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Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual inspection of a limited number of two-dimensional (2D) histology sections is often unreliable, which contributes to the under- and overtreatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for nondestructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analogue of standard hematoxylin and eosin (H&E) staining. This analysis is based on interpretable glandular features and is facilitated by the development of image translation–assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep learning–based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring immunolabeling. As a preliminary demonstration of the translational value of a computational 3D versus a computational 2D pathology approach, we imaged 300 ex vivo biopsies extracted from 50 archived radical prostatectomy specimens, of which, 118 biopsies contained cancer. The 3D glandular features in cancer biopsies were superior to corresponding 2D features for risk stratification of patients with low- to intermediate-risk prostate cancer based on their clinical biochemical recurrence outcomes. The results of this study support the use of computational 3D pathology for guiding the clinical management of prostate cancer. Significance: An end-to-end pipeline for deep learning–assisted computational 3D histology analysis of whole prostate biopsies shows that nondestructive 3D pathology has the potential to enable superior prognostic stratification of patients with prostate cancer.

A feature issue is being presented by a team of guest editors containing papers based on studies presented at the Optica Biophotonics Congress: Biomedical Optics held on April 24–27, 2022 in Fort Lauderdale, Florida, USA.

Context.— Anatomic pathologists render diagnosis on tissue samples sectioned onto glass slides and viewed under a bright-field microscope. This approach is destructive to the sample, which can limit its use for ancillary assays that can inform patient management. Furthermore, the subjective interpretation of a relatively small number of 2D tissue sections per sample contributes to low interobserver agreement among pathologists for the assessment (diagnosis and grading) of various lesions. Objective.— To evaluate 3D pathology data sets of thick formalin-fixed Barrett esophagus specimens imaged nondestructively with open-top light-sheet (OTLS) microscopy. Design.— Formalin-fixed, paraffin-embedded Barrett esophagus samples (N = 15) were deparaffinized, stained with a fluorescent analog of hematoxylin-eosin, optically cleared, and imaged nondestructively with OTLS microscopy. The OTLS microscopy images were subsequently compared with archived hematoxylin-eosin histology sections from each sample. Results.— Barrett esophagus samples, both small endoscopic forceps biopsies and endoscopic mucosal resections, exhibited similar resolvable structures between OTLS microscopy and conventional light microscopy with up to a ×20 objective (×200 overall magnification). The 3D histologic images generated by OTLS microscopy can enable improved discrimination of cribriform and well-formed gland morphologies. In addition, a much larger amount of tissue is visualized with OTLS microscopy, which enables improved assessment of clinical specimens exhibiting high spatial heterogeneity. Conclusions.— In esophageal specimens, OTLS microscopy can generate images comparable in quality to conventional light microscopy, with the advantages of providing 3D information for enhanced evaluation of glandular morphologies and enabling much more of the tissue specimen to be visualized nondestructively.

Recent technological advances have demonstrated the feasibility of achieving high-throughput slide-free three-dimensional (3D) pathology of biopsy and surgical specimens. In comparison to conventional slide-based pathology, 3D pathology has the potential to provide a transformative improvement in diagnostic performance for a number of reasons: (1) vastly greater (multiple log orders) sampling of tissue specimens, (2) volumetric imaging of cell distributions and tissue structures that are prognostic and predictive, (3) nondestructive imaging, which allows valuable biopsy specimens to be used for downstream molecular assays, and (4) a simplified process with cost benefits for pathology laboratories. However, due to the immense size of these feature-rich datasets, new challenges exist in terms of data management and computer-aided interpretation. In this forward-looking Perspective, we first provide a brief overview of the imaging technologies that can enable nondestructive 3D pathology, including computational tools needed to support these 3D methods. We then provide a roadmap for how machine learning, which is already being developed within the context of 2D digital pathology, should be leveraged and refined for 3D pathology. Finally, we discuss future challenges and opportunities for the clinical validation, regulatory approval, and clinical adoption of this new paradigm for precision medicine, including for reducing health disparities across populations. This includes learning from, and integrating with, other diagnostic modalities such as radiology and genomics.

As preclinical animal tests often do not accurately predict drug effects later observed in humans, most drugs under development fail to reach the market. Thus there is a critical need for functional drug testing platforms that use human, intact tissues to complement animal studies. To enable future multiplexed delivery of many drugs to one small biopsy, we have developed a mullti-well microfluidic platform that selectively treats cuboidal-shaped microdissected tissues or “cuboids” with well-preserved tissue microenvironments. We create large numbers of uniformly-sized cuboids by semi-automated sectioning of tissue with a commercially available tissue chopper. Here we demonstrate the microdissection method on normal mouse liver, which we characterize with quantitative 3D imaging, and on human glioma xenograft tumors, which we evaluate after time in culture for viability and preservation of the microenvironment. The benefits of size uniformity include lower heterogeneity in future biological assays as well as facilitation of their physical manipulation by automation. Our prototype platform consists of a microfluidic circuit whose hydrodynamic traps immobilize the live cuboids in arrays at the bottom of a multi-well plate. Fluid dynamics simulations enabled the rapid evaluation of design alternatives and operational parameters. We demonstrate the proof-of-concept application of model soluble compounds such as dyes (CellTracker, Hoechst) and the cancer drug cisplatin. Upscaling of the microfluidic platform and microdissection method to larger arrays and numbers of cuboids could lead to direct testing of human tissues at high throughput, and thus could have a significant impact on drug discovery and personalized medicine.

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

For breast cancer patients, the extent of regional lymph node (LN) metastasis influences the decision to remove all axillary LNs. Metastases are currently identified and classified with visual analysis of a few thin tissue sections with conventional histology that may underrepresent the extent of metastases.We sought to enable nondestructive three-dimensional (3D) pathology of human axillary LNs and to develop a practical workflow for LN staging with our method. We also sought to evaluate whether 3D pathology improves staging accuracy in comparison to two-dimensional (2D) histology.We developed a method to fluorescently stain and optically clear LN specimens for comprehensive imaging with multiresolution open-top light-sheet microscopy. We present an efficient imaging and data-processing workflow for rapid evaluation of HE-like datasets in 3D, with low-resolution screening to identify potential metastases followed by high-resolution localized imaging to confirm malignancy.We simulate LN staging with 3D and 2D pathology datasets from 10 metastatic nodes, showing that 2D pathology consistently underestimates metastasis size, including instances in which 3D pathology would lead to upstaging of the metastasis with important implications on clinical treatment.Our 3D pathology method may improve clinical management for breast cancer patients by improving staging accuracy of LN metastases.

Light-sheet microscopy has emerged as the preferred means for high-throughput volumetric imaging of cleared tissues. However, there is a need for a user-friendly system that can address diverse imaging applications with varied requirements in terms of resolution (mesoscopic to sub-micron), sample geometry (size, shape, and number), and compatibility with tissue-clearing protocols of different refractive indices. We present a hybrid system that combines a novel non-orthogonal dual-objective and conventional open-top light-sheet architecture for highly versatile multi-scale volumetric imaging. One sentence summary Glaser et al. describe a hybrid open-top light-sheet microscope to image cleared tissues at mesoscopic to sub-micron resolution and depths of up to 1 cm.

Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. In current clinical practice, the microscopic architecture of the prostate glands is what forms the basis for prognostic grading by pathologists. Interpretation of these convoluted 3D glandular structures via visual inspection of a limited number of 2D histology sections is often unreliable, which contributes to the under- and over-treatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for non-destructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analog of standard H&E staining. Our analysis is based on interpretable glandular features, and is facilitated by the development of image-translation-assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep-learning-based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring real immunolabeling. To provide evidence of the translational value of a computational 3D pathology approach, we analyzed ex vivo biopsies (n = 300) extracted from archived radical-prostatectomy specimens (N = 50), and found that 3D glandular features are superior to corresponding 2D features for risk stratification of low-to intermediate-risk PCa patients based on their clinical biochemical recurrence (BCR) outcomes.SignificanceWe present an end-to-end pipeline for computational 3D pathology of whole prostate biopsies, showing that non-destructive pathology has the potential to enable superior prognostic stratification for guiding critical oncology decisions.

Light-sheet microscopy has emerged as the preferred means for high-throughput volumetric imaging of cleared tissues. However, there is a need for a flexible system that can address imaging applications with varied requirements in terms of resolution, sample size, tissue-clearing protocol, and transparent sample-holder material. Here, we present a 'hybrid' system that combines a unique non-orthogonal dual-objective and conventional (orthogonal) open-top light-sheet (OTLS) architecture for versatile multi-scale volumetric imaging. We demonstrate efficient screening and targeted sub-micrometer imaging of sparse axons within an intact, cleared mouse brain. The same system enables high-throughput automated imaging of multiple specimens, as spotlighted by a quantitative multi-scale analysis of brain metastases. Compared with existing academic and commercial light-sheet microscopy systems, our hybrid OTLS system provides a unique combination of versatility and performance necessary to satisfy the diverse requirements of a growing number of cleared-tissue imaging applications.

Recent advances in optical clearing and light-sheet microscopy have provided unprecedented access to structural and molecular information from intact tissues. However, current light-sheet microscopes have imposed constraints on the size, shape, number of specimens, and compatibility with various clearing protocols. Here we present a multi-immersion open-top light-sheet microscope that enables simple mounting of multiple specimens processed with a variety of clearing protocols, which will facilitate wide adoption by preclinical researchers and clinical laboratories. In particular, the open-top geometry provides unsurpassed versatility to interface with a wide range of accessory technologies in the future., Light-sheet microscopes are increasingly used for imaging cleared tissues, but have imposed constraints on sample geometries and protocols. Here the authors present a multi-immersion open-top light-sheet microscope to overcome these limitations and enable high-throughput imaging of samples processed with various clearing protocols.

Context.—Ex vivo microscopy encompasses a range of techniques to examine fresh or fixed tissue with microscopic resolution, eliminating the need to embed the tissue in paraffin or produce a glass slide. One such technique is light-sheet microscopy, which enables rapid 3D imaging. Our pathology-engineering collaboration has resulted in an open-top light-sheet (OTLS) microscope that is specifically tailored to the needs of pathology practice.Objective.—To present an image atlas of OTLS images of prostate core needle biopsies.Design.—Core needle biopsies (N = 9) were obtained from fresh radical prostatectomy specimens. Each biopsy was fixed in formalin, dehydrated in ethanol, stained with TO-PRO3 and eosin, optically cleared, and imaged using OTLS microscopy. The biopsies were then processed, paraffin embedded, and sectioned. Hematoxylin-eosin and immunohistochemical staining for cytokeratin 5 and cytokeratin 8 was performed.Results.—Benign and neoplastic histologic structures showed high fidelity between OTLS and traditional light microscopy. OTLS microscopy had no discernible effect on hematoxylin-eosin or immunohistochemical staining in this pilot study. The 3D histology information obtained using OTLS microscopy enabled new structural insights, including the observation of cribriform and well-formed gland morphologies within the same contiguous glandular structures, as well as the continuity of poorly formed glands with well-formed glands.Conclusions.—Three-dimensional OTLS microscopy images have a similar appearance to traditional hematoxylin-eosin histology images, with the added benefit of useful 3D structural information. Further studies are needed to continue to document the OTLS appearance of a wide range of tissues and to better understand 3D histologic structures.

Dual-axis confocal (DAC) microscopy is a high-resolution optical imaging modality that utilizes simple low-numerical-aperture (NA) beams to achieve effective optical sectioning and superior image contrast in biological tissues. In addition to providing enhanced imaging performance, the DAC architecture provides certain advantages for miniaturization, facilitating the development of endoscopic, and handheld systems for in vivo imaging. This article reviews the principles of DAC microscopy, highlighting the differences between DAC microscopy and conventional confocal microscopy. Several technical variations of DAC microscopy will be surveyed, as well as clinical DAC microscopy prototypes that have been developed as noninvasive real-time alternatives to conventional biopsy and histopathology.

5-ALA-based fluorescence-guided surgery has been shown to be a safe and effective method to improve intraoperative visualization and resection of malignant gliomas. However, it remains ineffective in guiding the resection of lower-grade, non-enhancing, and deep-seated tumors, mainly because these tumors do not produce detectable fluorescence with conventional visualization technologies, namely, wide-field (WF) surgical microscopy. We describe some of the main factors that limit the sensitivity and accuracy of conventional WF surgical microscopy, and then provide a survey of commercial and research prototypes being developed to address these challenges, along with their principles, advantages and disadvantages, as well as the current status of clinical translation for each technology. We also provide a neurosurgical perspective on how these visualization technologies might best be implemented for guiding glioma surgeries in the future. Detection of PpIX expression in low-grade gliomas and at the infiltrative margins of all gliomas has been achieved with high-sensitivity probe-based visualization techniques. Deep-tissue PpIX imaging of up to 5 mm has also been achieved using red-light illumination techniques. Spectroscopic approaches have enabled more accurate quantification of PpIX expression. Advancements in visualization technologies have extended the sensitivity and accuracy of conventional WF surgical microscopy. These technologies will continue to be refined to further improve the extent of resection in glioma patients using 5-ALA-induced fluorescence.

Introduction: Interdisciplinary academic teams perform better when competent in teamwork; however, there is a lack of best practices of how to introduce and facilitate the development of effective learning and functioning within these teams in academic environments. Methods: To close this gap, we tailored, implemented, and evaluated team science training in the year-long Engineering Innovation in Health (EIH) program at the University of Washington (UW), a project-based course in which engineering students across several disciplines partner with health professionals to develop technical solutions to clinical and translational health challenges. EIH faculty from the UW College of Engineering and the Institute of Translational Health Sciences’ (ITHS) Team Science Core codeveloped and delivered team science training sessions and evaluated their impact with biannual surveys. A student cohort was surveyed prior to the implementation of the team science trainings, which served as a baseline. Results: Survey responses were compared within and between both cohorts (approximately 55 students each Fall Quarter and 30 students each Spring Quarter). Statistically significant improvements in measures of self-efficacy and interpersonal team climate (i.e., psychological safety) were observed within and between teams. Conclusions: Tailored team science training provided to student-professional teams resulted in measurable improvements in self-efficacy and interpersonal climate both of which are crucial for teamwork and intellectual risk taking. Future research is needed to determine long-term impacts of course participation on individual and team outcomes (e.g., patents, start-ups). Additionally, adaptability of this model to clinical and translational research teams in alternate formats and settings should be tested.

Glandular architecture is currently the basis for the Gleason grading of prostate biopsies. To visualize and computationally analyze glandular features in large 3D pathology datasets, we developed an annotation-free segmentation method for 3D prostate glands that relies upon synthetic 3D immunofluorescence (IF) enabled by generative adversarial networks. By using a fluorescent analog of H and E (cheap and fast stain) as an input, our strategy allows for accurate glandular segmentation that does not rely upon subjective and tedious human annotations or slow and expensive 3D immunolabeling. We aim to demonstrate that this 3D segmentation will enable improved prostate cancer prognostication.

Open-top light-sheet (OTLS) microscopy has recently been developed as a high-throughput, easy-to-use 3D microscopy technique for large specimens [1-2]. The oblique angle of the optical beams relative to the sample plate introduces challenges however, and previous solutions (such as a solid immersion lens) have been limiting [1]. Therefore we have developed a solid immersion meniscus lens (SIMlens), which enables optical beams to transition from air to a higher-index immersion medium without introducing aberrations [3]. A SIMlens is compatible with a turret of air objectives, enabling efficient multi-resolution workflows [4]. We present the first multi-resolution OTLS microscope, enabled by a SIMlens.

A current challenge is providing an accurate diagnosis in a timely manner for patients at risk of having prostate cancer. We developed and demonstrated a non-destructive procedure in which 12 biopsies can be cleared, fluorescently labeled, imaged with an open-top light-sheet (OTLS) microscope, and then diagnosed by a pathologist within an hour of biopsy. Using conventional histology as the gold standard, the accuracy, sensitivity, and specificity of 1Hr2Dx were all >90%. Such a method could potentially provide patients with a preliminary on-site diagnosis after a biopsy procedure, thereby alleviating anxiety and potentially expediting treatments.

Fluorescence-based slide-free digital pathology techniques, including 3D microscopy, are gaining interest as alternatives to traditional slide-based histology. Since pathologists are accustomed to the appearance of standard histology stains, the ability to render grayscale fluorescent images with color palettes that mimic traditional histology is valuable. We present FalseColor-Python, an open-source rapid digital-staining package that renders two-channel fluorescence images to mimic standard histology. Our package offers consistent color-space representations that are robust to both intra-specimen and inter-specimen variations in staining and imaging conditions, along with GPU-accelerated methods to process large datasets efficiently.

Light-sheet microscopy has emerged as the preferred means for high-throughput volumetric imaging of cleared tissues. However, there is a need for a user-friendly system that can address diverse imaging applications with varied requirements in terms of resolution (mesoscopic to sub-micron), sample geometry (size, shape, and number), and compatibility with tissue-clearing protocols of different refractive indices. We present a hybrid system that combines a novel non-orthogonal dual-objective and conventional open-top light-sheet architecture for highly versatile multi-scale volumetric imaging.

Light-sheet microscopy (LSM) is a powerful technique for rapid volumetric imaging of optically cleared specimens. Given the range of possible LSM configurations, designers would benefit from a systematic evaluation of the tradeoffs between different architectures. We present a simulation-based analysis of single- and dual-objective LSM designs for open-top, cleared-tissue imaging. System resolution and contrast are evaluated as functions of the crossing angle between the illumination and collection beams and each beam’s numerical aperture (NA). Our analysis reveals several key tradeoffs to guide designers in addition to potential advantages of a non-orthogonal dual-objective (NODO) architecture for moderate resolution imaging.

Light-sheet microscopy (LSM) has emerged as the technique of choice for many biologists imaging large cleared tissues due to its speed and optical efficiency, which make it possible to generate massive datasets of large specimens at high resolution. Here, we build on several recent innovations in LSM to present a non-orthogonal dual-objective (NODO) LSM system with axial sweeping in an open-top configuration. This system is specifically designed to image large cleared brain tissues, such as for axonal connectomics, and provides subcellular resolution (0.3 µm lateral, 2 µm axial) of large cleared samples up to 8 mm thick.

Fluorescence microscopy is a vital tool in biomedical research but faces considerable challenges in achieving uniform or bright labeling. For instance, fluorescent proteins are limited to model organisms, and antibody conjugates can be inconsistent and difficult to use with thick specimens. To partly address these challenges, we developed a labeling protocol that can rapidly visualize many well-contrasted key features and landmarks on biological specimens in both thin and thick tissues or cultured cells. This approach uses established reactive fluorophores to label a variety of biological specimens for cleared-tissue microscopy or expansion super-resolution microscopy and is termed FLARE (fluorescent labeling of abundant reactive entities). These fluorophores target chemical groups and reveal their distribution on the specimens; amine-reactive fluorophores such as hydroxysuccinimidyl esters target accessible amines on proteins, while hydrazide fluorophores target oxidized carbohydrates. The resulting stains provide signals analogous to traditional general histology stains such as HE or periodic acid-Schiff but use fluorescent probes that are compatible with volumetric imaging. In general, the stains for FLARE are performed in the order of carbohydrates, amine and DNA, and the incubation time for the stains varies from 1 h to 1 d depending on the combination of stains and the type and thickness of the biological specimens. FLARE is powerful, robust and easy to implement in laboratories that already routinely do fluorescence microscopy.

Significance: Processing and diagnosing a set of 12 prostate biopsies using conventional histology methods typically take at least one day. A rapid and accurate process performed while the patient is still on-site could significantly improve the patient’s quality of life. Aim: We develop and assess the feasibility of a one-hour-to-diagnosis (1Hr2Dx) method for processing and providing a preliminary diagnosis of a set of 12 prostate biopsies. Approach: We developed a fluorescence staining, optical clearing, and 3D open-top light-sheet microscopy workflow to enable 12 prostate needle core biopsies to be processed and diagnosed within an hour of receipt. We analyzed 44 biopsies by the 1Hr2Dx method, which does not consume tissue. The biopsies were then processed for routine, slide-based 2D histology. Three pathologists independently evaluated the 3D 1Hr2Dx and 2D slide-based datasets in a blinded, randomized fashion. Turnaround times were recorded, and the accuracy of our method was compared with gold-standard slide-based histology. Results: The average turnaround time for tissue processing, imaging, and diagnosis was 44.5 min. The sensitivity and specificity of 1Hr2Dx in diagnosing cancer were both >90%. Conclusions: The 1Hr2Dx method has the potential to improve patient care by providing an accurate preliminary diagnosis within an hour of biopsy.

FLARE enables rapid, feature-rich stains of chemical groups in biological samples for super-resolution and cleared tissue imaging., Fluorescence microscopy is a workhorse tool in biomedical imaging but often poses substantial challenges to practitioners in achieving bright or uniform labeling. In addition, while antibodies are effective specific labels, their reproducibility is often inconsistent, and they are difficult to use when staining thick specimens. We report the use of conventional, commercially available fluorescent dyes for rapid and intense covalent labeling of proteins and carbohydrates in super-resolution (expansion) microscopy and cleared tissue microscopy. This approach, which we refer to as Fluorescent Labeling of Abundant Reactive Entities (FLARE), produces simple and robust stains that are modern equivalents of classic small-molecule histology stains. It efficiently reveals a wealth of key landmarks in cells and tissues under different fixation or sample processing conditions and is compatible with immunolabeling of proteins and in situ hybridization labeling of nucleic acids.

Light-sheet microscopy (LSM) has emerged as a powerful tool for high-speed volumetric imaging of live model organisms and large optically cleared specimens. When designing cleared-tissue LSM systems with certain desired imaging specifications (e.g. resolution, contrast, and working distance), various design parameters must be taken into consideration. In order to elucidate some of the key design tradeoffs for LSM systems, we present a diffraction-based analysis of single- and dual-objective LSM configurations using simulations of LSM point spread functions. We assume Gaussian illumination is utilized. Specifically, we analyze the effects of the illumination and collection numerical aperture (NA), as well as their crossing angle, on spatial resolution and contrast. Assuming an open-top light-sheet (OTLS) architecture, we constrain these parameters based on fundamental geometric considerations as well as those imposed by currently available microscope objectives. In addition to revealing the performance tradeoffs of various single- and dual-objective LSM configurations, our analysis showcases the potential advantages of a novel, non-orthogonal dual-objective (NODO) architecture, especially for moderate-resolution imaging applications (collection NA of 0.5 to 0.8).

Light-sheet microscopy (LSM) has emerged as a powerful tool for high-speed volumetric imaging of live model organisms and large optically cleared specimens. When designing cleared-tissue LSM systems with certain desired imaging specifications (e.g. resolution, contrast, and working distance), various design parameters must be taken into consideration. In order to elucidate some of the key design trade-offs for LSM systems, we present a diffraction-based analysis of single- and dual-objective LSM configurations where Gaussian illumination is utilized. Specifically, we analyze the effects of the illumination and collection numerical aperture (NA), as well as their crossing angle, on spatial resolution and contrast. Assuming an open-top light-sheet (OTLS) architecture, we constrain these parameters based on fundamental geometric considerations as well as those imposed by currently available microscope objectives. In addition to revealing the performance tradeoffs of various single- and dual-objective LSM configurations, our analysis showcases the potential advantages of a novel, non-orthogonal dual-objective (NODO) architecture, especially for moderate-resolution imaging applications (collection NA of 0.5 to 0.8).

The rate of positive margins in head and neck cancers has remained stagnant over the past three decades and is consistently associated with poor overall survival. This suggests that significant improvements must be made intraoperatively to ensure negative margins. We discuss the important role of fluorescence imaging to guide surgical oncology in head and neck cancer. This review includes a general overview of the principles of fluorescence, available fluorophores used for fluorescence imaging, and specific clinical applications of fluorescence-guided surgery, as well as challenges and future directions in head and neck surgical oncology. Laryngoscope, 131:529-534, 2021.

Handheld and endoscopic optical-sectioning microscopes are being developed for noninvasive screening and intraoperative consultation. Imaging a large extent of tissue is often desired, but miniature in vivo microscopes tend to suffer from limited fields of view. To extend the imaging field during clinical use, we have developed a real-time video mosaicking method, which allows users to efficiently survey larger areas of tissue. Here, we modified a previous post-processing mosaicking method so that real-time mosaicking is possible at >30 frames/second when using a device that outputs images that are 400 × 400 pixels in size. Unlike other real-time mosaicking methods, our strategy can accommodate image rotations and deformations that often occur during clinical use of a handheld microscope. We perform a feasibility study to demonstrate that the use of real-time mosaicking is necessary to enable efficient sampling of a desired imaging field when using a handheld dual-axis confocal microscope.

In recent years we have developed open-top light-sheet microscopes for a variety of clinical applications. Here we present a new light-sheet micro-dissection microscope for improved molecular analysis of intact tissue specimens.

An ~45-minute workflow, consisting of fluorescence labeling, tissue clearing, and 3D non-destructive, open-top light-sheet (OTLS) microscopy, has been developed for diagnosis of 12 human prostate needle cores within an hour after biopsy.

Understanding how nucleation is driven by chemical reactions is essential for the optimal design of materials grown from molecular precursors. Typically, the design and analysis of nucleation react...

Intraoperative identification of carcinoma at lumpectomy margins would enable reduced re-excision rates, which are currently as high as 20% to 50%. Although imaging of disease-associated biomarkers can identify malignancies with high specificity, multiplexed imaging of such biomarkers is necessary to detect molecularly heterogeneous carcinomas with high sensitivity. We have developed a Raman-encoded molecular imaging (REMI) technique in which targeted nanoparticles are topically applied on excised tissues to enable rapid visualization of a multiplexed panel of cell surface biomarkers at surgical margin surfaces. A first-ever clinical study was performed in which 57 fresh specimens were imaged with REMI to simultaneously quantify the expression of four biomarkers HER2, ER, EGFR, and CD44. Combined detection of these biomarkers enabled REMI to achieve 89.3% sensitivity and 92.1% specificity for the detection of breast carcinoma. These results highlight the sensitivity and specificity of REMI to detect biomarkers in freshly resected tissue, which has the potential to reduce the rate of re-excision procedures in cancer patients. Cancer Res; 77(16); 4506–16. ©2017 AACR.

BACKGROUND Extent of resection is a prognostic factor for low- and high-grade gliomas. Fluorescence guided surgery (FGS) using five-aminolevulinic acid (5-ALA) is associated with greater extent of resection in high-grade gliomas. However, for low-grade gliomas, intraoperative imaging technologies such as FGS, have not been optimized to distinguish tumor from normal tissue. Intraoperative confocal microscopy can better visualize tissue cytoarchitecture in real-time. Here we report on the feasibility of a newly-developed, hand-held, line-scanned dual-axis (LS-DAC) confocal microscope in distinguishing tumor vs. normal cells in ex vivo human low-grade glioma tissue. METHOD Ten low-grade glioma patients who underwent craniotomy were enrolled. Resected specimens were labelled with acridine orange (1mM) for one minute, and exposed surfaces were immediately imaged by our device. Subsequently, specimens were cut into sections and stained with H&E for histopathological analysis. RESULTS LS-DAC confocal microscope visualized nuclei of tumor cells vs. surrounding tissue, demonstrating clear differences in cellularity in the two compartments. Acquired images were comparable to those observed on matched H&E-stained sections. Live images provided minimal motion artifact due to the higher frame rate of 16 Hz. CONCLUSION LS-DAC confocal microscope provided real-time, high-contrast mosaic images of human low-grade glioma tissue ex vivo. The ability to distinguish tumor vs. normal tissue at the cellular level with little motion artifact, as well as the device’s hand-held design, suggests this technology merits additional investigation as an intraoperative adjunct for low-grade glioma surgery.