Modification of a melanoma discrimination index derived from hyperspectral data: A clinical trial conducted in 2 centers between March 2011 and December 2013

T. Nagaoka*, Y. Kiyohara, H. Koga, A. Nakamura, T. Saida, T. Sota

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

Background: The morphology of pigmented skin lesions (PSLs) is predominantly a result of varying concentrations and distributions of pigmented molecules such as melanin and hemoglobin. Based on these differences and the fact that their information is contained in cutaneous spectra, a hyperspectral imager (HSI) for pigmented melanoma and a single discrimination index derived from the resultant hyperspectral data are proposed. Objective: To develop and evaluate a new discrimination index for melanomas, compared to the previous index. Methods: A HSI, which is convenient for both patients and clinicians, was newly developed and used in a clinical trial conducted in 2 centers with 80 patients with primary lesions and 17 volunteers between March 2011 and December 2013. There were 24 melanomas and 110 other PSLs. A previously proposed discrimination index was used without modifications. A new index, which emphasized the essential features of melanoma, was proposed, and its performance was examined. For each index, a threshold value was set to minimize the average value of the false positive and false negative fractions. The performances of both indices were compared. Results: The sensitivity and specificity of the old index were 75% and 97%, respectively, while those of the new index were 96% and 87%. Conclusion: The new index had a higher sensitivity and adequate specificity, indicating that it is more useful than the old index.

Original languageEnglish
Pages (from-to)278-283
Number of pages6
JournalSkin Research and Technology
Volume21
Issue number3
DOIs
Publication statusPublished - 2015 Aug 1

Keywords

  • Computer-assisted diagnosis
  • Early detection of melanoma
  • Melanoma
  • Spectrum analysis

ASJC Scopus subject areas

  • Dermatology

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