Diagnostic Performance of Vesical Imaging Reporting and Data System for the Prediction of Muscle-invasive Bladder Cancer: A Systematic Review and Meta-analysis

Abstract

Context: A noninvasive multiparametric magnetic resonance imaging (MRI)-based scoring system for predicting muscle-invasive bladder cancer (MIBC), the "Vesical Imaging Reporting and Data System" (VI-RADS), was recently developed by an international multidisciplinary panel. Since then, a few studies evaluating the value of VI-RADS for predicting MIBC have been published.

Objective: To review the diagnostic performance of VI-RADS for the prediction of MIBC.

Evidence acquisition: PubMed and EMBASE databases were searched up to November 10, 2019. We included diagnostic accuracy studies using VI-RADS to predict MIBC using cystectomy or transurethral resection as the reference standard. Methodological quality was evaluated with Quality Assessment of Diagnostic Accuracy Studies-2. Sensitivity and specificity were pooled and plotted using hierarchical summary receiver operating characteristics (HSROC) modeling. Meta-regression analyses were done to explore heterogeneity.

Evidence synthesis: Six studies (1770 patients) were included. Pooled sensitivity and specificity were 0.83 (95% confidence interval [CI] 0.70-0.90) and 0.90 (95% CI 0.83-0.95), and the area under the HSROC curve was 0.94 (95% CI 0.91-0.95). Heterogeneity was present among the studies (Q = 29.442, p < 0.01; I² = 87.93%, and 90.99% for sensitivity and specificity). Meta-regression analyses showed that the number of patients (>205 vs ≤205), magnetic field strength (3 vs 1.5 T), T2-weighted image slice thickness (3 vs 4 mm), and VI-RADS cutoff score (≥3 vs ≥4) were significant factors affecting heterogeneity (p ≤ 0.03).

Conclusions: VI-RADS shows good sensitivity and specificity for determining MIBC. Technical factors associated with MRI acquisition and cutoff scores need to be taken into consideration as they may affect performance.

Patient summary: A recently established noninvasive magnetic resonance imaging-based scoring system shows good diagnostic performance in detecting muscle-invasive bladder cancer.

Keywords: Bladder cancer; Magnetic resonance imaging; Meta-analysis; Muscle invasive; Systematic review; Vesical Imaging Reporting and Data System.