Quantification of hand synovitis in rheumatoid arthritis: Arterial mask subtraction reinforced with mutual information can improve accuracy of pixel‐by‐pixel time–intensity curve shape analysis in dynamic MRI. Issue 3 (1st March 2018)

• Record Type: Journal Article
• Authors: Kobayashi, Yuto; Kamishima, Tamotsu; Sugimori, Hiroyuki; Ichikawa, Shota; Noguchi, Atsushi; Kono, Michihito; Iiyama, Toshitake; Sutherland, Kenneth; Atsumi, Tatsuya
• Is Part Of: Journal of magnetic resonance imaging. Volume 48:Issue 3(2018)
• Page Start: 687
• Page End: 694
• Publication Date: 2018-03-01
• Subjects: dynamic contrast‐enhanced MRI -- time‐intensity curve shape analysis -- rheumatoid arthritis -- mutual information -- synovitis quantification; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.25995
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Background: Synovitis, which is a hallmark of rheumatoid arthritis (RA), needs to be precisely quantified to determine the treatment plan. Time–intensity curve (TIC) shape analysis is an objective assessment method for characterizing the pixels as artery, inflamed synovium, or other tissues using dynamic contrast‐enhanced MRI (DCE‐MRI). Purpose/Hypothesis: To assess the feasibility of our original arterial mask subtraction method (AMSM) with mutual information (MI) for quantification of synovitis in RA. Study Type: Prospective study. Subjects: Ten RA patients (nine women and one man; mean age, 56.8 years; range, 38–67 years). Field Strength/Sequence: 3T/DCE‐MRI. Assessment: After optimization of TIC shape analysis to the hand region, a combination of TIC shape analysis and AMSM was applied to synovial quantification. The MI between pre‐ and postcontrast images was utilized to determine the arterial mask phase objectively, which was compared with human subjective selection. The volume of objectively measured synovitis by software was compared with that of manual outlining by an experienced radiologist. Simple TIC shape analysis and TIC shape analysis combined with AMSM were compared in slices without synovitis according to subjective evaluation. Statistical Tests: Pearson's correlation coefficient, paired t ‐test and intraclass correlation coefficient (ICC). Results: TIC shape analysis was successfully optimized in the hand region with a correlation coefficient of 0.725 ( P < 0.01) with the results of manual assessment regarded as ground truth. Objective selection utilizing MI had substantial agreement (ICC = 0.734) with subjective selection. Correlation of synovial volumetry in combination with TIC shape analysis and AMSM with manual assessment was excellent ( r = 0.922, P < 0.01). In addition, negative predictive ability in slices without synovitis pixels was significantly increased ( P < 0.01). Data Conclusions: The combination of TIC shape analysis and image subtraction reinforced with MI can accurately quantify synovitis of RA in the hand by eliminating arterial pixels. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:687–694.