Diagnostic informativeness of compressed digital epiluminescence microscopy images of pigmented skin lesions compared with photographs.
Epiluminescence microscopy (ELM) is a useful method for improved diagnostic accuracy in early cutaneous melanoma. Conventional photographs of ELM images are commonly used for clinical research and documentation. Electronic images have advantages compared with photographs and are essential for medical informatics, computerized learning and telemedicine. Compression of electronic images allows a reduction in volume of data, but significant image deterioration may occur at high compression rates. We sought to study the diagnostic informativeness of compressed digital ELM images compared with conventional photographs. Fifty photographs of pigmented skin lesions, including 23 melanomas, were presented to eight dermatologists as photographic slides and as digital images with 30:1 Joint Photographic Experts Group (JPEG) compression. The diagnostic performance of the media and the readers was described in terms of sensitivity, specificity and areas under receiver operating characteristic curves (AUC). Agreement between the readings of the two types of media regarding the presence or absence of ELM criteria was assessed using kappa (kappa) statistics. The mean AUC was 0.81 (95% confidence interval [CI] = 0.73-0.90) for slides and 0.81 (95% CI = 0.72-0.90; P = 0.89) for digital images. Agreement between the readings of the two types of media regarding the presence or absence of ELM criteria ranged from kappa = 0.55 (95% CI = 0.22-0.88) for grey-blue area to kappa = 0.89 (95% CI = 0.74-1.00) for radial streaming. In conclusion, digital ELM images with 30:1 JPEG compression appear to be as informative as photographic slides when used to differentiate between melanoma and non-melanoma.
Kittler
H
H
Department of Dermatology, University of Vienna Medical School, Austria.
Seltenheim
M
M
Pehamberger
H
H
Wolff
K
K
Binder
M
M
D019540:Area Under Curve; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007642:Keratosis / Q000175:diagnosis* / Q000473:pathology; D008492:Medical Informatics Computing; D008545:Melanoma / Q000175:diagnosis* / Q000473:pathology; D008853:Microscopy / Q000379:methods*; D009508:Nevus, Pigmented / Q000175:diagnosis / Q000473:pathology; D010784:Photomicrography; D012680:Sensitivity and Specificity; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology; D017216:Telemedicine / Q000379:methods