Impact of digital dermoscopy analysis on the decision to follow up or to excise a pigmented skin lesion: a multicentre study.

BACKGROUND: The quality of early malignant melanoma (MM) diagnosis is dependent on the experience of dermatologists, tools like dermoscopy and histopathology, and awareness and education of the studied population. Does a higher rate of excision of pigmented skin lesions (PSL) increase the rate of detected melanomas? MATERIAL AND METHODS: The DB-MIPS objective tool, able to evaluate mathematical defined variables, has been used to verify the variability of measurements among PSL stored by five different centres located in Italy, Switzerland, and Germany. RESULTS: The objective analysis showed low differences in terms of moles' features among the different groups, arguing for robustness of the dermatological patient's PSL inspection. Differences in terms of false positives and predictive positive values have been detected. The tendency to follow up a lesion was proportional to the percentage of thin MM (<0.75 mm tumour thickness), while the interventism was proportional to the percentage of dysplastic moles. Similar percentage of thin melanoma has been observed in all the centres, indicating a standardization in early diagnosing among experienced dermatologists. The main difference among the centres was their mode of action, i.e. to follow up or remove suspicious PSL. CONCLUSION: Interventism depends neither on the geographic site nor on the features of the observed moles. Higher removal rates do not correspond to higher MM detections: this means that an in-depth knowledge of melanoma patterns is required and follow-up of suspicious moles is highly suggested.

Melanoma computer-aided diagnosis: reliability and feasibility study.

BACKGROUND: Differential diagnosis of melanoma from melanocytic nevi is often not straightforward. Thus, a growing interest has developed in the last decade in the automated analysis of digitized images obtained by epiluminescence microscopy techniques to assist clinicians in differentiating early melanoma from benign skin lesions. PURPOSE: The aim of this study was to evaluate diagnostic accuracy provided by different statistical classifiers on a large set of pigmented skin lesions grabbed by four digital analyzers located in two different dermatological units. EXPERIMENTAL DESIGN: Images of 391 melanomas and 449 melanocytic nevi were included in the study. A linear classifier was built by using the method of receiver operating characteristic curves to identify a threshold value for a fixed sensitivity of 95%. A K-nearest-neighbor classifier, a nonparametric method of pattern recognition, was constructed using all available image features and trained for a sensitivity of 98% on a large exemplar set of lesions. RESULTS: On independent test sets of lesions, the linear classifier and the K-nearest-neighbor classifier produced a mean sensitivity of 95% and 98% and a mean specificity of 78% and of 79%, respectively. CONCLUSIONS: In conclusion, our study suggests that computer-aided differentiation of melanoma from benign pigmented lesions obtained with DB-Mips is feasible and, above all, reliable. In fact, the same instrumentations used in different units provided similar diagnostic accuracy. Whether this would improve early diagnosis of melanoma and/or reducing unnecessary surgery needs to be demonstrated by a randomized clinical trial.