Concentration profiles of collagen and proteoglycan in articular cartilage by Fourier transform infrared imaging and principal component regression.

Fourier-transform infrared imaging (FT-IRI) technique with the principal component regression (PCR) method was used to quantitatively determine the 2D images and the depth-dependent concentration profiles of two principal macromolecular components (collagen and proteoglycan) in articular cartilage. Ten 6 μm thick sections of canine humeral cartilage were imaged at a pixel size of 6.25 μm in FT-IRI. The infrared spectra extracted from FT-IRI experiments were imported into a PCR program to calculate the quantitative distributions of both collagen and proteoglycan in dry cartilage, which were subsequently converted into the wet-weight based concentration profiles. The proteoglycan profiles by FT-IRI and PCR significantly correlated in linear regression with the proteoglycan profiles by the non-destructive μMRI (the goodness-of-fit 0.96 and the Pearson coefficient 0.98). Based on these concentration relationships, the concentration images of collagen and proteoglycan in both healthy and lesioned articular cartilage were successfully constructed two dimensionally. The simultaneous construction of both collagen and proteoglycan concentration images demonstrates that this combined imaging and chemometrics approach could be used as a sensitive tool to accurately resolve and visualize the concentration distributions of macromolecules in biological tissues.