Raman and FIBI-based slide-free imaging for rapid margin assessment in skin cancer surgery

Mohs micrographic surgery (Mohs) is the gold standard for treating high-risk basal cell carcinoma (BCC), but its reliance on frozen section histopathology limits intraoperative speed and access, especially in low-resource settings. To address this, we developed a multimodal imaging workflow that integrates Fluorescence-Imitating Brightfield Imaging (FIBI) with Raman spectroscopy (Raman) for rapid, slide-free margin assessment of Mohs excisions. In this pilot study, excised BCC tissue from twenty Mohs patients (ten positive margins, ten negative margins) was stained using a 2-minute rapid H&E protocol and imaged with FIBI for whole-slide morphological visualization in real time at video rate. Targeted Raman was then performed on BCC and normal skin structures (epidermis, dermis, sebaceous glands, subcutaneous fat, and hair follicles). A total of 243 Raman spectra were acquired and pre-processed using an in-house pipeline (wavelength calibration, background subtraction, cosmic ray removal, smoothing, and normalization), followed by principal component analysis (PCA), and linear discriminant analysis (LDA) with leave-one-patient-out (LOPO) and leave-one-spectrum-out (LOSO) cross-validation. Diagnostic performance was quantified using area under the ROC curve (AUC), sensitivity, and specificity. To further interpret the biochemical features of the spectra, we applied a published biophysical model to estimate the relative contributions of molecular components such as nucleus, keratin, collagen, ceramide, and triolein. In this preliminary analysis, Raman distinguished BCC from normal structures with AUCs of 0.98 (LOSO) and 0.93 (LOPO), achieving 90% sensitivity and 97% and 86% specificity, respectively. Biophysical analysis revealed elevated nuclear content and reduced collagen in BCC, while normal structures exhibited expected profiles (e.g., keratin-rich epidermis, triolein-rich fat). These findings support the potential of our approach as a real-time, slide-free tool for ex vivo margin evaluation in skin cancer surgery.