Assessment of active and inactive sacroiliitis in patients with ankylosing spondylitis using quantitative dynamic contrast‐enhanced MRI. Issue 1 (16th November 2016)

• Record Type: Journal Article
• Authors: Zhang, Mengchao; Zhou, Le; Huang, Ning; Zeng, Hong; Liu, Songyan; Liu, Lin
• Is Part Of: Journal of magnetic resonance imaging. Volume 46:Issue 1(2017)
• Page Start: 71
• Page End: 78
• Publication Date: 2016-11-16
• Subjects: dynamic contrast‐enhanced magnetic resonance imaging -- ankylosing spondylitis -- sacroiliitis -- quantitative imaging; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.25559
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : Purpose: To investigate the feasibility of using quantitative dynamic contrast enhanced magnetic resonance imaging (DCE‐MRI) to differentiate the active and inactive stage of sacroiliitis and the correlation between quantitative parameters and disease activity as measured by clinical scores. Materials and Methods: Forty‐two patients with ankylosing spondylitis underwent DCE‐MRI on a 3.0T MRI unit. According to the results of the blood sedimentation rate (ESR), C‐reactive protein (CRP), and Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the patients were grouped into inactive and active groups. Pharmacokinetic models were used to generate the semiquantitative and quantitative hemodynamic parameters of DCE‐MRI. The between‐group differences were analyzed using the Wilcoxon rank sum test, and the correlations between the pharmacokinetic parameters and BASDAI score were analyzed using Spearman's correlation coefficient. The efficacies of different parameters in differentiating the active and inactive phase of sacroiliitis were evaluated and compared using receiver operator characteristics (ROC) curve analysis. Results: K trans, Kep, Ve, time to peak (TTP), max concentration (MAX Conc), and area under the curve (AUC) of the active group were significantly higher than those of the inactive stage group ( P < 0.05). There were significant correlations between all parameters and BASDAI ( P < 0.05). AUC of the receiver operator characteristics curve (AUCR ) of different parameters were not statistically different ( P >0.05), except between AUC and MAX Conc ( P = 0.0012). Conclusion: Quantitative DCE‐MRI parameters can differentiate between active and inactive ankylosing spondylitis. Among those, K trans had the highest correlation coefficient with the BASDAI score. Level of Evidence: 2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:71–78