Medizinische Universität Graz Austria/Österreich - Forschungsportal - Medical University of Graz

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SHR Neuro Krebs Kardio Lipid

Rubegni, P; Cevenini, G; Nami, N; Argenziano, G; Saida, T; Burroni, M; Quaglino, P; Bono, R; Hofmann-Wellenhof, R; Fimiani, M; .
A simple scoring system for the diagnosis of palmo-plantar pigmented skin lesions by digital dermoscopy analysis.
J EUR ACAD DERMATOL VENEREOL. 2013; 27(3): e312-e319.
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Autor/innen der Med Uni Graz:
Hofmann-Wellenhof Rainer

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Background Many research groups have recently developed equipments and statistical methods enabling pattern classification of pigmented skin lesions. To differentiate between benign and malignant ones, the mathematical extraction of digital patterns together with the use of appropriate statistical approaches is a challenging task. Objective To design a simple scoring model that provides accurate classification of benign and malignant palmo-plantar pigmented skin lesions, by evaluation of parameters obtained by digital dermoscopy analysis (DDA). Patients and Methods In the present study we used a digital dermoscopy analyser to evaluate a series of 445 palmo-plantar melanocytic skin lesion images (25 melanomas 420 nevi). Area under the receiver operator curve, sensitivity and specificity were calculated to evaluate the diagnostic performance of our scoring model for the differentiation of benign and malignant palmo-plantar melanocytic lesions. Results Model performance reached a very high value (0.983). The DDA parameters selected by the model that proved statistically significant were: area, peripheral dark regions, total imbalance of colours, entropy, dark area and red and blue multicomponent. When all seven model variables were used in a multivariate mode, setting sensitivity at 100% to avoid false negatives, we estimated a minimum specificity of about 80%. Conclusions Simplicity of use and effectiveness of implementation are important requirements for the success of quantitative methods in routine clinical practice. Scoring systems meet these requirements. Their outcomes are accessible in real time without the use of any data processing system, thus allowing decisions to be made quickly and effectively.

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