MRI and biomechanics multidimensional data analysis reveals R₂ -R_1ρ as an early predictor of cartilage lesion progression in knee osteoarthritis.

ABSTRACT:

Purpose

To couple quantitative compositional MRI, gait analysis, and machine learning multidimensional data analysis to study osteoarthritis (OA). OA is a multifactorial disorder accompanied by biochemical and morphological changes in the articular cartilage, modulated by skeletal biomechanics and gait. While we can now acquire detailed information about the knee joint structure and function, we are not yet able to leverage the multifactorial factors for diagnosis and disease management of knee OA.

Materials and methods

We mapped 178 subjects in a multidimensional space integrating: demographic, clinical information, gait kinematics and kinetics, cartilage compositional T_1ρ and T₂ and R₂ -R_1ρ (1/T₂ -1/T_1ρ ) ac

SUBMITTER: Pedoia V 

PROVIDER: S-EPMC5967390 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature