (e.g., additional processing) by the PARS system using the K-means method. Any color space (e.g., RGB, YCbCr, CIELAB, sRGB, YPbPr, scRGB, HSV, CMYK, etc.) can be used to form the hue based on these features. For example, in the YCbCr color space, the color value of each pixel (i.e., the chroma-blue (Cb) and chroma-red (Cr) channels) is defined by the presence of features extracted using the K-means method. Simultaneously, the intensity value of the color (i.e., the luminance (Y)) channel is assigned based on the energy of the PARS non-radiative signal. That is, the color value assigned to a pixel can be determined based on the extracted features (e.g., k-means features), while the color intensity can be determined by the amount of energy absorbed. In this example, the measurements are scaled within the range [0,1] to utilize the full range of the YCbCr color map. FIG. 18 As shown, for example, a cell nucleus might appear as one color (white), while connective tissue might appear as different colors (blue and orange shading) depending on its signal composition. That is, white represents color values ​​235, 128, 128, and the intensity range depends on the intensity (from black to white) at a specific pixel from 16 to 235, while the exemplary blue and orange shading represent color values ​​X, 16, 240 and X, 220, 36, respectively, with intensity ranges from 16 to 235. In some cases, it may be desirable to convert the color value and / or intensity value of each pixel in the YCbCr color space to another color space, such as the RGB color space. It should be understood that blind clustering and / or dimensionality reduction methods may help to highlight proportional temporal features without depending on biomolecule concentration.

[0265] 9. Isolation of non-radiative initial temperature and pressure signals

[0266] As previously mentioned, in PARS, the initial nonradiative signal is attributed to the modulation induced by pressure (photoacoustic signal) and temperature (photothermal signal) in the local material properties of the sample. While heat is always deposited, photoacoustic pressure may only be generated under specific conditions. In the case of generated pressure, the initial pressure and temperature signals can be isolated and evaluated independently.

[0267] In the case where the amplitude modulation of the non-radiative signal as a confocal probe source is captured, in most samples, the pressure-induced modulation determined by the speed of sound is expected to be faster and orders of magnitude higher than the thermal modulation determined by the thermal conductivity. For example, the photo-thermal signal used to generate an image of the sample can be measured within 500 ms of the excitation event, while the photo-acoustic signal used to generate an image of the sample can be measured within 500 ns of the excitation event. More generally, temperature (e.g., photo-thermal signal) can be measured once the pressure (e.g., photo-acoustic signal) has left the region. This can be related to measuring temperature in the range of ps to ms (e.g., 1 ps to 500 ms) and pressure in the range of ps to ns or longer (e.g., 1 ps to 500 ms). The decay can occur within ps to ms, but it is contemplated in this disclosure to be able to measure faster. In particular cases (e.g., metal samples), the speed of occurrence of the temperature effect can be faster than the given range. This will be further explained below.

[0268] For example, FIG. 19 is the PARS non-radiative pressure (photo-acoustic) and temperature (photo-thermal) induced modulation in the local optical properties of the sample as observed by the probe source of the PARS system. FIG. 20A to FIG. 20C is shown the PARS non-radiative pressure (photo-acoustic signal) and temperature (photo-thermal signal) induced modulation in the local optical properties of the sample as observed by the probe source of the PARS system. In FIG. 19 With FIG. 20A to FIG. 20C In this case, the pressure signal is captured by an initial fast signal, while the temperature signal is a slower transient signal. This means that the pressure-induced signal can be isolated from the thermal signal, enabling specific assessment of independent features.

[0269] In particular, FIG. 20B is shown an exemplary time domain dominated by temperature, and the pressure signal cannot be distinguished. FIG. 20C is shown an exemplary time domain where the PARS probe point position is shifted with respect to the excitation point. This means that the fast propagating acoustic signal reaches the probe point before the slower propagating thermal signal, creating a directly distinguishable signal region.

[0270] By isolating the pressure signal, pressure-specific properties such as the speed of sound, acoustic impedance, and absorber size can be directly extracted from the PARS pressure modulation. For example, this can allow direct measurement of the speed of sound at the probe focus. Alternatively, since the pressure response is related to the absorber size, this can facilitate super-resolution imaging.

[0271] In contrast, if the thermal signal is isolated, properties such as the speed of thermal propagation or specific heat capacity can be determined independently. Furthermore, by isolating the two signals, the relationship between them can be assessed. Based on the relative presence and proportion of pressure and temperature modulation, properties such as photothermal conversion efficiency, isothermal compressibility, and elasto-optic properties can be measured (and thereby extracted and / or collected by the PARS system).

[0272] In some samples, specific portions of the non-radiative signal can be targeted as a way to improve the signal-to-noise ratio (SNR). Initial pressure modulation can provide a higher order of magnitude of modulation strength in some samples, allowing for a significant increase in image fidelity.

[0273] In another example, pressure modulation can be targeted with thermal modulation isolated to allow for faster imaging. The speed of propagation of the pressure signal in the sample is proportional to the speed of sound in the medium, which is typically about 1000 m / s in biological samples. The speed of propagation of the thermal signal in the sample is proportional to the thermal conductivity, which is typically about 0.001 m / s. Thus, the dissipation of pressure is orders of magnitude faster than temperature. By targeting only the pressure signal, the speed of imaging can be orders of magnitude faster, as the pressure signal propagates much faster than the thermal signal.

[0274] 10. Filter set / frequency-based extraction

[0275] Another method of capturing signal features can rely on the presence of frequency information encoded in the time-domain signal. To isolate the signal strength associated with a particular frequency or band of frequencies, a series of analog or digital filters can be used to isolate specific frequency bands in the time-domain signal. This can be performed by splitting the raw analog signal from the photodetector and recording it on two independent channels, or it can be performed digitally. The specific frequency bands can then be processed according to any of the methods described above, such as signal integration / energy extraction, blind clustering, or any other processing method.

[0276] 11. Fast signal acquisition

[0277] In some PARS architectures, the non-radiative absorption signal is probed as a modulation of the backscattered probe intensity. Extracting the modulation and its energy from the scattered signal is a key step in forming an image. One such method of extracting the PARS signal is to use an optimized analog or digital filtering method that uses targeted high-pass and low-pass filters to specifically isolate the non-radiative-induced modulation. This method is particularly beneficial because it guarantees that the non-radiative modulation occurs at a higher frequency than the local scattering contrast.

[0278] Thus, in PARS, a high-pass filter can be chosen to completely eliminate the scattered signal while preserving the PARS non-radiative modulation. To eliminate the scattered signal, the maximum spatial frequency of the scattering can be calculated as follows:

[0279]

[0280] where F is the maximum frequency of the scattered signal. In the case of the 1 MHz excitation source hybrid scan embodiment, this level is approximately 3.5 MHz. 散射信号最大

[0281] A low pass filter can be used in conjunction to eliminate extraneous high frequency noise in the signal while aiming to preserve as much information in the original PARS signal as possible. For example, in this system, a 50 MHz low pass filter is applied to eliminate extraneous electrical noise in the signal since the photodiode bandwidth is 50 MHz. By using a 3.5 MHz high pass filter and a 50 MHz low pass filter, the non-radiative signal can be directly isolated from the scattered signal. Then, a variety of methods (including maximum amplitude projection, matched filtering, etc.) can be used to calculate the modulated energy from the filtered signal.

[0282] PARS optimization

[0283] Since PARS (including the related architectures, systems, and methods) provides a unique set of contrasts, it is beneficial in some cases to further optimize PARS. Some of these optimization techniques or methods for PARS architectures and systems (e.g., system operation) and / or PARS extraction methods (e.g., imaging processing methods) can include, but are not limited to, the following optimization techniques or methods.

[0284] PARS architecture and system optimization

[0285] 1. System alignment

[0286] The PARS architectures and systems feature multiple excitation and detection points that are aligned in an appropriate arrangement, such as employing a confocal arrangement in some aspects, to obtain the expected pressure (photoacoustic) and temperature (photothermal) signals, similar to the case discussed with respect to FIG. 20B to FIG. 20C .

[0287] 2. Auto-focusing

[0288] In some cases, it can be very important to collect sample images and data from the best focus plane. As used herein, the term "best focus plane" refers to a particular location of any detection or excitation source of a PARS system at which the system can collect the sharpest images from a sample and / or can collect the most accurate data. An auto-focusing algorithm can be used to determine the best focus plane for the scattered, non-radiative, and / or radiative channels of any detection or excitation beam. For a given region of interest (ROI), multiple acquisitions are made at a given depth range (e.g., the Rayleigh range of the beam) at a particular interval distance. An exemplary depiction of this case is shown in​FIG. 21 is shown. FIG. 21 An example of an axial depth scan in 500 nm steps over a range of + / - 2 pm is shown. A much smaller depth scan area than the total ROI scan area is used to determine the focal point.

[0289] At each axial position, a scalar focus metric related to the relative sharpness of the given layer is then calculated. An appropriate function (e.g., parabolic or Gaussian) is then fit to the sharpness vs. axial position curve. The peak of this fit function corresponds to the best focus plane. An example of this case (based on FIG. 21 ) is shown in FIG. 22 .

[0290] A subset of the area of the entire scan ROI can be used as the depth scan area. In these cases, the best focus plane of the entire ROI is determined from this representative subset. This is depicted in FIG. 21 .

[0291] In some PARS systems, all excitation and probe beam spots can be axially co-aligned, thus sharing the same best focus plane. As a result, the auto-focus algorithm can be performed for a single wavelength or data channel. For example, the probe scattering channel can be used individually to determine the focus plane for all data channels collected using the PARS system.

[0292] The auto-focus algorithm can also be used as a tool to guide the axial co-alignment of all probe and excitation points present in the PARS system. With the auto-focus algorithm, the best focus plane of each excitation and probe beam can be determined. Using this information, each light spot position can be adjusted until their best focus planes match / align, thus achieving optimal axial beam overlap.

[0293] 3. Automated whole-slide imaging

[0294] In some examples, PARS is able to image a whole-slide sample (e.g., >1 cm2) by individually scanning various sub-areas (e.g., 0.5 mm2) at high resolution (e.g., 250 nm per pixel), which can then be recombined and stitched together using automated whole-slide imaging. In these cases, the sub-areas or tiles are arranged in a grid-like pattern to best cover the entire sample area. FIG. 23 An example of these sub-areas of a tissue slide is shown.

[0295] In automated whole slide imaging, tissue boundaries are determined using camera images or slide previews before the sample area is divided into sub-regions. Tissue boundaries or regions of interest can be manually traced or automatically determined using a boundary detection algorithm. As an alternative or in addition to a camera, a low and / or high resolution scatter of a probe laser can also be used to generate slide images or previews. In other architectures, camera-based imaging (e.g., attenuation, autofluorescence, or brightfield) can be used to guide PARS acquisition while providing additional details about the sample.

[0296] In some cases, there can be a small amount of intentional overlap between adjacent tiles. This provides some image redundancy between tiles to help with the stitching and contrast / brightness equalization of the entire whole slide image.

[0297] Tiles can be imaged at their best focus plane, which can be determined using an autofocus algorithm as described above. With reference to FIG. 23 , tiles can be labeled as edge tiles (blue) or interior tiles (red). As used herein, the term “edge tile” refers to a tile that does not cover enough tissue area for the autofocus algorithm to accurately assess focus. For example, if a tile contains mostly background glass, the algorithm can focus on the glass slide rather than the tissue. Edge tiles can be scanned at the same focal distance as the nearest red tile to approximate their best focus. Alternatively, the focus of an edge tile can also be found by running the focus algorithm after masking out pixels corresponding to the glass layer.

[0298] 4. Whole slide stitching and contrast equalization

[0299] In whole slide images, there can be subtle contrast and brightness variations between adjacent tiles. In these images, these variations exist in each image channel. FIG. 24 An example of these contrast variations in the scatter channel is shown.

[0300] Contrast equalization algorithms can be used to address the contrast and brightness variations. The contrast equalization algorithms can be broken down into two independent algorithms that run sequentially. The first algorithm is a global equalization algorithm that shifts and scales the histogram of each tile based on the difference in mean and standard deviation between the surrounding tiles and the overlapping pixels of the interior tile. The second algorithm corrects for two-dimensional contrast gradient shifts between tiles. These algorithms shift and scale individual pixels of each tile based on local intensity statistics that are interpolated from the difference between the surrounding tiles and the overlapping pixels of the interior tile. FIG. 25 The results of running this algorithm on the images in FIG. 24 are shown.

[0301] It should be appreciated that aspects disclosed in this section can be used with various types of systems and / or architectures, such as hybrid scanning, two-dimensional optical scanning, cameras, line scanning, etc.

[0302] PARS extraction method optimization

[0303] In addition to PARS architecture and system optimization, PARS extraction method optimization methods can also be used, such as image processing methods, which are particularly beneficial for PARS compared to images acquired from conventional modalities. These methods are specifically developed to handle the unique spatiotemporal evolution of PARS radiative and non-radiative (e.g., photoacoustic and photothermal) data. The methods described herein specifically exploit the unique characteristics of the PARS data channels to filter, enhance, or modify the data in a desired manner. Some of these methods can include, but are not limited to, the following methods.

[0304] 1. Local spatiotemporal averaging

[0305] In some cases, the signal-to-noise ratio can be affected by additive or measurement noise present in the system. It can be desirable to mitigate these effects by performing a specific filtering or averaging. In the case of PARS time-domain signals, samples present a high degree of spatial and temporal correlation. This high degree of correlation can be used to denoise the time-domain signals prior to intelligent clustering or signal extraction operations.

[0306] For example, data volumes are reconstructed according to two spatial axes, while the third axis contains the time-domain signals. This can facilitate spatial domain processing operations prior to time-domain signal extraction. Local averaging can be performed on the signals in the spatial axes to provide a smoothing effect while preserving information on the time axis. FIG. 26 is an example of a local spatiotemporal filtering implementation. The signal is spatially reshaped in the lateral and longitudinal dimensions, while the time constitutes the third dimension. Then, spatial filtering can be performed on the signal while preserving the time signal quality.

[0307] Similar non-intelligent methods can be performed on any or all of the PARS radiative, non-radiative, and scattering channels. This method can be applied to tasks such as denoising, followed by k-means clustering to explore previously explored signal shapes. As previously described, the same method can also be applied prior to extracting the absorbed energy of the signal.

[0308] 2. Local statistical image smoothing

[0309] In some PARS systems, the imaging noise of the non-radiative channel can be closely related to the measurement noise of the probe source. As the modulation intensity is reduced, the additive noise becomes larger relative to the PARS non-radiative amplitude modulation. That is, as the PARS signal level is reduced, the signal-to-noise ratio is expected to decrease. In view of this relationship, PARS images can be filtered based on the assumption that lower signal levels will exhibit lower SNR. The filtering acts as a kind of adaptive outlier rejection method, intended to correct for local variance in the PARS data based on expected variance and intensity. To perform this filtering, the mean and standard deviation of a local neighborhood is computed. The central pixel of the neighborhood is corrected to be within a given variance range of the local region. The allowed variance is scaled based on the local intensity, where lower intensities allow for smaller variance, as the expected noise will be higher. It will be appreciated that this filtering method can reject bright or dark outliers in the image without affecting image clarity or producing any blurring. FIG. 27 An example is shown of applying this PARS local statistical image filtering method to the non-radiative contrast channel of images captured in a human skin tissue thin section.

[0310] 3. Total absorption variance correction

[0311] In some PARS systems, there can be a high degree of correlation between the radiative and non-radiative sets at each pixel location. Since in these cases both contrasts are generated from the same excitation event, common mode noise associated with the excitation pulse can be present in both the radiative and non-radiative data sets. Furthermore, the structures can have significant spatial similarity in both visualizations. However, since the collection path and mechanism used by each contrast is slightly different, this amounts to two independent measurements of the contrast and excitation noise at each pixel. This high degree of correlation and measurement independence can be used to denoise the resulting radiative and non-radiative images.

[0312] A total absorption variance correction method can be used to isolate the common mode excitation pulse energy noise from the images. At spatial frequencies above the system resolution, excitation noise can occur in both data sets. To extract the sub-resolution excitation induced changes, the images can be high pass filtered. This provides two independent measurements of the local excitation noise (based on radiative and non-radiative). The measurements extracted from each data set (radiative and non-radiative) can then be used to correct for the excitation induced variance in the opposite data set. This amounts to performing a reference correction of the pulse energy. It will be appreciated that this filtering and correction method does not result in any image blurring, as the correction is derived from independent sources. FIG. 28 An example is shown of applying total absorption variance correction to a human skin tissue thin section.

[0313] Example

[0314] The following examples set forth preferred embodiments of the mechanisms, architectures, systems, and methods according to the present disclosure. It should be understood, however, that these examples are provided by way of illustration only, and that any combination of the elements from the examples provided herein should not be construed to limit the overall scope of the present disclosure.

[0315] Example 1

[0316] The proposed embodiment uses two excitation sources and one shared probe source. Each excitation wavelength is chosen to target the unique radiative and non-radiative absorption properties of local biomolecules. In this example, the first wavelength is 266 nm, which is highly absorbed by DNA. This reveals the nucleus structure and connective tissue, as shown in FIG. 29 reveals the red blood cell structure and connective tissue, as shown in FIG. 30 The probe source is a 405 nm continuous wave source. It is chosen to provide high resolution and sensitivity.

[0317] Radiative relaxation and inelastic scattering of these two wavelengths of radiation can capture a broad range of the most common biomolecules, such as collagen, elastin, myelin, etc. Each tissue responds slightly differently to 266 nm FIG. 31 ) and 532 nm FIG. 32 ) excitation. Specifically, FIG. 31 and FIG. 32 reveal the connective tissue structure and dust contamination artifacts.

[0318] Finally, PARS can also provide optical scattering from each beam that interacts with the sample. This includes both the excitation sources and the probe source. The scattering images primarily reveal the structural morphology of the sample. FIG. 33 An example of the light scattering contrast due to the 405 nm probe source is shown in FIG. 35 An example of the excitation scattering contrast due to the 266 nm excitation source is shown in

[0319] In addition to the morphological information, the scattering can also carry indirect absorption details. In some cases, the scattering intensity of the excitation and probe beams can have a slight dependence on the local absorption properties of the sample. As FIG. 34 shown, red blood cells (outlined by the dashed line) exhibit very high absorption at the 405 nm probe wavelength. Therefore, they appear as slightly dark spots in the scattering image. A biomolecule or target of interest can appear as a relatively dark spot in the light scattering contrast image compared to the surrounding non-absorbing medium.

Claims

1. An imaging device for histological and / or molecular imaging of a tissue sample, the device comprising: one or more light sources, wherein the one or more light sources are configured to generate: i) one or more excitation beams configured to be directed to an excitation location focused on the tissue sample to generate a signal in the tissue sample; and ii) one or more interrogation beams configured to be directed to a probe location, wherein a portion of the one or more interrogation beams returned from the tissue sample is indicative of at least some of the generated signal; a photodetector configured to probe a radiation signal from the tissue sample; and one or more processors configured to: generate an image of the tissue sample using only pressure (photoacoustic) signals from the generated signal; generate an image of the tissue sample using only temperature (photothermal) signals from the generated signal; and generate an image of the tissue sample using both photoacoustic and photothermal signals from the generated signal.

2. The device of claim 1, wherein photoacoustic signals used to generate the image of the tissue sample are measured in a range of one picosecond to 500 milliseconds of an excitation event caused by the one or more excitation beams.

3. The device of claim 2, wherein photothermal signals used to generate the image of the tissue sample are measured in a range of one microsecond to 500 milliseconds of the excitation event caused by the one or more excitation beams. a first excitation light source configured to emit light at a first wavelength; and a second excitation light source configured to emit light at a second wavelength different from the first wavelength.

5. The device of claim 4, wherein light at the first and second wavelengths is configured to target unique radiative and non-radiative absorption properties of local biomolecules in the tissue sample.

4. The apparatus of claim 1, wherein the one or more light sources comprise:

6. The device of claim 4, wherein the one or more processors are configured to generate an image based on photoacoustic and / or photothermal signals from: only excitation at the first wavelength; and only excitation at the second wavelength.

7. The device of claim 4, wherein the one or more processors are configured to generate an absorption difference image based on relative differences in 1) the photoacoustic and photothermal signals from only excitation at the first wavelength, and 2) the photoacoustic and photothermal signals from only excitation at the second wavelength.

8. The device of claim 1, wherein the one or more processors are configured to generate transmission and reflection attenuation maps via light scattering contrast images of the one or more interrogation or excitation beams.

9. The device of claim 8, wherein biomolecules or targets of interest appear as relatively darker spots in the light scattering contrast images than the surrounding non-absorbing medium. ​ ​ ​ 10. The apparatus of claim 1, wherein the tissue sample comprises one or more of a freshly excised tissue specimen, a preserved tissue specimen, a prepared tissue specimen, an extracted tissue specimen, or a live tissue.

11. The apparatus of claim 1, further comprising a temperature control device configured to adjust a temperature of the tissue sample.

12. The apparatus of claim 1, further comprising a glass slide for housing the tissue sample, wherein the glass slide comprises an ultraviolet transparent material configured to allow imaging through the glass slide.

13. The apparatus of claim 1, wherein the one or more processors are further configured to: calculate an intensity of a signal generated before excitation; subtract the calculated intensity from an intensity of a signal generated after excitation to determine a residual modulation; integrate the residual modulation; and use the integration to estimate a total absorption level of a radiative or non-radiative signal.

14. The apparatus of claim 13, wherein the one or more processors are configured to apply de-noising or filtering prior to extracting the integration.

15. The apparatus of claim 1, wherein the one or more processors are configured to use all of the photoacoustic signal, the photothermal signal, and the radiative signal to generate an image.

16. The apparatus of claim 1, wherein the one or more processors are configured to use 1) the photoacoustic signal and the photothermal signal and 2) a QER ratio of the radiative signal to generate an image.

17. The apparatus of claim 16, wherein the one or more processors are configured to use the following to generate a combined QER-total absorption image: i) the QER ratio to define a color of the combined QER-total absorption image; and ii) all of the photoacoustic signal, the photothermal signal, and the radiative signal to define an intensity of the combined QER-total absorption image.

18. The apparatus of claim 17, wherein the color provides information about a type of biomolecule in the combined QER-total absorption image and the intensity of the combined QER-total absorption image provides information about a concentration of the biomolecule.

19. The apparatus of claim 1, wherein the one or more processors are further configured to extract a time-domain characteristic to form a visualization that distinguishes different biomolecules with different colors.

20. The apparatus of claim 1, further comprising a secondary imaging head, wherein the secondary imaging head is a camera-based probe configured to perform wide-field, high-resolution imaging at a high rate.

21. The apparatus of claim 1, wherein the one or more light sources are one or more of: i) a white light source; and ii) an isolated wavelength; wherein the one or more light sources are configured to provide one or more of: i) a brightfield image; ii) a measurement of light attenuation within a sample; and iii) a measurement of autofluorescence within a sample.

22. The apparatus of claim 1, wherein the one or more excitation beams and / or the one or more interrogation beams do not fill the objective lens used for histology and / or molecular imaging of the tissue sample.

23. The apparatus of claim 1, wherein the one or more excitation beams and / or the one or more interrogation beams exactly fill or overfill the objective lens used for histology and / or molecular imaging of the tissue sample.

24. The apparatus of claim 1, the one or more processors are further configured to generate an image using radiation signals detected by the photodetector, the radiation signals being autofluorescence.

25. The apparatus of claim 1, the photodetector is configured to detect non-radiation signals dominated by temperature (photothermal) signals.

26. The apparatus of claim 1, the photodetector is configured to detect non-radiation signals dominated by pressure (photoacoustic) signals.

27. A method for configuring a scanning system to scan a sample at different pixels spaced a determined distance apart from each other, the different pixels corresponding to different locations of excitation events, the method comprising: performing a first scan in an area at more than one pixel of the sample; determining the determined distance between each pixel from the first scan, wherein the determined distance corresponds to a minimum distance that enables extraction of signals from a particular pixel such that the particular pixel is completely isolated and allows the sample to recover to thermal equilibrium before the sample is excited again; synchronizing a vibration frequency of a MEMS mirror with a pulse repetition frequency (PRF) of a laser source; and optically scanning, via the MEMS mirror, a beam generated by the laser source across the sample at each pixel in a sub-group, wherein the vibration frequency synchronized with the PRF enables the beam to be pulsed onto the sample at the determined distance.

28. The method of claim 27, the method further comprising: one or more additional beams generated by the laser source and / or one or more additional laser sources, wherein each of the one or more additional beams corresponds to a separate sub-group of pixels; and optically scanning, via the MEMS mirror, each of the one or more additional beams across the sample at each pixel in a corresponding sub-group, wherein a synchronized scanning frequency and the PRF enables the one or more additional beams to be pulsed onto the sample at the determined distance.

29. The method of claim 28, wherein each of the beam and the one or more additional beams are a distance of the determined distance apart from each other.

30. A method for configuring a scanning system to scan a sample at different pixels spaced a determined distance apart from each other, the different pixels corresponding to different locations of excitation events, the method comprising: performing a first scan in an area at more than one pixel of the sample; determining the determined distance between each pixel according to the first scan, wherein the determined distance corresponds to a minimum distance that enables extraction of a signal from a particular pixel such that the particular pixel is completely isolated and allows the sample to recover to thermal equilibrium before the sample is excited again; pulsing a plurality of light beams generated by one or more laser sources at a pulse repetition frequency (PRF), wherein each light beam of the plurality of light beams corresponds to a separate subset of pixels; and optically scanning the plurality of light beams across the sample at each pixel in the corresponding separate subset via a MEMS mirror such that the plurality of light beams are pulsed onto the sample at the determined distance.

31. The method of claim 30, wherein the PRF is greater than a vibration frequency of the MEMS mirror.

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