Fourier transform infrared spectroscopic imaging application for multi-stage discrimination in cartilage degeneration

Abstract

Fourier transform infrared spectroscopic imaging (FTIRI) technique can be used to obtain rich information about the chemical components in biological tissue such as articular cartilage, by employing quantitative chemometrics methods. In this study, the imaging technique was used for spectroscopic imaging on cartilage sections. The support vector machine discriminant analysis (SVM-DA) was then employed in imaging data analysis to distinguish among healthy and osteoarthritic (OA) articular cartilages at different degeneration stages for the first time. Briefly, the infrared spectra were extracted from the FTIR images and imported into Unscrambler software for the SVM-DA model construction and prediction. When the 3rd-polynomial kernel function was chosen as the kernel function and the parameters C in each range of 2782.5–10000, 2.3714–10 and 0.0032–0.01, respectively, and the corresponding optimal G was equal to 0.1, 1 and 10, the healthy, OA-8W (8 week after surgery) and OA-2Y (2 years after surgery) cartilage samples were effectively differentiated by the SVM-DA method with high accuracy of 100% for the training set and 86.67% for the prediction group. FTIRI with the use of chemometrics (SVM-DA) may become an effective method to distinguish multi-stage tissue degradation in the future.