Vesical Imaging-Reporting and Data System for Multiparametric MRI to Predict the Presence of Muscle Invasion for Bladder Cancer

Seung Baek Hong; Nam Kyung Lee; Suk Kim; Il Wan Son; Hong Koo Ha; Ja Yoon Ku; Kyung Hwan Kim; Won Young Park

doi:10.1002/jmri.27141

Vesical Imaging-Reporting and Data System for Multiparametric MRI to Predict the Presence of Muscle Invasion for Bladder Cancer

J Magn Reson Imaging. 2020 Oct;52(4):1249-1256. doi: 10.1002/jmri.27141. Epub 2020 Mar 27.

Authors

Seung Baek Hong¹, Nam Kyung Lee¹, Suk Kim¹, Il Wan Son¹, Hong Koo Ha², Ja Yoon Ku², Kyung Hwan Kim², Won Young Park³

Affiliations

¹ Department of Radiology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Busan, Korea.
² Department of Urology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Busan, Korea.
³ Department of Pathology, Biomedical Research Institute, Pusan National University Hospital, and Pusan National University School of Medicine, Busan, Korea.

PMID: 32220105
DOI: 10.1002/jmri.27141

Abstract

Background: The Vesical Imaging-Reporting and Data System (VI-RADS) is a newly developed system of bladder cancer staging with multiparametric MRI (mpMRI), which can be used to predict the presence of muscle invasion for bladder cancer.

Purpose: To evaluate the accuracy of three mpMRI series (T₂ WI, diffusion-weighted imaging [DWI], and dynamic contrast-enhanced image [DCEI]) and VI-RADS for diagnosing the muscle invasive bladder cancer (MIBC).

Study type: Retrospective.

Population: In all, 66 pathologically proven bladder cancers in 32 patients.

Field strength/sequence: Before the diagnostic MRI with an intramuscular antispasmodic agent, optimal bladder distension was confirmed. 3.0T MRI with T₂ WI, DWI, and DCEI.

Assessment: Three reviewers independently assessed and scored the bladder cancers in T₂ WI, DWI, and DCEI using a five-point score system. Based on the scores in the three sequences, reviewers scored each bladder cancer with reference to VI-RADS categories. We evaluated the diagnostic performance of each of three mpMRI sequences and the final VI-RADS categorization for diagnosing MIBC.

Statistical tests: Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and the area under the curve (AUC) of each of three sequences separately and VI-RADS categorization for diagnosing the MIBC.

Results: The diagnostic performances of each of the three mpMRI series and VI-RADS for diagnosing MIBC were excellent. Especially using the optimal cutoff score >3 for predicting MIBC on DWI, DCEI, and VI-RADS, the sensitivity, specificity, PPV, NPV, and AUC values were 90% (95% confidence interval [CI]: 0.56, 1.00), 100% (95% CI: 0.94, 1.00), 100% (95% CI: 0.66. 1.00), 98.3% (95% CI: 0.91, 1.00), and 0.95, respectively. DATA CONCLUSION: mpMRI based on VI-RADS can stratify patients with bladder cancer according to the presence of muscle invasion.

Level of evidence: 3.

Technical efficacy stage: 2. J. Magn. Reson. Imaging 2020;52:1249-1256.

Keywords: diagnosis; magnetic resonance imaging; neoplasm; tumor staging; urinary bladder.

MeSH terms

Humans
Male
Multiparametric Magnetic Resonance Imaging*
Muscles
Prostatic Neoplasms*
Retrospective Studies
Urinary Bladder Neoplasms* / diagnostic imaging