A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future

骨关节炎 医学 透视图(图形) 计算机科学 病理 人工智能 替代医学
作者
Frank W. Roemer,Mohamed Jarraya,Daichi Hayashi,M.D. Crema,I.K. Haugen,David J. Hunter,Ali Guermazi
出处
期刊:Osteoarthritis and Cartilage [Elsevier]
卷期号:32 (4): 460-472 被引量:2
标识
DOI:10.1016/j.joca.2024.01.001
摘要

Objective This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years. Methods Authors selected representative articles from a PubMed search to illustrate key steps in SQ MRI development, validation, and application. Topics include main scoring systems, reading techniques, responsiveness, reliability, technical considerations, and potential impact of artificial intelligence (AI). Results Based on original research published between 1993 and 2023, this article introduces available scoring systems, including but not limited to Whole-Organ Magnetic Resonance Imaging Score (WORMS) as the first system for whole-organ assessment of the knee and the now commonly used MRI Osteoarthritis Knee Score (MOAKS) instrument. Specific systems for distinct OA subtypes or applications have been developed as well as MRI scoring instruments for other joints such as the hip, the fingers or thumb base. SQ assessment has proven to be valid, reliable, and responsive, aiding OA investigators in understanding the natural history of the disease and helping to detect response to treatment. AI may aid phenotypic characterization in the future. SQ MRI assessment's role is increasing in eligibility and safety evaluation in knee OA clinical trials. Conclusions Evidence supports the validity, reliability, and responsiveness of SQ MRI assessment in understanding structural aspects of disease onset and progression. SQ scoring has helped explain associations between structural tissue damage and clinical manifestations, as well as disease progression. While AI may support human readers to more efficiently perform SQ assessment in the future, its current application in clinical trials still requires validation and regulatory approval.
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