MRI-derived Articular Cartilage Strains Predict Patient-Reported Outcomes Six Months Post Anterior Cruciate Ligament Reconstruction

Abstract

Background: Anterior cruciate ligament (ACL) injuries lead to an increased risk of osteoarthritis, characterized by altered cartilage tissue structure and function. Displacements under applied loading by magnetic resonance imaging (dualMRI) is a novel MRI technique that can be used to quantify mechanical strain in cartilage while undergoing a physiological load. Purpose: To determine if strains derived by dualMRI and relaxometry measures correlate with patient-reported outcomes at six months post unilateral ACL reconstruction. Study Design: Cohort study Methods: Quantitative MRI (T2, T2*, T1ρ) measurements and transverse, axial, and shear strains were quantified in the medial articular tibiofemoral cartilage of 35 participants at six-months post unilateral ACL reconstruction. The relationships between patient-reported outcomes (WOMAC, KOOS, MARS) and all qMRI relaxation times were quantified using general linear mixed-effects models. A combined best-fit multicontrast MRI model was then developed using backwards regression to determine the patient features and MRI metrics that are most predictive of patient-reported outcome scores. Results: Higher femoral strains were significantly correlated with worse patient-reported functional outcomes. Femoral shear and transverse strains were positively correlated with six-month KOOS and WOMAC scores, after controlling for covariates. No relaxometry measures were correlated with patient-reported outcome scores. We identified the best-fit model for predicting WOMAC score using multiple MRI measures and patient-specific information, including sex, age, graft type, femoral transverse strain, femoral axial strain, and femoral shear strain. The best-fit model significantly predicted WOMAC score (p<0.001) better than any one individual MRI metric alone. When we regressed the model-predicted WOMAC scores against the patient-reported WOMAC scores, we found that our model achieved a goodness of fit exceeding 0.52. Conclusions: This work presents the first use of dualMRI in vivo in a cohort of participants at risk for developing osteoarthritis. Our results indicate that both shear and transverse strains are highly correlated with patient-reported outcome severity could serve as novel imaging biomarkers to predict the development of osteoarthritis.