The performance of solarscan : an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma

Menzies, Scott W., Bischof, Leanne, Talbot, Hugues, Avramidis, Michelle, Wong, Livian, Lo, Sing Kai, Mackellar, Geoffrey, Skladnev, Victor, McCarthy, William, Kelly, John, Cranney, Brad, Lye, Peter, Rabinovitz, Harold, Oliveiro, Margaret, Blum, Andreas, Virol, Alexandra, De`Ambrosis, Brian, McCleod, Roderick, Koga, Hiroshi, Grin, Caron, Braun, Ralph and Johr, Robert 2005, The performance of solarscan : an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma, Archives of dermatology, vol. 141, no. 11, pp. 1388-1396.

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Title The performance of solarscan : an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma
Author(s) Menzies, Scott W.
Bischof, Leanne
Talbot, Hugues
Avramidis, Michelle
Wong, Livian
Lo, Sing Kai
Mackellar, Geoffrey
Skladnev, Victor
McCarthy, William
Kelly, John
Cranney, Brad
Lye, Peter
Rabinovitz, Harold
Oliveiro, Margaret
Blum, Andreas
Virol, Alexandra
De`Ambrosis, Brian
McCleod, Roderick
Koga, Hiroshi
Grin, Caron
Braun, Ralph
Johr, Robert
Journal name Archives of dermatology
Volume number 141
Issue number 11
Start page 1388
End page 1396
Publisher American Medical Association
Place of publication Chicago, Ill.
Publication date 2005-11
ISSN 0003-987X
Summary Objective To describe the diagnostic performance of SolarScan (Polartechnics Ltd, Sydney, Australia), an automated instrument for the diagnosis of primary melanoma.

Design Images from a data set of 2430 lesions (382 were melanomas; median Breslow thickness, 0.36 mm) were divided into a training set and an independent test set at a ratio of approximately 2:1. A diagnostic algorithm (absolute diagnosis of melanoma vs benign lesion and estimated probability of melanoma) was developed and its performance described on the test set. High-quality clinical and dermoscopy images with a detailed patient history for 78 lesions (13 of which were melanomas) from the test set were given to various clinicians to compare their diagnostic accuracy with that of SolarScan.

Setting Seven specialist referral centers and 2 general practice skin cancer clinics from 3 continents. Comparison between clinician diagnosis and SolarScan diagnosis was by 3 dermoscopy experts, 4 dermatologists, 3 trainee dermatologists, and 3 general practitioners.

Patients Images of the melanocytic lesions were obtained from patients who required either excision or digital monitoring to exclude malignancy.

Main Outcome Measures Sensitivity, specificity, the area under the receiver operator characteristic curve, median probability for the diagnosis of melanoma, a direct comparison of SolarScan with diagnoses performed by humans, and interinstrument and intrainstrument reproducibility.

Results The melanocytic-only diagnostic model was highly reproducible in the test set and gave a sensitivity of 91% (95% confidence interval [CI], 86%-96%) and specificity of 68% (95% CI, 64%-72%) for melanoma. SolarScan had comparable or superior sensitivity and specificity (85% vs 65%) compared with those of experts (90% vs 59%), dermatologists (81% vs 60%), trainees (85% vs 36%; P =.06), and general practitioners (62% vs 63%). The intraclass correlation coefficient of intrainstrument repeatability was 0.86 (95% CI, 0.83-0.88), indicating an excellent repeatability. There was no significant interinstrument variation (P = .80).

Conclusions SolarScan is a robust diagnostic instrument for pigmented or partially pigmented melanocytic lesions of the skin. Preliminary data suggest that its performance is comparable or superior to that of a range of clinician groups. However, these findings should be confirmed in a formal clinical trial.
Language eng
Field of Research 100499 Medical Biotechnology not elsewhere classified
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2005, American Medical Association
Persistent URL http://hdl.handle.net/10536/DRO/DU:30009321

Document type: Journal Article
Collection: Faculty of Health
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