Ex Vivo Microscopy: A Promising Next-Generation Digital Microscopy Tool for Surgical Pathology Practice

Ex Vivo Fluorescence Confocal Microscopy for Intraoperative Examinations of Lung Tumors as Alternative to Frozen Sections-A Proof-of-Concept Study

BACKGROUND

Intraoperative frozen sections (FS) are frequently used to establish the diagnosis of lung cancer when preoperative examinations are not conclusive. The downside of FS is its resource-intensive nature and the risk of tissue depletion when small lesions are assessed. Ex vivo fluorescence confocal microscopy (FCM) is a novel microimaging method for loss-free examinations of native materials. We tested its suitability for the intraoperative diagnosis of lung tumors.

METHODS

Samples from 59 lung resection specimens containing 45 carcinomas were examined in the FCM. The diagnostic performance in the evaluation of malignancy and histological typing of lung tumors was evaluated in comparison with FS and the final diagnosis.

RESULTS

A total of 44/45 (98%) carcinomas were correctly identified as malignant in the FCM. A total of 33/44 (75%) carcinomas were correctly subtyped, which was comparable with the results of FS and conventional histology. Our tests documented the excellent visualization of cytological features of normal tissues and tumors. Compared to FS, FCM was technically less demanding and less personnel intensive.

CONCLUSIONS

The ex vivo FCM is a fast, effective, and safe method for diagnosing and subtyping lung cancer and is, therefore, a promising alternative to FS. The method preserves the tissue without loss for subsequent examinations, which is an advantage in the diagnosis of small tumors and for biobanking.

Scattering-Based Light-Sheet Microscopy Imaging of Human Papillomavirus-Associated Squamous Lesions of the Anal Canal: A Proof-of-Principle Study

Demand for anal cancer screening is expected to rise following the recent publication of the Anal Cancer-HSIL Outcomes Research trial, which showed that treatment of high-grade squamous intraepithelial lesions significantly reduces the rate of progression to anal cancer. While screening for human papillomavirus-associated squamous lesions in the cervix is well established and effective, this is less true for other sites in the lower anogenital tract. Current anal cancer screening and prevention rely on high-resolution anoscopy with biopsies. This procedure has a steep learning curve for providers and may cause patient discomfort. Scattering-based light-sheet microscopy (sLSM) is a novel imaging modality with the potential to mitigate these challenges through real-time, microscopic visualization of disease-susceptible tissue. Here, we report a proof-of-principle study that establishes feasibility of dysplasia detection using an sLSM device. We imaged 110 anal biopsy specimens collected prospectively at our institution's dysplasia clinic (including 30 nondysplastic, 40 low-grade squamous intraepithelial lesion, and 40 high-grade squamous intraepithelial lesion specimens) and found that these optical images are highly interpretable and accurately recapitulate histopathologic features traditionally used for the diagnosis of human papillomavirus-associated squamous dysplasia. A reader study to assess diagnostic accuracy suggests that sLSM images are noninferior to hematoxylin and eosin images for the detection of anal dysplasia (sLSM accuracy = 0.87; hematoxylin and eosin accuracy = 0.80; P = .066). Given these results, we believe that sLSM technology holds great potential to enhance the efficacy of anal cancer screening by allowing accurate sampling of diagnostic tissue at the time of anoscopy. While the current imaging study was performed on ex vivo biopsy specimens, we are currently developing a handheld device for in vivo imaging that will provide immediate microscopic guidance to high-resolution anoscopy providers.

Structured illumination microscopy for cancer identification in diagnostic breast biopsies

Breast cancer is the second most common cancer diagnosed in women in the US with almost 280,000 new cases anticipated in 2023. Currently, on-site pathology for location guidance is not available during the collection of breast biopsies or during surgical intervention procedures. This shortcoming contributes to repeat biopsy and re-excision procedures, increasing the cost and patient discomfort during the cancer management process. Both procedures could benefit from on-site feedback, but current clinical on-site evaluation techniques are not commonly used on breast tissue because they are destructive and inaccurate. Ex-vivo microscopy is an emerging field aimed at creating histology-analogous images from non- or minimally-processed tissues, and is a promising tool for addressing this pain point in clinical cancer management. We investigated the ability structured illumination microscopy (SIM) to generate images from freshly-obtained breast tissues for structure identification and cancer identification at a speed compatible with potential on-site clinical implementation. We imaged 47 biopsies from patients undergoing a guided breast biopsy procedure using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. These biopsies had an average size of 0.92 cm2 (minimum 0.1, maximum 4.2) and had an average imaging time of 7:29 (minimum 0:22, maximum 37:44). After imaging, breast biopsies were submitted for standard histopathological processing and review. A board-certified pathologist returned a binary diagnostic accuracy of 96% when compared to diagnoses from gold-standard histology slides, and key tissue features including stroma, vessels, ducts, and lobules were identified from the resulting images.

High-resolution full-field optical coherence tomography microscope for the evaluation of freshly excised skin specimens during Mohs surgery: A feasibility study

Histopathology for tumor margin assessment is time-consuming and expensive. High-resolution full-field optical coherence tomography (FF-OCT) images fresh tissues rapidly at cellular resolution and potentially facilitates evaluation. Here, we define FF-OCT features of normal and neoplastic skin lesions in fresh ex vivo tissues and assess its diagnostic accuracy for malignancies. For this, normal and neoplastic tissues were obtained from Mohs surgery, imaged using FF-OCT, and their features were described. Two expert OCT readers conducted a blinded analysis to evaluate their diagnostic accuracies, using histopathology as the ground truth. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 basal cell carcinomas [BCCs] and 17 squamous cell carcinomas [SCCs]). The average reader diagnostic accuracy was 88.1%, with a sensitivity of 93.7%, and a specificity of 58.3%. The artificial intelligence (AI) model achieved a diagnostic accuracy of 87.6 ± 5.9%, sensitivity of 93.2 ± 2.1%, and specificity of 81.2 ± 9.2%. A mean intersection-over-union of 60.3 ± 10.1% was achieved when delineating the nodular BCC from normal structures. Limitation of the study was the small sample size for all tumors, especially SCCs. However, based on our preliminary results, we envision FF-OCT to rapidly image fresh tissues, facilitating surgical margin assessment. AI algorithms can aid in automated tumor detection, enabling widespread adoption of this technique.

Dynamic full-field optical coherence tomography module adapted to commercial microscopes allows longitudinal in vitro cell culture study

Dynamic full-field optical coherence tomography (D-FFOCT) has recently emerged as a label-free imaging tool, capable of resolving cell types and organelles within 3D live samples, whilst monitoring their activity at tens of milliseconds resolution. Here, a D-FFOCT module design is presented which can be coupled to a commercial microscope with a stage top incubator, allowing non-invasive label-free longitudinal imaging over periods of minutes to weeks on the same sample. Long term volumetric imaging on human induced pluripotent stem cell-derived retinal organoids is demonstrated, highlighting tissue and cell organization processes such as rosette formation and mitosis as well as cell shape and motility. Imaging on retinal explants highlights single 3D cone and rod structures. An optimal workflow for data acquisition, postprocessing and saving is demonstrated, resulting in a time gain factor of 10 compared to prior state of the art. Finally, a method to increase D-FFOCT signal-to-noise ratio is demonstrated, allowing rapid organoid screening.

Clinical Validation of Stimulated Raman Histology for Rapid Intraoperative Diagnosis of Central Nervous System Tumors

Stimulated Raman histology (SRH) is an ex vivo optical imaging method that enables microscopic examination of fresh tissue intraoperatively. The conventional intraoperative method uses frozen section analysis, which is labor and time intensive, introduces artifacts that limit diagnostic accuracy, and consumes tissue. SRH imaging allows rapid microscopic imaging of fresh tissue, avoids tissue loss, and enables remote telepathology review. This improves access to expert neuropathology consultation in both low- and high-resource practices. We clinically validated SRH by performing a blinded, retrospective two-arm telepathology study to clinically validate SRH for telepathology at our institution. Using surgical specimens from 47 subjects, we generated a data set composed of 47 SRH images and 47 matched whole slide images (WSIs) of formalin-fixed, paraffin-embedded tissue stained with hematoxylin and eosin, with associated intraoperative clinicoradiologic information and structured diagnostic questions. We compared diagnostic concordance between WSI and SRH-rendered diagnoses. Also, we compared the 1-year median turnaround time (TAT) of intraoperative conventional neuropathology frozen sections with prospectively rendered SRH-telepathology TAT. All SRH images were of sufficient quality for diagnostic review. A review of SRH images showed high accuracy in distinguishing glial from nonglial tumors (96.5% SRH vs 98% WSIs) and predicting final diagnosis (85.9% SRH vs 93.1% WSIs). SRH-based diagnosis and WSI-permanent section diagnosis had high concordance (κ = 0.76). The median TAT for prospectively SRH-rendered diagnosis was 3.7 minutes, approximately 10-fold shorter than the median frozen section TAT (31 minutes). The SRH-imaging procedure did not affect ancillary studies. SRH generates diagnostic virtual histologic images with accuracy comparable to conventional hematoxylin and eosin-based methods in a rapid manner. Our study represents the largest and most rigorous clinical validation of SRH to date. It supports the feasibility of implementing SRH as a rapid method for intraoperative diagnosis complementary to conventional pathology laboratory methods.

Core Needle Biopsy Guidance Based on Tissue Morphology Assessment with AI-OCT Imaging

This paper presents a combined optical imaging/artificial intelligence (OI/AI) technique for the real-time analysis of tissue morphology at the tip of the biopsy needle, prior to collecting a biopsy specimen. This is an important clinical problem as up to 40% of collected biopsy cores provide low diagnostic value due to high adipose or necrotic content. Micron-scale-resolution optical coherence tomography (OCT) images can be collected with a minimally invasive needle probe and automatically analyzed using a computer neural network (CNN)-based AI software. The results can be conveyed to the clinician in real time and used to select the biopsy location more adequately. This technology was evaluated on a rabbit model of cancer. OCT images were collected with a hand-held custom-made OCT probe. Annotated OCT images were used as ground truth for AI algorithm training. The overall performance of the AI model was very close to that of the humans performing the same classification tasks. Specifically, tissue segmentation was excellent (~99% accuracy) and provided segmentation that closely mimicked the ground truth provided by the human annotations, while over 84% correlation accuracy was obtained for tumor and non-tumor classification.

A biologist's guide to planning and performing quantitative bioimaging experiments

Technological advancements in biology and microscopy have empowered a transition from bioimaging as an observational method to a quantitative one. However, as biologists are adopting quantitative bioimaging and these experiments become more complex, researchers need additional expertise to carry out this work in a rigorous and reproducible manner. This Essay provides a navigational guide for experimental biologists to aid understanding of quantitative bioimaging from sample preparation through to image acquisition, image analysis, and data interpretation. We discuss the interconnectedness of these steps, and for each, we provide general recommendations, key questions to consider, and links to high-quality open-access resources for further learning. This synthesis of information will empower biologists to plan and execute rigorous quantitative bioimaging experiments efficiently.

Rapid On-Site Microscopy and Mapping of Diagnostic Biopsies for See-And-Treat Guidance of Localized Prostate Cancer Therapy

Prostate cancer continues to be the most diagnosed non-skin malignancy in men. While up to one in eight men will be diagnosed in their lifetimes, most diagnoses are not fatal. Better lesion location accuracy combined with emerging localized treatment methods are increasingly being utilized as a treatment option to preserve healthy function in eligible patients. In locating lesions which are generally <2cc within a prostate (average size 45cc), small variance in MRI-determined boundaries, tumoral heterogeneity, patient characteristics including location of lesion and prostatic calcifications, and patient motion during the procedure can inhibit accurate sampling for diagnosis. The locations of biopsies are recorded and are then fully processed by histology and diagnosed via pathology, often days to weeks later. Utilization of real-time feedback could improve accuracy, potentially prevent repeat procedures, and allow patients to undergo treatment of clinically localized disease at earlier stages. Unfortunately, there is currently no reliable real-time feedback process for confirming diagnosis of biopsy samples. We examined the feasibility of implementing structured illumination microscopy (SIM) as a method for on-site diagnostic biopsy imaging to potentially combine the diagnostic and treatment appointments for prostate cancer patients, or to confirm tumoral margins for localized ablation procedures. We imaged biopsies from 39 patients undergoing image-guided diagnostic biopsy using a customized SIM system and a dual-color fluorescent hematoxylin & eosin (H&E) analog. The biopsy images had an average size of 342 megapixels (minimum 78.1, maximum 842) and an average imaging duration of 145 s (minimum 56, maximum 322). Comparison of urologist's suspicion of malignancy based on MRI, to pathologist diagnosis of biopsy images obtained in real time, reveals that real-time biopsy imaging could significantly improve confirmation of malignancy or tumoral margins over medical imaging alone.

Ultrafast 3D histological imaging based on a minutes-time scale tissue clearing and multidirectional selective plane illumination microscopy

Conventional histopathological examinations are time-consuming and labor-intensive, and are insufficient to depict 3D pathological features intuitively. Here we report an ultrafast 3D histological imaging scheme based on optimized selective plane illumination microscopy (mSPIM), a minutes-time scale clearing method (FOCM), and a deep learning-based image enhancement algorithm (SRACNet) to realize histological preparation and imaging of clinical tissues. Our scheme enables 1-minute clearing and fast imaging (up to 900 mm²/min) of 200 µm-thick mouse kidney slices at micron-level resolution. With hematoxylin and eosin analog, we demonstrated the detailed 3D morphological connections between glomeruli and the surrounding tubules, which is difficult to identify in conventional 2D histology. Further, by the preliminary verification on human kidney tissues, this study will provide new, to the best of our knowledge, feasible histological solutions and inspirations in future 3D digital pathology.

Rapid slide-free and non-destructive histological imaging using wide-field optical-sectioning microscopy

Histopathology based on formalin-fixed and paraffin-embedded tissues has long been the gold standard for surgical margin assessment (SMA). However, routine pathological practice is lengthy and laborious, failing to guide surgeons intraoperatively. In this report, we propose a practical and low-cost histological imaging method with wide-field optical-sectioning microscopy (i.e., High-and-Low-frequency (HiLo) microscopy). HiLo can achieve rapid and non-destructive imaging of freshly-excised tissues at an extremely high acquisition speed of 5 cm²/min with a spatial resolution of 1.3 µm (lateral) and 5.8 µm (axial), showing great potential as an SMA tool that can provide immediate feedback to surgeons and pathologists for intraoperative decision-making. We demonstrate that HiLo enables rapid extraction of diagnostic features for different subtypes of human lung adenocarcinoma and hepatocellular carcinoma, producing surface images of rough specimens with large field-of-views and cellular features that are comparable to the clinical standard. Our results show promising clinical translations of HiLo microscopy to improve the current standard of care.

In vivo microscopy as an adjunctive tool to guide detection, diagnosis, and treatment

SIGNIFICANCE

There have been numerous academic and commercial efforts to develop high-resolution in vivo microscopes for a variety of clinical use cases, including early disease detection and surgical guidance. While many high-profile studies, commercialized products, and publications have resulted from these efforts, mainstream clinical adoption has been relatively slow other than for a few clinical applications (e.g., dermatology).

AIM

Here, our goals are threefold: (1) to introduce and motivate the need for in vivo microscopy (IVM) as an adjunctive tool for clinical detection, diagnosis, and treatment, (2) to discuss the key translational challenges facing the field, and (3) to propose best practices and recommendations to facilitate clinical adoption.

APPROACH

We will provide concrete examples from various clinical domains, such as dermatology, oral/gastrointestinal oncology, and neurosurgery, to reinforce our observations and recommendations.

RESULTS

While the incremental improvement and optimization of IVM technologies should and will continue to occur, future translational efforts would benefit from the following: (1) integrating clinical and industry partners upfront to define and maintain a compelling value proposition, (2) identifying multimodal/multiscale imaging workflows, which are necessary for success in most clinical scenarios, and (3) developing effective artificial intelligence tools for clinical decision support, tempered by a realization that complete adoption of such tools will be slow.

CONCLUSIONS

The convergence of imaging modalities, academic-industry-clinician partnerships, and new computational capabilities has the potential to catalyze rapid progress and adoption of IVM in the next few decades.

The Critical Role of Breast Specimen Gross Evaluation for Optimal Personalized Cancer Care

Gross examination is the foundation for the pathologic evaluation of all surgical specimens. The rapid identification of cancers is essential for intraoperative assessment and preservation of biomolecules for molecular assays. Key components of the gross examination include the accurate identification of the lesions of interest, correlation with clinical and radiologic findings, assessment of lesion number and size, relationship to surgical margins, documenting the extent of disease spread to the skin and chest wall, and the identification of axillary lymph nodes. Although the importance of gross evaluation is undeniable, current challenges include the difficulty of teaching grossing well and its possible perceived undervaluation compared with microscopic and molecular studies. In the future, new rapid imaging techniques without the need for tissue processing may provide an ideal melding of gross and microscopic pathologic evaluation.

Is Real-Time Microscopy on the Horizon? A Brief Review of the Potential Future Directions in Clinical Breast Tumor Microscopy Implementation

We will briefly review the current paradigm and some recent developments in the area of clinical breast microscopy, highlighting several promising commercially available, and research-based platforms. Confocal microscopy (reflectance, fluorescence, and spectrally encoded), optical coherence tomography (wide field and full field), stereomicroscopy, open-top light sheet microscopy, microscopy with ultraviolet surface excitation, nonlinear microscopy, Raman scattering microscopy, photoacoustic microscopy, and needle microendoscopy will be discussed. Non-microscopic methods for breast pathology assessment are beyond the scope of this review. These microscopic technologies have to varying degrees the potential for transforming breast cancer care, but in order for any of these to be integrated into clinical practice there are several hurdles to overcome. In our review we will focus on what needs to be done in order for the commercially available technologies to become more established, what the technologies in the research domain need to do in order to reach the commercial realm; and finally, what the field of breast pathology might look like if these technologies were to be widely adopted.

Ex Vivo Fluorescence Confocal Microscopy in Specimens of the Liver: A Proof-of-Concept Study

Ex vivo Fluorescence Confocal Microscopy (FCM) is a technique providing high-resolution images of native tissues. The method is increasingly used in surgical settings in areas of dermatology and urology. Only a few publications exist about examinations of tumors and non-neoplastic lesions of the liver. We report on the application of FCM in biopsies, surgical specimens and autopsy material (33 patients, 39 specimens) of the liver and compare the results to conventional histology. Our preliminary examinations indicated a perfect suitability for tumor diagnosis (ĸ = 1.00) and moderate/good suitability for the assessment of inflammation (ĸ = 0.4-0.6) with regard to their severity and localization. Macro-vesicular steatosis was reliably detected, micro-vesicular steatosis tended to be underestimated. Cholestasis and eosinophilic granules in granulocytes were not represented in the scans. The tissue was preserved as native material and maintained its quality for downstream histological, immunohistological and molecular examinations. In summary, FCM is a material sparing method that provides rapid feedback to the clinician about the presence of tumor, the degree of inflammation and structural changes. This can lead to faster therapeutic decisions in the management of liver tumors, treatment of hepatitis or in liver transplant medicine.

Information entropy of quantitative chemometric endogenous fluorescence improves photonic lung cancer diagnosis

Quantitative chemometric widefield endogenous fluorescence microscopy (CFM) maps the endogenous absolute chromophore concentration and spatial distribution in cells and tissue sections label-free from fluorescence color images under broadband excitation and detection. By quantifying the endogenous chromophores, including tryptophan, elastin, reduced nicotinamide adenine dinucleotide [NAD(P)H], and flavin adenine dinucleotide (FAD), CFM reveals the biochemical environment and subcellular structure. Here we show that the chromophore information entropy, marking its spatial distribution pattern of quantitative chemometric endogenous fluorescence at the microscopic scale, improves photonic lung cancer diagnosis with independent diagnostic power to the cellular metabolism biomarker. NAD(P)H and FAD's information entropy is found to decrease from normal to perilesional to cancerous tissue, whereas the information entropy for the redox ratios [FAD/tryptophan and FAD/NAD(P)H] is smaller for the normal tissue than both perilesional and cancerous tissue. CFM imaging of the specimen's inherent biochemical and structural properties eliminates the dependence on measurement details and facilitates robust, accurate diagnosis. The synergy of quantifying absolute chromophore concentration and information entropy achieves high accuracies for a three-class classification of lung tissue into normal, perilesional, and cancerous ones and a three-class classification of lung cancers into grade 1, grade 2, and grade 3 using a support vector machine, outperforming the chromophore concentration biomarkers.

Feasibility of using digital confocal microscopy for cytopathological examination in clinical practice

Optical imaging modalities are emerging as digital microscopy tools for tissue examination. The investigation of these techniques for potential applications in anatomic pathology practice has focused primarily on surgical pathology and has not included cytopathological specimens. We evaluated the feasibility of using digital confocal microscopy (CM) to examine cytopathological specimens. Smears and cell suspensions collected in RPMI solution were prepared from tissue scrapes obtained from surgical resections of breast, lung, liver, and kidney. Air-dried smears and cell pellets obtained from centrifugation of the cell suspensions were stained with 0.6 mM acridine orange and imaged with a CM platform. After completion of imaging, the smears were stained with Diff-Quik (DQ), and cell pellets were routinely processed, embedded in paraffin wax, cut, and stained with hematoxylin and eosin (H&E). We evaluated the mean time to acquire digital CM images; quality of images based on the extent of tissue recognition (0%, grade 0; 1-19%, grade 1; 20-50%, grade 2; >50%, grade 3); comparison of images with DQ- and H&E-stained specimens; and ability to make specific diagnoses. We imaged 91 smears and 52 cell pellets and acquired digital CM images within 2-3 min, with 92% and 88% of images, respectively, from smears and cell pellets showing grade 3 quality. On the basis of CM images, 8 smears (9%) and 7 cell pellets (14%) were categorized as benign, and 83 (91%) and 45 (88%), respectively, as malignant. Specific diagnoses were made by using digital CM images of smears and cell pellets that matched accurately with corresponding DQ- and H&E-stained preparations. The results of our first feasibility study clearly indicated the utility of CM as a next-generation digital microscopy tool for evaluating cytology specimens. Prospective clinical studies are warranted for validating our findings for potential incorporation into cytopathological clinical practice.

Machine Learning Based Prediction of Squamous Cell Carcinoma in Ex Vivo Confocal Laser Scanning Microscopy

Image classification with convolutional neural networks (CNN) offers an unprecedented opportunity to medical imaging. Regulatory agencies in the USA and Europe have already cleared numerous deep learning/machine learning based medical devices and algorithms. While the field of radiology is on the forefront of artificial intelligence (AI) revolution, conventional pathology, which commonly relies on examination of tissue samples on a glass slide, is falling behind in leveraging this technology. On the other hand, ex vivo confocal laser scanning microscopy (ex vivo CLSM), owing to its digital workflow features, has a high potential to benefit from integrating AI tools into the assessment and decision-making process. Aim of this work was to explore a preliminary application of CNN in digitally stained ex vivo CLSM images of cutaneous squamous cell carcinoma (cSCC) for automated detection of tumor tissue. Thirty-four freshly excised tissue samples were prospectively collected and examined immediately after resection. After the histologically confirmed ex vivo CLSM diagnosis, the tumor tissue was annotated for segmentation by experts, in order to train the MobileNet CNN. The model was then trained and evaluated using cross validation. The overall sensitivity and specificity of the deep neural network for detecting cSCC and tumor free areas on ex vivo CLSM slides compared to expert evaluation were 0.76 and 0.91, respectively. The area under the ROC curve was equal to 0.90 and the area under the precision-recall curve was 0.85. The results demonstrate a high potential of deep learning models to detect cSCC regions on digitally stained ex vivo CLSM slides and to distinguish them from tumor-free skin.

[Artificial intelligence in ex vivo confocal laser scanning microscopy]

BACKGROUND

Visual data, such as clinical photographs or pictures from imaging examination methods, such as ex vivo confocal laser scanning microscopy (CLSM), are particularly suitable for machine learning techniques.

OBJECTIVES

The aim was to find out whether data have already been published on this innovative application in ex vivo CLSM and what potential challenges and limitations could arise.

MATERIAL AND METHODS

Review of the literature and summary of current knowledge and personal experience on the use of artificial intelligence (AI) in ex vivo CLSM.

RESULTS

Successful integration of digital hematoxylin-eosin-like staining has made ex vivo CLSM significantly more accessible for digital assessments. Several machine learning techniques have been developed to date in such a way that they have been able to identify malignant skin lesions on clinical photographs and pathological microscopic images with similar accuracy compared to experts, or even find visual patterns that have been overlooked by experts and that correlate with certain dermatological diseases. One study on the use of AI in ex vivo CLSM for automated tumor detection has been published to date. Several challenges and limitations can arise when using AI in ex vivo CLSM.

CONCLUSIONS

The already digitized ex vivo CLSM, which was established for rapid section examination purposes, is a predestined method for the development and use of new applications with machine learning in the healthcare sector. The results of further studies on this topic are anticipated with great hope.

Ex vivo Fusion Confocal Microscopy of Colorectal Polyps: A Fast Turnaround Time of Pathological Diagnosis

BACKGROUND

Colorectal cancer screening programs have accomplished a mortality reduction from the disease but have created bottlenecks in endoscopy units and pathology departments. We aimed to explore the feasibility of ex vivo fusion confocal microscopy (FuCM) to improve the histopathology diagnostic efficiency and reduce laboratory workload.

METHODS

Consecutive fresh polyps removed at colonoscopy were scanned using ex vivo FuCM, then went through histopathologic workout and hematoxylin and eosin (H&amp;E) diagnosis. Two pathologists blinded to H&amp;E diagnosis made a diagnosis based on FuCM scanned images.

RESULTS

Thirty-six fresh polyps from 22 patients were diagnosed with FuCM and H&amp;E. Diagnostic agreement between H&amp;E and FuCM was 97.2% (kappa = 0.96) for pathologist #1 and 91.7% (kappa = 0.87) for pathologist #2. Diagnostic performance concordance between FuCM and H&amp;E to discern adenomatous from nonadenomatous polyps was 100% (kappa = 1) for pathologist #1 and 97.2% (kappa = 0.94) for pathologist #2. Global interobserver agreement was 94.44% (kappa = 0.91) and kappa = 0.94 to distinguish adenomatous from nonadenomatous polyps.

CONCLUSIONS

Ex vivo FuCM shows an excellent correlation with standard H&amp;E for the diagnosis of colorectal polyps. The clinical direct benefit for patients, pathologists, and endoscopists allows adapting personalized surveillance protocols after colonoscopy and a workload decrease in pathology departments.

Feasibility of dual-contrast fluorescence imaging of pathological breast tissues

The combination of intravital dye, methylene blue (MB), with molecular cancer marker, pH low insertion peptide (pHLIP) conjugated with fluorescent Alexa532 (Alexa532-pHLIP), was evaluated for enhancing contrast of pathological breast tissue ex vivo. Fresh, thick breast specimens were stained sequentially with Alexa532-pHLIP and aqueous MB and imaged using dual-channel fluorescence microscopy. MB and Alexa532-pHLIP accumulated in the nuclei and cytoplasm of cancer cells, respectively. MB also stained nuclei of normal cells. Some Alexa532-pHLIP fluorescence emission was detected from connective tissue and benign cell membranes. Overall, Alexa532-pHLIP showed high affinity to cancer, while MB highlighted tissue morphology. The results indicate that MB and Alexa532-pHLIP provide complementary information and show promise for the detection of breast cancer.

Rapid pseudo-H&E imaging using a fluorescence-inbuilt optical coherence microscopic imaging system

A technique using Linnik-based optical coherence microscopy (OCM), with built-in fluorescence microscopy (FM), is demonstrated here to describe cellular-level morphology for fresh porcine and biobank tissue specimens. The proposed method utilizes color-coding to generate digital pseudo-H&E (p-H&E) images. Using the same camera, colocalized FM images are merged with corresponding morphological OCM images using a 24-bit RGB composition process to generate position-matched p-H&E images. From receipt of dissected fresh tissue piece to generation of stitched images, the total processing time is <15 min for a 1-cm² specimen, which is on average two times faster than frozen-section H&E process for fatty or water-rich fresh tissue specimens. This technique was successfully used to scan human and animal fresh tissue pieces, demonstrating its applicability for both biobank and veterinary purposes. We provide an in-depth comparison between p-H&E and human frozen-section H&E images acquired from the same metastatic sentinel lymph node slice (∼10 µm thick), and show the differences, like elastic fibers of a tiny blood vessel and cytoplasm of tumor cells. This optical sectioning technique provides histopathologists with a convenient assessment method that outputs large-field H&E-like images of fresh tissue pieces without requiring any physical embedment.

Selective sensing of DNA and live/dead cells and histological imaging based on a perylene derivative

A mannose-modified perylene monoimide derivative PMI-Man was developed, which shows highly selective binding to double-stranded DNA molecules, potent live/dead cell imaging, and histological imaging via both confocal and light microscopies. This approach can be used to develop a universal colorful staining method for human tissues for both confocal and light microscopies.

Universal colorful staining of cancer tissues and normal tissues for histological diagnosis

The versatility of multicolor imaging of human tissues based on staining with perylene monoimide-mannose conjugates PMI-Man and co-staining with PMI-Man and eosin (P&E) was investigated for human cancer and normal tissues. Staining with PMI-Man or co-staining with PMI-Man and eosin showed a perfect histological morphology both in confocal fluorescence microscopy and light microscopy. This approach provided a universal colorful staining method for cancer tissues and normal tissues.

Deep learning automated pathology in ex vivo microscopy

Standard histopathology is currently the gold standard for assessment of margin status in Mohs surgical removal of skin cancer. Ex vivo confocal microscopy (XVM) is potentially faster, less costly and inherently 3D/digital compared to standard histopathology. Despite these advantages, XVM use is not widespread due, in part, to the need for pathologists to retrain to interpret XVM images. We developed artificial intelligence (AI)-driven XVM pathology by implementing algorithms that render intuitive XVM pathology images identical to standard histopathology and produce automated tumor positivity maps. XVM images have fluorescence labeling of cellular and nuclear biology on the background of endogenous (unstained) reflectance contrast as a grounding counter-contrast. XVM images of 26 surgical excision specimens discarded after Mohs micrographic surgery were used to develop an XVM data pipeline with 4 stages: flattening, colorizing, enhancement and automated diagnosis. The first two stages were novel, deterministic image processing algorithms, and the second two were AI algorithms. Diagnostic sensitivity and specificity were calculated for basal cell carcinoma detection as proof of principal for the XVM image processing pipeline. The resulting diagnostic readouts mimicked the appearance of histopathology and found tumor positivity that required first collapsing the confocal stack to a 2D image optimized for cellular fluorescence contrast, then a dark field-to-bright field colorizing transformation, then either an AI image transformation for visual inspection or an AI diagnostic binary image segmentation of tumor obtaining a diagnostic sensitivity and specificity of 88% and 91% respectively. These results show that video-assisted micrographic XVM pathology could feasibly aid margin status determination in micrographic surgery of skin cancer.

Assessment of breast cancer surgical margins with multimodal optical microscopy: A feasibility clinical study

Providing surgical margin information during breast cancer surgery is crucial for the success of the procedure. The margin is defined as the distance from the tumor to the cut surface of the resection specimen. The consensus among surgeons and radiation oncologists is that there should be no tumor left within 1 to maximum 2 mm from the surface of the surgical specimen. If a positive margin remains, there is substantial risk for tumor recurrence, which may also result in potentially reduced cosmesis and eventual need for mastectomy. In this paper we report a novel multimodal optical imaging instrument based on combined high-resolution confocal microscopy-optical coherence tomography imaging for assessing the presence of potential positive margins on surgical specimens. Since rapid specimen analysis is critical during surgery, this instrument also includes a fluorescence imaging channel to enable rapid identification of the areas of the specimen that have potential positive margins. This is possible by specimen incubation with a cancer specific agent prior to imaging. In this study we used a quenched contrast agent, which is activated by cancer specific enzymes, such as urokinase plasminogen activators (uPA). Using this agent or a similar one, one may limit the use of high-resolution optical imaging to only fluorescence-highlighted areas for visualizing tissue morphology at the sub-cellular scale and confirming or ruling out cancer presence. Preliminary evaluation of this technology was performed on 20 surgical specimens and testing of the optical imaging findings was performed against histopathology. The combination of the three imaging modes allowed for high correlation between optical image analysis and histological ground-truth. The initial results are encouraging, showing instrument capability to assess margins on clinical specimens with a positive predictive value of 1.0 and a negative predictive value of 0.83.

Ex vivo confocal microscopy: revolution in fast pathology in dermatology

Confocal microscopy with in vivo and ex vivo modalities has been used in the evaluation of skin cancer and other dermatological disorders. Recent developments in ex vivo confocal microscopy allow for faster pathology assessment with greater accuracy by the visualization of cellular and architectural details, similarly to standard pathology, in either paraffin-embedded or frozen samples. They include the possibility of multimodal confocal microscopy using different lasers and fusion images. New staining protocols including immunostaining, with no damage to conventional histopathology preparation, have been recently described in melanocytic tumours and inflammatory skin diseases. Digital staining with haematoxylin and eosin is also incorporated in the new devices. In this review the applications of ex vivo confocal microscopy will be presented with the description of the technique and the technology, clinical evidence in dermatology and other fields, and further applications.

Comparison of Real-Time Fluorescence Confocal Digital Microscopy With Hematoxylin-Eosin-Stained Sections of Core-Needle Biopsy Specimens

IMPORTANCE

Strategies to procure high-quality core-needle biopsy (CNB) specimens are critical for making basic tissue diagnoses and for ancillary testing.

OBJECTIVES

To investigate acquisition of fluorescence confocal microscopy (FCM) images of interventional radiology (IR)-guided CNB in real time in the radiology suite and to compare the accuracy of FCM diagnoses with those of hematoxylin-eosin (H&E)-stained CNB sections.

DESIGN, SETTING, AND PARTICIPANTS

In this diagnostic study, FCM imaging of IR-guided CNBs was performed in the radiology suite at a major cancer center for patients with an imaging abnormality from August 1, 2016, to April 30, 2019. The time taken to acquire FCM images and the quality of FCM images based on percentage of interpretable tissue with optimal resolution was recorded. The FCM images were read by 2 pathologists and categorized as nondiagnostic, benign/atypical, or suspicious/malignant; these diagnoses were compared with those made using H&E-stained tissue sections. Cases with discrepant diagnosis were reassessed by the pathologists together for a consensus diagnosis. Data were analyzed from June 3 to July 19, 2019.

INTERVENTIONS

Each IR-guided CNB was stained with 0.6mM acridine orange, subjected to FCM imaging, and then processed to generate H&E-stained sections.

MAIN OUTCOMES AND MEASURES

Mean time taken for acquisition of FCM images, quality of FCM images based on interpretable percentage of the image, and accuracy of diagnostic categorization based on FCM images compared with H&E-stained sections.

RESULTS

A total of 105 patients (57 male [54.3%]; mean [SD] age, 63 [13] years) underwent IR-guided CNBs in a mean (SD) of 7 (2) minutes each. The FCM images showed at least 20% of the tissue with optimal quality in 101 CNB specimens (96.2%). The FCM images were accurately interpreted by the 2 pathologists in 100 of 105 cases (95.2%) (2 false-positive and 3 false-negative) and 90 of 105 cases (85.7%) (6 false-positive and 9 false-negative). A reassessment of 14 discordant diagnoses resulted in consensus diagnoses that were accurate in 101 of 105 cases (96.2%) (1 false-positive and 3 false-negative).

CONCLUSIONS AND RELEVANCE

The ease of acquisition of FCM images of acceptable quality and the high accuracy of the diagnoses suggest that FCM may be useful for rapid evaluation of IR-guided CNBs. This approach warrants further investigation.