Abstract

To examine the clinical significance of the Vesical Imaging-Reporting and Data System (VI-RADS) in predicting outcome of multimodal treatment (MMT) in muscle-invasive bladder cancer (MIBC) patients. We reviewed 78 pathologically proven MIBC patients who underwent MMT including transurethral resection and chemoradiotherapy, followed by partial or radical cystectomy. Treatment response was assessed through histologic evaluation of cystectomy specimens. Two radiologists categorized the index lesions of pretherapeutic MRI according to the 5-point VI-RADS score. The associations of VI-RADS score with the therapeutic effect of MMT were analyzed. The diagnostic performance of VI-RADS scores with a cut-off VI-RADS scores ≤ 2 or ≤ 3 for predicting pathologic complete response to MMT (MMT-CR) was evaluated. MMT-CR was achieved in 2 (100%) of VI-RADS score 1 (n = 2), 16 (84%) of score 2 (n = 19), 12 (86%) of score 3 (n = 14), 7 (64%) of score 4 (n = 11), and 14 (44%) of score 5 (n = 32). VI-RADS score was inversely associated with the incidence of MMT-CR (p = 0.00049). The cut-off VI-RADS score ≤ 2 and ≤ 3 could predict the favorable therapeutic outcome of MMT with high specificity (0.89 with 95% confidence interval [CI]: 0.71-0.98 and 0.82 with 95% CI: 0.62-0.94, respectively) and high positive predictive value (0.86 with 95% CI: 0.64-0.97 and 0.86 with 95% CI: 0.70-0.95, respectively). VI-RADS score may serve as an imaging marker in MIBC patients for predicting the therapeutic outcome of MMT. Muscle-invasive bladder cancer patients with a lower Vesical Imaging-Reporting and Data System score can be a good candidate for bladder-sparing treatment incorporating multimodal treatment. • Vesical Imaging-Reporting and Data System (VI-RADS) score was potentially valuable for classifying pathologic tumor response in patients with muscle-invasive bladder cancer. • The likelihood of achieving complete response of multimodal treatment (MMT) decreased with increasing VI-RADS score. • VI-RADS score could serve as an imaging marker that optimizes patient selection for MMT.

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