WO2021096950A1

WO2021096950A1 - Cryostat or microtome with optical imaging detector

Info

Publication number: WO2021096950A1
Application number: PCT/US2020/060003
Authority: WO
Inventors: Sunil Singhal; Mitchell BRYSKI; Lydia Frenzel SULYOK
Original assignee: The Trustees Of The University Of Pennsylvania
Priority date: 2019-11-12
Filing date: 2020-11-11
Publication date: 2021-05-20

Abstract

The present invention provides a system including a cryomicrotome including a blade and a sample holder, and an imaging system comprising at least one detector and a controller coupled to the at least one detector. The imaging system is positioned such that the detector captures at least one signal as at least one of the blade and the sample holder are moved with respect to each other to slice a tissue sample obtained from a subject, and the controller is programmed to detect a signal from the sample, process the signal, and generate an alert regarding the signal from the sample.

Description

CRYOSTAT OR MICROTOME WITH OPTICAL IMAGING DETECTOR

CROSS-REFERENCE TO RELATED APPLICATION This application claims the benefit of priority of U S. Provisional Patent Application Serial No. 62/934,154, filed November 12, 2019. The entire content of this application is hereby incorporated by reference herein.

BACKGROUND OF THE INVENTION A cryostat, also called a cryotome or biological microtome, is a device used in a pathology lab to cut a human tissue, typically an organ or lymph node, into small pieces (1-10 micrometers thick). A typical cryostat is depicted in FIG. 1. Cut pieces of tissue, referred to as tissue sections or sections, are placed on a slide and subsequently stained so that a pathologist can make a frozen section (“quick section”) diagnosis.

Cancer surgery relies on cryostats. During an operation, cancer surgeons provide tissue to pathologists and wait for the results of the frozen section to continue the operation. The surgeon usually wants specific information regarding: (a) the presence of tumor cells, (b) the margin or edge of the tumor from the specimen borders, and (c) the type of tumor. The specimen is provided to a technician who cuts the specimen and places sections onto a microscope slide. Then, the pathologist reviews the slides to make the frozen diagnosis. There is a significant unmet need because the technician and/or pathologist may select a section of tissue that misses the disease. Sampling error resulting in incorrect frozen diagnosis could change the course of the operation for the patient, both affecting patient care and ultimately burdening hospitals with major financial consequences (range $5,000-$20,000 USD).

SUMMARY OF THE INVENTION

In certain embodiments, the present invention provides a system having a cryomicrotome and an imaging system. The cryomicrotome includes a blade and a sample holder. The imaging system has at least one detector and a controller coupled to the at least one detector. The imaging system is positioned such that the detector captures at least one signal as at least one of the blade and the sample holder are moved with respect to each other to slice a tissue sample obtained from a subject. The controller is programmed to detect a signal from the sample, process the signal, and generate an alert regarding the signal from the sample. In some embodiments, the imaging system further includes a light source. In some embodiments, the light source is a fluorescence light source.

In some embodiments, the detector includes a camera. In some embodiments, the camera includes at least one selected from the group consisting of: a fluorescence camera and a near- infrared camera. In some embodiments, the detector is a single-cell, spectroscopic detector. In some embodiments, the detector is a photoacoustic imaging device. In some embodiments, the detector includes a Geiger counter.

In some embodiments, the tissue sample includes one or more regions of interest. In some embodiments, the region of interest includes one or more selected from the group consisting of: tumor tissue, hyperplastic tissue, dysplastic tissue, lymph node, glandular tissue, inflamed tissue, infected tissue, and normal tissue. In some embodiments, the subject is a mammal.

In certain aspects, the present invention provides a method of detecting a signal within a sample, the method comprising: (a) embedding the sample in a fixing medium; (b) positioning the embedded sample within the system as described herein; (c) sectioning the sample while simultaneously detecting a signal from each section of the sample; and (d) repeating step (c) until an alert is generated by the controller.

In some embodiments, the signal is a fluorescence signal. In some embodiments, the fluorescence signal includes a near-infrared fluorescence signal. In some embodiments, the signal is a radioactivity signal.

In some embodiments, step (c) of the method further includes detecting a signal from the section.

In some embodiments, the method further includes step (a’) treating the sample with a tracer. In some embodiments, the tracer includes a fluorescence tracer. In some embodiments, the fluorescence tracer is a near-infrared fluorescence tracer. In some embodiments, the tracer includes a radioactive tracer.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an exemplary system of the present invention as contemplated herein.

FIGS. 2A and 2B depict human tissue mounted on a chuck for processing in the cryostat during frozen sectioning. FIG. 2A depicts the mounted tissue imaged using a visible-light channel. FIG. 2B depicts the mounted tissue imaged using a near-infrared (NIR) fluorescent-light channel.

FIGS. 3A and 3B depict representative frozen section slides from a pre-clinical experiment. In FIG. 3A, the top row depicts “Smart-Cut positive” panels, which are shown as fluorescence (detected with an 800-nm filter) in a tumor section, and correlates to the presence of cancer on the hematoxylin-and-eosin-stained (H&E) panel. “Smart-Cut negative” shown in the bottom row is the lack of fluorescence (detected with an 800-nm filter) in muscle, which correlates to the absence of cancer on the H&E panel. DAPI nuclear stain is blue, and is shown in the representative panels in the third column from the left. The 800-nm NIR fluorescence is pseudo-colored green and is shown in the panels on the far right. All microscopy was done at 20x, and the scale bar is 50 pm. FIG. 3B depicts NIR 800 nm channel imaging showing positive (top) or negative (bottom) fluorescence. Circles indicate areas where mean fluorescence intensity was calculated for TBRs.

FIGS. 4A and 4B depict sections of lung cancer tissue cut from a lung wedge. FIG. 4A depicts sections, stained and unstained. Panel A depicts a section stained with H&E, the traditional method to make a diagnosis. Panel B depicts a section stained with immunohistochemistry, showing the receptor to which this example dye selectively attaches (i.e., FR-alpha). Panel C depicts an unstained section, imaged at the relevant wavelength on the LICOR ODYSSEY^® CLx imaging system, which selectively excites the dye within the tissue (e.g., 800 nm). Panel D depicts an unstained section, imaged at the relevant wavelength (e.g., 800 nm channel) on the LEICA© fluorescence microscope. FIG. 4B depicts tumor sections, stained and unstained. Panel A depicts sections stained with H&E. Panel B depicts sections stained for the receptor targeted by the dye (e.g., FR-alpha). Panel C depicts unstained sections, imaged using a fluorescence channel at 800 nm. In the example, there is a direct correlation between the tumor cells of interest, as seen by visible light stained with H&E, which are fluorescing in the expected wavelength, due to the dye having selectively attached to the receptor positively expressed in the tumor.

FIGS. 5A and 5B depicts images from an optical biopsy, showing visible, near infra-red (NIR), and overlaid channels. The strong fluorescent signal suggests a diagnosis of adenocarcinoma, and allows for rapid, fool-proof localization of the nodule both during surgery and in pathology. FIG. 5A depicts in vivo imaging. FIG. 5B depicts ex vivo imaging of a tissue wedge and bisected tissue.

FIG. 6 depicts images of both murine pancreatic cancer cell line 4662 and human pancreatic adenocarcinoma demonstrating that indocyanine green (ICG) staining selectively accumulates in pancreatic cancer tissue. This example demonstrates the utility of this technology not only in the clinic but also in the translational research setting.

FIGS. 7A and 7B depict pre-clinical murine model specimens with ICG fluorescence contrast agent. FIG. 7A depicts frozen sections that were cut directly from murine flank tumor, in order to show near infrared fluorescence throughout the tumor. FIG. 7B depicts frozen sections that were cut from the margin between flank tumor and muscle, in order to demonstrate specificity of the near infrared dye for the tumor and not for the normal tissue. Broadly, this technique can be used to alert a pathologist or technician to the edge of the tumor or cancer, and to inspect the adjacent margin, which is increasingly helpful if the microtome were automatically reading each slice as it cut through the tumor. FIGS. 8A and 8B depicts human specimens from clinical trials stained using ICG fluorescence contrast agent. FIG. 8A depicts sections that were cut through pancreatic tumor, showing ICG accumulation in pancreatic adenocarcinoma. FIG. 8B depicts sections that were cut from a cystic pancreatic tumor, showing accumulation of ICG.

FIG. 9 depicts an exemplary workflow according to an embodiment of the invention. FIG. 10 illustrates the integration of the Smart-Cut system into pathology workflow according to an embodiment of the invention.

FIG. 11 depicts a schematic representation of an exemplary Smart-Cut workflow. After grossing the specimen (A), either with or without fluorescence imaging by Smart-Cut, the neoplasm is frozen (B) for quick sectioning and fluorescence visualization on the Smart-Cut. The Smart-Cut system includes an LED light source (C), filter (D), and NIR camera used in conjunction with a standard cryostat (F). The Smart-Cut system excites a contrast agent localized to the lesion. Emitted light is interpreted by the computer (G) such that changes in detected fluorescence intensity are used to differentiate between cancer and normal tissue. The slide can then be prepared for reading by the pathologist (H). The star on the display screen represents fluorescence detected in a tumor section. FIGS. 12, Panels A-H depict an exemplary workflow of surgery with IMI. FIG. 12,

Panel A depicts traditional video-assisted thoracoscopic surgery (VATS) visualization of a lesion. FIG. 12, Panel B depicts IMI performed intraoperatively localizes the target lesion in situ. FIG. 12, Panel C illustrates that after excision of the specimen, margins can be grossly assessed on the back table and further visualized with IMI (shown in FIG. 12, Panel D). Opening the specimen, shown in FIG. 12, Panel E, demonstrates lesion-specific uptake of the dye (shown in FIG. 12, Panel F). FIG. 12, Panel G depicts frozen section samples of uninvolved lung (left) and the cancerous lesion (right). FIG. 12, Panel H demonstrates that, using IMI, the cancerous lesion can be identified and distinguished from adjacent normal tissue. DETAILED DESCRIPTION

Definitions

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, the preferred methods and materials are described.

As used herein, each of the following terms has the meaning associated with it in this section.

The articles “a” and “an” are used herein to refer to one or to more than one (i.e., to at least one) of the grammatical object of the article. By way of example, “an element” means one element or more than one element.

“About” as used herein when referring to a measurable value such as an amount, a temporal duration, and the like, is meant to encompass variations of ±20%, ±10%, ±5%, ±1%, or ±0.1% from the specified value, as such variations are appropriate to perform the disclosed methods.

Ranges: throughout this disclosure, various aspects of the invention can be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the invention. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 2.7, 3, 4, 5, 5.3, and 6. This applies regardless of the breadth of the range. Description

The present invention provides cryomicrotome systems and methods for preparing a tissue sample using the cryomicrotome system, and method for detecting a signal in a tissue sample.

Cryomicrotome System Embodiments of the present invention provide cryomicrotome systems for sectioning, imaging, and processing biological samples. The cryomicrotome may include one or more of a cryostat/microtome system, an imaging system and an image processing system. The biological sample may include tissue samples such as tumor tissue, hyperplastic tissue, dysplastic tissue, lymph node, glandular tissue, inflamed tissue, infected tissue, normal tissue, and the like. The cryomicrotome systems as described herein may assist in more accurate and rapid diagnosing of tissues (e.g. pathological tissues) in a subject. The subject may include a mammal (e.g. human), or more simply a eukaryotic organism.

Referring now to FIG. 1, embodiments of the cryomicrotome system 100 of the present invention include one or more temperature-controlling cryostats and/or tissue sectioning microtomes. The cryostat/microtome 110 may include one or more standard cryostats/microtomes as understood in the art. The cryostat may include one or more cryostats that maintains an internal temperature of about -10°C, from about -10°C to about -20°C, from about -20°C to about -30°C, or below about -30°C. The one or more microtomes can include one or more blades suitable for cutting samples including frozen tissue samples. The frozen tissue samples may be embedded in one or more suitable media including for example optimal cutting temperature compound (OCT). The cryostat/microtome may include one or more sample holders including for example a chuck on which one or more samples can be mounted using a compound such as OCT. The one or more sample holders may include standard sample holders as understood in the art. The cryostat/microtome may include one or more switchable light sources such as a white light source for visualizing objects including samples inside the cryostat. The objects may include samples mounted on the microtome and/or other objects for use in sectioning. The one or more switchable light sources may be switched to an off position allowing for nearly complete darkness within the inside of the cryostat.

Embodiments of the cryomicrotome system 100 include one or more imaging systems 120. The imaging system 120 may include at least one controlled light source, at least one detector, and at least one controller. The at least one controlled light source may include at least one fluorescence light source. The controlled light source may include at least one laser light source. The controlled light source may have excitation channels ranging from less than 400 nm (ultraviolet wavelengths), about 400 nm to about 900 nm (visible light wavelengths), about 700 nm to about 1000 nm (near-infrared wavelengths), or greater than 1000 nm (infrared wavelengths). The controlled light source may have excitation channels with filter bandwidths ranging from about 5 nm to about 10 nm, about 10 nm to about 20 nm, about 20 nm to about 30 nm, and the like. In some embodiments, the one or more samples are excited with one or more pulsed laser light sources. In some embodiments, the one or more samples are excited with one or more pulsed radiofrequency sources. Thus, the controlled light source 120 can be matched ( e.g ., by emission spectra, filtering, and the like) to one or more dyes to be utilized, which specify appropriate excitation spectra.

In some embodiments, the imaging system is sold separately as an upgrade to cryostat.

Embodiments of the imaging system include at least one detector. The at least one detector can include, for example at least one camera capable of detecting light from one or more samples, the light having emission wavelengths ranging from about 400 nm to about 900 nm, and or greater than 900 nm. The detector may be capable of detecting emission signals having ultraviolet wavelengths (less than about 400 nm), visible light wavelengths (about 400 nm to about 800 nm), near-infrared emission wavelengths (great than about 800 nm), and/or combinations thereof. Other exemplary detectors include a stereoscope, a photoacoustic imager, or any imaging device that can either create a three-dimensional rendition or see optical signals deeper than the surface.

The detector may have emission filters having a bandwidth ranging from about 10 nm, about 10 nm to about 20 nm, about 20 nm to about 30 nm, about 30 nm to about 50 nm, or greater than about 50 nm. The detector may have an unfiltered (e.g. open filter) detector. The detector may have multiple channels for detecting more than one signal from the sample. For example the detector may detect emission signals from the sample using at least two channels, at least three channels, at least four channels, up to five channels, up to eight channels, up to 10 channels and the like. In certain embodiments, the detector may include an ultrasound detector, for example, a photoacoustic detector. In certain embodiments, the detector includes a single-cell spectroscopic detector. The spectroscopic detector may include a single channel detector, a continuous spectrum detector, multiple discrete wavelength channel detectors, and/or combinations thereof.

Embodiments of the imaging system include at least one controller. The controller can be coupled to the at least one detector. The controller can be programmed to receive and/or detect a signal from the detector. In some embodiments, the controller generates an alert ( e.g ., an audio alert, a visual alert, an interrupt, a push notification, a message, and the like) when a signal from the sample is detected from the detector. In some embodiments, when a signal is detected, the controller provides feedback to and/or controls the cryomicrotome system resulting in the microtome ceasing to cut the sample. In some embodiments, when a signal is detected, the system acquires an image, and advances to cutting a series of sections, acquiring an image of each section. In some embodiments, the controller compiles the series of acquired images. In some embodiments, the controller reconstructs an image (e.g. three-dimensional reconstruction) of the signal-generating region of the sample from the series of acquired images. In some embodiments, the series of acquired images includes a series of up to 10 images, from 10 to 20 images, from 20 to 30 images, from 30 to 40 images, from 40 to 50 images, or greater than 50 images. Embodiments of the controller can be programmed to measure and/or quantify the fluorescence signal detected from the sample. The controller can be implemented in hardware (e.g., a processor, an Application-Specific Integrated Circuit (ASIC), and the like) and/or software and can operate without human intervention. Embodiments of the imaging system include one or more radiation detectors. For example, the imaging system may include one or more Geiger counters for detecting radiation in the sample. The one or more Geiger counters may include Geiger counters capable of detecting emissions from particle alpha decay, beta decay, gamma decay, positron decay, proton emission, etc. In some embodiments, the sample may have a radiolabeled portion, for example a radiolabeled tumor portion within the tissue sample.

One exemplary workflow that can be implemented by a controller is depicted in FIG. 9. In step S902, the sample is sliced.

In step S904, an image can be acquired. The image can be of the relatively thin portion that was most-recently removed from the sample or can be of the freshly-exposed new surface of the sample. As used herein, an image can be a spatially defined capture of an image ( e.g ., fluorescence) or can be non-spatially-defmed (e.g., with a Geiger counter).

In step S906, the image is assessed for the presence of a probe. For example, the controller can apply a threshold. In other embodiments, artificial intelligence can be applied to provide a more sophisticated autonomous interpretation. If the probe is not detected, the slicing (S902) and imaging (S904) can continue until a probe is detected. Once the probe is detected, one or more actions can be taken. Additional images (e.g., visible light) can be captured (S908), the one or more images previously captured in S904 and S908 can be stored (S910), an alert can be generated (S912), and/or the cryostat can be paused (S914). The controller can be programmed to perform other actions based on one or more conditions. Methods

The present invention provides methods for detecting a signal in a sample. The sample can include a biological sample such as a tissue sample. The biological sample may include tissue samples such as tumor tissue, hyperplastic tissue, dysplastic tissue, lymph node, glandular tissue, inflamed tissue, infected tissue, normal tissue, and the like. The tissue may include one or more regions of interest. In some embodiments, the regions of interest may include regions labeled with one or more compounds including one or more tracers such as fluorescence tracers, radioactive or radiolabeled tracers, bioluminescence tracers, and the like. In some embodiments, the one or more regions of interest may include unlabeled regions that are treated with one or more tracers while being sectioned. In some embodiments, the sample is treated with one or more tracers ex vivo. In some embodiments, the sample is collected from a tissue that was treated with one or more tracers in vivo. The tissue may have been treated with one or more tracers systemically, locally, and/or a combination thereof.

Embodiments of the methods of the invention include embedding the sample in a compound such as a fixing medium. The compound can include any suitable mediums for sectioning frozen tissue as understood in the art, including, for example optimal cutting temperature compound. The embedded sample may be fixed and/or mounted onto a chuck or other suitable device for mounting the sample onto the microtome of the cryomicrotome system as described herein.

Embodiments of the methods include positioning the mounted, embedded sample within the cryomicrotome system. The embedded, mounted sample is positioned within the system so that an appropriate cutting angle is able to be generated and so that the sample is able to be suitably imaged by the imaging system as described herein.

Embodiments of the methods include sectioning the sample while simultaneously detecting a signal from each subsequent section of the sample. The sections may include sections having a thickness of less than 10 pm, about 10 pm to about 20 pm, about 20 pm to about 30 pm, about 30 pm to about 40 pm, about 40 pm to about 50 pm, about 50 pm to about 60 pm, about 60 pm to about 70 pm, about 70 pm to about 80 pm, about 80 pm to about 90 pm, about 90 pm to about 100 pm, and so on. An image may be acquired of each section and not of the mounted sample. The cut section may be simultaneously mounted onto a slide and imaged on the slide. Alternatively, an image may be acquired of the cut sample, and not of the cut section. The cut, non-imaged section may fall freely away from the mounted sample, allowing for an unobstructed image of the cut, mounted sample to be acquired. In some embodiments, an image is acquired of both the mounted sample and the cut section.

Embodiments of the methods include treating the sample with a reagents or tracer after each section is cut, and then imaging the sample. The reagent/tracer may be applied to the sample using a suitable technique including for example, spraying, painting, adding dropwise, pouring in excess, pouring a thin layer, and the like.

Embodiments of the methods include continuing to cut/section the sample and acquire at least one image of the mounted sample and/or the cut section until a signal is detected. The signal may include a fluorescence signal, a bioluminescence signal, Cherenkov luminescence signal, radioactivity signal, and the like. Embodiments of the method include continuing to cut the sample until the controller processes that a signal is detected and generates an alert. The method may include ceasing to cut the sample once an alert is generated. The method may include proceeding to cut a single section for mounting on a slide once the controller generates an alert. The method may include proceeding to cut a series of additional images once an alert is generated. The series of images may include a series of up to 10 images, about 10 images to about 25 images, about 25 images to about 50 images, about 50 images to about 100 images, or more than 100 images. The series of images may be used to generate a three-dimensional reconstruction of the signal -generating region of interest in the sample. The series of images may be used to determine whether a physiological or pathophysiological feature of interest is present or absent in the sample. For example, the series may be used in order to determine whether a lung adenocarcinoma is present. The series may be used to determine whether an infection, a tumor or neoplastic tissue, fatty tissue (e.g., fatty live disease), collagenous tissue (e.g., interstitial pulmonary fibrosis), and the like are present.

The controller may process the one or more images. For example, the controller may quantify the detected signal. The signal may be quantified relative to a comparator control.

EXPERIMENTAL EXAMPLES

Example 1. Molecular Imaging to Enhance Frozen Section Pathology Introduction

Intraoperative frozen section (FS) consultation is a valuable tool in surgical oncology to rapidly obtain data that will affect the patient’s operative plan. Most commonly, FS is used to evaluate margin status, identify benign versus malignant tissue and lymph nodes, or classify tumors. FS consultation is particularly important in thoracic oncology, where almost half of patients undergo pulmonary resection for a suspicious lung mass without a pre-operative tissue biopsy. Because the operation is effectively put on hold while awaiting the results of FS consultation, speed is an important consideration for patient safety, with most FS results reported back to the OR within 20-30 minutes. While aiming for quick results and utilizing only a small portion of the resected tissue, FS consultation suffers from numerous shortcomings, most notably tissue sampling error. Tissue sampling error can occur when the specimen submitted for FS analysis does not contain the lesion of interest (which is discovered in the additional tissue submitted for permanent sections), or when pathologic tissue is present only in deeper sections of the FS block not reviewed during intraoperative FS consultation. These sampling errors result from an inability to identify or visualize pathologic tissue during grossing and sectioning.

Over the last 5 years, a new approach called Intraoperative Molecular Imaging (IMI) has been used effectively by surgeons to visualize pathologic lesions during surgery. During IMI, a fluorescent contrast agent is injected into the patient prior to surgery and localizes to the target lesion. During surgery, a light source is used to excite the optical contrast agent in the organ of interest and the resulting optical emission is detected with a camera system. IMI allows surgeons to clearly visualize lesions that are invisible to the naked eye, imperceptible on palpation, or even radiographically occult. IMI requires a suitable fluorescent contrast agent, ideally with emission in the NIR range (700-900nm), and a specialized imaging system to quantify the dye. The fluorescent dye can localize to the tumor based on its comparatively leaky vasculature via the Enhanced Permeability and Retention (EPR) Effect or by actively targeting tumor markers through receptor-ligand binding or antibody. By conjugating a fluorophore to a ligand or antibody targeting tumor-specific cell markers, dyes can localize to the tumor for sensitive and specific visualization, adding a new tool to the surgeon’s arsenal beyond mere visual inspection and manual palpation. Once the dye has localized to the tumor (a process that can take minutes or days, depending on the pharmacokinetics of the dye), it can be excited with the specialized imaging system to make the tumor glow. Materials and Methods

Fluorescence Detection System

In this early prototype, a small, portable fluorescence imaging system developed by the inventors, the SPIIF, was re-purposed for integration into Smart-Cut. The SPIIF has been described in detail previously (Okusanya OT, et al. Technol Cancer Res Treat. 2015; 14(2):213- 220). Briefly, the SPIIF system is composed of a NIR charge-coupled device (CCD) camera with an articulating light filter and LED light source mounted with a screw and washer system to a weighted platform. The SPIIF was selected due to its small footprint (15 cm x 10 cm) and low weight (less than one kilogram). For preliminary testing of the Smart-Cut system, the SPIIF was optimized for imaging with ICG using an LED of 740 nm for excitation and a long-pass filter at 800 nm for signal collection. However, as an interchangeable imager, the SPIIF can be configured to image other dyes at different wavelengths, for example, fluorescein in the visible range.

For use in the clinical case presentation, a commercially available NIR imaging system (VS3 Iridium, Visionsense, USA) was brought into the surgical pathology suite and used as a proof-of-principle for the Smart-Cut technology. Mechanical Cryostat System

The SPIIF imaging system was mounted to a standard research cryostat (CM3050, Leica Biosystems, Germany). The camera head was directed at the cryochamber, pointing directly at the mounting head and cryostat blade - where the specimen was mounted for sectioning after freezing in OCT (FIG. 1).

Animal Experimental Model

Twelve female athymic nude mice (Charles River Laboratories, USA) were purchased and housed in pathogen-free conditions and used for experiments at eight weeks of age or older for our flank tumor model. The KB cell line was cultured, maintained, and passaged in RIO media, consisting of RPMI (RPMI 1640 Medium, Gibco Life Technologies) supplemented with 10% fetal bovine serum (FBS; Hy clone), 1% penicillin/1% streptomycin (Gibco Life Technologies) and 1% L-glutamine (Coming).

Mice were injected subcutaneously with 1 x 10⁶ cells suspended in 100 pL of R10 media and MATRIGEL® matrix in a 1 : 1 ratio. The tumors were allowed to grow to a size of at least 500 mm³ and were then injected with 100 pL of 10 pM ICG through the tail vein. 24 hours after ICG injection, the mice were imaged on a NIR small-animal imaging system (Pearl Trilogy, LI-COR, USA) and the tumors harvested along with adjacent normal muscle tissue.

The tissue was frozen in OCT and sectioned on the Smart-Cut cryostat. Frozen tissue was trimmed until ICG fluorescent signal was detected. Then, two consecutive cuts were mounted on slides (UNIFROST® Microscope Slides, Azer Scientific, USA), one stained with H&E and one with DAPI (PROLONG™ Diamond Antifade Mountant with DAPI, Thermofisher, USA), and then imaged under brightfield and NIR light (DM6B Microscope, Leica Microsystems, Germany).

Consecutive cuts of non-fluorescent tissue were also taken as a negative control, and as above, stained with either H&E or DAPI, and imaged for brightfield and fluorescence microscopy.

Tumor-to-background ratios (TBRs) were calculated using region of interest (ROI) analysis comparing fluorescent area to an adjacent non-fluorescent area on IMAGEJ™ software (ImageJ 1.50i, NIH, USA). Clinical Validation

As part of an ongoing clinical trial (NCT02651246) of the TUMORGLOW® process for intraoperative identification of cancer, a 45-year-old woman with a history of stage III colon cancer status post hemicolectomy with adjuvant chemotherapy presented to the thoracic surgery clinic for diagnostic biopsy of bilateral lung nodules. She underwent a left VATS wedge resection 24 hours after receiving a 3 mg/kg dose of ICG for intraoperative imaging. Two nodules were resected and sent to the pathology suite for intraoperative FS consultation. Fluorescence imaging of the frozen specimen was conducted in the clinical pathology suite as Smart-Cut proof-of-principle to identify cancer. Results Workflow

To ensure Smart-Cut’s potential for broad uptake in frozen section consultation,

Applicant designed the device to be easily integrated into the pathology suite with minimal disruption to existing workflows (FIG. 10). The device can be used at multiple steps in the frozen section process to confirm the presence of cancer and is designed as an adjunct to the standard cryostat, an instrument that is currently available in typical pathology suites in hospitals (FIG. 11).

The camera system is small and ergonomic (weighing less than 1 kilo). The camera’s small footprint (15 cm x 10 cm) allows it to be attached to the cryostat without impinging on its sectioning performance or the comfort of the technician. Additionally, with the interchangeable capabilities of the imaging system, the LED light source and optical filters can be switched out to image a range of contrast agents in the visible and NIR ranges without increasing the device footprint. The Smart-Cut system is easily integrated into existing workflows and instruments of the pathology suite. Animal Experiments

The Smart-Cut device prototype and proposed workflow were tested in a pre-clinical setting to validate its efficacy.

Twelve athymic nude mice with xenograft flank tumors (KB CVCL0372 cells) were injected with ICG, as previously described (Madajewski B, et al. Clin Cancer Res. 2012;18(20):5741-5751). The flank tumors were imaged on a commercially-available small animal imaging system (Pearl Trilogy, LI-COR, USA) to confirm the presence of the fluorophore within the tumor tissue. All 12 flank tumors were fluorescent with mean TBR 4.4 (SD±1.2). The tumor was harvested, frozen in OCT and sectioned on Smart-Cut. Once fluorescent signal was detected in the OCT block by Smart-Cut, a 5 pm section was cut, mounted, H&E stained, and imaged on a brightfield microscope (LEICA© DM6B, Germany). A consecutive slide was then cut and counter-stained with DAP1 for fluorescence microscopy.

All 12 Smart-Cut fluorescent slides showed cancer present on H&E.

As a negative control, tissue read as non-fluorescent by the Smart-Cut system was also H&E stained with consecutive cuts counter- stained with DAPI. All 12 slides had normal muscle tissue with no cancer present.

Mean TBR of fluorescent to non-fluorescent tissue sections was 6.8 (SD±3.8) (FIG. 3).

The Smart-Cut system detected cancer by fluorescence on frozen section with no false negatives or false positives in a pre-clinical murine model. Clinical Validation

Next, the Smart-Cut prototype and workflow were assessed as part of an ongoing clinical trial (NCT02651246) of the TUMORGLOW® process for intraoperative identification of cancer, shown in FIGS. 12, Panels A-H. A patient presented for surgical resection of suspected colorectal adenocarcinoma metastases to the lung. Two lesions (one of which was radiographically occult) were identified intraoperatively, as previously reported (Newton AD, et al. J Thorac Dis. 2018;10(7):E544-E548). The specimens were sent for frozen section pathology, with the suspected lesions mounted in OCT for sectioning. Fluorescence imaging of the specimen on the chuck helped identify the 2 mm occult lesion (TBR 3.1). The frozen section cut from this fluorescent tissue was read as colorectal adenocarcinoma and reported back to the OR. The combination of fluorescence imaging and frozen sectioning embodied in the Smart-

Cut system identifies cancer and has the potential to streamline intraoperative FS consultation.

Discussion

Intraoperative consultation with frozen section pathology is a valued element of surgical care, but it has several limitations. Chief amongst these limitations is sampling error, which, in a retrospective review of all intraoperative frozen section consultations from a tertiary-level hospital and cancer center during a 6 month period (n=1042), was responsible for 50% of all discordance between intraoperative consultation with frozen section and final diagnosis. Here, a solution is proposed to reduce the occurrence of sampling error by introducing molecular imaging to the pathology suite through Smart-Cut, a cryostat integrated with optical imaging capability that was tested in the pre-clinical and clinical settings.

Smart-Cut has the potential to be broadly used in surgical pathology because of its integrability into existing workflows. With the imaging system’s small footprint incorporated with a standard cryostat, Smart-Cut brings the added benefit of optical imaging to the pathology suite without the additional bulk of traditional back-table imaging devices.

Additionally, in a pre-clinical murine model, Smart-Cut demonstrated the potential to identify cancer in frozen section tissue with neither false positives nor false negatives. This reassurance from optical imaging can give the pathologist additional confidence that the pathologic lesion has been appropriately sampled with the potential to minimize the incidence of sampling error. Confirmation with fluorescent signal also has the potential to speed up the FS consultation by limiting the need for re-sectioning tissue to confirm the presence of cancer.

Finally, the theory behind Smart-Cut was actualized in the surgical pathology suite of a high-volume academic center to validate the principles of optical imaging for frozen section consultation. In this case study, NIR imaging quickly located both pathologic lesions, after initial grossing under white light located only one. Smart-Cut therefore has potential to speed up the FS consultation process, and possibly even identify lesions that would previously have been found only on permanent section.

In some instance Smart-Cut for FS consultation secondary to intraoperative molecular imaging may be limited by the efficacy of the targeting agent. However, this can be addressed by optimizing the contrast agents used for each patient, based on clinical judgement, pre-operative tissue biopsy, and/or radiographic presentation to assure dye uptake in the lesion. Additionally, the use of multiple contrast agents in a “dye cocktail” may improve sensitivity of Smart-Cut. By using dyes of differing emission wavelengths, Smart-Cut can leverage the interchangeability of its SPIIF imaging platform to maintain receptor-specificity of each individual dye while still appreciating the improved sensitivity of a dye cocktail. EQUIVALENTS

Although preferred embodiments of the invention have been described using specific terms, such description is for illustrative purposes only, and it is to be understood that changes and variations may be made without departing from the spirit or scope of the following claims. INCORPORATION BY REFERENCE

The entire contents of all patents, published patent applications, and other references cited herein are hereby expressly incorporated herein in their entireties by reference.

Claims

1. A system comprising: a cryomicrotome comprising: a blade; and a sample holder; and an imaging system comprising: at least one detector; and a controller coupled to the at least one detector; wherein: the imaging system is positioned such that the detector captures at least one signal as at least one of the blade and the sample holder are moved with respect to each other to slice a tissue sample obtained from a subject; and the controller is programmed to: detect a signal from the sample; process the signal; and generate an alert regarding the signal from the sample.

2. The system of claim 1, wherein the imaging system further comprises: a light source.

3. The system of claim 2, wherein the light source is a fluorescence light source.

4. The system of claim 1, wherein the detector comprises a camera.

5. The system of claim 4, wherein the camera comprises at least one selected from the group consisting of: a fluorescence camera and a near-infrared camera.

6. The system of claim 1, wherein the detector is a single-cell, spectroscopic detector.

7. The system of claim 1, wherein the detector is a photoacoustic imaging device.

8 The system of claim 1, wherein the detector comprises a Geiger counter.

9. The system of claim 1, wherein the tissue sample comprises one or more regions of interest.

10. The system of claim 9, wherein the region of interest comprises one or more selected from the group consisting of: tumor tissue, hyperplastic tissue, dysplastic tissue, lymph node, glandular tissue, inflamed tissue, infected tissue, and normal tissue.

11. The system of claim 1, wherein the subject is a mammal.

12. A method of detecting a signal within a sample, the method comprising:

(a) embedding the sample in a fixing medium;

(b) positioning the embedded sample within the system of claim 1;

(c) sectioning the sample while simultaneously detecting a signal from each section of the sample; and

(d) repeating step (c) until an alert is generated by the controller.

13. The method of claim 12, wherein the signal is a fluorescence signal.

14. The method of claim 13, wherein the fluorescence signal comprises a near-infrared fluorescence signal.

15. The method of claim 12, wherein the signal is a radioactivity signal.

16. The method of claim 12, wherein step (c) further comprises detecting a signal from the section.

17. The method of claim 12, wherein the method further comprises (a’) treating the sample with a tracer.

18. The method of claim 17, wherein the tracer comprises a fluorescence tracer.

19. The method of claim 18, wherein the fluorescence tracer is a near-infrared fluorescence tracer.

20. The method of claim 17, wherein the tracer comprises a radioactive tracer