BACKGROUND/ PURPOSE: Many differences in color, shape and dimension exist between different moles even in the same individual. Major differences might be accounted for anatomical location, genetic factors and by environmental factors, mainly sunlight exposure. Therefore, it would be of great value, when evaluating skin lesions, to take into account the degree of intra- and inter-variability of several diagnostic parameters. In order to assess the morphologic and chromatic differences between lesions belonging to different patients and between lesions belonging to the same individual, we examined objective digital parameters obtained with dermatoscopic analysis, using the DBDermo MIPS system (BIO MIPS Engineering, S.R.L, siena, Italy). METHODS: The automatic classifier inside the software is based on a 'match by similarity' algorithm, based on the measurement of the Euclidean distances of all variables considered from the reference image. Two-hundred and four clinically benign pigmented lesion, belonging to 18 patients were examined, stored and automatically processed. For each lesion objective parameters related to geometry, color and texture were automatically evaluated. RESULTS: We found skin color (healthy skin) is objectively different from subject to subject and the lesion color is more similar among different lesions of the same patient than among lesions belonging to different individuals both in their darkest and slightly dark component. We also observed that lesion dimensions are individual correlates, i.e. the probability for a lesion to be large is higher when the other, in the same patient, is large. CONCLUSION: Many parameters of pigmented skin lesions evaluated by digital dermoscopy analysis are similar in the same patient and different from those belonging to different individuals. This indicates that, when considering a lesion, we should take into account the peculiar patient's characteristics.
BACKGROUND/ PURPOSE: Many differences in color, shape and dimension exist between different moles even in the same individual. Major differences might be accounted for anatomical location, genetic factors and by environmental factors, mainly sunlight exposure. Therefore, it would be of great value, when evaluating skin lesions, to take into account the degree of intra- and inter-variability of several diagnostic parameters. In order to assess the morphologic and chromatic differences between lesions belonging to different patients and between lesions belonging to the same individual, we examined objective digital parameters obtained with dermatoscopic analysis, using the DBDermo MIPS system (BIO MIPS Engineering, S.R.L, siena, Italy). METHODS: The automatic classifier inside the software is based on a 'match by similarity' algorithm, based on the measurement of the Euclidean distances of all variables considered from the reference image. Two-hundred and four clinically benign pigmented lesion, belonging to 18 patients were examined, stored and automatically processed. For each lesion objective parameters related to geometry, color and texture were automatically evaluated. RESULTS: We found skin color (healthy skin) is objectively different from subject to subject and the lesion color is more similar among different lesions of the same patient than among lesions belonging to different individuals both in their darkest and slightly dark component. We also observed that lesion dimensions are individual correlates, i.e. the probability for a lesion to be large is higher when the other, in the same patient, is large. CONCLUSION: Many parameters of pigmented skin lesions evaluated by digital dermoscopy analysis are similar in the same patient and different from those belonging to different individuals. This indicates that, when considering a lesion, we should take into account the peculiar patient's characteristics.
Authors: William V Stoecker; Mark Wronkiewiecz; Raeed Chowdhury; R Joe Stanley; Jin Xu; Austin Bangert; Bijaya Shrestha; David A Calcara; Harold S Rabinovitz; Margaret Oliviero; Fatimah Ahmed; Lindall A Perry; Rhett Drugge Journal: Comput Med Imaging Graph Date: 2010-10-30 Impact factor: 4.790