Comfere, Nneka I.

ABSTRACT Part I of our three‐part series outlines the essential technical and operational components required for successful digital pathology implementation including hardware, software, and IT infrastructure. It reviews the rationale for digitization, highlighting improvements in workflow efficiency, diagnostic collaboration, and preparedness for computational applications. Key components of Whole Slide Imaging (WSI) systems are discussed, including practical considerations for scanner selection, scanning modalities, and performance trade‐offs relevant to dermatopathology. The article also examines image compression strategies and pyramid image representation, with attention to balancing image quality and storage efficiency. Finally, we review DICOM standards and storage infrastructure options, including cloud, on‐premises, and hybrid models, and associated network bandwidth requirements.

Patzelt et al. previously characterized dermal-binding autoantibodies using an indirect immunofluorescence (IIF) mosaic assay with cells transfected with p200-laminin β4, laminin-332 or collagen VII subunits among specimens showing a dermal pattern on IIF using salt-split skin (IIF-SSS) and IgG. This study expanded testing to include specimens with either a dermal or mixed pattern on IIF-SSS and demonstrated improved test sensitivity with modified testing methods.

Abstract Cutaneous squamous cell carcinoma (cSCC) poses significant clinical challenges due to its rising incidence and potential for metastasis. Histopathologic risk stratification is further limited by substantial inter-observer variability. Unsupervised AI approaches based on content-based image retrieval offer scalable and interpretable decision support for diagnostic pathology. The objective of this study was to evaluate the use of image retrieval within histopathology atlases to stratify cSCC tumor differentiation from whole-slide images (WSIs), while comparing different patch selection and feature extraction strategies. This retrospective study included 552 archived WSIs comprising 385 well-differentiated, 102 moderately differentiated, and 66 poorly differentiated cases collected across Mayo Clinic sites in Arizona, Florida, and Minnesota. Image atlases were constructed using multiple patch aggregation strategies (Mosaic, Collage, and Montage) and deep learning encoders (KimiaNet, PathDino, and H-Optimus-0). A leave-one-WSI-out evaluation framework was used to assess differentiation classification performance using accuracy, specificity, sensitivity, and F1 score. Mosaic combined with KimiaNet achieved the highest Top-1 accuracy (74.9%) and specificity (92.6%), while Mosaic with H-Optimus-0 yielded the best Top-5 accuracy (79.0%) and macro-F1 score (62.6%). Collage combined with KimiaNet produced the highest Top-5 specificity (99.5%). The generalizability of the evaluated AI models varied across hospitals, reflecting differences in imaging protocols, staining practices, and patient populations. Overall, unsupervised image search and retrieval provides effective, annotation-free support for cSCC differentiation and has the potential to enhance dermatopathology workflows when appropriate combinations of patch selection and feature ex-traction methods are employed.

Introduction: Outcomes from multidisciplinary lymphoma tumor boards in the molecular era are limited, and the effects of transitioning to virtual formats during the COVID-19 pandemic are not well-documented. This study evaluates how the transition of the Mayo Clinic Lymphoma Tumor Board to a virtual format has impacted its effectiveness and operations. The board, part of the International Mayo Clinic Care Network (MCCN), involves case presentations, subspecialist reviews, and collaborative recommendations. Methods: The Mayo Clinic Lymphoma Tumor Board, an integral part of the Mayo Clinic Care Network (MCCN), conducted a comprehensive review of lymphoma cases from 2014 to 2024. The board's review process involves a structured approach including the presentation of clinical case details, radiology and hematopathology findings, proposed treatment options, relevant literature review, and discussions. From 2014 to 2024, the Mayo Clinic Lymphoma Tumor Board reviewed a total of 722 patients. The review process involves a multidisciplinary team, including physicians, pharmacists, clinical research associates, and trainees. Recommendations and changes related to radiology interpretation, pathologic diagnosis, and treatment approaches were documented and tracked prospectively. In March 2020, the board transitioned to a virtual format due to the COVID-19 pandemic. This shift allowed for remote participation and continued collaborative review while maintaining the board's structured approach and documentation practices. Results: In a total of 722 patients, changes in care were identified in 423 patients, including 287 with newly diagnosed lymphoma and 136 with relapse or refractory disease. Among those who experienced changes, 94 had diffuse large B-cell lymphoma, 49 had follicular lymphoma, 39 had marginal zone lymphoma, 36 had classical Hodgkin lymphoma, and 29 had mantle cell lymphoma. Prior to the COVID-19 pandemic, 431 patients were analyzed, with 217 (50.3%) experiencing changes. A total of 268 changes were documented among these patients. Changes in radiologic interpretation occurred in 9 patients (2.1% of 431 total patients). Pathologic diagnosis changes were noted in 42 patients (9.7%). Additional testing was recommended for 73 patients (16.9%), and clinical management was altered for 144 patients (33.4%). After transitioning to a virtual format, 291 patients were reviewed post-COVID, with 206 (70.8%) having recommended changes. The total number of change recommendations was 322, reflecting increases across all components compared to previous data, with adjustments for varying numbers of patients reviewed. Specifically, radiologic interpretation changes occurred in 21 patients (7.2%), pathologic diagnosis changes in 57 patients (19.6%), additional testing recommendations for 85 patients (29.2%), and clinical management alterations in 159 patients (54.7%). Conclusion: Transitioning to a virtual format in the Mayo Clinic Lymphoma Tumor Board's continued to demonstrate the effectiveness, with increased changes in diagnostic interpretations and clinical management. These results illustrate the potential of virtual tumor boards to improve collaborative decision-making and adapt to evolving clinical needs.

AbstractHistiocytoid Sweet syndrome (H‐SS) is a histopathological variant of Sweet syndrome (SS) defined by cutaneous infiltration of immature myeloid cells morphologically resembling histiocytes. The association of H‐SS with underlying malignancy, particularly myelodysplastic syndromes, is well‐established. Myelodysplasia cutis (MDS‐cutis) has been proposed to describe cases historically diagnosed as H‐SS but characterized by shared clonality of the myeloid infiltrate in skin and bone marrow. Therefore, identifying patients who might have MDS‐cutis is critical for the management of the associated hematologic malignancy. VEXAS syndrome, an adult‐onset autoinflammatory disease, should also be included in the histopathologic differential diagnosis of H‐SS, as it shares clinical and pathologic features with MDS‐cutis. Through the presentation of two cases, we aim to highlight the defining features and key clinical implications of MDS‐cutis and VEXAS syndrome.

AbstractAn 11‐year‐old female was referred from an outside institution after a diagnostic biopsy and subsequent excision of a progressively enlarging reddish‐brown nodule demonstrated features concerning for a balloon cell nevus with severe atypia versus a high‐grade melanocytoma. Upon review of the initial biopsy specimen and molecular data, we favored the diagnosis to be consistent with a high‐grade melanocytoma with balloon cell changes while considering the possibility of balloon cell melanoma due to concerning histopathologic and genetic abnormalities. In this case study, we discuss critical diagnostic considerations in this rare pediatric case and highlight important pathologic and clinical features of melanocytomas and balloon cell melanoma.

AbstractBackgroundTechnology has revolutionized not only direct patient care but also diagnostic care processes. This study evaluates the transition from glass‐slide microscopy to digital pathology (DP) at a multisite academic institution, using mixed methods to understand user perceptions of digitization and key productivity metrics of practice change.MethodsParticipants included dermatopathologists, pathology reporting specialists, and clinicians. Electronic surveys and individual or group interviews included questions related to technology comfort, trust in DP, and rationale for DP adoption. Case volumes and turnaround times were abstracted from the electronic health record from Qtr 4 2020 to Qtr 1 2023 (inclusive). Data were analyzed descriptively, while interviews were analyzed using methods of content analysis.ResultsThirty‐four staff completed surveys and 22 participated in an interview. Case volumes and diagnostic turnaround time did not differ across the institution during or after implementation timelines (p = 0.084; p = 0.133, respectively). 82.5% (28/34) of staff agreed that DP improved the sign‐out experience, with accessibility, ergonomics, and annotation features described as key factors. Clinicians reported positive perspectives of DP impact on patient safety and interdisciplinary collaboration.ConclusionsOur study demonstrates that DP has a high acceptance rate, does not adversely impact productivity, and may improve patient safety and care collaboration.