BACKGROUND: The diagnosis of melanomas at an early stage is associated with improved survival, so the recognition of changes in pigmented skin lesions over time is important. We have developed a computer imaging system with the aim of assisting clinicians in differentiating early melanomas from benign pigmented skin lesions. The objective of this study was to investigate the system's reliability over time in measuring diagnostic characteristics of pigmented skin lesions, including their color, size, shape, and distinctness of boundary. METHODS: We captured video images of 5 lesions, all larger than 2 mm in greatest dimension, on each of 66 Australian adolescents on 2 occasions approximately 1 month apart. Features extracted by computer image analysis included area, perimeter, and regularity of outline of the lesions, the mean and standard deviation of reflectance at red, green, and blue wavelengths, and the mean and standard deviation of the gradients of red, green, and blue reflectance at the lesion boundary. RESULTS: All measurements showed moderate to high reliability (intraclass correlation coefficients 0.66-0.94), except for the standard deviations of the color gradients, whose reliability improved to moderate levels (0.68-0.71) when the mean of 5 lesions was considered. For most outcomes, reasonable within subject reliability was achieved when five lesions per subject were measured. CONCLUSIONS: These results, in combination with previous work demonstrating the reasonable ability of this computer imaging system to discriminate between malignant melanomas and other pigmented lesions, indicates that the system has the potential to become a useful tool for clinicians in following people with pigmented lesions over time to detect early malignant changes.
BACKGROUND: The diagnosis of melanomas at an early stage is associated with improved survival, so the recognition of changes in pigmented skin lesions over time is important. We have developed a computer imaging system with the aim of assisting clinicians in differentiating early melanomas from benign pigmented skin lesions. The objective of this study was to investigate the system's reliability over time in measuring diagnostic characteristics of pigmented skin lesions, including their color, size, shape, and distinctness of boundary. METHODS: We captured video images of 5 lesions, all larger than 2 mm in greatest dimension, on each of 66 Australian adolescents on 2 occasions approximately 1 month apart. Features extracted by computer image analysis included area, perimeter, and regularity of outline of the lesions, the mean and standard deviation of reflectance at red, green, and blue wavelengths, and the mean and standard deviation of the gradients of red, green, and blue reflectance at the lesion boundary. RESULTS: All measurements showed moderate to high reliability (intraclass correlation coefficients 0.66-0.94), except for the standard deviations of the color gradients, whose reliability improved to moderate levels (0.68-0.71) when the mean of 5 lesions was considered. For most outcomes, reasonable within subject reliability was achieved when five lesions per subject were measured. CONCLUSIONS: These results, in combination with previous work demonstrating the reasonable ability of this computer imaging system to discriminate between malignant melanomas and other pigmented lesions, indicates that the system has the potential to become a useful tool for clinicians in following people with pigmented lesions over time to detect early malignant changes.
Authors: R Joe Stanley; William V Stoecker; Randy H Moss; Harold S Rabinovitz; Armand B Cognetta; Giuseppe Argenziano; H Peter Soyer Journal: Skin Res Technol Date: 2008-11 Impact factor: 2.365
Authors: R Joe Stanley; Randy Hays Moss; William Van Stoecker; Chetna Aggarwal Journal: Comput Med Imaging Graph Date: 2003 Sep-Oct Impact factor: 4.790