Ugly Duckling Sign as a Major Factor of Efficiency in Melanoma Detection.

Importance: Understanding the contribution of the ugly duckling sign (a nevus that is obviously different from the others in a given individual) in intrapatient comparative analysis (IPCA) of nevi may help improve the detection of melanoma. Objectives: To assess the agreement of dermatologists on identification of the ugly duckling sign and estimate the contribution of IPCA to the diagnosis of melanoma. Design, Setting, and Participants: The same 2089 digital images of the nevi of a sample of 80 patients (mean age, 42 years [range, 19-80 years]; 33 men and 47 women), as well as 766 dermoscopic images from a subset of 30 patients (mean age, 40 years [range, 21-75 years]; 12 men and 18 women), were randomly presented to the same 9 dermatologists for blinded assessment from September 22, 2011, to April 1, 2013. The first experiment was designed to mimic an IPCA situation, with images of all nevi of each patient shown to the dermatologists, who were asked to identify ugly duckling nevi (UDN). The second experiment was designed to mimic a lesion-focused analysis to identify morphologically suspicious nevi. Data analysis was conducted from November 1, 2012, to June 1, 2013. Main Outcomes and Measures: Number of nevi labeled UDN and morphologically suspicious nevi, specificity of lesion-focused analysis and IPCA, and number of nevi identified for biopsy. Results: Of the 2089 clinical images of nevi from 80 patients (median number of nevi per patient, 26 [range, 8-81]) and 766 dermoscopic images (median number of nevi per patient, 19 [range, 8-81]), all melanomas were labeled UDN and as morphologically suspicious nevi by the 9 dermatologists. The median number of UDN detected per patient was 0.8 among the clinical images of nevi (mean, 1.0; range, 0.48-2.03) and 1.26 among the dermoscopic images (mean, 1.4; range, 1.00-2.06). The propensity to consider more or fewer nevi as having ugly duckling signs was independent of the presentation (clinical or dermoscopic). The agreement among the dermatologists regarding UDN was lower with dermoscopic images (mean pairwise agreement, 0.53 for clinical images and 0.50 for dermoscopic images). The specificity of IPCA was 0.96 for clinical images and 0.95 for dermoscopic images vs 0.88 and 0.85, respectively, for lesion-focused analysis. When both IPCA and lesion-focused analyses were used, the number of nevi considered for biopsy was reduced by a factor of 6.9 compared with lesion-focused analysis alone. Conclusions and Relevance: Intrapatient comparative analysis is of major importance to the effectiveness of the diagnosis of melanoma. Introducing IPCA using the ugly duckling sign in computer-assisted diagnosis systems would be expected to improve performance.

Evidence of a limited intra-individual diversity of nevi: intuitive perception of dominant clusters is a crucial step in the analysis of nevi by dermatologists.

Although nevi are highly polymorphous, it has been suggested that each individual is characterized by only a few dominant patterns of nevi. Therefore, a nevus that does not fit in with these patterns, the "ugly duckling" nevus, is suspicious. Our objective was to study the intra-individual diversity of nevi, using human ability to build "perceived similarity clusters" (PSCs). Nine dermatologists had to cluster all the nevi of 80 patients into PSCs, at the clinical scale (CS) and at the dermoscopic scale (DS) (subset of 30 patients). Nine novices did the same in a subset of 11 patients. The experts identified a mean of 2.8 PSCs/patient at CS. Concordance was higher between experts than between novices at CS and at DS. Despite a trend for more PSCs at DS than at CS, the number of nevus patterns per patient remained low, regardless of the number of nevi. Inter-expert concordance permits a consensus representation of nevus diversity in each individual. Nevus diversity is limited in each patient and constitutes an individual reference system, which we can intuitively perceive. This reference is probably crucial for nevus analysis and melanoma detection and opens perspectives for computer-aided diagnostics.