N-dihydrogalactochitosan reduces mortality in a lethal mouse model of SARS-CoV-2.

The rapid emergence and global dissemination of SARS-CoV-2 that causes COVID-19 continues to cause an unprecedented global health burden resulting in nearly 7 million deaths. While multiple vaccine countermeasures have been approved for emergency use, additional treatments are still needed due to sluggish vaccine rollout, vaccine hesitancy, and inefficient vaccine-mediated protection. Immunoadjuvant compounds delivered intranasally can guide non-specific innate immune responses during the critical early stages of viral replication, reducing morbidity and mortality. N-dihydrogalactochitosan (GC) is a novel mucoadhesive immunostimulatory polymer of ß-0-4-linked N-acetylglucosamine that is solubilized by the conjugation of galactose glycans with current applications as a cancer immunotherapeutic. We tested GC as a potential countermeasure for COVID-19. GC was well-tolerated and did not produce histopathologic lesions in the mouse lung. GC administered intranasally before and after SARS-CoV-2 exposure diminished morbidity and mortality in humanized ACE2 receptor expressing mice by up to 75% and reduced infectious virus levels in the upper airway. Fluorescent labeling of GC shows that it is confined to the lumen or superficial mucosa of the nasal cavity, without involvement of adjacent or deeper tissues. Our findings demonstrate a new application for soluble immunoadjuvants such as GC for preventing disease associated with SARS-CoV-2 and may be particularly attractive to persons who are needle-averse.

Utility of fluorescence imitating brightfield imaging microscopy for the diagnosis of feline chronic enteropathy.

Fluorescence imitating brightfield imaging (FIBI) is a novel microscopy method that allows for real-time, nondestructive, slide-free tissue imaging of fresh, formalin-fixed, or paraffin-embedded tissue. The nondestructive nature of the technology permits tissue preservation for downstream analyses. The objective of this observational study was to assess the utility of FIBI compared with conventional hematoxylin and eosin (H&E)-stained histology slides in feline gastrointestinal histopathology. Formalin-fixed paraffin-embedded full-thickness small intestinal tissue specimens from 50 cases of feline chronic enteropathy were evaluated. The ability of FIBI to evaluate predetermined morphological features (epithelium, villi, crypts, lacteals, fibrosis, submucosa, and muscularis propria) and inflammatory cells was assessed on a 3-point scale (0 = FIBI cannot identify the feature; 1 = FIBI can identify the feature; 2 = FIBI can identify the feature with more certainty than H&E). H&E and FIBI images were also scored according to World Small Animal Veterinary Association (WSAVA) Gastrointestinal Standardization Group guidelines. FIBI identified morphological features with similar or, in some cases, higher confidence compared with H&E images. The identification of inflammatory cells was less consistent. FIBI and H&E images showed an overall poor agreement with regard to the assigned WSAVA scores. While FIBI showed an equal or better ability to identify morphological features in intestinal biopsies, its ability to identify inflammatory cells is currently inferior compared with H&E-based imaging. Future studies on the utility of FIBI as a diagnostic tool for noninflammatory histopathologic lesions are warranted.

Systematically higher Ki67 scores on core biopsy samples compared to corresponding resection specimen in breast cancer: a multi-operator and multi-institutional study.

Ki67 has potential clinical importance in breast cancer but has yet to see broad acceptance due to inter-laboratory variability. Here we tested an open source and calibrated automated digital image analysis (DIA) platform to: (i) investigate the comparability of Ki67 measurement across corresponding core biopsy and resection specimen cases, and (ii) assess section to section differences in Ki67 scoring. Two sets of 60 previously stained slides containing 30 core-cut biopsy and 30 corresponding resection specimens from 30 estrogen receptor-positive breast cancer patients were sent to 17 participating labs for automated assessment of average Ki67 expression. The blocks were centrally cut and immunohistochemically (IHC) stained for Ki67 (MIB-1 antibody). The QuPath platform was used to evaluate tumoral Ki67 expression. Calibration of the DIA method was performed as in published studies. A guideline for building an automated Ki67 scoring algorithm was sent to participating labs. Very high correlation and no systematic error (p = 0.08) was found between consecutive Ki67 IHC sections. Ki67 scores were higher for core biopsy slides compared to paired whole sections from resections (p ≤ 0.001; median difference: 5.31%). The systematic discrepancy between core biopsy and corresponding whole sections was likely due to pre-analytical factors (tissue handling, fixation). Therefore, Ki67 IHC should be tested on core biopsy samples to best reflect the biological status of the tumor.

CoreView: fresh tissue biopsy assessment at the bedside using a millifluidic imaging chip.

Minimally invasive core needle biopsies for medical diagnoses have become increasingly common for many diseases. Although tissue cores can yield more diagnostic information than fine needle biopsies and cytologic evaluations, there is no rapid assessment at the point-of-care for intact tissue cores that is low-cost and non-destructive to the biopsy. We have developed a proof-of-concept 3D printed millifluidic histopathology lab-on-a-chip device to automatically handle, process, and image fresh core needle biopsies. This device, named CoreView, includes modules for biopsy removal from the acquisition tool, transport, staining and rinsing, imaging, segmentation, and multiplexed storage. Reliable removal from side-cutting needles and bidirectional fluid transport of core needle biopsies of five tissue types has been demonstrated with 0.5 mm positioning accuracy. Automation is aided by a MATLAB-based biopsy tracking algorithm that can detect the location of tissue and air bubbles in the channels of the millifluidic chip. With current and emerging optical imaging technologies, CoreView can be used for a rapid adequacy test at the point-of-care for tissue identification as well as glomeruli counting in renal core needle biopsies.

Real-time polarization microscopy of fibrillar collagen in histopathology.

Over the past two decades, fibrillar collagen reorganization parameters such as the amount of collagen deposition, fiber angle and alignment have been widely explored in numerous studies. These parameters are now widely accepted as stromal biomarkers and linked to disease progression and survival time in several cancer types. Despite all these advances, there has not been a significant effort to make it possible for clinicians to explore these biomarkers without adding steps to the clinical workflow or by requiring high-cost imaging systems. In this paper, we evaluate previously described polychromatic polarization microscope (PPM) to visualize collagen fibers with an optically generated color representation of fiber orientation and alignment when inspecting the sample by a regular microscope with minor modifications. This system does not require stained slides, but is compatible with histological stains such as H&E. Consequently, it can be easily accommodated as part of regular pathology review of tissue slides, while providing clinically useful insight into stromal composition.

Banff Digital Pathology Working Group: Going digital in transplant pathology.

The Banff Digital Pathology Working Group (DPWG) was formed in the time leading up to and during the joint American Society for Histocompatibility and Immunogenetics/Banff Meeting, September 23-27, 2019, held in Pittsburgh, Pennsylvania. At the meeting, the 14th Banff Conference, presentations directly and peripherally related to the topic of "digital pathology" were presented; and discussions before, during, and after the meeting have resulted in a list of issues to address for the DPWG. Included are practice standardization, integrative approaches for study classification, scoring of histologic parameters (eg, interstitial fibrosis and tubular atrophy and inflammation), algorithm classification, and precision diagnosis (eg, molecular pathways and therapeutics). Since the meeting, a survey with international participation of mostly pathologists (81%) was conducted, showing that whole slide imaging is available at the majority of centers (71%) but that artificial intelligence (AI)/machine learning was only used in ≈12% of centers, with a wide variety of programs/algorithms employed. Digitalization is not just an end in itself. It also is a necessary precondition for AI and other approaches. Discussions at the meeting and the survey highlight the unmet need for a Banff DPWG and point the way toward future contributions that can be made.

Pigeons (Columba livia) as Trainable Observers of Pathology and Radiology Breast Cancer Images.

Pathologists and radiologists spend years acquiring and refining their medically essential visual skills, so it is of considerable interest to understand how this process actually unfolds and what image features and properties are critical for accurate diagnostic performance. Key insights into human behavioral tasks can often be obtained by using appropriate animal models. We report here that pigeons (Columba livia)-which share many visual system properties with humans-can serve as promising surrogate observers of medical images, a capability not previously documented. The birds proved to have a remarkable ability to distinguish benign from malignant human breast histopathology after training with differential food reinforcement; even more importantly, the pigeons were able to generalize what they had learned when confronted with novel image sets. The birds' histological accuracy, like that of humans, was modestly affected by the presence or absence of color as well as by degrees of image compression, but these impacts could be ameliorated with further training. Turning to radiology, the birds proved to be similarly capable of detecting cancer-relevant microcalcifications on mammogram images. However, when given a different (and for humans quite difficult) task-namely, classification of suspicious mammographic densities (masses)-the pigeons proved to be capable only of image memorization and were unable to successfully generalize when shown novel examples. The birds' successes and difficulties suggest that pigeons are well-suited to help us better understand human medical image perception, and may also prove useful in performance assessment and development of medical imaging hardware, image processing, and image analysis tools.

Immunohistochemistry and mass spectrometry for highly multiplexed cellular molecular imaging.

The role of immunohistochemistry (IHC) in the management of cancer has expanded to provide improved diagnostic classification, as well as guidance on disease prognosis, therapy, and relapse. These new tasks require evaluation of an increasing number of protein targets; however, conventional multiplexing, usually achieved using serial tissue sections stained for a single analyte per slide, can exhaust small biopsy specimens, complicate slide-to-slide protein expression correlation, and leave insufficient material for additional molecular assays. A new approach, mass spectrometry immunohistochemistry (MSIHC), compatible with high levels of target multiplexing and suitable for use on formalin-fixed, paraffin-embedded samples can circumvent many of these issues. The strategy employs antibodies that are labeled with elemental mass tags, such as isotopically pure lanthanides not typically found in biological specimens, rather than with typical fluorophores or chromogens. The metal-labeled antibodies are then detected in tissue using lasers or ion beams to liberate the tags for subsequent mass spectrometry detection. Within a given multiplexed IHC panel, the metal labels are selected so that their respective masses do not overlap. More than 30 antibodies have been imaged simultaneously, and up to 100 antibodies could potentially be detected at once if the full available mass spectrum is deployed. MSIHC has a number of advantages over conventional IHC techniques. Background due to autofluorescence is absent and the dynamic range is 10(5), exceeding immunofluorescence and chromogenic IHC by 100-fold and 1000-fold, respectively. Detection of labeled primary antibodies improves assay linearity over both chromogenic and fluorescent IHC. Multiplexed mass-tagged antibodies incubated simultaneously with tissue do not appear to cross-interfere, and because the mass tags do not degrade, samples are stable indefinitely. The imaging resolution of multiplexed ion-beam imaging can be better than light microscopy. With appropriate instrumentation, MSIHC has the potential to transform research and clinical pathology practice.

Multiplexed ion beam imaging of human breast tumors.

Immunohistochemistry (IHC) is a tool for visualizing protein expression that is employed as part of the diagnostic workup for the majority of solid tissue malignancies. Existing IHC methods use antibodies tagged with fluorophores or enzyme reporters that generate colored pigments. Because these reporters exhibit spectral and spatial overlap when used simultaneously, multiplexed IHC is not routinely used in clinical settings. We have developed a method that uses secondary ion mass spectrometry to image antibodies tagged with isotopically pure elemental metal reporters. Multiplexed ion beam imaging (MIBI) is capable of analyzing up to 100 targets simultaneously over a five-log dynamic range. Here, we used MIBI to analyze formalin-fixed, paraffin-embedded human breast tumor tissue sections stained with ten labels simultaneously. The resulting data suggest that MIBI can provide new insights into disease pathogenesis that will be valuable for basic research, drug discovery and clinical diagnostics.

High-speed spectral nanocytology for early cancer screening.

High-throughput partial wave spectroscopy (HTPWS) is introduced as a high-speed spectral nanocytology technique that utilizes the field effect of carcinogenesis to perform minimally invasive cancer screening on at-risk populations. HTPWS uses fully automated hardware and an acousto-optic tunable filter to scan slides at low magnification, to select cells, and to rapidly acquire spectra at each spatial pixel in a cell between 450 and 700 nm, completing measurements of 30 cells in 40 min. Statistical quantitative analysis on the size and density of intracellular nanostructures extracted from the spectra at each pixel in a cell yields the diagnostic biomarker, disorder strength (Ld). Linear correlation between Ld and the length scale of nanostructures was measured in phantoms with R2=0.93. Diagnostic sensitivity was demonstrated by measuring significantly higher Ld from a human colon cancer cell line (HT29 control vector) than a less aggressive variant (epidermal growth factor receptor knockdown). Clinical diagnostic performance for lung cancer screening was tested on 23 patients, yielding a significant difference in Ld between smokers and cancer patients, p=0.02 and effect size=1.00. The high-throughput performance, nanoscale sensitivity, and diagnostic sensitivity make HTPWS a potentially clinically relevant modality for risk stratification of the large populations at risk of developing cancer.

Real-time pathology through in vivo microscopy.

Miniature microscopes are being developed to examine tissue in situ for early anatomic and molecular indicators of disease, in real time, and at cellular resolution. These new devices will lead to a shift from the current diagnostic paradigm of biopsy followed by histopathology and recommended therapy, to one of non-invasive point-of-care diagnosis with the possibility of treatment in the same session. This potential revolution in disease management may have a major impact on the training of future physicians to include the use and interpretation of real-time in vivo microscopic data, and will also affect the emerging fields of telepathology and telemedicine. Implementation of new technologies into clinical practice is a complex process that requires multidisciplinary communication and collaboration among clinicians, engineers and scientists. As such, our aim is to provide a forward-looking view of the critical issues facing the development of new technologies and directing clinical education. Here, we focus on the use of in vivo microscopy for detection of malignant and pre-malignant lesions as well as for guiding therapy. We will highlight some of the areas in which in vivo microscopy could address unmet clinical needs, and then review the technological challenges that are being addressed, or need to be addressed, for in vivo microscopy to become an effective clinical tool.

Advances in optics for biotechnology, medicine and surgery.

The editors introduce the Biomedical Optics Express feature issue, "Advances in Optics for Biotechnology, Medicine and Surgery," which includes 12 contributions from attendees of the 2011 conference Advances in Optics for Biotechnology, Medicine and Surgery XII.

Point-of-care pathology with miniature microscopes.

Advances in optical designs are enabling the development of miniature microscopes that can examine tissue in situ for early anatomic and molecular indicators of disease, in real time, and at cellular resolution. These new devices will lead to major changes in how diseases are detected and managed, driving a shift from today's diagnostic paradigm of biopsy followed by histopathology and recommended therapy, to non-invasive point-of-care diagnosis with possible same-session definitive treatment. This shift may have major implications for the training requirements of future physicians to enable them to interpret real-time in vivo microscopic data, and will also shape the emerging fields of telepathology and telemedicine. Implementation of new technologies into clinical practice is a complex process that requires bridging gaps between clinicians, engineers and scientists. This article provides a forward-looking discussion of these issues, with a focus on malignant and pre-malignant lesions, by first highlighting some of the clinical areas where point-of-care in vivo microscopy could address unmet needs, and then by reviewing the technological challenges that are being addressed, or need to be addressed, for in vivo microscopy to become a standard clinical tool.

In vivo stable tumor-specific painting in various colors using dehalogenase-based protein-tag fluorescent ligands.

In vivo fluorescence cancer imaging is an important tool in understanding tumor growth and therapeutic monitoring and can be performed either with endogenously produced fluorescent proteins or with exogenously introduced fluorescent probes bound to targeting molecules. However, endogenous fluorescence proteins cannot be altered after transfection, thus requiring rederivation of cell lines for each desired color, while exogenously targeted fluorescence probes are limited by the heterogeneous expression of naturally occurring cellular targets. In this study, we adapted the dehalogenase-based protein-Tag (HaloTag) system to in vivo cancer imaging, by introducing highly expressed HaloTag receptors (HaloTagR) in cancer cells coupled with a range of externally injected fluorophore-conjugated dehalogenase-reactive reactive linkers. Tumor nodules arising from a single transfected cell line were stably labeled with fluorescence varying in emission spectra from green to near-infrared. After establishing and validating a SHIN3 cell line stably transfected with HaloTagR (HaloTagR-SHIN3), in vivo spectral fluorescence imaging studies were performed in live animals using a peritoneal dissemination model. The tumor nodules arising from HaloTagR-SHIN3 could be successfully labeled by four different fluorophore-conjugated HaloTag-ligands each emitting light at different wavelengths. These fluorophores could be alternated on serial imaging sessions permitting assessment of interval growth. Fluorescence was retained in histological specimens after fixation. Thus, this tagging system proves versatile both for in vivo and in vitro imaging without requiring modification of the underlying cell line. Thus, this strategy can overcome some of the limitations associated with the use of endogenous fluorescent proteins and exogenous targeted optical agents in current use.

Fine-needle aspiration of follicular adenoma versus parathyroid adenoma: the utility of multispectral imaging in differentiating lesions with subtle cytomorphologic differences.

BACKGROUND: Multispectral image analysis is an emerging tool that utilizes both spatial and spectral image information to classify images that can be used for the differentiation between benign versus malignant cells. The aim of the current study was to analyze the ability of this tool in differentiating subtle cytologic differences that cannot be appreciated by the human eye. Herein, the authors used fine-needle aspirations (FNAs) of follicular adenoma (FA) and parathyroid adenoma (PA) as a test case. METHODS: The Nuance platform was used to collect image stacks that were subsequently analyzed with CRI-MLS software, a neural network-based artificial intelligence system that can classify images using automatically "learned" spatial-spectral features. CRI-MLS was trained on random, well-preserved FA cells and PA cells from the training set (n = 45 cells each). An algorithmic solution was developed and then validated on an independent series comprised of 1904 FA cells from 5 FA cases and 690 PA cells from 5 PA cases. RESULTS: The solution from the CRI-MLS classifier showed 1876 FA cells (98.5%) as true FA and 28 FA cells (1.5%) as false PA, whereas 663 PA cells (96%) were true PA and 27 PA cells (4%) were false FA. The summary result of this solution was a sensitivity of 98.5%, a specificity of 96.1%, and a positive predictive value of 98.6%. CONCLUSIONS: The best spatial-spectral imaging solution was able to correctly classify 2534 of 2594 cells (98%) and misclassified only 55 of 2594 cells (2%). These data suggest that this technology may be valuable in a clinical setting to help differentiate and classify morphologically similar lesions.

Semiautomated multiplexed quantum dot-based in situ hybridization and spectral deconvolution.

Gene expression profiling has identified several potentially useful gene signatures for predicting outcome or for selecting targeted therapy. However, these signatures have been developed in fresh or frozen tissue, and there is a need to apply them to routinely processed samples. Here, we demonstrate the feasibility of a potentially high-throughput methodology combining automated in situ hybridization with quantum dot-labeled oligonucleotide probes followed by spectral imaging for the detection and subsequent deconvolution of multiple signals. This method is semiautomated and quantitative and can be applied to formalin-fixed, paraffin-embedded tissues. We have combined dual in situ hybridization with immunohistochemistry, enabling simultaneous measurement of gene expression and cell lineage determination. The technique achieves levels of sensitivity and specificity sufficient for the potential application of known expression signatures to biopsy specimens in a semiquantitative way, and the semiautomated nature of the method enables application to high-throughput studies.

Spectral imaging perspective on cytomics.

BACKGROUND: Cytomics involves the analysis of cellular morphology and molecular phenotypes, with reference to tissue architecture and to additional metadata. To this end, a variety of imaging and nonimaging technologies need to be integrated. Spectral imaging is proposed as a tool that can simplify and enrich the extraction of morphological and molecular information. Simple-to-use instrumentation is available that mounts on standard microscopes and can generate spectral image datasets with excellent spatial and spectral resolution; these can be exploited by sophisticated analysis tools. METHODS: This report focuses on brightfield microscopy-based approaches. Cytological and histological samples were stained using nonspecific standard stains (Giemsa; hematoxylin and eosin (H&E)) or immunohistochemical (IHC) techniques employing three chromogens plus a hematoxylin counterstain. The samples were imaged using the Nuance system, a commercially available, liquid-crystal tunable-filter-based multispectral imaging platform. The resulting data sets were analyzed using spectral unmixing algorithms and/or learn-by-example classification tools. RESULTS: Spectral unmixing of Giemsa-stained guinea-pig blood films readily classified the major blood elements. Machine-learning classifiers were also successful at the same task, as well in distinguishing normal from malignant regions in a colon-cancer example, and in delineating regions of inflammation in an H&E-stained kidney sample. In an example of a multiplexed ICH sample, brown, red, and blue chromogens were isolated into separate images without crosstalk or interference from the (also blue) hematoxylin counterstain. CONCLUSION: Cytomics requires both accurate architectural segmentation as well as multiplexed molecular imaging to associate molecular phenotypes with relevant cellular and tissue compartments. Multispectral imaging can assist in both these tasks, and conveys new utility to brightfield-based microscopy approaches.

Detection of malignancy in cytology specimens using spectral-spatial analysis.

Despite low sensitivity (around 60%), cytomorphologic examination of urine specimens represents the standard procedure in the diagnosis and follow-up of bladder cancer. Although color is information-rich, morphologic diagnoses are rendered almost exclusively on the basis of spatial information. We hypothesized that quantitative assessment of color (more precisely, of spectral properties) using liquid crystal-based spectral fractionation, combined with genetic algorithm-based spatial analysis, can improve the accuracy of traditional cytologic examination. Images of various cytological specimens were collected every 10 nm from 400 to 700 nm to create an image stack. The resulting data sets were analyzed using the Los Alamos-developed GENetic Imagery Exploitation (GENIE) package, a hybrid genetic algorithm that segments (classifies) images using automatically 'learned' spatio-spectral features. In an evolutionary fashion, GENIE generates a series of algorithms or 'chromosomes', keeping the one with best fitness with respect to a user-defined training set. First, we tested the system to determine if it could recognize malignant cells using artificial cytology specimens constructed to completely avoid the requirement for human interpretation. GENIE was able to differentiate malignant from benign cells and to estimate their relative proportions in controlled mixtures. We then tested the system on routine cytology specimens. When targeted to detect malignant urothelial cells in cytology specimens, GENIE showed a combined sensitivity and specificity of 85 and 95%, in samples drawn from two separate institutions over a span of 4 years. When trained on cases initially diagnosed as 'atypical' but with unequivocal follow-up by biopsy, surgical specimen or cytology, GENIE showed efficiency superior to the cytopathologist with respect to predicting the follow-up result in a cohort of 85 cases. We believe that, in future, this type of methodology could be used as an ancillary test in cytopathology, in a manner analogous to immunostaining, in those situations when a definitive diagnosis cannot be rendered based solely on the morphology.

Autofluorescence removal, multiplexing, and automated analysis methods for in-vivo fluorescence imaging.

The ability to image and quantitate fluorescently labeled markers in vivo has generally been limited by autofluorescence of the tissue. Skin, in particular, has a strong autofluorescence signal, particularly when excited in the blue or green wavelengths. Fluorescence labels with emission wavelengths in the near-infrared are more amenable to deep-tissue imaging, because both scattering and autofluorescence are reduced as wavelengths are increased, but even in these spectral regions, autofluorescence can still limit sensitivity. Multispectral imaging (MSI), however, can remove the signal degradation caused by autofluorescence while adding enhanced multiplexing capabilities. While the availability of spectral "libraries" makes multispectral analysis routine for well-characterized samples, new software tools have been developed that greatly simplify the application of MSI to novel specimens.