Richard R Winkelmann1, Darrell S Rigel2, Laura Ferris3, Arthur Sober4, Natalie Tucker5, Clay J Cockerell6. 1. Rigel Dermatology, New York, New York; 2. Department of Dermatology, New York University, New York, New York; 3. Department of Dermatology, University of Pittsburgh, Pittsburgh, Pennsylvania; 4. Harvard Medical School, Boston, Massachusetts; 5. MELA Sciences Inc., Irvington, New York; 6. University of Texas Southwestern Medical Center, Dallas, Texas.
Abstract
OBJECTIVE: To correlate Multi-spectral Digital Skin Lesion Analysis classifier scores with histopathological severity of pigmented lesions and clinical features of melanoma. DESIGN: Classifier scores were computed for 1,632 skin lesions. Dermatologists evaluated the same lesions for Asymmetry, Border Irregularity, Color variegation, Diameter >6mm, Evolution, Patient's Concern, Regression, and/or "Ugly Duckling" sign. Classifier scores were correlated to the number of clinical risk features and for six histopathological severity levels of pigmented lesions. MEASUREMENTS: Average classifier score, Welch's t-test, and chi-square analysis. RESULTS: Melanomas had higher mean classifier scores (3.5) than high-grade dysplastic nevi (2.7, p=0.002), low-grade dysplastic nevi (1.7, p<0.0001), non-dysplastic nevi (1.6, p<0.0001), and benign non-melanocytic lesions (2.0, p<0.0001). Classifier score and the number of clinical risk characteristics directly correlated (Pearson coefficient 0.32, p<0.0001). CONCLUSION: Correlation of classifier scores to clinical and histological melanoma features supports the effectiveness of Multi-spectral Digital Skin Lesion Analysis in assessing the risk of pigmented lesions requiring biopsy. Optimizing outcomes of dermatologist decisions to biopsy suspicious pigmented lesions may be enhanced utilizing Multi-spectral Digital Skin Lesion Analysis.
OBJECTIVE: To correlate Multi-spectral Digital Skin Lesion Analysis classifier scores with histopathological severity of pigmented lesions and clinical features of melanoma. DESIGN: Classifier scores were computed for 1,632 skin lesions. Dermatologists evaluated the same lesions for Asymmetry, Border Irregularity, Color variegation, Diameter >6mm, Evolution, Patient's Concern, Regression, and/or "Ugly Duckling" sign. Classifier scores were correlated to the number of clinical risk features and for six histopathological severity levels of pigmented lesions. MEASUREMENTS: Average classifier score, Welch's t-test, and chi-square analysis. RESULTS:Melanomas had higher mean classifier scores (3.5) than high-grade dysplastic nevi (2.7, p=0.002), low-grade dysplastic nevi (1.7, p<0.0001), non-dysplastic nevi (1.6, p<0.0001), and benign non-melanocytic lesions (2.0, p<0.0001). Classifier score and the number of clinical risk characteristics directly correlated (Pearson coefficient 0.32, p<0.0001). CONCLUSION: Correlation of classifier scores to clinical and histological melanoma features supports the effectiveness of Multi-spectral Digital Skin Lesion Analysis in assessing the risk of pigmented lesions requiring biopsy. Optimizing outcomes of dermatologist decisions to biopsy suspicious pigmented lesions may be enhanced utilizing Multi-spectral Digital Skin Lesion Analysis.
Authors: R P Braun; D Gutkowicz-Krusin; H Rabinovitz; A Cognetta; R Hofmann-Wellenhof; V Ahlgrimm-Siess; D Polsky; M Oliviero; I Kolm; P Googe; R King; V G Prieto; L French; A Marghoob; M Mihm Journal: Dermatology Date: 2012-03-20 Impact factor: 5.366
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Authors: Lavinia Ferrante di Ruffano; Yemisi Takwoingi; Jacqueline Dinnes; Naomi Chuchu; Susan E Bayliss; Clare Davenport; Rubeta N Matin; Kathie Godfrey; Colette O'Sullivan; Abha Gulati; Sue Ann Chan; Alana Durack; Susan O'Connell; Matthew D Gardiner; Jeffrey Bamber; Jonathan J Deeks; Hywel C Williams Journal: Cochrane Database Syst Rev Date: 2018-12-04