Fourier Transform Infrared Microscopic Imaging and Fisher Discriminant Analysis for Identification of Healthy and Degenerated Articular Cartilage

Fourier transform infrared microscopy imaging (FT-IRI) can be used to collect the infrared spectra and morphology of the samples. As combined with chemometric method, the content and spatial distribution of the principal components in biological tissues can be studied quantitatively. In this study, FT-IRI combined with principal component analysis (PCA) and Fisher discriminant analysis (FDA) was applied to identify healthy and degenerated articular cartilage samples. First, FT-IRI and spectral analysis on articular cartilage specimens were achieved, as well as PCA on the infrared spectra in SPSS software. And then FDA was adopted to construct the classification function based on the principal component score matrix for classifying the articular cartilage samples. The healthy and degenerated cartilage samples were effectively discriminated with very high accuracy of 95.7% for initial samples and 94.3% for cross-validation, respectively. It is indicated that the hyphenated technique can be used to effectively discriminate the healthy and degenerated cartilages, which opens a newly effective way of monitoring osteoarthritis generation and reparation.

A newly developed analytical tool, Fourier transform infrared imaging (FT-IRI), was combined with Fisher discrimination to identify healthy and degenerated articular cartilage. The accuracies were 95.7% and 94.3% for initial samples and cross-validation, respectively. The figure shows the FT-IR images and corresponding visible images of healthy and degenerated cartilage sections obtained by FT-IRI.Figure optionsDownload as PowerPoint slide