Evaluation of the Accuracy of Multi-Parametric MRI with Adding St-ADC Values in the Detection of Muscle Invasion in Bladder Cancer Using the Vesical Imaging-Reporting and Data System (VI-RADS)
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Abstract
Background: Bladder cancer is the 9th most prevalent cancer globally and the 7th in men. Treatment depends on muscle invasion status. Traditionally, staging relies on clinical exams, transurethral resection of bladder tumor specimens (TURB), and imaging. Multiparametric MRI (mp-MRI) is regarded as the optimal imaging for local staging and can complement TURBT. Vesical Imaging-Reporting and Data System (VI-RADS) offers a 5-point scoring system based on various MRI sequences to assess the likelihood of muscle invasion. This study evaluate VI-RADS diagnostic accuracy and the impact of standardized tumor ADC (sT-ADC) values on its sensitivity and specificity.
The aim of the study is to evaluate the accuracy of mp-MRI use (adding sT-ADC values) before TURBT in bladder cancer patients using VI-RADS for discrimination between NMIBC and MIBC.
Materials and methods: This study included 65 patients with suspected bladder cancer who underwent mp-MRI and transurethral biopsy. Two radiologists independently assessed the images. Histopathology confirmed tumor grade and muscle invasion. Statistical analysis evaluated VI-RADS and sT-ADC accuracy for detecting muscle-invasive cancer.
Results: ROC analysis identified a VI-RADS score of ≥3 as the best predictor for MIBC, with 91.5% accuracy, 97.3% sensitivity, and 81.8% specificity (AUC 0.98). For sT-ADC, significant differences were found between NMIBC and MIBC (p < 0.001), with 83.7% accuracy at a cut-off of 0.895 (AUC 88.8%). Combining VI-RADS and sT-ADC yielded 100% sensitivity and NPV when results conflicted, and 100% specificity and PPV when both tests agreed.
Conclusion: The Vesical Imaging-Reporting and Data System (VI-RADS) is a thorough scoring system with perfect sensitivity, specificity, and diagnostic value for assessment of deep muscle invasion in bladder cancer cases with a promising add on value regarding the use of ADC in assessment.