Tissue optical properties combined with machine learning enables estimation of articular cartilage composition and functional integrity.

Absorption and reduced scattering coefficients ( μ a , μ s ' ) of biological tissues have shown significant potential in biomedical applications. Thus, they are effective parameters for the characterization of tissue integrity and provide vital information on the health of biological tissues. This study investigates the potential of optical properties ( μ a , μ s ' ) for estimating articular cartilage composition and biomechanical properties using multivariate and machine learning techniques. The results suggest that μa could optimally estimate cartilage proteoglycan content in the superficial zone, in addition to its equilibrium modulus. While μ s ' could effectively estimate the proteoglycan content of the middle and deep zones in addition to the instantaneous and dynamic moduli of articular cartilage.