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A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.
Roemer, Frank W; Jarraya, Mohamed; Hayashi, Daichi; Crema, Michel D; Haugen, Ida K; Hunter, David J; Guermazi, Ali.
Affiliation
  • Roemer FW; Universitätsklinikum Erlangen & Friedrich Alexander Universität (FAU) Erlangen-Nürnberg, Erlangen, Germany; Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA. Electronic address: froemer@bu.edu.
  • Jarraya M; Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
  • Hayashi D; Tufts Medical Center, Tufts University School of Medicine, Boston, MA, USA; Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA.
  • Crema MD; Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA; Institute of Sports Imaging, French National Institute of Sports (INSEP), Paris, France.
  • Haugen IK; Center for Treatment of Rheumatic and Musculoskeletal Diseases (REMEDY), Diakonhjemmet Hospital, Oslo, Norway.
  • Hunter DJ; Department of Rheumatology, Royal North Shore Hospital and Sydney Musculoskeletal Health, Kolling Institute, University of Sydney, St. Leonards, NSW, Australia.
  • Guermazi A; Chobanian & Avedisian School of Medicine, Boston University, Boston, MA, USA; Boston VA Healthcare System, West Roxbury, MA, USA.
Osteoarthritis Cartilage ; 32(4): 460-472, 2024 Apr.
Article de En | MEDLINE | ID: mdl-38211810
ABSTRACT

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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Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Intelligence artificielle / Gonarthrose Limites: Humans Langue: En Journal: Osteoarthritis Cartilage Sujet du journal: ORTOPEDIA / REUMATOLOGIA Année: 2024 Type de document: Article Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Intelligence artificielle / Gonarthrose Limites: Humans Langue: En Journal: Osteoarthritis Cartilage Sujet du journal: ORTOPEDIA / REUMATOLOGIA Année: 2024 Type de document: Article Pays de publication: Royaume-Uni