SummaryBackground. The cutaneous manifestations of COVID‐19 disease are poorly characterized.Objectives. To describe the cutaneous manifestations of COVID‐19 di

Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinicopathological practice. The objective of the study was to systematically analyse the current state of research on reader studies involving melanoma and to assess their potential clinical relevance by evaluating three main aspects: test set characteristics (holdout/out-of-distribution data set, composition), test setting (experimental/clinical, inclusion of metadata) and representativeness of participating clinicians. PubMed, Medline and ScienceDirect were screened for peer-reviewed studies published between 2017 and 2021 and dealing with AI-based skin cancer classification involving melanoma. The search terms skin cancer classification, deep learning, convolutional neural network (CNN), melanoma (detection), digital biomarkers, histopathology and whole slide imaging were combined. Based on the search results, only studies that considered direct comparison of AI results with clinicians and had a diagnostic classification as their main objective were included. A total of 19 reader studies fulfilled the inclusion criteria. Of these, 11 CNN-based approaches addressed the classification of dermoscopic images; 6 concentrated on the classification of clinical images, whereas 2 dermatopathological studies utilised digitised histopathological whole slide images. All 19 included studies demonstrated superior or at least equivalent performance of CNN-based classifiers compared with clinicians. However, almost all studies were conducted in highly artificial settings based exclusively on single images of the suspicious lesions. Moreover, test sets mainly consisted of holdout images and did not represent the full range of patient populations and melanoma subtypes encountered in clinical practice.

We review the most characteristic clinical and histopathologic findings of the cutaneous manifestations of the occlusive nonvasculitic vasculopathic disorders. Clinically, most of these conditions are characterized by retiform purpura. Histopathologic findings consist of occlusion of the vessel lumina with no vasculitis. Different disorders may produce nonvasculitic occlusive vasculopathy in cutaneous blood and lymphatic vessels, including embolization due to cholesterol and oxalate emboli, cutaneous intravascular metastasis from visceral malignancies, atrial myxomas, intravascular angiosarcoma, intralymphatic histiocytosis, intravascular lymphomas, endocarditis, crystal globulin vasculopathy, hypereosinophilic syndrome, and foreign material. Other times, the occlusive disorder is due to platelet pugging, including heparin necrosis, thrombocytosis secondary to myeloproliferative disorders, paroxysmal nocturnal hemoglobinuria, and thrombotic thrombocytopenic purpura. Occlusive vasculopathy may also appear in cold-related gelling agglutination, like that occurring in cryofibrinogenemia, cryoglobulinemia, cold agglutinin syndrome, and crystalglobulinemia. Microorganisms may also occlude the vessels lumina and this is especially frequent in ecthyma gangrenosum, opportunistic fungi as aspergillosis or fusariosis, Lucio phenomenon of lepromatous leprosy and disseminated strongyloidiasis. Systemic coagulopathies due to defects of C and S proteins, coumarin/warfarin-induced skin necrosis, disseminated intravascular coagulation, and antiphospholipid antibody/lupus anticoagulant syndrome may also result in occlusive nonvasculitic vasculopathy. Finally, vascular coagulopathies such as Sneddon syndrome, livedoid vasculopathy, and atrophic papulosis may also cause occlusion of the vessels of the dermis and/or subcutis. Histopathologic study of occlusive vasculopathic lesions is the first step to achieve an accurate diagnosis, and they should be correlated with clinical history, physical examination, and laboratory findings to reach a final diagnosis.