To evaluate role of Multiparametric MRI in differentiation between invasive and non-invasive bladder cancer and accuracy of vesical imaging reporting and data system (VI-RADS) score.

Fifty patients diagnosed as cancer bladder were enrolled in this study, mp-MRI including conventional (T1WI and high resolution T2WI) and functional sequences (Diffusion WI and DCE-MRI) were done, all data were regrouped to evaluate the accuracy of each separate sequence and mp-MRI in distinguishing non-muscle invasive from muscle-invasive tumors, with VI-RADS score application and comparison with pathological findings, then interobserver agreement for detection of muscle invasion according to mp-MRI and VI-RADS scoring system findings was calculated.

Diagnostic accuracy of mp-MRI in differentiation between muscle invasive (MIBC) and non-muscle invasive bladder cancer (NMIBC) was (84%) with highest sensitivity (78%), very good agreement between mp-MRI and histopathological data (k = 0.87), and highest area under curve (AUC) reaching 0.83, DCE-MRI sequence showed the highest accuracy in muscle invasion detection by (88%), with highest AUC 0.83. Diagnostic accuracy of VI-RADS score in detection of muscle invasion was 84%, with specificity and negative predictive value of 88% and AUC was 0.83. Interobserver agreement was strong as regard diagnostic performance of mp-MRI and VI-RADS scoring for detection of muscle invasion reaching (K = 0.82, p < 0.001) and (K = 0.87, p < 0.001) respectively.

mp-MRI is considered as comprehensive and effective tool for determination of muscle invasion in cases of urinary bladder cancer. Also VI-RADS scoring system can accurately differentiate between invasive and non-invasive bladder cancer.

The VI-RADS system was recently suggested for the uniform evaluation of muscle invasion in cancer bladder by mp-MRI. In this paper we applied this system to 50 cases to evaluate its ease and compared the results with the histopathologic findings for evaluation of its accuracy.

The British journal of radiology. 2019 Oct 01 [Epub ahead of print]

Marwa Makboul, Shimaa Farghaly, Islam F Abdelkawi

Lecturer of radio diagnosis, Radio diagnosis department, Faculty of Medicine, Assiut University, Assiut, Egypt.