ArticleACR open rheumatology2022
Computer-Assisted Image Analysis in Assessment of Peripheral Joint MRI in Inflammatory Arthritis: A Systematic Review and Meta-analysis.
Article in ACR open rheumatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- nnUnet-based automated quantification of wrist joint synovitis volume in patients with rheumatoid arthritis: a feasibility study.Radiology advances · 2026Article
- Imaging in clinical trials of rheumatoid arthritis: where are we in 2025?Skeletal radiology · 2025Review
- Deep Learning Based Automatic Ankle Tenosynovitis Quantification from MRI in Patients with Psoriatic Arthritis: A Feasibility Study.Diagnostics (Basel, Switzerland) · 2025Article
- Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?La Radiologia medica · 2025Review
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Authors and funding
5 authors.
Funding
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Abstract
objectiveTo summarize the feasibility of computer-assisted quantification of joint pathologies on magnetic resonance imaging (MRI) in patients with inflammatory arthritis by evaluating the published data on reliability, validity, and feasibility.
methodsA systematic literature search was performed for original articles published from January 1, 1985, to January 1, 2021. We selected studies in which patients with inflammatory arthritis were enrolled, and arthritis-related structural damage/synovitis in peripheral joints was assessed on non-contrast-enhanced, contrast-enhanced (CE), or dynamic CE (DCE)-MRI using (semi)automated methods. Data were pooled using random-effects model.
resultsTwenty-eight studies consisting of 1342 MRIs were included (mean age, 54.8 years; 66.7% female; duration of arthritis, 3.6 years). Among clinical/laboratory factors, synovial membrane volume (SV) was moderately correlated with erthrocyte sedimentation rate (ESR) level (P < 0.01). Pooled analysis showed an overall excellent intra- and inter-reader reliability for computer-aided quantification of bone erosion volume (BEV; r = 0.97 [95% CI: 0.92-0.99], 0.93 [0.87-0.97]), SV (r = 0.98 [95% CI: 0.90-0.99], 0.86 [0.78-0.91]), and DCE-MRI perfusion parameters (r = 0.96-0.99). Meta-regression showed that computer-aided and manual methods provide comparable reliability (P > 0.05). Computer-aided measurement of BEV (r = 0.92), SV (r = 0.82), and DCE-MRI biomarkers (r = 0.72 N-total; r = 0.74 N-plateau; r = 0.64 N-washout) were significantly correlated with the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS; P < 0.01), allowing for earlier assessment of drug efficacy. On average, (semi)automated analysis of BEV/SV took 17 minutes (vs. 9 minutes for the RAMRIS) and DCE-MRI took 4 minutes (vs. 33 minutes for manual assessment).
conclusionComputer-aided image quantification technologies demonstrate excellent reliability and validity when used to quantify MRI pathologies of peripheral joints in patients with inflammatory arthritis. Computer-aided evaluation of inflammatory arthritis is an emerging field and should be considered as a viable complement to conventional observer-based scoring methods for clinical trials application.
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