KEY TERMS: Multicontrast and Multiparametric, Magnetic Resonance Imaging, Osteoarthritis, Functional Biomechanical Imaging, Knee Joint Degeneration What is known about the subject: dualMRI has been used to quantify strains in a healthy human population in vivo and in cartilage explant models. Previously, OA severity, as determined by histology, has been positively correlated to increased shear and transverse strains in cartilage explants. What this study adds to existing knowledge: This is the first in vivo use of dualMRI in a participant demographic post-ACL reconstruction and at risk for developing osteoarthritis. This study shows that dualMRI-derived strains are more significantly correlated with patient-reported outcomes than any MRI relaxometry metric. 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.
