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Updated: Feb 17, 2026

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors
Published on: March 29, 2019
The Diagnostic Value of MR Imaging in Differentiating T Staging of Bladder Cancer: A Meta-Analysis
Li Huang1, Qingcong Kong1, Zhenzhen Liu1
1From the Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China (L.H.); and Department of Radiology, the Third Affiliated Hospital, Sun Yat-Sen University, 600 Tianhe Rd, Guangzhou 510630, China (Q.K., Z.L., J.W., Z.K., Y.Z.).
Abstract:
Purpose To assess the diagnostic accuracy of magnetic resonance (MR) imaging for differentiating stage T1 or lower tumors from stage T2 or higher tumors and to analyze the influence of different imaging protocols in patients with bladder cancer. Materials and Methods A systematic literature search for original diagnostic studies was performed in PubMed, Medline, the Cochrane Library, and Web of Science. The methodologic quality of each study was evaluated by two independent reviewers who used the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Data necessary to complete 2 × 2 tables were obtained, and patient, study, and imaging characteristics were extracted. Statistical analysis included data pooling, heterogeneity testing, sensitivity analyses, and forest plot construction. Results Seventeen studies (1449 patients with bladder cancer) could be analyzed. The pooled sensitivity and specificity of MR imaging were 0.90 (95% confidence interval [CI]: 0.83, 0.94) and 0.88 (95% CI: 0.77, 0.94), respectively, for differentiating tumors staged T1 or lower from those staged T2 or higher. Diffusion-weighted imaging and use of higher field strengths (3 T) improved sensitivity (0.92; 95% CI: 0.86, 0.96) and specificity (0.96; 95% CI: 0.93, 0.98). Conclusion This meta-analysis demonstrated high diagnostic performance of MR imaging for differentiating T1 or lower tumors from T2 or higher tumors in patients with bladder cancer. Higher field strength (3 T) and the use of diffusion-weighted imaging can slightly help improve sensitivity and specificity. © RSNA, 2017.
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