Optical spectroscopy as a method for skin cancer risk assessment

Eladio Rodriguez-Diaz, Danielle Manolakos, Holly Christman*, Michael A. Bonning, John K. Geisse, Ousama M. A'Amar, David J. Leffell, Irving J. Bigio

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)


    Skin cancer is the most prevalent cancer, and its assessment remains a challenge for physicians. This study reports the application of an optical sensing method, elastic scattering spectroscopy (ESS), coupled with a classifier that was developed with machine learning, to assist in the discrimination of skin lesions that are concerning for malignancy. The method requires no special skin preparation, is non-invasive, easy to administer with minimal training, and allows rapid lesion classification. This novel approach was tested for all common forms of skin cancer. ESS spectra from a total of 1307 lesions were analyzed in a multi-center, non-randomized clinical trial. The classification algorithm was developed on a 950-lesion training dataset, and its diagnostic performance was evaluated against a 357-lesion testing dataset that was independent of the training dataset. The observed sensitivity was 100% (14/14) for melanoma and 94% (105/112) for non-melanoma skin cancer. The overall observed specificity was 36% (84/231). ESS has potential, as an adjunctive assessment tool, to assist physicians to differentiate between common benign and malignant skin lesions.

    Original languageEnglish
    Pages (from-to)1441-1445
    Number of pages5
    JournalPhotochemistry and Photobiology
    Issue number6
    Publication statusPublished - 1 Nov 2019


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