Estimation of articular cartilage properties using multivariate analysis of optical coherence tomography signal

Abstract

Objective: The aim was to investigate the applicability of multivariate analysis of optical coherence tomography (OCT) information for determining structural integrity, composition and mechanical properties of articular cartilage.

Design: Equine osteochondral samples (N = 65) were imaged with OCT, and their total attenuation and backscattering coefficients (μt and μb) were measured. Subsequently, the Mankin score, optical density (OD) describing the fixed charge density, light absorbance in amide I region (Aamide), collagen orientation, permeability, fibril network modulus (Ef) and non-fibrillar matrix modulus (Em) of the samples were determined. Partial least squares (PLS) regression model was calculated to predict tissue properties from the OCT signals of the samples.

Results: Significant correlations between the measured and predicted mean collagen orientation (R(2) = 0.75, P < 0.0001), permeability (R(2) = 0.74, P < 0.0001), mean OD (R(2) = 0.73, P < 0.0001), Mankin scores (R(2) = 0.70, P < 0.0001), Em (R(2) = 0.50, P < 0.0001), Ef (R(2) = 0.42, P < 0.0001), and Aamide (R(2) = 0.43, P < 0.0001) were obtained. Significant correlation was also found between μb and Ef (ρ = 0.280, P = 0.03), but not between μt and any of the determined properties of articular cartilage (P > 0.05).

Conclusion: Multivariate analysis of OCT signal provided good estimates for tissue structure, composition and mechanical properties. This technique may significantly enhance OCT evaluation of articular cartilage integrity, and could be applied, for example, in delineation of degenerated areas around cartilage injuries during arthroscopic repair surgery.

Keywords: Articular cartilage; Degeneration; Optical coherence tomography; Partial least squares regression.