Raman Spectroscopy of Biofluids: Fusion Strategies for Detecting Oral Potentially Malignant Disorders and Oral Cancers.

Abstract

Minimally invasive screening tools are essential for early detection of oral cancers to reduce mortality. A key necessity is the ability to differentiate highly heterogeneous oral potentially malignant disorders (OPMDs) and cancers. This study evaluated serum and salivary Raman spectroscopy (RS) for detecting OPMDs and oral cancers. Blood and saliva were collected from 13 non-habitual controls (NHC), 13 tobacco habitués (HC), 10 leukoplakia (L), 25 oral submucous fibrosis (OSMF), and 14 oral squamous cell carcinoma (OSCC) subjects. Raman spectra were acquired, pre-processed, and analyzed using multivariate methods. Serum outperformed saliva in individual classification models, achieving accuracies of 92%, 85%, 100%, 88%, and 85% for NHC, HC, L, OSMF, and OSCC, respectively. Saliva, despite its non-invasive advantage, showed higher misclassification among HC, L, OSMF, and OSCC. Low-level fusion of serum and saliva spectral data improved the classification of OSMF, OSCC, and NHC groups compared to saliva models. Mid-level fusion surpassed both biofluids, reaching 100% accuracy for NHC, L, and OSMF. Multivariate curve resolution-alternating least squares analysis of serum revealed altered protein- and lipid-related features among groups. These findings demonstrate the potential of serum and salivary RS, particularly with data fusion, as effective tools for OPMD and oral cancer screening.