Apparatus, system and method for three-dimensional microdissection of a sample - Patents.com

Abstract

Some embodiments of the present disclosure relate to devices, systems, and methods for 3D microdissection of a sample. The microdissection system includes an imaging system and an extraction system. The imaging system may include a fluorescence microscope and collects a 3D image of a sample. A region of interest is identified within the sample based on the 3D image. The extraction system extracts the identified region of interest. The imaging, identification, and / or extraction may be manual, automated, or a combination thereof.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims the benefit under 35 U.S.C. § 119 of the earlier filing date of U.S. Provisional Application No. 63 / 315,444, filed March 1, 2022, the entire contents of which are hereby incorporated by reference for all purposes.

[0002] This invention was made with government support under Grant Nos. K99 CA240681 and R01 EB031002 awarded by the National Institute of Health Sciences, and Grant Nos. W81XWH-18-1-0358 and W81XWH-19-1-0589 awarded by the US Army Medical Research and Materiel Command. The US Government has certain rights in the invention. [Background technology]

[0003] There may be many applications where identifying and isolating a region of interest within a sample is useful for subsequent analysis. For example, a biological specimen can be examined under a microscope and a portion of the sample can be removed. However, existing techniques may be limited in terms of the size, shape, and location of the region of interest that can be identified within the sample, or may be limited in that they introduce undesirable chemical and / or physical changes to the sample. For example, formalin-fixed paraffin-embedded (FFPE), developed in the 1890s, reduces the nucleic acid yield from the extracted region of interest and induces "spurious" mutations that alter the sequencing results in both DNA / RNA assays. As for laser capture microdissection (LCM), it is time-consuming, costly, and produces low yields of tumor tissue and nucleic acid. Furthermore, samples obtained with LCM (5 μm-thick thin sections) are generally small (<100 cells), and the data may not be representative of the 3D cell population. Due to these limitations, crude macrodissection is more commonly used in laboratories. In crude macrodissection, slide-mounted tissue sections are manually annotated and scraped off the slide with a razor blade. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] International Publication No. 2021 / 119201 [Patent Document 2] US Patent Application Publication No. 2010 / 0000383 Summary of the Invention [Problem to be solved by the invention]

[0005] Therefore, there is a need for a technique that can image, locate, and section regions of interest within relatively thick samples. [Means for solving the problem]

[0006] In at least one embodiment, the present disclosure relates to a method comprising generating a 3D image of a volume of a sample using fluorescence microscopy, identifying a region of interest within the sample based on the 3D image, and extracting the region of interest from the sample.

[0007] The method may further include generating a 3D image with an open-top light sheet microscope. The method may further include purifying a nucleic acid, a protein, a metabolite, a carbohydrate, a lipid, or a combination thereof. The method may include generating a 3D image with a first system and cropping the region of interest with a second system separate from the first system.

[0008] The method may include performing automatic identification of the region of interest using a trained classifier. The method may include training the classifier with 2D training images, 3D training images, or a combination thereof. The method may include capturing a plurality of 2D images of the sample and generating the 3D image based on the plurality of 2D images. The method may include virtually extracting the region of interest. The method may include physically extracting the region of interest by one of a mechanical cut-out element and an optical cut-out element. The method may include labeling the sample with a fluorescent dye specific to one or more constituents of the region of interest.

[0009] In at least one embodiment, the present disclosure relates to a system including an imaging system and an extraction system, the imaging system capturing a 3D image of a sample based on fluorescence microscopy, and the extraction system extracting material from the sample based on coordinates of a region of interest located within the 3D image.

[0010] The imaging system may include an open-top light sheet microscope. The imaging system may include an illumination objective, a first focusing objective, and a second focusing objective. The first focusing objective may have a higher resolution than the second focusing objective. The illumination objective has an illumination optical axis, the first focusing objective has a first optical axis that forms a first angle with the illumination optical axis, and the second focusing objective has a second optical axis that forms a second angle with the illumination optical axis. The first angle and the second angle may be different. The imaging system may include a stage configured to support the sample on a first surface, and the illumination objective, the first focusing objective, and the second focusing objective may be located below a second surface of the stage opposite the first surface.

[0011] The extraction system may be mounted on the imaging system. The extraction system may be a modular component that is attached to a stage of the imaging system. The imaging system may include a biopsy holder for holding a core needle biopsy sample. The system may further include a controller configured to identify the region of interest based on the 3D image. The controller may operate the extraction system to extract the region of interest.

[0012] In at least one embodiment, the present disclosure relates to a system including an imaging system that captures a 3D image of a sample based on fluorescence microscopy, an extraction system including an extraction tool, and a computing system, the computing system including a processor and a non-transitory computer readable medium having instructions encoded thereon that, when executed by the processor, cause the computing system to identify a region of interest within the sample based on the 3D image and extract the identified region of interest with the extraction tool.

[0013] The non-transitory computer readable medium may further include a classifier, and the region may be identified in part based on the classifier. The computing system may further include a display for displaying the 3D image, and an input / output system for enabling manual identification of the region of interest based on the displayed 3D image.

[0014] The imaging system may be an open-top light sheet microscope. The computing system may operate an actuator to move the extraction tool relative to the sample, move the sample relative to the extraction tool, or a combination thereof. When executed by the processor, the instructions may further cause the system to capture a first 3D image at a first resolution, identify a provisional region of interest based on the first 3D image, capture a second 3D image of the provisional region of interest based on the first 3D image, the second 3D image being at a second resolution higher than the first resolution, and determine whether the provisional region of interest is the region of interest based on the second 3D image. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a block diagram of a microdissection system according to some embodiments of the present disclosure. [Diagram 2] FIG. 1 is a block diagram of a microdissection system according to some embodiments of the present disclosure. [Diagram 3] FIG. 1 is a schematic diagram of a microdissection system according to some embodiments of the present disclosure. [Figure 4] FIG. 1 is a schematic diagram of an exemplary microdissection system according to some embodiments of the present disclosure. [Diagram 5] FIG. 1 is a flow diagram of an exemplary application of microdissection using 3D imaging. [Figure 6A] FIG. 1 illustrates an exemplary image of a sample, according to some embodiments of the present disclosure. [Figure 6B] FIG. 6B shows an exemplary image of a sample and analysis results of a genome purified from an identified region of interest according to the embodiment of FIG. 6A. [Figure 6C] FIG. 6B shows an exemplary image of a sample and analysis results of a genome purified from an identified region of interest according to the embodiment of FIG. 6A. [Figure 6D] FIG. 6B shows the results of an analysis of a genome purified from an identified region of interest according to the embodiment of FIG. 6A. [Figure 7] 1 is a flowchart of a method according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] The following description of specific embodiments is merely exemplary in nature and is not intended to limit the scope of the disclosure or its application or uses. In the following detailed description of the embodiments of the disclosed system and method, reference is made to the accompanying drawings. These drawings form a part of this specification and show, by way of example, specific embodiments in which the disclosed system and method may be practiced. The description of these embodiments is in sufficient detail to enable one skilled in the art to practice the disclosed system and method. It is to be understood that other embodiments may be utilized and that structural and logical changes may be made without departing from the spirit and scope of the present disclosure. Moreover, for purposes of clarity, detailed description of certain features will not be provided if they are obvious to one skilled in the art so as not to obscure the description of the embodiments of the present disclosure. Therefore, the following detailed description is not to be taken in a limiting sense, and the scope of the present disclosure is defined only by the appended claims.

[0017] Samples, such as biological samples, may contain various regions of interest within them. To analyze these regions of interest, it may be useful to remove the regions of interest from a larger sample. For example, if one wishes to perform genomic or proteomic analysis on a particular tissue type, it may be useful to look at the tissue and separate the tissue of interest (such as a cancer type) from the larger sample for subsequent sequencing or other analysis of the removed tissue of interest.

[0018] Current sectioning techniques can have limitations. For example, samples can be relatively thick and it can be difficult to image the sample in its entirety. Techniques that involve sectioning tissue can require such samples to be fixed, frozen, and / or embedded in a medium, which can be time-consuming and tedious and can result in undesirable changes to the structure and chemistry of the sample. Thus, there is a need to locate and extract a region of interest from within a larger volumetric volume of a specimen.

[0019] The present disclosure is directed to three-dimensional microdissection of a sample. A sample can be imaged to generate a 3D image of the sample (or a portion of the sample), a region of interest can be identified based on the 3D image, and the identified region of interest can be retrieved with an extraction system. For example, an imaging system, such as an open-top light sheet (OTLS) microscope, can capture multiple image slices across a tissue and assemble them into a 3D volumetric image of the sample. In some embodiments, the imaging system may first perform a (relatively) low-resolution survey of the sample and then perform a (relatively) high-resolution imaging of a selected portion of the sample based on the region identified in the low-resolution survey. The identification of the region of interest can be based on a high-resolution image, a low-resolution image, or a combination thereof.

[0020] Identification of an area of ​​interest may be performed within the 3D image. For example, automatic and / or manual segmentation may be used to select an area of ​​interest within the 3D image. In some exemplary applications, imaging and / or labeling of a sample may aid in identifying the area of ​​interest (e.g., by selectively labeling tissue of interest). In some embodiments, an automated tool such as a trained classifier may be used to automatically identify an area of ​​interest within an imaged sample.

[0021] Once a region of interest (ROI) has been identified, the ROI can be extracted from the sample. For example, an extraction tool, such as a cropping element, can be used to extract the region of interest based on the location identified in the 3D image. In some embodiments, the extraction tool can be attached to an actuator, which can enable automated (or semi-automated) movement of the extraction tool relative to the sample. For example, coordinates of the ROI in the 3D image can be used to guide the relative position of the extraction tool and the sample. In some embodiments, the extraction tool can be operated manually or semi-manually. In some embodiments, the extraction tool can be attached to the imaging system. In some embodiments, the extraction tool can be a separate system from the imaging system.

[0022] In an exemplary application, the extracted tissue can be further processed, for example, to purify one or more biomolecules for subsequent analysis. For example, nucleic acids (such as DNA or RNA), proteins, metabolic markers, other chemicals, or combinations thereof, can be purified or otherwise extracted from the extracted tissue. The purified biomolecules can then be used for analysis, monitoring, diagnosis, research, and / or other purposes. In an exemplary application, 3D microscopy and 3D microdissection can be used to characterize response and resistance to neoadjuvant total androgen deprivation therapy (AAT) in high-risk localized prostate cancer (PC) patients. OTLS microscopy can be used to image prostate samples (such as prostate biopsy samples), and 3D microdissection can be used to extract regions of interest (such as identified cancer types). Molecular analysis results from the extracted regions of interest can be compared to pre-treatment biopsy samples and lymph node metastases (if present). This can help interpret the response of prostate cancer to full AAT, which can ultimately lead to more personalized treatment for high-risk localized prostate cancer patients.

[0023] FIG. 1 is a block diagram of a microdissection system according to some embodiments of the present disclosure. The microdissection system 100 includes an imaging system 102, shown in this case as an OTLS microscope 102, an extraction system 140, and an optional controller 104. In some embodiments, instead of or in addition to the controller 104, the imaging system and / or the extraction system 140 may include manual control mechanisms not shown in FIG. 1. Structural elements such as connectors and housings are omitted from the diagram of FIG. 1. In some embodiments, one or more components of the imaging system 102, the extraction system 140, and / or the controller 104 may be integrated. In some embodiments, some or all of the imaging system 102, the extraction system 140, and / or the controller 104 may be separate systems.

[0024] The microscope 102 includes a sample holder 108 that supports a sample 106 along its upper surface. The microscope 102 has an illumination path and one or more collection paths, which are independent of one another. The illumination path includes a light source 118, illumination optics 120, and an illumination objective 122. The illumination path provides an illumination beam 124 that passes through the sample holder 108 and illuminates the sample 106.

[0025] Each of the collection paths includes a collection objective and collection optics. Their function is to couple light from the focal region 126 illuminated by the illumination beam 124 to one or more detectors 132. In the exemplary configuration of FIG. 1, two separate collection paths are shown, with each collection path coupled to the same detector 132. However, more or fewer collection paths may be used, and in some embodiments, each collection path may include a separate detector. The first collection path includes a first collection objective 128 and a first collection optic 130. The second collection path includes a second collection objective 134 and a second collection optic 136. The optical axis of the collection objective 128 may be at an angle θ with respect to the optical axis of the illumination objective 122 (e.g., at an angle θ with respect to the illumination beam 124). The angle θ may be a non-orthogonal angle (e.g., an acute angle). Such an arrangement of illumination and optics may generally be referred to as a non-orthogonal dual objective lens (NODO) system. The collection objective lens 134 has an optical axis that forms an angle φ with the optical axis of the illumination objective lens 122. In some embodiments, the angle φ may be orthogonal (e.g., 90°). Such an arrangement may be referred to as an orthogonal dual objective lens (ODO) system. The exemplary embodiment of FIG. 1 includes both a NODO collection path and an ODO collection path. However, other exemplary imaging systems 102 may include only a single collection path (e.g., either NODO or ODO).

[0026] The microdissection system 100 may be used for physical extraction of the region of interest 125, virtual extraction of the region of interest 125, or a combination thereof. Virtual extraction may involve identifying the region of interest 125 and then performing a second imaging on the region of interest 125. For example, the first imaging may be at a first resolution and the second imaging may be at a second resolution that is higher than the first resolution. Physical extraction may involve separating the region of interest 125 from the surrounding portion of the sample 106 using the extraction system 140 in order to remove the region of interest 125 for further imaging / analysis.

[0027] In some embodiments, extraction system 140 may be a virtual extraction system and may encompass one or more components of imaging system 102. For example, a collection path including objective lenses 134 and 136 may be part of extraction system 140 and may be used to capture a high-resolution image of region of interest 125 identified by system 100.

[0028] In some embodiments, the extraction system 140 may be a physical extraction system and may include an extraction tool or element 144 that can be used to remove the identified region of interest 125 from the sample 106. In some embodiments, the extraction tool 144 may be a contact tool (such as a blade) that can mechanically contact the sample 106 to separate the region of interest 125. In some embodiments, the extraction tool 144 may be a non-contact tool (such as a laser cutter) that separates the region of interest 125 without physical contact. The region of interest 125 may be identified based on images collected using the imaging system 102. The identification and / or extraction may be automatic, manual, or a combination thereof. The controller 104 may operate the imaging system 102 and / or the extraction system 140 to collect images, identify the region of interest 125 based on the images, and / or extract the region of interest 125.

[0029] The illumination objective 122 and the collection objective 128 may typically be located below the bottom surface of the sample holder 108. This may leave the top surface of the sample holder 108 relatively open, which may in turn facilitate placement of the sample 106 on the sample holder 108. For example, the sample holder may have a top surface that includes a flat plate (e.g., similar to a commercially available flatbed scanner) on which various samples may be placed. This may also reduce / eliminate lateral constraints on the sample 106.

[0030] The imaging system 102 may enable rapid 3D microscopy of relatively large samples 106. For example, the OTLS imaging system 102 may be capable of imaging samples up to 10 cm x 10 cm x 0.4 cm in size. This may be advantageous as other imaging systems may be more limited in the size and thickness of samples they can accommodate. The OTLS imaging system 102 may be capable of imaging the entire thickness of the specimen (e.g., 0.4 cm). In contrast, traditional slide-based pathology specimens may only be able to visualize a 5 micron section of a thick (~0.4 cm) tissue specimen.

[0031] The extraction system 140 may enable relatively accurate extraction of the region of interest 125 from the sample 106. In an exemplary embodiment, the extraction tool 144 may be a razor blade that may have an accuracy of about 0.1 mm, and a motorized stage driven by the actuator 142 may have an accuracy of 200 nm.

[0032] In some embodiments, the extraction system 140 may be attached to the imaging system 102. The extraction system 140 may be integrated into the imaging system 102 or may be a modular component that is attached to the imaging system. For example, the extraction system 140 may be attached to a stage or sample holder 108 of the imaging system 102. In some embodiments, the extraction element 144 may be mounted to maintain a fixed position relative to the sample holder 108, and movement of the extraction element 144 relative to the sample 106 may depend on movement of the sample holder 108 (e.g., by an actuator 109). In another exemplary embodiment, the extraction element 144 may include its own actuator 142 and may move relative to the sample 106 and the sample holder 108. In some embodiments, the extraction element 144 may be able to change the area of ​​the sample being processed without moving relative to the sample 106 (or in combination with such movement). For example, in some embodiments, the extraction element 144 may be a non-contact tool, such as a laser cutter, and the beam may be redirected by a focusing element.

[0033] In some embodiments, the extraction system 140 and the imaging system 102 may be separate systems. In some embodiments, the sample holder 108 may also be a modular component and may be removed from the imaging system 102 and instead installed in the extraction system. For example, the sample holder 108 may be installed in the imaging system 102 to generate a 3D image. A region of interest 125 may be identified in the 3D image. The sample holder 108 may be removed and installed in the extraction system 140. The extraction system 140 may extract the region of interest 125 from the sample based on the coordinates of the region of interest 125 relative to the sample holder.

[0034] The extraction tool 144 may be a contact tool, such as a mechanical cutting tool. For example, a razor blade "guillotine" may be used as the extraction tool 144. In other examples, other tools, such as a biopsy punch tool, may be attached to the manipulator. The extraction tool 144 may be a non-contact tool, such as a laser cutter. In some embodiments, the extraction tool may be one or more optical components (e.g., a focusing objective or other focusing optics) that are used to virtually extract the sample.

[0035] In some embodiments, the imaging system 102 may include an optional immersion fluid chamber 110, which contains an immersion fluid 112. The immersion fluid 112 may aid in coupling of illumination and / or collected light into the sample. For example, the immersion fluid 112 may act as an index matching fluid with the sample holder 108 and / or sample 106, reducing refraction of light passing therethrough. In some embodiments, one or both of the illumination objective 122 and the collection objective 128 may be air objectives surrounded by a surrounding medium (such as air). Thus, light may pass between the air and the immersion fluid 112. Optional optical elements, such as lenses and windows, may aid in coupling of light across the air / immersion fluid interface. In some embodiments, one or both of the illumination objective 122 and the collection objective 128 may be immersion objectives. In an immersion objective, at least a portion of the objective (e.g., the front lens) is in contact with the immersion liquid 112. For example, the illumination objective 122 may be an air objective, where the illumination beam 124 passes through air, through a lens / window (not shown), and into the immersion liquid 112 before reaching the sample 106. Light from the focal region 126 may pass through the immersion liquid 112 without passing through air and be collected by the collection objective 128.

[0036] The light source 118 provides illumination light along an illumination path to illuminate the focal region 126 of the sample 106. The light source 118 may be a narrowband light source capable of emitting a narrow spectrum of light, such as a laser or a light emitting diode (LED). In some embodiments, the light source may be a broadband light source (such as an incandescent light source, an arc light source, etc.) capable of producing a broad spectrum (such as white) illumination. In some embodiments, one or more portions of the illumination light may be outside the visible range. In some embodiments, a filter (not shown) may be used as part of the illumination path to further narrow the wavelength of the illumination light. For example, a bandpass filter may receive the broadband illumination from the light source 118 and provide a narrower spectrum of illumination light. In some embodiments, the light source 118 may be a laser and may produce collimated light.

[0037] In some embodiments, the optical system 100 can be used to image the fluorescent emission in the sample 106. The illumination beam 124 can include light at a specific excitation wavelength that can excite fluorophores in the sample 106. The illumination beam 124 can include a broad spectrum of light that includes the excitation wavelength, or it can be narrow band centered around the excitation wavelength. In some embodiments, the light source 118 can generate a narrow spectrum of light centered around (or near) the excitation wavelength. In some embodiments, a filter (not shown) can be used in the illumination optics 120 to restrict the illumination beam 124 to wavelengths near the excitation wavelength. When excited by the illumination beam 124, fluorophores in the sample 106 can emit light (which can be centered around a certain emission wavelength). The collection path (e.g., collection optics 130) can include one or more filters that can be used to restrict the light reaching the detector 132 to wavelengths of light near the emission wavelength.

[0038] The illumination optics 120 can couple light from the light source 118 to the illumination objective 122. For example, the illumination optics 120 can include an optical fiber that transmits light from the light source 118 to the back end of the illumination objective 122. In some embodiments, the illumination optics 120 can couple light between the light source 118 and the objective 122 without substantially changing the light provided by the light source 118. In some embodiments, the illumination optics 120 can change the shape, wavelength, intensity, and / or other characteristics of the light provided by the light source 118. For example, the illumination optics 120 can receive broadband light from the light source 118 and filter the light (e.g., with a filter, a diffraction grating, an acousto-optic modulator, etc.) to provide narrowband light to the objective 122.

[0039] In some embodiments, the illumination optics 120 can include scanning optics (e.g., a scanning mirror) that can be used to scan the illumination light. In some embodiments, the scanning optics can be used to generate the illumination beam 124 in the form of a light sheet (e.g., by scanning light back and forth in one axis and not in the other axis). In some embodiments, the scanning optics can be used to change the position of the field of view relative to the sample 106.

[0040] In some embodiments, the illumination optics 120 may be adjustable. For example, if the microscope 102 supports multiple imaging modes (e.g., multiple collection objectives share the same illumination objective), the illumination optics 120 may include one or more components that can be adjusted or tuned depending on the imaging mode. An example of a microscope using multiple imaging modes is described in more detail in FIG. 3, and an example of tuning the illumination optics 120 is described in more detail in FIG. 5.

[0041] As part of light sheet microscopy or light sheet fluorescence microscopy (LSFM), the illumination path may provide an illumination beam 124 that is a light sheet. The light sheet may have a generally elliptical cross section with a first numerical aperture along a first axis (e.g., the y-axis) and a second numerical aperture along a second axis that is orthogonal to the first axis that is greater than the first numerical aperture. The illumination optics 120 may include optics that shape the light received from the light source 118 into an illumination sheet. For example, the illumination optics 120 may include one or more cylindrical optics that focus light in one axis but not in an orthogonal axis.

[0042] In some embodiments, the illumination optics 120 can include scanning optics that can be used to scan the illumination beam 124 relative to the sample 106. For example, the area illuminated by the illumination beam may be smaller than the desired focal region 126. In this case, the illumination optics 120 can rapidly shuttle the illumination beam 124 across the desired focal region 126 to ensure that the focal region 126 is illuminated.

[0043] The illumination objective 122 may include one or more lenses that provide the illumination beam 124. For example, the illumination objective 122 may focus the illumination beam 124 toward a focal region 126. The sample holder 108 may position the sample 106 such that the focal region 126 is approximately within the sample 106. In some embodiments, the sample holder 108 may include one or more actuators that may position the sample 106 relative to the focal region 126. In some embodiments, the illumination objective may be a commercially available objective that includes one or more internal optical elements. In some embodiments, the illumination objective 122 may be surrounded by an ambient environment (such as air), and the illumination objective 122 may be an air objective. The illumination objective 122 may be characterized by one or more numerical apertures. The numerical aperture may be based on the angle at which light is focused at the focal region 126. In some embodiments, the illumination objective 122 may be an immersion objective, and at least a portion of the illumination objective 122 may be in contact with the immersion liquid 112 .

[0044] In some embodiments, the focal region 126 may be idealized as a focal plane. An illumination beam 124 may be directed toward the sample 106 to create the focal region 126. This focal region 126 may be idealized as a flat (e.g., 2D) plane that is illuminated by the illumination light sheet 124. The focal plane may be aligned with the illumination light sheet 124. This focal plane may be an area from which the focusing objective 128 may collect light and an area where an image is formed by the illumination beam 124. In some embodiments, the focal region 126 may be a single field of view of the focusing objective 128. In some embodiments, the focal region 126 may be an area where the field of view of the focusing objective 128 may be scanned.

[0045] The sample 106 may be supported by the top surface of the sample holder 108. In some embodiments, the sample 106 may be placed directly on the top surface of the sample holder 108. In some embodiments, the sample 106 may be placed in a container (e.g., on a glass slide, in a well plate, in a tissue culture flask, etc.) and the container may be placed on the sample holder 108. In some embodiments, the container may be integrated into the sample holder 108. In some embodiments, the sample 106 may be processed prior to imaging with the optical system 100. For example, the sample 106 may be washed, sectioned, and / or labeled prior to imaging.

[0046] In some embodiments, the sample 106 may be a biological sample. For example, the sample 106 may be tissue taken from a suspected diseased area (e.g., cancer). In some embodiments, the tissue may undergo various processes, such as optical clearing, tissue sectioning, and / or labeling, prior to examination by the optical system 100. In some embodiments, examination of the tissue by the optical system 100 may be used for diagnosis, to determine progress of a treatment, to monitor disease progression, etc. The sample 106 may be fresh, frozen, fixed, sectioned, deparaffinized, or otherwise prepared.

[0047] In some embodiments, the sample 106 may be non-biological. For example, the sample 106 may be a fluid and may include one or more constituents of interest. For example, the sample 106 may be a combustion gas, and the optical system 100 may perform particle image velocimetry (PIV) measurements to characterize the constituents of the gas.

[0048] In some embodiments, the sample 106 may include one or more types of fluorophores. The fluorophores may be intrinsic to the sample 106 (e.g., DNA and proteins in a biological sample) or may be fluorescent labels applied to the sample 106 (e.g., acridine orange, eosin). Some samples 106 may include a mixture of intrinsic types of fluorophores and fluorescent labels. Each type of fluorophore may have an excitation spectrum that may be centered around a particular excitation wavelength. When excited by light of the excitation spectrum, the fluorophore may emit light with an emission spectrum that may be centered around an emission wavelength different from the excitation wavelength (e.g., a wavelength red-shifted from the excitation wavelength).

[0049] The sample holder 108 may support the sample 106 on a material that is substantially transparent to the illumination beam 124 and substantially transparent to light collected from a focal region 126 of the sample 106. In some embodiments, the sample holder 108 may include a window of a transparent material over which the sample 106 may be positioned, and the remainder of the sample holder 108 may be formed of an opaque material. In some embodiments, the sample holder 108 may be made of a transparent material. For example, the sample holder 108 may include a glass plate that supports the sample 106.

[0050] In some embodiments, the sample holder 108 may include one or more structures for supporting the sample 106. For example, the sample holder 108 may include a clip or a well. In some embodiments, the sample holder 108 may be a modular component of the system 100, allowing different sample holders 108 to be swapped in depending on the type of sample, the type of imaging, the wavelength of light being illuminated / collected, and combinations thereof.

[0051] The sample holder 108 may have a second surface (e.g., a bottom surface) opposite its surface that supports the sample 106. In some embodiments, an immersion chamber 110 that holds immersion liquid 112 may be positioned below the second surface of the sample holder 108. In some embodiments, the top of the immersion chamber 110 may be open and the immersion liquid 112 may contact the second surface of the sample holder 108. In some embodiments, the second surface of the sample holder 108 may be in contact with the immersion liquid 112 while the first surface of the sample holder 108 (the surface that supports the sample 106) may be in contact with the same environment (e.g., air) as the objective lenses 122 and 128.

[0052] The sample holder 108 can be coupled to an actuator 109, which can move the sample holder 108 in one or more directions. In some embodiments, the sample holder 108 can be movable in one or more dimensions relative to the immersion chamber 110 and the objective lenses 122 and 128. For example, the sample holder 108 can be movable along the x-axis, y-axis, and / or z-axis, and / or can rotate (e.g., tilt, tilt, etc.). The movement of the sample holder 108 can be performed to change the position of the focal region 126 within the sample 106 and / or to move the sample holder 108 between a loading position and an imaging position. In some embodiments, the actuator can be a manual actuator, such as a screw or a coarse / fine adjustment knob. In some embodiments, the actuator can be automated, such as an electric motor that can respond to manual input and / or commands from the controller 104. In some embodiments, the actuator 109 may be responsive to both manual adjustment and automatic control (eg, a knob that responds to both manual rotation and commands from the controller 104).

[0053] Like the actuator 109, the actuator 142 can be manual, automatic, or a combination thereof. In some embodiments, one actuator can be automatic and the other manual. For example, the actuator 109 can be motorized and can position the sample relative to the XY axis, while the actuator 142 can be manually controlled to lower the extraction tool 144 into an engagement position for extraction.

[0054] The optional immersion chamber 110 contains the immersion liquid 112. In some embodiments, the immersion chamber 110 may include a supply and / or inlet that may aid in replacing the immersion liquid 112. For example, the immersion chamber 110 may be coupled to a fluid input line that supplies the immersion liquid 112 (the fluid input line may be coupled to a pump and / or reservoir) and a drain that may be opened to remove the immersion liquid 112 from the immersion chamber 110. As described in detail herein, the type of immersion liquid may be selected based on the refractive index of the sample 106 and / or sample holder 108.

[0055] The collection path may receive light from focal region 126 and direct the received light to detector 132, which may image and / or otherwise measure the received light. The light from focal region 126 may be redirected portions of illumination beam 124 (e.g., scattered and / or reflected light), or may be light emitted from focal region 126 in response to illumination beam 124 (e.g., light from fluorescent emission), or a combination thereof. This collected light may be transmitted through sample holder 108 towards collection objective lens 128.

[0056] In the NODO geometry of FIG. 1, the collection path may have a main optical axis disposed at an angle γ with respect to the plane of the sample holder 108 (e.g., the XY plane of FIG. 1). In some embodiments, such as the one shown in FIG. 1, the angle γ may be around 90°, i.e., the collection path may have a main optical axis that is nearly orthogonal to the plane of the sample holder 108. If the quality of the image collected by the collection objective remains diffraction-limited, i.e., using the Strehl ratio as a figure of merit, the angle γ may be close enough to 90°, i.e., nearly orthogonal, if the Strehl ratio is greater than approximately 0.8. As will be apparent to one skilled in the art, the Strehl ratio may also depend on many parameters in addition to the angle γ that may potentially be applied to a given OTLS microscope system. These parameters include, for example, the refractive index mismatch (i.e. the optical path difference, or the product of the refractive index difference between the holder and the immersion medium / cleared tissue sample and the holder thickness), the NA of the illumination / collection objectives, the field of view of these objectives, the wavelength of the illumination and / or collection light, and the particular objectives used.

[0057] The illumination path may have a principal optical axis disposed at an angle θ relative to the principal optical axis of the collection path, and the angle θ may be a non-orthogonal angle, i.e., an acute angle. The range of acceptable values ​​for the angle θ may be limited by several considerations. For example, it may not be practical for the angle to be 90° or nearly 90°, i.e., nearly parallel to the plane of the specimen holder, since the principal optical axis of the illumination path intersects the specimen holder, limiting the lateral width of the specimen. Furthermore, the constraints on index matching may be too large, even for a relatively small NA of the illumination beam. Other factors may limit the lower limit of the range of values ​​for the angle θ. These factors include physical constraints imposed by the mechanical housing of the collection objective.

[0058] The shape of the focal region 126 may be determined in part by the field of view of the collection path, which in turn may be determined in part by the numerical aperture of the collection objective 128 or 134. The two collection paths have substantially similar components, so a detailed description of the components of only one of the collection paths is provided. Like the illumination objective 122, the collection objective 128 may be a commercially available objective including one or more lenses. In some embodiments, the collection objective 128 may be an air objective. In some embodiments, the collection objective 128 may be an immersion objective (e.g., an oil immersion objective). In some embodiments, the collection objective 128 may use an immersion medium that is different from the immersion fluid 112 used in the illumination path. In some embodiments, the focal region of the collection path and the focal region of the illumination path may substantially overlap at the focal region 126. In some embodiments, the illumination path and the collection path may have different focal region shapes, sizes, and / or locations.

[0059] The collection path includes collection optics 130, which may redirect light from the collection objective to a detector 132. For example, collection optics 130 may be an imaging lens designed to focus light from the back end of the collection objective into an image that is projected onto detector 132. In some embodiments, collection optics 130 may include one or more elements that change the light received from collection objective 128. For example, collection optics 130 may include filters, mirrors, descanning optics, or a combination thereof.

[0060] The collection optics 130 may include optics that can redirect the field of view of the focal region 126. The axis of the collection objective lens 128 is at an angle θ with respect to the focal region 126, which can distort the image. The collection optics 130 may include one or more mechanisms that can redirect the image to offset the angle θ before projecting the image onto the detector 132. For example, the collection optics 130 may include an indirect focus, where a first lens projects an image of the light collected by the collection objective lens 128, and a second lens images the indirect image at an angle that offsets the angle θ. This allows the distortion due to the angle θ to be corrected before the light reaches the detector 132. In other exemplary embodiments, other methods of redirecting the image may be used.

[0061] Detector 132 may be used to image focal region 126. In some embodiments, detector 132 may be an eyepiece, so that a user can view focal region 126. In some embodiments, detector 132 may generate a signal to record an image of focal region 126. For example, detector 132 may include a CCD or CMOS array, which may generate an electronic signal based on light incident thereon.

[0062] The microscope 102 may be coupled to a controller 104. The controller 104 may be used to operate one or more components of the microscope 102 and / or the extraction system 140. For example, the controller 104 may instruct the imaging system 102 to collect images from the sample 106. The controller 104 may determine a region of interest 125 within the sample based on the images. The controller 104 may instruct the extraction system 140 to extract the region of interest 125.

[0063] FIG. 2 is a block diagram of a microdissection system according to some embodiments of the present disclosure. The microdissection system 200 of FIG. 2 may, in some embodiments, implement the microdissection system 100 of FIG. 1. The microdissection system 200 of FIG. 2 includes an imaging system 250 (e.g., microscope 102 of FIG. 1), an extraction system 260 (e.g., 140 of FIG. 1), and a computing system. The computing system 202 may function as a controller for the imaging system 250 and / or the extraction system 260. Although a single computing system 202 is shown in FIG. 2, in other exemplary embodiments, separate computing systems may be used, such as a system for controlling the imaging system 250 and a system for controlling the extraction system 260.

[0064] The imaging system 250 (e.g., 102 in FIG. 1 ) includes an illumination source 252, which includes one or more components (e.g., 118, 120, and 122 in FIG. 1 ) that generate an illumination beam. In some embodiments, the beam may be in the form of a light sheet. The imaging system 250 includes one or more sets of collection optics 258 (e.g., 128 and 130, and / or 134 and 136 in FIG. 1 ). The collection optics 258 form an image of one or more focal regions (e.g., 126 in FIG. 1 ). The imaging system 250 further includes a positioning control mechanism 256. The positioning control mechanism 256 (e.g., 109 in FIG. 1 ) adjusts the position of the focal region with respect to a sample disposed in the imaging system 250. The imaging system 250 includes a detector 254 (e.g., 132 in FIG. 1 ). The detector 254 receives the light collected by the collection optics 258 and generates a signal based on the light. This signal is provided to the computing system 202 .

[0065] In some embodiments, the imaging system 250 can include an additional optical control mechanism 259 that can be manipulated to adjust the imaging system 250. For example, the imaging system 250 can include two collection paths as part of the collection optics 258, and the optical control mechanism 259 can select which collection path provides the light that is collected at the detector 254. Another example of the optical control mechanism 259 can be a filter wheel. The filter wheel controls the wavelengths of light from the illumination source 252 and / or the wavelengths of light that pass through the collection optics 258. This can be useful when one wants to switch between different fluorophores in fluorescence imaging.

[0066] The extraction system 260 (e.g., 140, FIG. 1) includes a positioning system 262 (e.g., 142, FIG. 1) and an extraction tool 264 (e.g., 144, FIG. 1). Either or both of the positioning system 262 and the extraction tool 264 may be operated by the computing system 202 to extract a region of interest from the sample. For example, in some embodiments, the positioning system 262 may be operated to move the extraction tool 264 relative to the sample. In some embodiments, the extraction tool 264 may be a contact tool, such as a cutting element (e.g., a razor, scalpel, blade, punch biopsy tool, etc.). In some embodiments, the extraction tool may be a non-contact tool (e.g., a laser cutting element) and may include a control mechanism that may be operated by the computing system 202.

[0067] In some embodiments, the extraction system 260 can be used for virtual extraction, and similar to the imaging system 250, the extraction system 260 can include one or more optical components for imaging. In some embodiments, the extraction system 260 can be incorporated into the imaging system 250, and the extraction system 260 can share components with the imaging system 250. For example, the extraction system 260 can be a second light collection path, such as an ODO path. This second light collection path shares the same detector 254 as the imaging system 250.

[0068] In some embodiments, the extraction system 260 and the imaging system 250 may be used in combination. For example, the extraction system 260 may be a modular component that is attached to the imaging system 250. In another example, the extraction system 260 may be integrated with the imaging system. In some embodiments, when the extraction system 260 and the imaging system are combined, the positioning systems 256 and 262 may work together to perform the extraction. For example, the positioning system 262 may move the extraction tool 264 between its disengaged and engaged positions, and the positioning system 256 may be used to move the sample relative to the extraction tool 264 when the tool 264 is engaged. In some embodiments, the positioning system 262 may be omitted.

[0069] The computing system 202 includes one or more processors 206 that operate one or more instructions 216 stored in a memory 214 of the computing system 202. The processor 206 may operate one or more controllers 208 based on the instructions and various data received from the imaging system 250 and the extraction system 260. The controller 208 may provide various signals to the imaging system 250 and / or the extraction system 260, which may effect various operations of the imaging system and / or the extraction system (e.g., by providing signals to actuators, etc.). Signals between the imaging system 250 / extraction system 260 and the computing system 202 may pass through a communication module 210 (e.g., a wired and / or wireless communication module).

[0070] Computing system 202 includes a display 203 and one or more input / output (I / O) systems 204 that allow a user to interact with computing system 202. For example, I / O system 204 may include various input devices such as a keypad, a mouse, a touch screen, etc. Display 203 displays various information, such as images based on data from detector 254 and a graphical user interface. The graphical user interface allows a user to visualize various controls and data.

[0071] The memory 214 includes a set of instructions 216, such as a computer program, that enables the computing system 202 to operate the imaging system 250 and the extraction system 260 to image, identify, and extract regions of interest from a sample. The memory 214 also includes other information that may be useful, such as stored images 226, trained classifiers 228, and image analysis software 230.

[0072] Instructions 216 include a box 218, which represents generating a 3D image of the sample. For example, box 218 may include instructions that, when executed by processor 206, cause computing system 202 to operate the imaging system. In some embodiments, the 3D image may be constructed from multiple image slices across the sample. For example, instructions 218 may direct imaging system 250 to capture a first image at a first location, operate positioning system 256 to move a focal region to a second location, and then capture a second image, etc. Instructions 216 may include instructions to combine the image slices into an overall 3D image. For example, in some embodiments, positioning system 256 may provide coordinates of the image slices, and the 3D image may be constructed in part based on the coordinates. In some embodiments, the image slices may include overlapping regions with one or more adjacent image slices, and instructions 216 may include a registration process to match the overlapping regions. In some embodiments, a combination of techniques may be used to generate the 3D image.

[0073] Instructions 216 include box 220, which represents identifying a region of interest within the sample. The region of interest (e.g., 125 in FIG. 1) may be selected based on the particular application. For example, if the application is to measure biomarkers in a particular tissue type, the region of interest may be the tissue of that type within the sample.

[0074] In some embodiments, the region of interest may be identified manually: for example, display 203 may display an image of the 3D image to a user, who may use one or more I / O tools to manually draw an outline around a desired region of interest.

[0075] In some embodiments, the computing system 202 may automatically select the region of interest. For example, the memory 214 may include one or more image analysis tools 230 that may be used to select the region of interest based on characteristics of the 3D image. In some embodiments, how the region of interest is identified may be determined by how the sample is prepared and / or imaged. For example, if the sample is prepared with a fluorescent stain specific to the tissue type of interest, the analysis tool 230 may be an intensity threshold. The intensity threshold is used to select regions of the image to illuminate in the fluorescent imaging method. Other analysis tools 230 may include segmentation of the image, such as, for example, nuclear and cytoplasmic segmentation.

[0076] In some embodiments, the memory 214 can include a trained classifier 228 that can be used to identify the region of interest. The classifier 228 can be trained based on a set of training images and a machine learning algorithm. For example, the training images can be images labeled with labels that contain (or do not contain) the tissue of interest. The machine learning algorithm can adjust the weights (or other parameters) of the classifier 228 as part of the training process on the training images, and the classifier 228 can be generated based on the machine learning algorithm. The training images can be 2D images, 3D images, or a combination thereof.

[0077] In some embodiments, a combination of manual and automatic classification may be used, for example, computing system 202 may generate an initial region of interest boundary, which display 203 may display to the user, who may further refine and adjust it via I / O system 204.

[0078] The instructions include box 222. This box represents instructions for extracting the region of interest from the sample. This extraction may be virtual, physical, or a combination thereof.

[0079] In some embodiments, the instructions in box 222 may include a virtual extraction of the region of interest. This virtual extraction may include imaging at a first resolution (e.g., as part of box 218) and then performing a virtual extraction at a second resolution level. For example, if the sample is relatively large, it may be inefficient to collect a high-resolution 3D image of the entire sample, while a low-resolution image may not contain enough information to perform a high-quality identification of the region of interest. Thus, box 218 may instruct the imaging system 250 to collect a first set of images of the sample using a low-resolution collection path (e.g., 128 and 130 in FIG. 1). Instructions 216 may include instructions to virtually extract a provisional region of interest within the sample based on the first set of images by then collecting a second set of high-resolution images of the provisional region of interest. The high-resolution images may be collected using a second set of collection optics (e.g., 134 and 136 in FIG. 1). The provisional region of interest may be identified in a manner similar to the identification described in box 220. The virtually extracted region may then be further used or analyzed. In some embodiments, the virtually extracted region may be displayed to a user by the display 203. In some embodiments, one or more post-virtual extraction steps may be performed, such as image analysis, annotation, region segmentation, or a combination thereof.

[0080] In some embodiments, the instructions in box 222 may include a physical extraction of the region of interest. Instructions 222 may cause the computing system 202 to operate the extraction system 260 to move an extraction tool 264 relative to the sample via a positioning system 262. For example, the extraction tool 264 may be a cutting tool and may be moved around the outline of the region of interest (or around the area that includes the region of interest). In some embodiments, the extraction tool 264 may cut out a fixed shape (e.g., a punch biopsy tool) and may be instructed to cut out an area that includes the region of interest. In some embodiments, a combination of manual and automatic control may be used. For example, the display 203 may indicate the position of the cutting tool relative to the displayed image, and a user may guide the positioning system 262 to perform the extraction.

[0081] In some embodiments, the instructions in box 222 may perform both virtual and manual extraction. For example, a first set of images may be acquired to identify tentative regions of interest (e.g., similar to box 218), and then a second, higher resolution image of those tentative regions may be generated. In some embodiments, the instructions 216 may include refining the tentative regions of interest to regions of interest based on the higher resolution images. Manual extraction may then be performed on the regions of interest to remove them from the sample.

[0082] 2 as a single unit separate from the imaging system 250 and the extraction system 260. In some embodiments, there may be more than one computing system (e.g., one for the imaging system 250, one for the extraction system 260, etc.). In some embodiments, the computing system (or one or more components of the computing system) may be integrated with the imaging system 250 and / or the extraction system 260. In some embodiments, the computing system 202 may be a general-purpose computing system that executes software to operate the imaging system 250 and / or the extraction system 260.

[0083] In some embodiments, various controls of the computing system 202, the imaging system 250, and / or the extraction system 260 may be manual, automatic, or a combination thereof. For example, the positioning systems 256 and 262 may include computing system driven actuators, manual control mechanisms, or a combination thereof. For example, the computing system 202 may move the position of the extraction tool relative to the sample while the manual control mechanism may allow a user to move the extraction tool 264.

[0084] Figure 3 is a schematic diagram of a microdissection system according to some embodiments of the present disclosure. Microdissection system 300 may, in some embodiments, implement microdissection system 100 of Figure 1 and / or microdissection system 200 of Figure 2. Microdissection system 300 illustrates an embodiment in which the imaging system is an ODO system with a modular extraction system mounted on the stage of the system. For the sake of simplicity, certain components of the microdissection system, such as the light source, detector, and various optics, are omitted from Figure 3.

[0085] The microdissection system 300 includes an illumination objective 302 (e.g., 122 in FIG. 1 ) and a collection objective 304 (e.g., 134 in FIG. 1 ). The illumination objective 302 may project an illumination light sheet through a lens or window 318 into the immersion liquid 316 of the sample holder 314. The illumination sheet passes through the immersion liquid and into the sample 308 through a glass slide 306 attached to the sample holder 314. The collection objective 304 collects light from the focal area illuminated by the illumination objective 302 that has passed through the sample 308 and the immersion liquid 316. In the embodiment of FIG. 3 , the collection objective 304 is an immersion objective and may be in contact with the immersion liquid 316. Since the embodiment of FIG. 3 illustrates an ODO system, the optical axis of the illumination objective 302 and the optical axis of the collection objective 304 may be orthogonal to each other (e.g., 90° or nearly 90°). The inset shows how the illumination objective and the collection objective interact with sample 308 to image region of interest 314. The inset shows an alternative embodiment in which collection objective 304 is not an immersion objective, but is instead separated from immersion fluid 316 by a window, also similar to window 318.

[0086] In the embodiment of FIG. 3, the extraction system 312 is attached to the sample holder 314. For example, the extraction system 312 may be integrated with the sample holder 314 or may be a modular component that is attached to said sample holder. The extraction system 312 includes a frame (armature) that supports the extraction tool 310 (in this case a cutting element such as a blade). The frame of the extraction system 312 includes a motorized manipulator (e.g., actuator 142 of FIG. 1) that can move the extraction tool 310 relative to the sample 308 and the sample holder 314. The extraction system 312 may be attached to the top surface of the sample holder 314 opposite the side where the objectives 302 and 304 are located.

[0087] 4 is a schematic diagram of an exemplary microdissection system according to some embodiments of the present disclosure. The exemplary microdissection system 400 may, in some embodiments, implement the microdissection system 100 of FIG. 1 and / or the microdissection system 200 of FIG. 2. The microdissection system 400 may be similar to the microdissection system 300 of FIG. 3, except that in the microdissection system 400, the tissue sample is not on a glass slide, but a core needle biopsy sample (CNB), such as 410. The CNB may be positioned in a biopsy holder 404, and its excision may be performed based on coordinates of a region of interest in a 3D image of the CNB, using a powered razor "guillotine" 406 as an extraction system.

[0088] Acquisition of images may be performed by an OTLS imaging system 408 (e.g., an ODO and / or NODO system) similar to those previously described with respect to Figures 1-3. Because the imaging system 408 is largely similar, for purposes of brevity, a detailed description will not be repeated with respect to Figure 4. From the perspective of Figure 4, many of the components of the imaging system 408 are obscured from view by the sample holder 402.

[0089] The microdissection system 400 includes a sample holder 402 (e.g., 108 in FIG. 1), such as a motorized XY stage. The sample holder 402 can move back and forth and side to side along two orthogonal axes by being operated by a control device (e.g., 104 in FIG. 1 or 202 in FIG. 2), not shown in FIG. 4. The sample holder 402 supports a biopsy holder 404, a portion of which is shown in detail in the inset. The biopsy holder 404 includes a number of grooves or wells, each of which can hold a CNB, such as 410. The bottom of the biopsy holder 404 is formed of a transparent material, such as a glass slide or a cover slip 412. A motorized guillotine cutter 406 can function as an extraction system, and can be used to slice the CNB in ​​the biopsy holder 404.

[0090] In an exemplary operation, the CNBs can be removed from the specimen and then prepared for imaging. For example, the CNBs can be optically cleared and then each optically cleared CNB can be placed in a biopsy holder 404. The biopsy holder 404 can be a modular 3D printed biopsy holder located on the stage 402 of the system 400. In some embodiments, multiple CNBs can be placed in individual "biopsy wells" of the biopsy holder 404. In one exemplary implementation, each biopsy well can be approximately 1.5 mm wide by 3 cm long (sized to accommodate the largest CNB), allowing for precise mechanical microdissection of the biopsy sample using a motorized razor blade "guillotine" 406 mounted above the sample translation stage 402. The biopsy wells can have a quartz coverslip 412 affixed to the bottom of the vessel. The glass plate sample holder and this coverslip material (fused quartz) are ideally index matched via a thin film of index matching oil.

[0091] A biopsy holder 404 can be placed on the stage 402, and the biopsy sample in the well of the biopsy holder 404 can be imaged using an optical system 408. For example, the imaging system 408 can slice the biopsy sample throughout to perform fluorescence imaging, and then combine the slices into an overall 3D image of the CNB. Once a 3D image of the volumetric area of ​​the sample has been collected, a region of interest can be identified. For example, a trained pathologist can review the 3D visualization of the prostate CNB and specify the axial (x-axis) coordinates of a region with relatively high tumor cell content (>75% tumor content) throughout the diameter of the CNB. These coordinates are used for mechanical sectioning. This mechanical sectioning is performed using a guillotine mechanism mounted above the microscope stage without removing the CNB from the microscope stage. In another exemplary embodiment, automatic identification of the region of interest can be performed.

[0092] After 3D microdissection, the glass coverslip at the bottom of the biopsy well is removed and the tumor area is isolated and subjected to sequencing. The pathologist can then carefully examine these 3D histological datasets to definitively diagnose and grade the tumor, thereby determining prognosis and treatment options.

[0093] FIG. 5 is a flow diagram of an exemplary application of microdissection using 3D imaging. This flow diagram may represent a workflow using any of the systems or devices described herein. For example, the method of FIG. 5 may be implemented using one or more of the microdissection systems of FIGS. 1-4. In the exemplary application illustrated in flow chart 500, tissue removed from a patient is analyzed to identify the location of a cancer, so that the removed region of interest (e.g., cancer) can be further analyzed (e.g., by purifying biomarkers from the cancer).

[0094] In the flow diagram 500, an exemplary image 502 of a tissue slice is shown. The tissue image 502 shows a low-resolution scanned image of a relatively large tissue slice. Based on the whole tissue image 502, two regions of interest 504 and 506 are identified and high-resolution 3D images are generated for those regions (represented here as cubes). For example, various image planes can be collected and assembled into a 3D volumetric image of the sample. The identification of the regions of interest 504 and 506 can be automatic, manual, or a combination thereof. For example, a trained pathologist can review the whole image 502 and segment regions that may contain cancers 504 and 506. High-resolution imaging of those regions can be performed and the pathologist can segment the cancers within those regions based on the high-resolution 3D images.

[0095] Based on the two identified regions of interest 504 and 506, two extraction regions 514 and 516 may be extracted from the tissue. For example, an extraction system may move an extraction tool relative to the sample (and / or move the sample relative to the cutting tool) to slice out extraction regions 514 and 516. Extraction region 514 may include all (or a portion) of region 504, and extraction region 516 may include all (or a portion) of region of interest 506. In some embodiments, movement of the sample and / or cutting tool may be manual, automatic, or a combination thereof.

[0096] Flowchart 500 further includes box 520, which represents purifying the extracted tissue samples 514 and 516. The extracted tissues may be subjected to purification such that one or more biomarkers or other chemicals are isolated from the extracted tissues 514 and 516. Because the extracted tissues 514 and 516 are regions identified as primarily containing a single tissue type (cancer in this example), the purified biomarkers may be strongly associated with that tissue type.

[0097] 6A-6D are a series of diagrams showing exemplary images of a sample and analysis of genomes purified from identified regions of interest, according to some embodiments of the present disclosure. Data 600 in FIGS. 6A-6D are exemplary data collected using one or more microdissection systems, such as microdissection systems 100, 200, 300, and / or 400 of FIGS. 1-4. The analysis is a specific exemplary application based on imaging prostate tissue, extracting ROIs, and performing genomic analysis on them.

[0098] Image 610 of FIG. 6A shows a 2D image of a fluorescently labeled human prostate biopsy sample. The biopsy sample is optically cleared, stained, and then imaged. The biopsy sample is placed on a stage or sample holder of an imaging system. The 2D image of image 610 may be a slice of a 3D image collected from the tissue. Based on this 3D image of which image 610 is a part, various regions of interest are identified. In the example of FIGS. 6A-6D, these regions of interest are identified based on cell and tissue morphology, such as glandular structure. For example, a trained pathologist may review the 3D image to identify the locations of the regions of interest. In the example of FIGS. 6A-6D, three different regions of interest, ROI1, ROI2, and ROI3, are identified. FIGS. 620 (FIG. 6B) and 630 (FIG. 6C) show exemplary high-resolution images of ROI1 and ROI2, respectively. Based on the above identification, the three regions of interest are extracted using an extraction system. In this exemplary application, purification of nucleic acids from the extracted ROIs and genomic sequencing of those nucleic acids are performed. Figures 625 (Figure 6B), 635 (Figure 6C), and 615 (Figure 6D) show graphs of the genetic analysis results of ROI1, 2, and 3, respectively.

[0099] Three regions of interest (ROIs) with different morphologies were identified for DNA sequencing. The three ROIs were extracted and sequenced. A graph of the loci of key genes with different copy numbers is shown. ROI1 has pure cribriform morphology (grade group 4) and APC gene mutation with loss of heterozygosity. ROI2 has a mixture of cribriform and clear glands (grade group 3) and POLE loss. ROI3 has mostly clear glands (grade group 2) and is wild type for APC and POLE.

[0100] 7 is a flow chart of a method according to some embodiments of the present disclosure. Method 700 may, in some embodiments, be performed by one or more of the microdissection systems described herein. For example, method 700 may be performed by one or more of microdissection systems 100, 200, 300, and / or 400 of FIGS. 1-4.

[0101] Method 700 may generally begin at box 710, which represents generating a 3D image of a volumetric region of a sample using fluorescence microscopy. Method 700 may include generating the 3D image using an OTLS microscope (e.g., imaging system 102 of FIG. 1 and / or 250 of FIG. 2). For example, method 700 may include generating an illumination light sheet (e.g., 124 of FIG. 1), directing the light sheet through a window or other transparent surface into the sample, and then focusing the light through the sample and the window. In some embodiments, method 700 may include capturing a number of images of slices across the sample and then combining the slices into a 3D image. For example, method 700 may include acquiring a first slice image at a first location, acquiring a second slice image at a second location, and so on. In some embodiments, method 700 may include moving a stage of the imaging system to change the slice being imaged. In some embodiments, the stage may move automatically (eg, by the controller 104 of FIG. 1 and / or the computing system 202 of FIG. 2 operating actuators).

[0102] In some embodiments, method 700 may include one or more sample preparation steps prior to imaging in box 710. For example, if the sample is biological tissue, method 700 may include removing the sample from the organism (e.g., taking a biopsy, such as a CNB, from a patient). Method 700 may include optically preparing the sample for imaging. For example, method 700 may include optically clearing the sample. In some embodiments, method 700 may include applying one or more stains or dyes to the sample. In some embodiments, method 700 may include applying one or more specific stains targeted to various biomarkers of interest. For example, method 700 may include applying a fluorescent dye specific to one or more constituents of the region of interest, such as a particular tissue type or a particular biomarker.

[0103] Box 710 may typically be followed by box 720, which represents identifying a region of interest within the sample based on the 3D image. Method 700 may include identifying the region of interest manually, automatically, or a combination thereof. For example, method 700 may include manually selecting a region of interest based on review by a trained pathologist. In some embodiments, method 700 may include displaying the 3D image (e.g., on display 203 of FIG. 2) and determining coordinates of the region of interest based on manual input (e.g., via I / O 204 of FIG. 2).

[0104] In some embodiments, automatic identification may be used, such as by computing system 202 of FIG. 2. In some embodiments, method 700 may include identifying the region based at least in part on image analysis. For example, if the sample is prepared with a fluorescent dye specific to the region of interest, method 700 may include applying an intensity threshold to the image and selecting the region of interest based on regions that exceed the intensity threshold. In some embodiments, method 700 may include identifying the region of interest using a trained classifier (e.g., 228 of FIG. 2). In some embodiments, a classifier may be trained on 2D images, 3D images, or a combination thereof.

[0105] Box 720 may typically be followed by box 730. Box 730 represents extracting the region of interest from the sample. The extraction may be virtual, physical, or a combination thereof. Method 700 may include virtually extracting the region of interest, such as by generating a first low-resolution image of the sample, selecting a tentative region of interest, and then virtually extracting the tentative region of interest by generating a high-resolution image of the tentative region of interest, and determining whether the tentative region of interest is the region of interest based on the high-resolution image. The imaging and selection of the tentative region of interest may be generally similar to the steps of boxes 710 and 720 described herein. In some embodiments, the low-resolution image may be captured in a first collection path of the imaging system (e.g., 128 and 130 in FIG. 1 ) and the high-resolution image may be captured in a second collection path of the imaging system (e.g., 134 and 136 in FIG. 1 ).

[0106] In some embodiments, the method 700 may include physically extracting the region of interest. For example, the method 700 may include extracting the region of interest using an extraction system (e.g., 140 of FIG. 1 and / or 260 of FIG. 2). For example, the method 700 may include moving an extraction tool relative to the sample, moving the sample relative to the extraction tool, or a combination thereof. In some embodiments, the method 700 may include moving the extraction tool (and / or the sample) manually, automatically, or a combination thereof. For example, the method 700 may include displaying an outline of the region of interest and a current position of the extraction tool to enable manual movement of the extraction tool. In some embodiments, a controller, such as the computing system 202 of FIG. 2, may automatically move the extraction tool. In some embodiments, the extraction tool may be a cutting element, such as a blade, a guillotine cutter, a punch biopsy tool, or other sharp blade. In some embodiments, the extraction tool may be an optical cutting tool, such as a laser cutter.

[0107] In some embodiments, method 700 may include both virtual and physical extraction of the region of interest. For example, method 700 may include virtually extracting the region of interest and then physically extracting the region of interest.

[0108] In some embodiments, method 700 may include processing the extracted regions of interest. For example, method 700 may include purifying nucleic acids, proteins, metabolites, carbohydrates, lipids, or combinations thereof from the extracted regions of interest.

[0109] In some embodiments, method 700 may include performing the imaging of the sample on a first system and performing the extraction on a second system separate from the first system, hi some embodiments, method 700 may include performing the imaging and the extraction on the same system.

[0110] Of course, it should be understood that any example, embodiment, or process described herein may be combined with one or more other examples, embodiments, and / or processes, or may be separated and / or performed among separate devices or portions of devices, depending on the systems, devices, and methods herein.

[0111] Finally, the above description is merely illustrative of the system herein and should not be construed as limiting the scope of the appended claims to a particular embodiment or set of embodiments. Thus, while the system herein has been described in particular detail with reference to certain exemplary embodiments, it should also be understood that those skilled in the art may devise many modifications and alternative embodiments without departing from the broader and intended spirit and scope of the system as set forth in the following claims. Thus, the specification and drawings should be regarded as illustrative and not intended to limit the scope of the appended claims.

Claims

1. generating a 3D image of a volumetric region of the sample using fluorescence microscopy; Identifying a region of interest within the sample based on the 3D image; Extracting the region of interest from the sample; The method includes:

2. The method of claim 1 , further comprising generating the 3D image with an open-top light sheet microscope.

3. 10. The method of claim 1, further comprising purifying the nucleic acid, protein, metabolite, carbohydrate, lipid, or combination thereof.

4. The method of claim 1 , further comprising generating the 3D image with a first system and extracting the region of interest with a second system separate from the first system.

5. The method of claim 1 , further comprising performing automatic identification of the region of interest using a trained classifier.

6. The method of claim 5 , further comprising training the classifier with 2D training images, 3D training images, or a combination thereof.

7. 10. The method of claim 1, further comprising capturing a plurality of 2D images of the sample and generating the 3D image based on the plurality of 2D images.

8. The method of claim 1 , further comprising virtually extracting the region of interest.

9. The method of claim 1 , further comprising physically extracting the region of interest with one of a mechanical and an optical cutting element.

10. The method of claim 1 , further comprising labeling the sample with a fluorescent dye specific for one or more constituents of the region of interest.

11. an imaging system configured to capture a 3D image of the sample based on fluorescence microscopy; an extraction system configured to extract material from the sample based on coordinates of a region of interest located within the 3D image; A system including:

12. The system of claim 11 , wherein the imaging system comprises an open-top light sheet microscope.

13. The system of claim 11 , wherein the imaging system includes an illumination objective, a first focusing objective, and a second focusing objective, the first focusing objective having a higher resolution than the second focusing objective.

14. 14. The system of claim 13, wherein the illumination objective lens has an illumination optical axis, the first focusing objective lens has a first optical axis that forms a first angle with the illumination optical axis, and the second focusing objective lens has a second optical axis that forms a second angle with the illumination optical axis, the first angle and the second angle being different.

15. 14. The system of claim 13, wherein the imaging system includes a stage configured to support the sample on a first surface, and the illumination objective lens, the first focusing objective lens and the second focusing objective lens are located below a second surface of the stage opposite the first surface.

16. The system of claim 11 , wherein the extraction system is attached to the imaging system.

17. The system of claim 16 , wherein the extraction system is a modular component that is mounted on a stage of the imaging system.

18. The system of claim 11 , wherein the imaging system includes a biopsy holder configured to hold a core needle biopsy sample.

19. The system of claim 11 , further comprising a controller configured to identify the region of interest based on the 3D image.

20. The system of claim 19 , wherein the controller is further configured to operate the extraction system to extract the region of interest.

21. an imaging system configured to capture a 3D image of the sample based on fluorescence microscopy; an extraction system including an extraction tool; Computing systems and 1. A system comprising: A processor; A non-transitory computer readable medium encoded with instructions; wherein the instructions, when executed by the processor, cause the computing system to: Identifying a region of interest within the sample based on the 3D image; extracting the identified region of interest with the extraction tool; system.

22. 22. The system of claim 21, wherein the non-transitory computer readable medium further comprises a classifier, and the region is identified based in part on the classifier.

23. the computing system further comprising: a display configured to display the 3D image; and an input / output system configured to enable manual identification of the region of interest based on the displayed 3D image.

22. The system of claim 21.

24. 22. The system of claim 21, wherein the imaging system is an open-top light sheet microscope.

25. 22. The system of claim 21, wherein the computing system is further configured to operate an actuator to move the extraction tool relative to the sample, move the sample relative to the extraction tool, or a combination thereof.

26. The instructions, when executed by the processor, further cause the system to: Capturing a first 3D image at a first resolution; Identifying a provisional region of interest based on the first 3D image; capturing a second 3D image of the provisional region of interest based on the first 3D image, the second 3D image being of a second resolution higher than the first resolution; determining whether the provisional region of interest is the region of interest based on the second 3D image; 22. The system of claim 21.

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