A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.
MRI
osteoarthritis
radiography
responsiveness
semi-quantitative scroring
validity
Journal
Osteoarthritis and cartilage
ISSN: 1522-9653
Titre abrégé: Osteoarthritis Cartilage
Pays: England
ID NLM: 9305697
Informations de publication
Date de publication:
09 Jan 2024
09 Jan 2024
Historique:
received:
21
09
2023
revised:
15
12
2023
accepted:
04
01
2024
medline:
12
1
2024
pubmed:
12
1
2024
entrez:
11
1
2024
Statut:
aheadofprint
Résumé
This perspective describes the evolution of semi-quantitative (SQ) MRI in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years. 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). Based on original research published between 1993 and 2023, this article introduces available scoring systems, including but not limited to WORMS as the first system for whole-organ assessment of the knee and the now commonly used 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. 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.
Identifiants
pubmed: 38211810
pii: S1063-4584(24)00003-7
doi: 10.1016/j.joca.2024.01.001
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Informations de copyright
Copyright © 2024. Published by Elsevier Ltd.