Purpose: Evaluate the diagnostic accuracy of multi-parametric magnetic resonance imaging (mp-MRI) for local staging of bladder cancer (BCa). Materials and Methods: The databases of PubMed, Web of Science, Wanfang, and CNKI were searched for related literatures about BCa diagnosed by mp-MRI from January 1, 2000 to April 12, 2019. The strict inclusion and exclusion criteria were set up to extract records. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 was used to evaluate quality of the candidate studies. The pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (-LR), and diagnostic odds ratio (DOR) were calculated to assess the diagnostic authenticity of mp-MRI. The summarized receiver operating characteristic (SROC) curve corresponding with the area under the curve (AUC) were analyzed to comprehensively evacuate the diagnostic value of mp-MRI. Results: A total of 140 studies were retrieved by computer-based searching. After quality control, 4 studies with 259 patients were enrolled for meta-analysis. The pooled results showed 0.84 of sensitivity [95% confidence interval (CI) = 0.79-0.89], 0.91 of specificity (95% CI = 0.87-0.93), 8.24 of +LR (95% CI = 4.87-13.92), 0.18 of -LR (95% CI = 0.10-0.31), 49.42 of DOR (95% CI = 19.07-128.09), and 0.946 of AUC. The Spearman correlation analysis found no threshold effect (p = 0.684). A significant heterogeneity existed among 4 included studies with sensitivity (I2 = 65.7%), specificity (I2 = 60.0%) and diagnostic OR (I2 = 67.5%). The Begg’s test (p = 0.497) and the egger’s test (p = 0.337) found no publication bias. Conclusion: mp-MRI acts a good diagnostic performance for bladder cancer. It is plausible that mpMRIs can be used as an important method for bladder cancer staging.

Frontiers in oncology. 2019 Oct 04*** epublish ***

Nieke Zhang, Xiaoyan Wang, Chunying Wang, Shuqiu Chen, Jianping Wu, Guangyuan Zhang, Weidong Zhu, Jing Liu, Bin Xu, Mulong Du, Ming Chen

Department of Urology, Affiliated Zhongda Hospital of Southeast University, Nanjing, China., Department of Nursing, Affiliated Zhongda Hospital of Southeast University, Nanjing, China., Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Department of Environmental Genomics, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.