| Title | Dermoscopic diagnosis by a trained clinician vs. a clinician with minimal dermoscopy training vs. computer-aided diagnosis of 341 pigmented skin lesions: a comparative study. | | Author(s) | Piccolo D, Ferrari A, Peris K, Diadone R, Ruggeri B, Chimenti S | | Institution | Department of Dermatology, University of L'Aquila, Via Vetoio - Coppito 2, 67100 L'Aquila, Italy. | | Source | Br J Dermatol 2002 Sep; 147(3):481-6. | | MeSH | Adolescent
Adult
Aged
Aged, 80 and over
Child
Child, Preschool
Clinical Competence
Comparative Study
Dermatology
Diagnosis, Computer-Assisted
Diagnosis, Differential
Female
Humans
Image Processing, Computer-Assisted
Male
Melanoma
Microscopy, Video
Middle Aged
Neural Networks (Computer)
Nevus, Pigmented
Predictive Value of Tests
Reproducibility of Results
Research Support, Non-U.S. Gov't
Sensitivity and Specificity
Skin Neoplasms
| | Abstract | BACKGROUND: In the last few years digital dermoscopy has been introduced as an additional tool to improve the clinical diagnosis of pigmented skin lesions.
OBJECTIVE: To evaluate the validity of digital dermoscopy by comparing the diagnoses of a dermatologist experienced in dermoscopy (5 years of experience) with those of a clinician with minimal training in this field, and then comparing these results with those obtained using computer-aided diagnoses.
METHODS: Three hundred and forty-one pigmented melanocytic and non-melanocytic skin lesions were included. All lesions were surgically excised and histopathologically examined. Digital dermoscopic images of all lesions were framed and analysed using software based on a trained artificial neural network. Cohen's kappa statistic was calculated to assess the validity with regard to the correct diagnoses of melanoma and non-melanoma.
RESULTS: Sensitivity was high for the experienced dermatologist and the computer (92%) and lower for the inexperienced clinician (69%). Specificity of the diagnosis by the experienced dermatologist was higher (99%) than that of the inexperienced clinician (94%) and the computer assessment (74%). Notably, computer analysis gave a higher number of false positives (26%) compared with the experienced dermatologist (0.6%) and the inexperienced clinician (5.5%).
CONCLUSIONS: Our results indicate that analysis either by a trained dermatologist or an artificial neural network-trained computer can improve the diagnostic accuracy of melanoma compared with that of an inexperienced clinician and that the computer diagnosis might represent a useful tool for the screening of melanoma, particularly at centres not experienced in dermoscopy. | | Language | eng | | Pub Type(s) | Evaluation Studies
Journal Article
| | PubMed ID | 12207587 |
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