{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T17:19:42Z","timestamp":1773249582039,"version":"3.50.1"},"reference-count":57,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2022,6,10]],"date-time":"2022-06-10T00:00:00Z","timestamp":1654819200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":["acrjournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["ACR Open Rheumatology"],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:sec><jats:title>Objective<\/jats:title><jats:p>To summarize the feasibility of computer\u2010assisted quantification of joint pathologies on magnetic resonance imaging (MRI) in patients with inflammatory arthritis by evaluating the published data on reliability, validity, and feasibility.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A 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\u2010related structural damage\/synovitis in peripheral joints was assessed on non\u2010contrast\u2010enhanced, contrast\u2010enhanced (CE), or dynamic CE (DCE)\u2010MRI using (semi)automated methods. Data were pooled using random\u2010effects model.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Twenty\u2010eight studies consisting of 1342 MRIs were included (mean age, 54.8\u2009years; 66.7% female; duration of arthritis, 3.6\u2009years). Among clinical\/laboratory factors, synovial membrane volume (SV) was moderately correlated with erthrocyte sedimentation rate (ESR) level (<jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01). Pooled analysis showed an overall excellent intra\u2010 and inter\u2010reader reliability for computer\u2010aided quantification of bone erosion volume (BEV; r\u2009=\u20090.97 [95% CI: 0.92\u20100.99], 0.93 [0.87\u20100.97]), SV (r\u2009=\u20090.98 [95% CI: 0.90\u20100.99], 0.86 [0.78\u20100.91]), and DCE\u2010MRI perfusion parameters (r\u2009=\u20090.96\u20100.99). Meta\u2010regression showed that computer\u2010aided and manual methods provide comparable reliability (<jats:italic>P<\/jats:italic>\u2009&gt;\u20090.05). Computer\u2010aided measurement of BEV (r\u2009=\u20090.92), SV (r\u2009=\u20090.82), and DCE\u2010MRI biomarkers (r\u2009=\u20090.72 N\u2010total; r\u2009=\u20090.74 N\u2010plateau; r\u2009=\u20090.64 N\u2010washout) were significantly correlated with the Rheumatoid Arthritis Magnetic Resonance Imaging Score (RAMRIS; <jats:italic>P<\/jats:italic>\u2009&lt;\u20090.01), 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\u2010MRI took 4 minutes (vs. 33 minutes for manual assessment).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>Computer\u2010aided image quantification technologies demonstrate excellent reliability and validity when used to quantify MRI pathologies of peripheral joints in patients with inflammatory arthritis. Computer\u2010aided evaluation of inflammatory arthritis is an emerging field and should be considered as a viable complement to conventional observer\u2010based scoring methods for clinical trials application.<\/jats:p><\/jats:sec>","DOI":"10.1002\/acr2.11450","type":"journal-article","created":{"date-parts":[[2022,6,11]],"date-time":"2022-06-11T00:12:45Z","timestamp":1654906365000},"page":"721-734","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Computer\u2010Assisted Image Analysis in Assessment of Peripheral Joint <scp>MRI<\/scp> in Inflammatory Arthritis: A Systematic Review and Meta\u2010analysis"],"prefix":"10.1002","volume":"4","author":[{"given":"Arya","family":"Haj\u2010Mirzaian","sequence":"first","affiliation":[{"name":"Johns Hopkins Hospital  Baltimore Maryland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Olga","family":"Kubassova","sequence":"additional","affiliation":[{"name":"Image Analysis Group  London United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mikael","family":"Boesen","sequence":"additional","affiliation":[{"name":"University Hospital Bispebjerg and Frederiksberg; The Parker Institute  Copenhagen Denmark"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"Carrino","sequence":"additional","affiliation":[{"name":"Hospital for Special Surgery  Hackensack New Jersey"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2277-8337","authenticated-orcid":false,"given":"Paul","family":"Bird","sequence":"additional","affiliation":[{"name":"University of New South Wales  Sydney New South Wales Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,6,10]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1002\/art.39480"},{"key":"e_1_2_7_3_1","article-title":"Ide ZJb. 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