Abstract #4278

VI-RADS combined with decision tree model preoperatively predict the pathological grade of bladder cancer with high (≥3) and low (≤2) scores

Bohong Cao¹, Qing Li¹, Shuai Jiang¹, Yunfei Zhang², Yongming Dai², and Jianjun Zhou¹

¹Zhongshan Hospital, Fudan University, Shanghai, China, ²MR Collaboration, Central Research Institute, United Imaging Healthcare, Shanghai, China

Synopsis

Keywords: Urogenital, BladderBladder cancer pathology grading is currently obtained mainly by invasive cystoscopic biopsy or surgical pathology. This study aimed to investigate the effectiveness of Vesical Imaging Reporting and Data System (VI-RADS) in the diagnosis of high-grade bladder cancer (HG-BC) and explore a new preoperative non-invasive grading prediction system. We demonstrate that most bladder cancers with a VI-RADS score ≥3 are high-grade and that the decision tree model is a good predictor of pathological grading in patients with VI-RADS ≤2. Thus, VI-RADS can be a grouping imaging biomarker for noninvasive prediction of bladder cancer grade.

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