Vesical Imaging-Reporting and Data System (VI-RADS®): Initial experience in the classification of muscle-invasive bladder cancer

Diagnostic validity of the vesical imaging-reporting and data system (VI-RADS): a real-world study

OBJECTIVES

Preoperative Vesical Imaging-Reporting and Data System (VI-RADS) becomes widespread. We aimed to validate the diagnostic performance of VI-RADS in differentiating muscle-invasive (MIBC) from non-muscle-invasive bladder cancer (NMIBC) in a real-world setting.

METHODS

Between December 2019 and February 2022 suspected primary bladder cancer patients were reviewed. Those with proper multiparametric MRI (mpMRI) protocol for VI-RADS before any invasive treatment were included. Patients were locally staged according to transurethral resection, second resection, or radical cystectomy as the reference standard. Two experienced genitourinary radiologists who were blinded to clinical and histopathological data evaluated the mpMRI images independently and retrospectively. The diagnostic performance of both radiologists and the interreader agreement were analyzed.

RESULTS

Among 96 patients, 20 (20.8%) had MIBC, and 76 (79.2%) had NMIBC. Both radiologists had great diagnostic performance in diagnosing MIBC. The first radiologist had an area under curve (AUC) of 0.83 and 0.84, the sensitivity of 85% and 80%, and the specificity of 80.3% and 88.2% for VI-RADS ≥3 and ≥4, respectively. The second radiologist had an area under curve (AUC) of 0.79 and 0.77, the sensitivity of 85% and 65%, and the specificity of 73.7% and 89.5% for VI-RADS ≥3 and ≥4, respectively. The overall VI-RADS score agreement between the two radiologists was moderate (κ = 0.45).

CONCLUSION

VI-RADS is diagnostically powerful in differentiating MIBC from NMBIC prior to transurethral resection. The agreement between radiologists is moderate.

Can Only the Shape Feature in Radiomics Help Machine Learning Show That Bladder Cancer Has Invaded Muscles?

OBJECTIVES

The presence of muscle invasion is an important factor in establishing a treatment strategy for bladder cancer (BCa). The aim of this study is to reveal the diagnostic performance of radiomic shape features in predicting muscle-invasive BCa.

METHODS

In this study, 60 patients with histologically proven BCa who underwent a preoperative MRI were retrospectively recruited. The whole tumor volume was segmented on apparent diffusion coefficient (ADC) maps and T2W images. Afterward, the shape features of the volume of interest were extracted using PyRadiomics. Machine learning classification was performed using statistically different shape features in MATLAB® (The MathWorks, Inc., Natick, Massachusetts, United States).

RESULTS

The findings revealed that 27 bladder cancer patients had muscle invasion, while 33 had superficial bladder cancer (53 men and seven women; mean age: 62±14). Surface area, volume, and relevant features were significantly greater in the invasive group than in the non-invasive group based on the ADC maps (P<0.05). Superficial bladder cancer had a more spherical form compared to invasive bladder cancer (P=0.05) with both imaging modalities. Flatness and elongation did not differ significantly between groups with either modality (P>0.05). Logistic regression had the highest accuracy of 83.3% (sensitivity 82.8%, specificity 84%) in assessing invasion based on the shape features of ADC maps, while K-nearest neighbors had the highest accuracy of 78.2% (sensitivity 79.1%, specificity 69.4%) in assessing invasion based on T2W images.

CONCLUSIONS

Shape features can be helpful in predicting muscle invasion in bladder cancer using machine learning methods.

To determine correlation between VIRADS scoring and pathological staging in bladder cancer: A prospective study and review of literature

The development of standardized reporting systems is of paramount importance in medical-imaging. Based on the "RADS" methodology, PIRADS and BI-RADS have been successfully used. The management of bladder cancer (BC) depends on the stage at the time of identification. Accurate assessment of the muscle-invasive stage can alter therapies that are radically different. MRI can accurately diagnose this in a standardized manner (Vesical Imaging-Reporting and Data System: VIRADS) and spare additional procedures. The aim of the study is to determine diagnostic accuracy of VIRADS scoring in evaluation of muscle invasiveness in patients with BC. This study was conducted in a single center over a period of 2 years from April 2020. A total of 76 patients with bladder SOL/diagnosed BC were included. Final VIRADS scoring was calculated and compared with histopathological report.76 patients were evaluated which included 64 males and 12 females. Most of the cases came under the VIRADS-II category (23, 30.26%) followed by VIRADS-V (17, 22.36%). VIRADS-I was reported in 14 cases (18.42%). A total of 8 cases (10.52 %) were reported as VIRADS III and 14 cases (18.42%) as VIRADS IV. VIRADS-III was taken as cut off and found to have a sensitivity of 94.44%, a specificity of 87.50%, a positive predictive value of 87.17% and a negative predictive value of 94.59%. Though number of cases are still less to accurately predict test characteristics of VIRADS, our results are consistent with previously done retrospective studies and VIRADS has got good correlation with pathological staging.

Biparametric magnetic resonance imaging assessment for detection of muscle-invasive bladder cancer: a systematic review and meta-analysis

OBJECTIVES

To investigate if removing DCE from the Vesical Imaging Reporting and Data System (VI-RADS) influences the diagnostic accuracy of muscle-invasive bladder cancer (MIBC). We also explored using different reference standards on the MRI diagnostic performance.

METHODS

We searched the Cochrane Library, Embase, and PubMed databases to June 26, 2021. Pooled biparametric MRI (bpMRI, T2WI+DWI) and multiparametric MRI (mpMRI, T2WI+DWI+DCE) sensitivities and specificities and the diagnostic performances of these methods for MIBC were compared using different reference standards.

RESULTS

Seventeen studies with 2344 patients were finally included, of which 7 studies, including 1041 patients, reported the diagnostic performance of bpMRI. VI-RADS showed sensitivities and specificities of 0.91 (95% CI 0.87-0.94) and 0.86 (95% CI 0.77-0.91) at cutoff scores of 3, and 0.85 (95% CI 0.77-0.90) and 0.93 (95% CI 0.89-0.96) at cutoff scores of 4. BpMRI showed sensitivities and specificities of 0.90 (95% CI 0.69-0.97) and 0.90 (95% CI 0.81-0.95), and 0.84 (95% CI 0.78-0.88) and 0.97 (95% CI 0.87-0.99), respectively, for cutoff scores of 3 and 4. The sensitivities of bpMRI vs mpMRI for MIBC were not significantly different, but bpMRI was more specific than mpMRI at cutoff scores of 3 (p = 0.02) and 4 (p = 0.02). The VI-RADS studies using primary transurethral resection of bladder tumors (TURBT) as the reference standard had significantly higher sensitivities (p < 0.001) than those using secondary TURBT or radical cystectomy as the reference.

DATA CONCLUSION

BpMRI and conventional VI-RADS had similar diagnostic efficacies for MIBC. Since MRI overestimated MIBC diagnoses using primary TURBT as the reference standard, we recommend using secondary TURBT as the reference standard.

KEY POINTS

• Biparametric MRI without DCE had similar diagnostic efficacies for MIBC compared with conventional VI-RADS. • The sensitivity of VI-RADS was overestimated when referring to the primary TURBT results. • Biparametric MRI comprised of T2WI and DWI could be used for detecting MIBC in clinical practice.

The accuracy of Vesical Imaging-Reporting and Data System (VI-RADS): an updated comprehensive multi-institutional, multi-readers systematic review and meta-analysis from diagnostic evidence into future clinical recommendations

Purpose

To determine through a comprehensive systematic review and meta-analysis the cumulative diagnostic performance of vesical imaging-reporting and data system (VIRADS) to predict preoperative muscle-invasiveness among different institutions, readers, and optimal scoring accuracy thresholds.

Methods

PubMed, Cochrane and Embase were searched from inception up to May 2021. Sensitivity (Sn), Specificity (Sp) were first estimated and subsequently pooled using hierarchical summary receiver operating characteristics (HSROC) modeling for both cut-off ≥ 3 and ≥ 4 to predict muscle-invasive bladder cancer (MIBC). Further sensitivity analysis, subgroup analysis and meta-regression were conducted to investigate contribution of moderators to heterogeneity.

Results

In total, n = 20 studies from 2019 to 2021 with n = 2477 patients by n = 53 genitourinary radiologists met the inclusion criteria. Pooled weighted Sn and Sp were 0.87 (95% CI 0.82–0.91) and 0.86 (95% CI 0.80–0.90) for cut-off ≥ 3 while 0.78 (95% CI 0.74–0.81) and 0.94 (95% CI 0.91–0.96) for cut-off ≥ 4. The area under the HSROC curve was 0.93 (95% CI 0.90–0.95) and 0.91 (95% CI 0.88–0.93) for cut-off ≥ 3 and ≥ 4, respectively. Meta-regression analyses showed no influence of clinical characteristics nor cumulative reader’s experience while study design and radiological characteristics were found to influence the estimated outcome.

Conclusion

We demonstrated excellent worldwide diagnostic performance of VI-RADS to determine pre-trans urethral resection of bladder tumor (TURBT) staging. Our findings corroborate wide reliability of VI-RADS accuracy also between different centers with varying experience underling the importance that standardization and reproducibility of VI-RADS may confer to multiparametric magnetic resonance imaging (mpMRI) for preoperative BCa discrimination.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00345-022-03969-6.