New Meta-Analysis Confirms High Diagnostic Performance of Vesical Imaging-Reporting and Data System (VI-RADS) in Suspected Muscle-invasive Bladder Cancer

Among patients with bladder cancer, approximately 75% present with early-stage disease, i.e., non-muscle-invasive bladder cancer (NMIBC). The other 25% present with muscle-invasive bladder cancer (MIBC), with a high risk of metastasis and death associated with distant metastases. NMIBC is a heterogeneous disease with variable risks of recurrence, progression, and death. Low-risk tumors (e.g., Ta and low grade) often recur, but they are seldom lethal in the absence of progression.¹ However, more aggressive cancers (e.g., T1, high grade) frequently progress to muscle-invasive disease,¹ which carries a high risk of mortality. Accurate and precise staging of bladder cancer at the time of diagnosis, and the ability to predict risk of progression, is critical for determining the optimal treatment for individual patients.

Proper clinical staging of a newly diagnosed patient will primarily involve physical examination, including a bimanual examination under anesthesia, pathologic review of the transurethral resection (TURBT) specimen, and a cross-sectional contrast enhanced CT scan of the abdomen and pelvis. Despite the comprehensive clinical staging protocol, reports of disease upstaging on pathologic specimen after definitive therapy, such as radical cystectomy, are as high as 41%.⁹ The role of cross-sectional imaging is emphasized prior to TURBT, especially when there is significant concern for muscle invasive disease as obtaining imaging after TURBT can result in false positive suspicion for muscle invasion³. Radiologic analyses of bladder cancer patients have shown that contrast enhanced CT alone yields specificities up to 92%⁴. In comparison to computed tomography (CT), MRI has been shown to have greater accuracy in differentiating the clinical stage of the tumor compared to CT, especially with contrast enhancement and newer 3T MRI machines³. In comparison to CT, MRI can be utilized several times throughout the treatment course to evaluate tumor burden due to the lack of radiation exposure. Furthermore, cross sectional imaging can help identify predictors of advanced disease such as hydronephrosis and nodal disease.

The Vesical Image-Reporting and Data System (VI-RADS) is a structured reporting algorithm that was introduced to provide a systemic and standardized approach incorporating findings on T2-weighted, diffusion weighted imaging, and dynamic contrast-enhanced mpMRI sequences to convey the likelihood of MIBC³ Its development and introduction followed the earlier success of a similar algorithm, PI-RADS,  for mpMRI in the evaluation of suspected prostate cancer in the treatment-naive prostate. This has been widely adopted and has been reported to have revolutionized clinical practice in the detection, characterization, and management of prostate cancer.⁴ Other benefits of using a standard reporting system include improving communication among healthcare providers and better comparison of patient characteristics.

The VI-RADS consists of a 5-point category scale for MRI of the bladder that allows the radiologist to assign a numbered category to bladder lesions that defines the risk of muscle invasiveness. VI-RADS 1 and 2 represent, respectively, very low and low likelihood of muscle invasion; VI-RADS 3 indicates that the presence of muscle invasion is equivocal; and VI-RADS 4 and 5 represent, respectively, high and very high likelihood of muscle invasion. VI-RADS ≥3 is usually regarded as indicating MIBC, with information on VI-RADS 4 also considered useful. The VI-RADS score has been validated in a number of studies that showed good diagnostic performance in detecting MIBC.^5-7

A recently reported meta-analysis of the utility of VI-RADS in diagnosing MIBC, published in Urologic Oncology,⁸ also concluded that VI-RADS shows high diagnostic performance in detection of MIBC. Researchers from the Department of Urology at the University of Florida College of Medicine, Jacksonville, led by Mark Bandyk, MD, MPH, MS, searched the Scopus, Wen of Science, PubMed, and EMBASE databases for articles reporting studies of VI-RADS use in bladder cancer published up to March 2021 in any language. They also reviewed bibliographies of relevant reviews and guidelines to ensure that no additional articles were missed. After excluding duplicates and articles that were considered irrelevant or that contained insufficient data, 22 articles, all published between 2019 and 2021, were included in the meta-analysis.

The 22 articles reported studies mainly conducted at single centers (18) in Asia (13 studies), Europe (6), Africa (2) and South America (1). They involved a total of 2576 patients enrolled between 2010 and 2020. The mean age of the patients ranged from 57.1 to 73.5 years and the majority (71.0% to 94.4%) were male, consistent with known bladder cancer epidemiology. MIBC prevalence ranged from 18.4% to 57.0% (35% of all participants). Thirteen studies used 3-T MRI, 7 studies 1.5-T MRI, and the other 2 studies either 1.5- or 3-T MRI.

Pooled analysis of sensitivity and specificity values for all VI-RADS scores demonstrated that VI-RADS ≥3 had maximum diagnostic performance with sensitivity and specificity of 89% and 84%, respectively. For VI-RADS ≥4, pooled analysis showed a higher specificity (94%), but due to lower sensitivity (77%), the cutoff of VI-RADS ≥3 would be preferable in clinical practice, the investigators suggest. Evaluation of the accuracy of VI-RADS using the area under the curve (AUC) of hierarchical summary receive operating characteristics (HSROC) revealed that the VI-RADS had an accuracy of 0.93 at cutoff values of 3 and 4. VI-RADS ≥3 was also shown to be the optimum cutoff value for MIBC prediction when only one radiologist interpreted MRI reports and rated VI-RADS scores. When a consensus report of MIR findings and VI-RADS was achieved by more than one radiologist, VI-RADS ≥4 was the optimum cutoff for MIBC detection, but the accuracy was 0.94 compared with 0.95 at the cutoff of 3.

Studies that used scanners of 3 T and T2WI slide thickness of 2 or 3 mm had higher sensitivity than those that used 1.5 T scanners and T2WI thickness of 4 or 5 mm at VI-RADS ≥3. The number of radiologists (1 vs ≥2) involved, and histology of tumors significantly affected only sensitivity. Higher pooled sensitivity was seen with consensus vs individual reports, but the increased number of readers on consensus reports was associated with decreased pooled sensitivity. However, this finding is of little practical value, the investigators comment.

The investigators concluded that VI-RADS can improve staging evaluation of bladder cancer patients and can point to whether early or late endoscopic interventions are needed. However, they cautioned that VI-RADS cannot evaluate the presence of important prognostic factors such as carcinoma in situ, lymphovascular invasion, or histological variants, or detect extravesical involvement.

The data also provide evidence in support of the role of mpMRI in the management of bladder cancer. Although current guidelines recommend cross-sectional imaging, the improved diagnostic accuracy of mpMRI, especially through the utility of standardized reporting systems such as VI-RADS can improve patient care substantially by providing the entire treatment team from the surgeon to the pathologist with more accurate information. For the surgeon, mpMRI can provide information that can assist in both initial TURBT or repeat-TURBT, thereby improving the pathologic sample that the pathologist will examine. The researchers involved in the latest meta-analysis  suggest that future studies should examine factors that might impact the performance of MRI in detecting muscle invasion, including timing (whether it should be performed before or after initial TURBT), newly diagnosed vs recurrent tumors, and the location of the tumor in the bladder.

Akhil Abraham Saji, MD is a urology resident at New York Medical College / Westchester Medical Center. His interests include urology education and machine learning applications in urologic care. He is a founding and current member of the EMPIRE Urology New York AUA section team.  

References 

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