Characterization of benign and malignant melanocytic skin lesions using optical coherence tomography in vivo

BackgroundAlthough optical coherence tomography (OCT) is a promising noninvasive imaging technique for the micromorphology of the skin, OCT has not been studied systematically in skin cancer such as malignant melanoma (MM).ObjectiveWe sought to visualize and characterize melanocytic skin lesions (MSL) by using OCT in vivo, compare OCT features of benign nevi (BN) and MM, and histologically validate the OCT findings.MethodsIn all, 75 patients with 92 MSL, including 52 BN and 40 MM, were included in this study. MSL were investigated by OCT in vivo and consecutive histology. We compared the OCT images with the corresponding histologic slices of BN and MM. To ascertain accuracy of correlation between OCT images and histologic sections, the excised lesions were tattooed according to the level of OCT scanning. For every MSL, serial histologic slices were prepared.ResultsMM often showed a marked architectural disarray (P = .036) and rarely displayed a clear dermoepidermal border (P = .0031) when compared with BN. OCT of MM infrequently demonstrated a dermoepidermal junction zone with finger-shaped elongated rete ridges as typically seen in BN (P = .011). Compared with BN, the papillary and superficial reticular dermis in MM frequently displayed a more diffuse or patchy reflectivity with loss of the typical bright horizontal linear structures (P = .022). However, more or less large vertical, icicle-shaped structures were the most striking OCT feature of MM, which were not observed in BN (P < .001).LimitationsThe diagnostic performance of OCT in the diagnosis of MSL could not be fully determined. Sensitivity and specificity studies also including other skin tumors have not been performed.ConclusionIn this study, distinct OCT features of MSL could be correlated to histopathologic findings. With regard to the micromorphologic features visualized by OCT, we detected significant differences between BN and MM. These OCT features might serve as useful discriminating parameters of MSL.