Quantitation of bladder cancer for the prediction of muscle layer invasion as a complement to the vesical imaging-reporting and data system

• Published in: European radiology 2021-03, Vol.31 (3), p.1656-1666
• Main Authors: Ahn, Hyungwoo, Hwang, Sung Il, Lee, Hak Jong, Choe, Gheeyoung, Oh, Jong Jin, Jeong, Seong Jin, Byun, Seok-Soo, Kim, Jung Kwon
• Format: Article
• Language: English
• Subjects: Accuracy; Bladder; Bladder cancer; Cancer; Contact length; Correlation coefficient; Correlation coefficients; Diagnostic Radiology; Diagnostic systems; Generalized linear models; Humans; Imaging; Indicators; Internal Medicine; Interventional Radiology; Magnetic resonance imaging; Medical imaging; Medicine; Medicine & Public Health; Muscles; Muscles - pathology; Neoplasm Invasiveness - pathology; Neoplasm Staging; Neuroradiology; Quantitation; Radiology; Regression analysis; Reproducibility of Results; Retrospective Studies; Statistical models; Tumors; Ultrasound; Urinary Bladder Neoplasms - diagnostic imaging; Urinary Bladder Neoplasms - pathology; Urogenital
• ISSN: 0938-7994; 1432-1084
• DOI: 10.1007/s00330-020-07224-7

Objectives To examine the diagnostic performance of Vesical Imaging-Reporting and Data System (VIRADS) and to find a quantitative indicator for predicting muscle layer invasion of bladder cancer. Methods 3-T MRI of 82 patients performed before transurethral resection of bladder tumors or radical cystectomy between July 2018 and June 2019 were retrospectively analyzed. For one index lesion of each patient, two radiologists independently assigned VIRADS score and measured tumor-wall interface (contact length between tumor and bladder wall) on T2-weighted, diffusion-weighted, and dynamic contrast-enhanced MRI. Inter-reader agreement was assessed, and logistic regression analysis was performed to find indicators of muscle layer invasion. Comparison of indicators’ diagnostic performance was done with receiver operating characteristic (ROC) curve and generalized linear model analyses. Optimal cutoff point was determined by the Youden index J . Results Inter-reader agreement was at least substantial for VIRADS categorization ( κ 0.77–0.81), and almost perfect for tumor-wall interface (intraclass correlation coefficient 0.88–0.90). Tumor-wall interface (odds ratio [OR] 1.90–2.00) and VIRADS score (OR 8.59–8.89) were independently associated with muscle layer invasion ( p  ≤ 0.02). For VIRADS, area under the ROC curve (AUROC) was 0.94, and the accuracy was 0.93 at score 3, the optimal threshold for predicting muscle layer invasion. Depending on the MRI sequence, tumor-wall interface showed AUROCs of 0.90–0.92 and accuracy of 0.84–0.90 at suggested thresholds (3 ± 0.3 cm). Tumor-wall interface showed insignificant differences in accuracy compared with VIRADS ( p > 0.10), except as measured on diffusion-weighted images ( p = 0.01). Conclusions VIRADS is a good predictor of muscle layer invasion. As an independent quantitative indicator, tumor-wall interface may complement VIRADS to enhance prediction. Key Points • Vesical Imaging-Reporting and Data System (VIRADS) is a promising predictor of muscle invasion of bladder cancer with good reproducibility, as suggested by previous studies. • VIRADS score and the tumor-wall interface (curvilinear contact length between the tumor and the bladder wall) are independent predictors of muscle layer invasion. • As an easy-to-use quantitative indicator, tumor-wall interface is expected to be used as an indicator complementary to VIRADS, a qualitative indicator.