High resolution full-field optical coherence tomography for the
evaluation of freshly excised skin specimens during Mohs surgery: A
feasibility study
Abstract
Histopathology for tumor margin assessment is time-consuming and
expensive. High-resolution full-field optical coherence tomography
(FF-OCT) images fresh tissues rapidly at cellular resolution,
facilitating evaluation. We imaged fresh ex vivo skin tissues (normal
and neoplastic) from Mohs surgery. FF-OCT features were defined and
diagnostic accuracy for malignancies was performed by the two experts
OCT readers via a blinded analysis. A convolutional neural network was
built to distinguish and outline normal structures and tumors. Of the
113 tissues imaged, 95 (84%) had a tumor (75 BCCs and 17 SCCs). The
average reader diagnostic accuracy was 88.1%, a sensitivity of 93.7%,
and a specificity of 58.3%. The AI model achieved a diagnostic accuracy
of 87.6%±5.9%, sensitivity of 93.2%±2.1%, and specificity of
81.2%±9.2%. A mean intersection-over-union of 60.3%±10.1% was
achieved delineating nodular BCC from normal. We envision FF-OCT for
rapid evaluation of surgical margins and AI tumor detection leading to
widespread technique integration.