Accuracy of the Vesical Imaging–Reporting and Data System (VIRADS) for pre-treatment staging of bladder cancer in an Australian cohort

Shiwei Huang*, James Bain, Ting Wai Yiu, Daniel Gilbourd, Tarun Jain, Rajeev Jyoti*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Introduction: To evaluate the performance of the Vesical Imaging–Reporting and Data System (VIRADS) in differentiating muscle-invasive and non-muscle-invasive bladder cancer and whether this reporting system improves inter-reader agreement. Methods: Sixty-four cases of multiparametric 3 tesla bladder MRI from January 2014 to May 2020 were reviewed retrospectively. T2-weighted, diffusion and post-contrast images were reviewed. All magnetic resonance images were reported by a radiologist with 15 years’ experience (Reader 1) and a final year radiology trainee with a special interest in urogenital imaging with 3 years of experience (Reader 2). Both readers were blinded to clinical history and histopathology results when scoring each lesion. Results: The sensitivity and specificity for differentiating MIBC and NMIBC were 91% and 68%, respectively, for Reader 1 and 91% and 63%, respectively, for Reader 2. The inter-reader agreement for assigning VIRADS scores was 0.79. The area under the receiver operator curve for Reader 1 and 2 were not significantly different (Reader 1 = 0.79, Reader 2 = 0.77, P = 0.83). Conclusions: Staging of bladder cancer prior to treatment can be accurately and reliably diagnosed using VIRADS, a novel, standardised reporting system for bladder MRI.

Original languageEnglish
Pages (from-to)370-376
Number of pages7
JournalJournal of Medical Imaging and Radiation Oncology
Volume66
Issue number3
DOIs
Publication statusPublished - 2021

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