The Vesical Imaging-Reporting and Data System (VI-RADS) was introduced to standardize bladder magnetic resonance imaging (MRI) interpretation, mainly in treatment-naïve patients. However, most patients undergo MRI after transurethral resection of bladder tumor (TURBT), where postprocedural changes compromise diagnostic accuracy. This study aimed to identify the dominant sequence for post-TURBT VI-RADS scoring, define optimal MRI timing, and evaluate the effect of image quality.
This retrospective single-center study included patients with bladder cancer who underwent TURBT followed by MRI. Three radiologists assigned standard, diffusion-weighted imaging (DWI)-dominant, and dynamic contrast-enhanced (DCE)-dominant VI-RADS scores using a cutoff of ≥3. Histopathology from re-TURBT or cystectomy served as the reference standard. Diagnostic performance was assessed with receiver operating characteristic analysis and stratified by time interval (<2 wk, 2-4 wk, >4 wk) and VI-RADS Quality Score (QS). Inter-reader agreement was evaluated using pairwise Cohen's κ and overall Fleiss' κ.
The final cohort comprised 123 patients. Standard and DCE-dominant VI-RADS produced identical results (area under the curve [AUC] = 0.81; sensitivity = 95%; specificity = 67%; accuracy = 77%). For DWI-dominant VI-RADS, AUC ranged from 0.86 to 0.95 and accuracy from 86% to 96% across readers. Inter-reader agreement was excellent (overall Fleiss' κ = 0.91-0.96; pairwise Cohen's κ = up to 0.98). Diagnostic accuracy varied by time interval, reaching its lowest within 2 wk (specificity = 13%, accuracy = 26%) and improving at 2-4 wk (accuracy = 94-98%). Accuracy also improved with increasing QS. The study is limited by its retrospective design and single-center setting.
Bladder MRI after TURBT remains accurate when timing, sequence weighting, and image quality are considered. DWI-dominant VI-RADS shows numerically higher diagnostic estimates. Scheduling MRI ≥2-4 wk after TURBT and ensuring adequate image quality may improve reliability.
European urology oncology. 2026 Jul 17 [Epub ahead of print]
Ailin Dehghanpour, Martina Pecoraro, Gu-Mu-Yang Zhang, Antonella Borrelli, Ludovica Laschena, Francesca Mezzapesa, Riccardo Mastroianni, Emanuele Messina, Fabio Massimo Magliocca, Giuseppe Simone, Valeria Panebianco
Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy; Department of Experimental Medicine, Sapienza University of Rome, Italy., Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy., Department of Radiology, State Key Laboratory of Complex Severe and Rare Disease, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China., Uro-oncology Program, IRCCS Regina Elena National Cancer Institute, Rome, Italy., Department of Pathology, University Sapienza, Rome, Italy., Department of Radiological Sciences, Oncology and Pathology, Sapienza University/Policlinico Umberto I, Rome, Italy. Electronic address: .