COVID Purpura (Toes) Case Series: A Chilblains-Like Vasculopathy.

ABSTRACT: Biopsies were taken from 4 patients who presented to their dermatologist with violaceous papules and plaques of the dorsal toes (COVID Toes) associated with varying degrees of severe acute respiratory syndrome coronavirus 2 exposure and COVID-19 testing. Major histopathologic findings were lymphocytic eccrine inflammation and a spectrum of vasculopathic findings to include superficial and deep angiocentric-perivascular lymphocytic inflammation, lymphocytes in vessel walls (lymphocytic vasculitis), endothelial swelling, red blood cell extravasation, and focal deposits of fibrin in both vessel lumina, and vessel walls. Interface changes were observed to include vacuolopathy and apoptotic keratinocytes at the basement membrane. Immunostains showed a dominant T-cell lineage (positive for T-cell receptor beta, CD2, CD3, CD5, and CD7). B-cells were rare and clusters of CD123-positive dermal plasmacytoid dendritic cells were observed surrounding eccrine clusters and some perivascular zones. The consistent perieccrine and vasculopathic features represent important pathologic findings in the diagnosis of COVID toes and are suggestive of pathogenetic mechanisms. Clinicopathologic correlation, the epidemiological backdrop, and the current worldwide COVID-19 pandemic favor a viral causation and should alert the physician to initiate a workup and the appropriate use of COVID-19 testing.

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system's use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications.

Diagnostic Accuracy of Virtual Pathology vs Traditional Microscopy in a Large Dermatopathology Study.

Importance: Digital pathology represents a transformative technology that impacts dermatologists and dermatopathologists from residency to academic and private practice. Two concerns are accuracy of interpretation from whole-slide images (WSI) and effect on workflow. Studies of considerably large series involving single-organ systems are lacking. Objective: To evaluate whether diagnosis from WSI on a digital microscope is inferior to diagnosis of glass slides from traditional microscopy (TM) in a large cohort of dermatopathology cases with attention on image resolution, specifically eosinophils in inflammatory cases and mitotic figures in melanomas, and to measure the workflow efficiency of WSI compared with TM. Design, Setting, and Participants: Three dermatopathologists established interobserver ground truth consensus (GTC) diagnosis for 499 previously diagnosed cases proportionally representing the spectrum of diagnoses seen in the laboratory. Cases were distributed to 3 different dermatopathologists who diagnosed by WSI and TM with a minimum 30-day washout between methodologies. Intraobserver WSI/TM diagnoses were compared, followed by interobserver comparison with GTC. Concordance, major discrepancies, and minor discrepancies were calculated and analyzed by paired noninferiority testing. We also measured pathologists' read rates to evaluate workflow efficiency between WSI and TM. This retrospective study was caried out in an independent, national, university-affiliated dermatopathology laboratory. Main Outcomes and Measures: Intraobserver concordance of diagnoses between WSI and TM methods and interobserver variance from GTC, following College of American Pathology guidelines. Results: Mean intraobserver concordance between WSI and TM was 94%. Mean interobserver concordance was 94% for WSI and GTC and 94% for TM and GTC. Mean interobserver concordance between WSI, TM, and GTC was 91%. Diagnoses from WSI were noninferior to those from TM. Whole-slide image read rates were commensurate with WSI experience, achieving parity with TM by the most experienced user. Conclusions and Relevance: Diagnosis from WSI was found equivalent to diagnosis from glass slides using TM in this statistically powerful study of 499 dermatopathology cases. This study supports the viability of WSI for primary diagnosis in the clinical setting.