Application of Dynamic Contrast-Enhanced MRI in the Diagnosis of Rheumatoid Arthritis. (21st June 2022)

• Record Type: Journal Article
• Authors: Zhang, Bin; Xiao, Li; Zhou, Hui; Li, Ming; Wang, Jingming; Guo, Lina
• Other Names: Chumnanvej Sorayouth Academic Editor.
• Is Part Of: Contrast media & molecular imaging. Volume 2022(2022)
• Publication Date: 2022-06-21
• Subjects: Diagnostic imaging -- Periodicals; Magnetic resonance imaging -- Periodicals; Contrast media (Diagnostic imaging) -- Periodicals; Contrast Media -- Periodicals; Diagnostic Imaging -- Periodicals; Substances de contraste -- Périodiques; Diagnostics moléculaires -- Périodiques; Imagerie médicale; Substance de contraste; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.0754
• DOI: 10.1155/2022/3055465
• Languages: English
• ISSNs: 1555-4309

Abstract

Abstract : In order to solve the application problem of dynamic contrast-enhanced MRI in the diagnosis of rheumatoid arthritis, this paper proposes application research based on dynamic contrast-enhanced MRI in the staging diagnosis of rheumatoid arthritis. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has a high value in evaluating the activity of patients with early rheumatoid arthritis (RA). This paper discusses the correlation between hemodynamic parameters and omeractramris score, clinical laboratory indexes, and activity score (DAS28), analyzes its feasibility in evaluating the prognosis of RA, and provides a reliable basis for the rational formulation of an early RA treatment plan. After reviewing the previous cases, 33 patients with subclinical synovitis of RA were selected for wrist joint contrast-enhanced ultrasonography. The data were analyzed by contrast-enhanced software, and the quantitative parameters of contrast-enhanced were obtained: start development time (AT), peak time (TTP), peak intensity (PI), grad gradient, and area under the curve (AUC). The synovial blood supply was classified by CEUS, and the CEUS blood supply classification and power Doppler (PDUS) blood supply classification were compared. The results of regression analysis showed that AUC (or = 1.026, 95% CI: 1.001–1.052) and PI (or = 1.561, 95% CI: 1.019–2.393) were independent risk factors for predicting the aggravation of the disease. The diagnostic efficacy of AUC and PI in predicting the aggravation of the disease was analyzed. The areas under the ROC curve of AUC and PI were 0.935 and 0.927, respectively, and the difference between them was not statistically significant.