Diagnostic efficiency of the main dermatoscopic symptoms and algorithms for detecting skin melanoma

Abstract

AIM: to assess the diagnostic accuracy of the main dermatoscopic signs and algorithms used to diagnose skin melanoma. MATERIALS AND METHODS: To assess the diagnostic effectiveness of the performed dermatoscopy in detecting skin melanoma, the main dermatoscopic signs that occur in this disease were identified: atypical pigment network, atypical globules, asymmetry of pigmentation and structure, asymmetric stripes, asymmetric zones of hyperpigmentation (spots), blue-white (white-blue) veil, graininess, scar-like foci of depigmentation, white shiny stripes, negative pigment network. The study was carried out based on the analysis of 34 archival dermatoscopic images of melanocytic skin lesions with a morphologically verified diagnosis (11 melanomas and 23 melanocytic nevi). In addition, a comparison was made of the indicators of the diagnostic efficiency of two main dermatoscopic algorithms used in the diagnosis of skin melanoma: the algorithm by 3 signs and by 7 signs. For this, 186 archived dermatoscopic images of melanocytic skin lesions were analyzed. All patients included in the study were examined and treated at the clinic for skin and venereal diseases in the period from 2015 to 2019. The study was carried out using a HEINE DELTA 20 Plus dermatoscope in immersion mode and in cross-polarization. RESULTS: The following dermatoscopic features had the highest diagnostic efficiency for the diagnosis of skin melanoma: blue-white veil (86.8%), asymmetry of pigmentation and structure (82.6%), and white shiny stripes (72.8%). The diagnostic efficiency of the 3 signs algorithm was 93.0%, the 7 signs algorithm 90.5%. CONCLUSION: Diagnostic algorithms for confirming melanoma can be successfully used by both general practitioners and medical specialists (dermatologists, oncologists). In this case, it is preferable to use the three signs algorithm at the initial admission of patients as a screening option, and the seven-signs algorithm by experienced specialists in the field of dermatoscopy to confirm the diagnosis (4 figures, 3 tables, bibliography: 11 refs).