Purpose: To assess whether magnetic resonance (MR) imaging-based cross-sectional measures of structural joint damage can be used to predict knee replacement during the following year.
Materials and methods: Participants were drawn from the Osteoarthritis Initiative, a longitudinal observational study that includes 4796 participants who have knee osteoarthritis or are at risk. The HIPAA-compliant protocol was approved by the institutional review boards of all participating centers, and written informed consent was obtained from all participants. During the 5 years of follow-up, 199 knees underwent knee replacement and were matched with 199 control knees that did not undergo knee replacement. Knees were matched according to radiographic disease stage and patient sex and age. All knees that underwent knee replacement and had MR images available from the year before surgery were included. MR images were assessed for cartilage damage, bone marrow lesions, meniscal damage, meniscal extrusion, synovitis, and effusion prior to reported knee replacement. Conditional logistic regression was applied to assess the risk of knee replacement. Analyses were performed on a compartmental and knee level.
Results: Participants had a mean age ± standard deviation of 64.2 years ± 8.4 (range, 47-82 years) and were predominantly women (232 of 398 participants, 58.3%). Risk for knee replacement was significantly increased for knees that exhibited two or more subregions with severe cartilage loss (odds ratio [OR], 16.5; 95% confidence interval [CI]: 3.96, 68.76), more than two subregions with bone marrow lesions (OR, 4.00; 95% CI: 1.75, 9.16), medial meniscal maceration (OR, 1.84; 95% CI: 1.13, 2.99), effusion (OR, 4.75; 95% CI: 2.55, 8.85), or synovitis (OR, 2.17; 95% CI: 1.33, 3.56), but not extrusion (OR, 1.00; 95% CI: 0.60,1.67), when compared with knees that did not exhibit these features as the reference standard.
Conclusion: Apart from meniscal extrusion, all features of tissue abnormalities at MR imaging were related to clinical prognosis and could be used to predict knee replacement in the following year.