In this preliminary study on synovial fluid (SF), knee osteoarthritis (OA) grading of n = 23 patients was accomplished by combining two methods: resonant Raman spectroscopy, and surface-enhanced Raman scattering (SERS) of native proteins acquired with iodide-modified silver nanoparticles and a laser emitting at 633 nm. Based on principal component analysis-linear discriminant analysis (PCA-LDA), the SERS spectra of proteins enabled the classification of low-grade and high-grade OA groups with an accuracy of 91%. Resonant Raman spectra of SF, recorded with laser excitation at 532 nm, exhibited carotenoid-associated bands that were less intense in the case of high-grade knee OA patients. Based on the resonant Raman spectra, the grading of OA patients was accomplished with an accuracy of 74%. Concatenating SERS and Raman spectral information increased the classification accuracy between the two groups to 100%. These results demonstrate the potential of Raman and SERS as a point-of-care method for aiding OA grading.
Keywords: Osteoarthritis; PCA–LDA; Raman spectroscopy; SERS; Synovial fluid.
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