To investigate the diagnostic performance of the overall Vesical Imaging Reporting and Data System (VI-RADS) score and its individual magnetic resonance imaging (MRI) parameters in assessing grade and muscle invasiveness of bladder cancer (BC).
This IRB-approved retrospective, single-center, cross-sectional study included patients with BC wo underwent 3 Tesla preoperative multiparametric (mp)-MRI including T2-weighted (T2w), diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) sequences. An independent evaluation according to VI-RADS was performed by two radiologists in separate sessions, blinded to histological findings.
The mean age of 59 included patients was 68.2 (±13.6 standard deviation) years. Among bladder cancer patients, 26 (51%) were identified as high grade and 14 (27.5%) as muscle invasive urothelial carcinomas in histological sections. The area under the curve (AUC) for the overall VI-RADS score to predict muscle invasion was 0.986 (R1) and 0.992 (R2). The AUC to diagnose high grade bladder cancer was 0.908 (R1) and 0.905 (R2). There was no significance difference between the AUC of single parameters (T2w, DWI and DCE) compared to the total VI-RADS score (P > 0.05, respectively). Upon multivariate logistic regression, only the T2w VI-RADS score contributed independently to the diagnosis of high grade and muscle invasive bladder cancer (P = 0.001 (R1) and P = 0.0022 (R2) for high grade cancer; P = 0.0007 (R1) and P = 0.0019 (R2) for muscle invasiveness).
VI-RADS provides high diagnostic accuracy to diagnose high grade and muscle invasive BC. Our results suggest, that mp-MRI parameters provide overlapping information and for sake of clinical simplicity, a biparametric, contrast free image acquisition may be approached without sacrificing diagnostic accuracy.
European journal of radiology. 2021 Jun 24 [Epub ahead of print]
Jasmin Gmeiner, Nathalie Garstka, Thomas H Helbich, Shahrokh F Shariat, Pascal A Baltzer
Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria., Department of Urology, Medical University of Vienna, Vienna, Austria., Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria. Electronic address: .