Background: Machine learning models provide significant opportunities for improvement in health care, but their “black-box” nature poses many risks. Methods: We built a custom Python module as part of a framework for generating artifacts that are meant to be tunable and describable to allow for future testing needs. We conducted an analysis of a previously published digital pathology classification model and an internally developed kidney tissue segmentation model, utilizing a variety of generated artifacts including testing their effects. The artifacts simulated were bubbles, tissue folds, uneven illumination, marker lines, uneven sectioning, altered staining, and tissue tears. Results: We found that there is some performance degradation on the tiles with artifacts, particularly with altered stains but also with marker lines, tissue folds, and uneven sectioning. We also found that the response of deep learning models to artifacts could be nonlinear. Conclusions: Generated artifacts can provide a useful tool for testing and building trust in machine learning models by understanding where these models might fail.

Background: With the emergence of whole slide imaging (WSI) and widespread access to high-speed Internet, pathology labs are now poised to implement digital pathology as a way to access diagnostic pathology expertise. This paper describes a collaborative partnership between a high-volume reference diagnostic laboratory (Labcorp) and an academic pathology department (Mount Sinai Hospital) in the transition from a traditional glass slide service to a digital platform. Using the standard framework of implementation science, we evaluate the consistency and quality of the Philips IntelliSite Pathology Solution (PIPS) in delivering save and efficient diagnostic services. Materials and Methods: Digital and glass slide diagnoses of all consult cases were documented over a 12-month period. The Proctor guideline was used to quantitatively and qualitatively measure (e.g., focus group studies, field notes, and administrative data) implementation success. Lean techniques (e.g., value stream mapping) were applied to measure changes in efficiency with the transition to a digital platform. Results: Our study supports the acceptability, high adoption, appropriateness, feasibility, fidelity, and sustainability of the digital pathology platform. The digital portal also improved the quality of patient care by increasing efficiency, effectiveness, safety, and timeliness. The intraobserver concordance rate was 100%. The digital transition resulted in a reduction in turnaround time from 86 h to an average 35 min and a 20-fold increase in efficiency of the consultation process. Conclusion: As the pathology community contemplates digital pathology as a transformational tool in providing broad access to diagnostic expertise across time and space, our study provides an implementation strategy along with evidence that the digital platform is safe, effective, and efficient.

Multiparametric fluorescence imaging through CODEX allows the simultaneous imaging of many biomarkers in a single tissue section. While the digital fluorescence data thus obtained can provide highly specific characterizations of individual cells and microenvironments, the images obtained are different from those usually interpreted by pathologists (i.e., hematoxylin and eosin [H&E] slides and 3,3′-diaminobenzidine-stained immunohistochemistry slides). Having the fluorescence data plus coregistered H&E or similar data could facilitate the adoption of multiparametric imaging into regular workflows, as well as facilitate the transfer of algorithms and machine learning previously developed around H&E slides. Since commercial CODEX instruments do not produce H&E-like images by themselves, we developed a staining protocol and associated image processing to make “virtual H&E” images that can be incorporated into the CODEX workflow. While there are many ways to achieve virtual H&E images, including the use of a fluorescent nuclear stain and tissue autofluorescence to simulate eosin staining, we opted to combine fluorescent nuclear staining (through 4′,6-diamidino-2-phenylindole) with actual eosin staining. We also output images derived from fluorescent nuclear staining and autofluorescence images for additional evaluation.

Digital pathology (DP) has disrupted the practice of traditional pathology, including applications in education, research, and clinical practice. Contemporary whole slide imaging (WSI) devices include technological advances that help address some of the challenges facing modern pathology, such as increasing workloads with fewer subspecialized pathologists, expanding integrated delivery networks with global reach, and greater customization when working up cases for precision medicine. This review focuses on integral hardware components of 43 market available and soon-to-be released digital WSI devices utilized throughout the world. Components such as objective lens type and magnification, scanning camera, illumination, and slide capacity were evaluated with respect to scan time, throughput, accuracy of scanning, and image quality. This analysis of assorted modern WSI devices offers essential, valuable information for successfully selecting and implementing a digital WSI solution for any given pathology practice.

Introduction: Manual gating of flow cytometry (FCM) data for marrow cell analysis is a standard approach in current practice, although it is time- and labor-consuming. Recent advances in cytometry technology have led to significant efforts in developing partially or fully automated analysis methods. Although multiple supervised and unsupervised FCM data analysis algorithms have been developed, they have not been widely adopted by the clinical and research laboratories. In this study, we evaluated flowDensity, an open source freely available algorithm, as an automated analysis tool for classification of lymphocyte subsets in the bone marrow biopsy specimens. Materials and Methods: FlowDensity-based gating was applied to 102 normal bone marrow samples and compared with the manual analysis. Independent expression of each cell marker was assessed for comprehensive expression analysis and visualization. Results: Our findings showed a correlation between the manual and flowDensity-based gating in the lymphocyte subsets. However, flowDensity-based gating in the populations with a small number of cells in each cluster showed a low degree of correlation. Comprehensive expression analysis successfully identified and visualized the lymphocyte subsets. Discussion: Our study found that although flowDensity might be a promising method for FCM data analysis, more optimization is required before implementing this algorithm into day-to-day workflow.

Introduction: The coronavirus disease 2019 (COVID-19) pandemic has increased the use of technology for communication including departmental conferences, working remotely, and distance teaching. Methods to enable these activities should be developed and promulgated. Objective: To repurpose a preexisting educational website to enable the development of a COVID-19 autopsy biorepository to support distance teaching and COVID-19 research. Methods: After consent was obtained, autopsies were performed on patients with a confirmed positive severe acute respiratory syndrome coronavirus-2 reverse-transcriptase-polymerase-chain reaction test. Autopsies were performed according to a COVID-19 protocol, and all patients underwent both gross and microscopic examination. The H and E histology slides were scanned using a Leica Biosystems Aperio CS ScanScope whole slide scanner and the digital slide files were converted to deep zoom images that could be uploaded to the University of Alabama at Birmingham (UAB) Pathology Educational Instructional Resource website where virtual microscopy of the slides is available. Results: A total of 551 autopsy slides from 24 UAB COVID-19 cases, 1 influenza H1N1 case and 1 tuberculosis case were scanned and uploaded. Five separate COVID-19 research teams used the digital slides remotely with or without a pathologist on a Zoom call. The scanned slides were used to produce one published case report and one published research project. The digital COVID-19 autopsy biorepository was routinely used for educational conferences and research meetings locally, nationally and internationally. Conclusion: The repurposing of a pre-existing website enabled telepathology consultation for research and education purposes. Combined with other communication technology (Zoom) this achievement highlights what is possible using pre-existing technologies during a global pandemic.