Mri-Defined Tissue Damage As Predictors of the Incidence and Progression of Knee Osteoarthritis: A Systematic Review Publisher



Mohammadi S ; Harandi H ; Alikarami S ; Fattahniya S ; Samiee R ; Ghavam M ; Karimi E ; Jahanshahi A ; Roemer FW ; Hunter DJ ; Guermazi A
Source: Seminars in Arthritis and Rheumatism Published:2026

Abstract

Background: MRI is increasingly recognized not only for visualization of knee joint structures in knee osteoarthritis (KOA), but also for its potential to predict KOA incidence and progression. Objective: We aim to provide a comprehensive overview of how different types of MRI-detected joint tissue pathology perform in predicting radiographic progression and longitudinal evolution of clinical outcomes and functional decline. Methods: The study protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO; registration number CRD420251132451). A systematic literature search was performed in PubMed, Scopus, and Web of Science. After removal of duplicates, 4810 studies underwent a multi-step screening process, of which 99 were included in the qualitative synthesis. The quality of included studies was evaluated using the Newcastle-Ottawa Scale and the Downs and Black checklist. Results: Most of the included studies were of good quality. Strong predictors of KOA incidence included baseline bone marrow lesions (BMLs), specific bone shape patterns (ORs up to 12.5 (95% CI, 4.0–39.3)), meniscal tears, and synovitis. Predictors of KOA progression, characterized by increasing cartilage damage, were meniscal extrusion, synovitis, and BMLs. Notably, baseline cartilage T2 signal abnormalities were a powerful predictor of the future development of new structural cartilage defects (OR = 21.3 (95% CI, 11.1, 40.6)), highlighting a pathway from compositional to structural deterioration in knees with and without pre-existing disease. Conclusion: Several MRI-detected joint tissue pathologies longitudinally associated with structural progression and clinically relevant outcomes, such as total knee arthroplasty, allowing patient stratification for disease-modifying osteoarthritis drug (DMOAD) trials. These associations may be further strengthened using compositional and multi-featured MRI models as well as AI-based feature extraction. © 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.