Non-Invasive Diagnostic Technologies for Melanoma
Abstract
Clinical examination followed by excisional biopsy and histopathologic analysis of suspicious pigmented lesions remains the gold-standard for melanoma diagnosis. Unfortunately, the performance of the unaided “melanoma detection pathway” is far from optimal with dermatologists demonstrating only 63.6% sensitivity and primary care physicians only 40.2% sensitivity for correct melanoma identification in a community-based screening setting. The accuracy of unaided melanoma detection is also low with a number needed to excise (NNE), defined as the number of suspicious lesions that must be excised to detect a single melanoma, of 29.4 for non-specialists and 8.7 for specialists. In order to improve melanoma detection, new non-invasive techniques have emerged including dermoscopy, total body photography, reflectance confocal microscopy and the pigmented lesion assay, which have a potential capacity to improve melanoma diagnosis. Such techniques used either alone, in combination, or with computational approaches including artificial intelligence (AI), have the potential to revolutionize the melanoma detection pathway for the benefit of patients and clinicians alike. Some of these technologies also provide an alternative to surgical biopsy in cases where patients decline such a procedure or to aid in the decision of whether to proceed with surgical biopsy when the clinical findings are equivocal. Such techniques also have application in the assessment and monitoring of high-risk patients including those with a history of melanoma, with multiple atypical nevi or with melanoma predisposition syndromes. They may also improve triage of referrals from non-specialists and help reduce healthcare costs by decreasing unnecessary surgical biopsies. In this review, the key features of established and emerging visual and non-visual non-invasive melanoma diagnostic technologies are highlighted.
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