Computer-Assisted Image Analysis in Assessment of Peripheral Joint MRI in Inflammatory Arthritis: A Systematic Review and Meta-analysis

Abstract

Objective: To 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. Methods: 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-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. Results: Twenty-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). Conclusion: Computer-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.