Microscopy-based classification of moles A European study utilised microscopy-based technology for the classification of moles. This imaging method is non-invasive and allows the monitoring of skin lesions over time. Health © Albina Glisic, Shutterstock Melanocytic nevi known as moles are the strongest indicator of an increased risk of melanoma. Recent evidence suggests that nevi consist of distinct subsets, which may be associated with different levels of melanoma risk. Until now, nevus classification has been based on histopathological analysis, which requires surgical excision. Researchers on the EU-funded NEVUS CLASSIFICATION (Classification and longitudinal follow-up of common melanocytic nevi with in vivo reflectance confocal microscopy) project utilised reflectance confocal microscopy (RCM) for nevus classification. RCM is a cutting-edge technology that allows non-invasive skin imaging at cellular-level resolution. They hypothesised that RCM could identify distinct subsets of nevi. RCM imaging data of benign nevi were compared with respective histopathological data and led to the identification of five distinct RCM patterns. These patterns served as the basis for a RCM nevus classification, which was subsequently implemented towards the characterisation of nearly 350 nevi. Additionally, RCM was used to longitudinally track individual cellular structures in nevi and monitor their evolution over time. The use of RCM for nevus classification has opened up new avenues towards its implementation to monitor skin lesions at the cellular level. RCM could be used for differentiating benign nevi from malignant melanoma by recognising deviations indicative of malignancy. Also, it has the potential to differentiate between high- versus low-risk melanoma based on the microscopic pattern of patient nevi. As a result, it is expected to improve prognosis and early diagnosis of melanoma. Keywords Mole, imaging, melanocytic nevi, melanoma, reflectance confocal microscopy
