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Background: Cutaneous leishmaniasis (CL) incidence in Switzerland is rising due to factors like migration and globalization. The aim of this work was to investigate CL frequency in Switzerland and identify clinical and histopathological difficulties in diagnosing CL in a non-endemic country., Patients and Methods: This retrospective study evaluated the clinical and histopathological characteristics of all CL cases from two dermatopathology laboratories between 2000 and 2022. Skin biopsies were histopathologically reviewed using HE, Giemsa, and immunohistochemical stain for CD1a and a specific Leishmania antibody (LA). PCR to detect Leishmania DNA was performed if sufficient tissue was available., Results: 42 cases (27 m, 15 f) were included. The correct clinical diagnosis of CL was only made in 15 (35.7%) cases. In seven (16.6%) cases, CL was missed in the initial histopathologic evaluation. Two main histopathological patterns were observed: granulomatous and pseudolymphomatous. Immunohistochemical staining with CD1a and Leishmania-specific antibody was positive in 91% and 80% of cases, respectively. Leishmania PCR was positive in 25 of 26 cases, mainly detecting Old World species., Conclusions: CL is rare in Switzerland and often misdiagnosed clinically and histopathologically. CD1a and specific Leishmania antibody stainings are useful. CL should be considered in non-healing ulcers, even without a history of travel to endemic areas., (© 2024 Deutsche Dermatologische Gesellschaft (DDG).)

Background: Semitranslucency, defined as a smooth, jelly-like area with varied, near-skin-tone color, can indicate a diagnosis of basal cell carcinoma (BCC) with high specificity. This study sought to analyze potential areas of semitranslucency with histogram-derived texture and color measures to discriminate BCC from non-semitranslucent areas in non-BCC skin lesions., Methods: For 210 dermoscopy images, the areas of semitranslucency in 42 BCCs and comparable areas of smoothness and color in 168 non-BCCs were selected manually. Six color measures and six texture measures were applied to the semitranslucent areas of the BCC and the comparable areas in the non-BCC images., Results: Receiver operating characteristic (ROC) curve analysis showed that the texture measures alone provided greater separation of BCC from non-BCC than the color measures alone. Statistical analysis showed that the four most important measures of semitranslucency are three histogram measures: contrast, smoothness, and entropy, and one color measure: blue chromaticity. Smoothness is the single most important measure. The combined 12 measures achieved a diagnostic accuracy of 95.05% based on area under the ROC curve., Conclusion: Texture and color analysis measures, especially smoothness, may afford automatic detection of BCC images with semitranslucency.