Research on Enhancement Detection of Synovial Fluid and Pathogenesis of Osteoarthritis With Enhanced Raman Spectroscopy Techniques

ABSTRACT

Osteoarthritis (OA) is a common degenerative joint disease with limited early diagnostic options, highlighting the need for molecular‐level detection methods. This study systematically compared the performance of Raman scattering (RS), fiber‐enhanced Raman scattering (FERS), and surface‐enhanced Raman scattering (SERS) for synovial fluid (SF) analysis and OA staging, and further investigated the effect of SF phase transition on spectral responses. Results showed that, compared with RS, liquid‐phase FERS reduced drying‐induced molecular redistribution and conformational changes, thereby improving reproducibility and quantitative reliability. All three techniques consistently captured OA‐related molecular alterations, including progressive extracellular matrix degradation and accumulation of collagen degradation products in SF. Machine learning analysis demonstrated that SERS achieved the best staging performance, with the highest classification accuracy (77%) and AUC across all models. Importantly, fusion of FERS and SERS further improved accuracy to 83%, highlighting the advantage of complementary information integration. These findings emphasize the importance of detection state in spectral analysis and support Raman techniques as promising tools for minimally invasive OA diagnosis and staging.