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. 2016 Mar;9(3):36-8.
Epub 2016 Mar 1.

Correlation Between the Evaluation of Pigmented Lesions by a Multi-spectral Digital Skin Lesion Analysis Device and the Clinical and Histological Features of Melanoma

Richard R Winkelmann  1 , Darrell S Rigel  2 , Laura Ferris  3 , Arthur Sober  4 , Natalie Tucker  5 , Clay J Cockerell  6
Affiliations

Correlation Between the Evaluation of Pigmented Lesions by a Multi-spectral Digital Skin Lesion Analysis Device and the Clinical and Histological Features of Melanoma

Richard R Winkelmann et al. J Clin Aesthet Dermatol. 2016 Mar.

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.

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References

    1. [March 9, 2015]. http://www.who.int/uv/health/uv_health2/en/index1.html “Health Effects of UV Radiation.” Ultraviolet radiation and the INTERSUN Programme. 2015. World Health Organization. Available at:
    1. [March 9, 2015.]. http://www.cancer.orgacs/groups/content/@epidemiologysurveil ance/docume... American Cancer Society Cancer Facts and Figures. Available at:
    1. Gutkowicz-Krusin D, Elbaum M, Jacobs A, et al. Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind multispectral digital dermoscope. Melanoma Res. 2000;10(6):563–570-E7. - PubMed
    1. Rigel DS, Roy M, Yoo J, et al. Impact of guidance from a computer-aided multispectral digital skin lesion analysis device on decision to biopsy lesions clinically suggestive of melanoma. Arch Dermatol. 2012;148(4):541–543. - PubMed
    1. Monheit G, Cognetta AB, Ferris L, et al. The performance of MelaFind: a prospective multicenter study. Arch Dermatol. 2010;147(2):188–194. - PubMed

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