Magnetic resonance imaging-based biomarkers for knee osteoarthritis outcomes: A narrative review of prediction but not association studies. European journal of radiology BACKGROUND:Magnetic Resonance Imaging (MRI) is frequently used in recent studies on knee osteoarthritis (KOA), focusing on developing innovative MRI-based biomarkers to predict KOA outcomes. The growing volume of publications devoted to this subject highlights the need for an up-to-date review. METHODS:In this narrative review, we utilized the PubMed database to identify studies examining MRI-based biomarkers for the prediction of knee osteoarthritis (KOA), focusing on those reporting relevant prediction, not association, metrics. The identified articles were subsequently categorized into three distinct outcomes: Prediction of KOA incidence (KOAi), KOA progression (KOAp) and total knee arthroplasty risk (TKAr). Within each category, results were organized by the nature of biomarker(s) used, as either quantitative, semi-quantitative or compound. RESULTS:Due to the lack of predictive metrics such as the area under the ROC curve (AUC) scores, sensitivity or specificity, 27 studies were excluded. A final set of 23 studies were deemed eligible for our analysis. The mean AUC scores reported ranged from 0.67 to 0.83 for predicting KOAi, 0.54 to 0.84 for KOAp and 0.55 to 0.94 for TKAr. Excellent predictive performance (AUC>0.8) was observed for the prediction of radiographic KOAi, KOAp and TKAr when using cartilage and meniscal-based measures, osteophyte scores and infrapatellar fat pad texture, and bone marrow lesions, respectively. CONCLUSION:The results showed that numerous studies highlighted the importance of MRI-based biomarkers as promising predictors of the three key outcomes. In addition, this narrative review also emphasized the necessity for KOA prediction studies to include adequate reporting of predictive metrics. 10.1016/j.ejrad.2024.111731

30 Years of MRI-based cartilage & bone morphometry in knee osteoarthritis: From correlation to clinical trials. Osteoarthritis and cartilage OBJECTIVE:The first publication on morphometric analysis of articular cartilage using magnetic resonance imaging (MRI) in 1994 set the scene for a game change in osteoarthritis (OA) research. The current review highlights milestones in cartilage and bone morphometry, summarizing the rapid progress made in imaging, its application to understanding joint (patho-)physiology, and its use in interventional clinical trials. METHODS:Based on a Pubmed search of articles from 1994 to 2023, the authors subjectively selected representative work illustrating important steps in the development or application of magnetic resonance-based cartilage and bone morphometry, with a focus on studies in humans, and on the knee. Research on OA-pathophysiology is addressed only briefly, given length constraints. Compositional and semi-quantitative assessment are not covered here. RESULTS:The selected articles are presented in historical order as well as by content. We review progress in the technical aspects of image acquisition, segmentation and analysis, advances in understanding tissue growth, physiology, function, and adaptation, and a selection of clinical trials examining the efficacy of interventions on knee cartilage and bone. A perspective is provided of how lessons learned may be applied to future research and clinical management. CONCLUSIONS:Over the past 30 years, MRI-based morphometry of cartilage and bone has contributed to a paradigm shift in understanding articular tissue physiology and OA pathophysiology, and to the development of new treatment strategies. It is likely that these technologies will continue to play a key role in the development and (accelerated) approval of therapy, potentially targeted to different OA phenotypes. 10.1016/j.joca.2024.02.002

The role of imaging in osteoarthritis. Best practice & research. Clinical rheumatology Osteoarthritis is a complex whole-organ disorder that involves molecular, anatomic, and physiologic derangement. Advances in imaging techniques have expanded the role of imaging in evaluating osteoarthritis and functional changes. Radiography, magnetic resonance imaging, computed tomography (CT), and ultrasonography are commonly used imaging modalities, each with advantages and limitations in evaluating osteoarthritis. Radiography comprehensively analyses alignment and osseous features, while MRI provides detailed information about cartilage damage, bone marrow edema, synovitis, and soft tissue abnormalities. Compositional imaging derives quantitative data for detecting cartilage and tendon degeneration before structural damage occurs. Ultrasonography permits real-time scanning and dynamic joint evaluation, whereas CT is useful for assessing final osseous detail. Imaging plays an essential role in the diagnosis, management, and research of osteoarthritis. The use of imaging can help differentiate osteoarthritis from other diseases with similar symptoms, and recent advances in deep learning have made the acquisition, management, and interpretation of imaging data more efficient and accurate. Imaging is useful in monitoring and predicting the prognosis of osteoarthritis, expanding our understanding of its pathophysiology. Ultimately, this enables early detection and personalized medicine for patients with osteoarthritis. This article reviews the current state of imaging in osteoarthritis, focusing on the strengths and limitations of various imaging modalities, and introduces advanced techniques, including deep learning, applied in clinical practice. 10.1016/j.berh.2023.101866

Imaging of Osteoarthritis of the Knee. Radiologic clinics of North America Knee osteoarthritis is rising in prevalence, and more imaging studies are being requested to evaluate these patients. Although conventional radiographs of the knee are the most widely requested and available studies, other imaging modalities such as MRI, CT, and ultrasound may also be used. This article reviews commonly used imaging modalities, advantages and limitations of each, and their clinical applicability in diagnosing and monitoring knee osteoarthritis. New and advanced imaging techniques are also discussed as possible methods of early diagnosis and improved understanding of osteoarthritis pathophysiology. 10.1016/j.rcl.2022.03.004