title: Digital computer analysis of dermatoscopical images of 260 melanocytic skin lesions; perimeter/area ratio for the differentiation between malignant melanomas and melanocytic nevi.
abstract: BACKGROUND
  Digital computer analysis of dermatoscopical images has been reported to facilitate the differential diagnosis of pigmented skin lesions in recent years.
  
  
  OBJECTIVE
  The aim of our study was to perform digital computer analysis of a set of different melanocytic lesions and compare the objective results.
  
  
  METHODS
  The set of 260 melanocytic lesions (150 excised difficult cases (46 melanomas, 47 atypical nevi, 57 common nevi and 110 unexcised common nevi) was automatically analysed by the digital dermatoscopical system microDERM. We searched for differences in asymmetry, size, compactness and colour distribution. Perimeter/area ratio was calculated.
  
  
  RESULTS
  The perimeter/area ratio was detected as the most important criterion for differentiation between malignant and benign melanocytic lesions (sensitivity 91.3% and specificity 90.7% for malignant melanomas vs. all benign nevi; sensitivity 91.3% and specificity 80.8% for melanomas vs. clinically atypical nevi). Differences in size of the lesion, shape and asymmetry of colour were found and statistically verified. Using step-wise logistic regression the formula for calculation of probability of malignant nature of every analysed lesion was constructed.
  
  
  CONCLUSIONS
  The perimeter/area ratio is a simple parameter for the differential diagnosis of melanocytic skin lesions.
authors.affiliation: Department of Dermatology, Faculty of Medicine, Charles University, Pilsen, Czech Republic. fikrle@fnplzen.cz
authors.forename: T
authors.initials: T
authors.lastname: Fikrle
authors.forename: K
authors.initials: K
authors.lastname: Pizinger
mesh_terms: D003937:Diagnosis, Differential; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008545:Melanoma / Q000175:diagnosis*; D009506:Nevus / Q000175:diagnosis*; D012878:Skin Neoplasms / Q000175:diagnosis*