Computer-aided dermoscopy for diagnosis of melanoma

We studied 122 pigmented skin lesions which were referred for diagnostic evaluation or cosmetic reasons. Each lesion was examined by two clinicians with naked eyes and all of their clinical diagnostic considerations were recorded. The lesions were analyzed using a microDERM？ dermoscopy unit. The output value of the software for each lesion was a score between 0 and 10. All of the lesions were excised and examined histologically.Histopathological examination revealed melanoma in six lesions. Considering only the most likely clinical diagnosis, sensitivity and specificity of clinical examination for diagnosis of melanoma were 83% and 96%, respectively. Considering all clinical diagnostic considerations, the sensitivity and specificity were 100% and 89%. Choosing a cut-off point of 7.88 for dermoscopy score, the sensitivity and specificity of the score for diagnosis of melanoma were 83% and 96%, respectively. Setting the cut-off point at 7.34, the sensitivity and specificity were 100% and 90%.The diagnostic accuracy of the dermoscopy system was at the level of clinical examination by dermatologists with naked eyes. This system may represent a useful tool for screening of melanoma, particularly at centers not experienced in the field of pigmented skin lesions.The incidence of melanoma is much lower in Asia than in western countries [1]. Clinicians sometimes misdiagnose early melanoma especially in areas with lower incidence of disease [2]. Because advanced cutaneous melanoma is still incurable, early detection by means of accurate screening is an important step towards a reduction in mortality.Recently, computer-aided dermoscopy using artificial neural networks (ANNs) has been reported to be an accurate tool for the evaluation of pigmented skin lesions (PSLs) [3-5].To our knowledge, the accuracy of such system for diagnosis of PSL has not been demonstrated in the Middle East, where most of the patients have Fitzpatrick skin type III-IV. We set out to determine the sensi