Predicting Meniscus Mechanical Properties using Quantitative Magnetization Transfer Magnetic Resonance Imaging

Abstract

Osteoarthritis (OA) is a degenerative joint disease that affects the entire knee joint, afflicting approximately 13% of the Canadian population. The meniscus plays a key role in load bearing and stability of the knee joint, and its functionality is compromised throughout OA progression. Currently there does not exist a way to study the relationship between meniscal tissue degeneration and mechanical properties in vivo, but Quantitative Magnetization Transfer Magnetic Resonance Imaging (qMT MRI) is a quantitative MRI technique which may be a good candidate for this application. This is because qMT models soft tissues in a comparable way to how tissues are modeled mechanically, and qMT is dependent on water/macromolecule interactions similar to meniscal tissue functionality. The aim of this project is to assess whether qMT metrics – bound-pool fraction (f), magnetization exchange rate (k), and relaxation times of the free and bound pools (T1f, T2f, and T2b) – accurately predict experimentally-derived mechanical properties – aggregate modulus (Ha) and permeability (kp) – of excised meniscal samples. Six human cadaver knee specimens were imaged using qMT MRI techniques in order to obtain imaging metrics of the menisci. Subsequent to imaging, 59 core meniscal samples were tested using a stress relaxation approach in a confined compression testing configuration in order to obtain Ha and kp of the samples as measures of mechanical properties. A Spearman’s rho correlation was then performed on the mechanical properties and the imaging metrics of the core samples of the menisci to determine how well the imaging metrics predict the mechanical properties. One correlation, albeit weak, was found between mechanical properties and qMT metrics (Ha and T2b); however, this may be due to homogeneity in meniscal health of the specimens limiting the ability for correlations to be detected. Moderate to strong negative correlations between T1 relaxation time and f, and k were found. These relationships should be further explored as T1 is an often neglected imaging metric, and qMT in the meniscus is quite unexplored. T1 was found to have a moderate correlation with T2. These results reinforce that qMT is viable to use in the meniscus, but that further work needs to be done in order to determine if it can be used as a non-invasive method of assessing meniscal tissue mechanical properties.