Use of magnetic resonance imaging to assess tibiofemoral cartilage behaviour following loading: a multi-disciplinary evaluation of cartilage mechanics

Abstract

Understanding articular cartilage mechanics is imperative to gain insight into tissue tolerances and loads, and how these may change with disease. This thesis used a multi-disciplinary approach to quantify cartilage mechanics using magnetic resonance imaging (MRI), a non-invasive tool for the evaluation of soft tissues. Study 1 (Chapter 2) outlined an in vivo study that aimed to identify the effect of 1) running; 2) biological sex; and 3) their interaction on tibial and femoral cartilage thickness changes following running using Statistical Parametric Mapping (SPM). Running caused deformation in all knee compartments, and especially in the lateral tibia (p < 0.0001). Females had thinner cartilage than males (p < 0.009). Finally, clusters indicating an interaction of Running and Sex were identifi ed on the posterior lateral tibia, suggesting females experienced greater cartilage deformation than males (p < 0.012). Studies 2 and 3 (Chapters 3 and 4) integrated MRI and biomechanical datasets to explore the loading environment at the knee. Study 2 investigated the effect of daily cumulative knee load (measured using musculoskeletal modeling and accelerometry) on cartilage response (change in morphology, composition) following running in women. This cumulative loading metric was related to tibial volume change (F(4, 14) = 4:68, p = 0.013, R2 = 0.50), suggesting a potential cartilage conditioning effect. Study 3 outlined the use of an ex vivo porcine stifle model to build a 3D voxelwise statistical map exploring the relationship between cartilage mechanical properties (measured via automated indentation mapping) and cartilage outcomes from MRI (cartilage thickness, T2 change) following static loading. No signi ficant relationships were identi fied; however, this novel integration of indentation mapping and MRI cartilage outcomes shows utility moving forward. Overall, this thesis characterizes cartilage response to biomechanical load using novel tools derived by integrating engineering, biomechanics, and imaging. Together this work provides an exciting opportunity to explore and quantify spatial relationships between mechanical properties and cartilage MRI outcomes.