Optical coherence tomography (OCT) is a non-invasive diagnostic method. Numerous morphological OCT features have been described for diagnosis of basal cell carcinoma (BCC). The aim of this study is to evaluate the diagnostic value of established OCT features and to explore whether the use of a small set of OCT features enables accurate discrimination between BCC and non-BCC lesions and between BCC subtypes. For each lesion, the presence or absence of specific OCT features was recorded. Histopathology was used as a gold standard. Diagnostic parameters were calculated for each OCT feature, and multivariate logistic regression analyses were performed to evaluate the loss in discriminative ability when using a small subset of OCT features instead of all features that are characteristic for BCC according to the literature. The results show that the use of a limited number of OCT features allows for good discrimination of superficial BCC from non-superficial BCC and non-BCC lesions. The prevalence of BCC was 75.3% (225/299) and the proposed diagnostic algorithm enabled detection of 97.8% of BCC lesions (220/225). Subtyping without the need for biopsy was possible in 132 of 299 patients (44%), with a predictive value for presence of superficial BCC of 84.3% vs 98.8% for presence of non-superficial BCC.

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