Role of Vesical Imaging–Reporting and Data System in predicting muscle‐invasive bladder cancer: A diagnostic meta‐analysis
The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging–Reporting and Data System for predicting muscle‐invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper...
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Published in | International journal of urology Vol. 29; no. 3; pp. 186 - 195 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
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01.03.2022
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Abstract | The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging–Reporting and Data System for predicting muscle‐invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging–Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies‐2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta‐regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut‐off point was 3, the pooled sensitivity and specificity were 0.92 (0.89–0.94) and 0.85 (0.78–0.90), respectively, and 0.82 (0.75–0.88) and 0.95 (0.91–0.97), respectively, when the cut‐off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion‐weighted imaging, and dynamic contrast‐enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut‐off point was 3 and specificity heterogeneity when the cut‐off point was 4. Multiple image acquisition plane of diffusion‐weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion‐weighted imaging in both the Vesical Imaging–Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging–Reporting and Data System 4 group. Another significant source of heterogeneity was the cut‐off point. The diagnostic performance of the Vesical Imaging–Reporting and Data System for predicting muscle‐invasive bladder cancer was excellent in both cut‐off points of the Vesical Imaging–Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion‐weighted imaging should be given more attention in the Vesical Imaging–Reporting and Data System. |
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AbstractList | The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging–Reporting and Data System for predicting muscle‐invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging–Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies‐2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta‐regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut‐off point was 3, the pooled sensitivity and specificity were 0.92 (0.89–0.94) and 0.85 (0.78–0.90), respectively, and 0.82 (0.75–0.88) and 0.95 (0.91–0.97), respectively, when the cut‐off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion‐weighted imaging, and dynamic contrast‐enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut‐off point was 3 and specificity heterogeneity when the cut‐off point was 4. Multiple image acquisition plane of diffusion‐weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion‐weighted imaging in both the Vesical Imaging–Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging–Reporting and Data System 4 group. Another significant source of heterogeneity was the cut‐off point. The diagnostic performance of the Vesical Imaging–Reporting and Data System for predicting muscle‐invasive bladder cancer was excellent in both cut‐off points of the Vesical Imaging–Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion‐weighted imaging should be given more attention in the Vesical Imaging–Reporting and Data System. The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging-Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta-regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut-off point was 3, the pooled sensitivity and specificity were 0.92 (0.89-0.94) and 0.85 (0.78-0.90), respectively, and 0.82 (0.75-0.88) and 0.95 (0.91-0.97), respectively, when the cut-off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut-off point was 3 and specificity heterogeneity when the cut-off point was 4. Multiple image acquisition plane of diffusion-weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion-weighted imaging in both the Vesical Imaging-Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging-Reporting and Data System 4 group. Another significant source of heterogeneity was the cut-off point. The diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer was excellent in both cut-off points of the Vesical Imaging-Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion-weighted imaging should be given more attention in the Vesical Imaging-Reporting and Data System.The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging-Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta-regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut-off point was 3, the pooled sensitivity and specificity were 0.92 (0.89-0.94) and 0.85 (0.78-0.90), respectively, and 0.82 (0.75-0.88) and 0.95 (0.91-0.97), respectively, when the cut-off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut-off point was 3 and specificity heterogeneity when the cut-off point was 4. Multiple image acquisition plane of diffusion-weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion-weighted imaging in both the Vesical Imaging-Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging-Reporting and Data System 4 group. Another significant source of heterogeneity was the cut-off point. The diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer was excellent in both cut-off points of the Vesical Imaging-Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion-weighted imaging should be given more attention in the Vesical Imaging-Reporting and Data System. |
Author | Cao, Qiang Zhang, Yudong Wu, Qikai Li, Pengchao Sun, Xueying Yuan, Baorui Lu, Qiang Cai, Lingkai Zhuang, Juntao Yang, Xiao |
Author_xml | – sequence: 1 givenname: Baorui surname: Yuan fullname: Yuan, Baorui organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 2 givenname: Lingkai surname: Cai fullname: Cai, Lingkai organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 3 givenname: Qiang surname: Cao fullname: Cao, Qiang organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 4 givenname: Qikai surname: Wu fullname: Wu, Qikai organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 5 givenname: Juntao surname: Zhuang fullname: Zhuang, Juntao organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 6 givenname: Xueying surname: Sun fullname: Sun, Xueying organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 7 givenname: Yudong surname: Zhang fullname: Zhang, Yudong organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 8 givenname: Pengchao surname: Li fullname: Li, Pengchao organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 9 givenname: Xiao surname: Yang fullname: Yang, Xiao organization: The First Affiliated Hospital of Nanjing Medical University – sequence: 10 givenname: Qiang orcidid: 0000-0003-3589-2507 surname: Lu fullname: Lu, Qiang email: doctorlvqiang@sina.com organization: The First Affiliated Hospital of Nanjing Medical University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34923686$$D View this record in MEDLINE/PubMed |
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Keywords | multiparametric magnetic resonance imagine urothelial carcinoma muscle-invasive bladder cancer staging Vesical Imaging-Reporting and Data System |
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SubjectTerms | Bladder cancer Cancer Diffusion Magnetic Resonance Imaging Humans Invasiveness Magnetic resonance imaging Magnetic Resonance Imaging - methods Meta-analysis multiparametric magnetic resonance imagine Muscles muscle‐invasive bladder cancer Patients Quality control Sensitivity and Specificity staging Urinary Bladder - diagnostic imaging Urinary Bladder - pathology Urinary Bladder Neoplasms - diagnostic imaging Urinary Bladder Neoplasms - pathology urothelial carcinoma Vesical Imaging–Reporting and Data System |
Title | Role of Vesical Imaging–Reporting and Data System in predicting muscle‐invasive bladder cancer: A diagnostic meta‐analysis |
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