Diagnostic accuracy and reliability of VI-RADS in assessing muscle invasion in bladder cancer: Insight from a prospective tertiary care study.

Preoperative prediction of muscle invasion in bladder cancer in the Indian population using the Vesical Imaging-Reporting and Data System (VI-RADS) score and individual multiparametric magnetic resonance imaging (MRI) characteristics.

To comprehensively assess the diagnostic performance of Vesical Imaging-Reporting and Data System (VI-RADS) score for detecting the muscle invasion of bladder cancer. PubMed, Web of Science, and Embase were searched up to November 20, 2019. QUADAS-2 tool assessed the quality of included studies. The diagnostic estimates including sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and the area under the curve (AUC) of hierarchical summary receiver operating characteristic (HSROC) were calculated. Further subgroup analysis, meta-regression and sensitivity analysis were conducted. Six studies with 1064 patients were finally included. The pooled sensitivity, specificity, and AUC value were 0.90 (95% CI 0.86-0.94), 0.86 (95% CI 0.71-0.94), and 0.93 (95% CI 0.91-0.95) for VI-RADS 3 as the cutoff value. The corresponding estimates were 0.77 (95% CI 0.65-0.86), 0.97 (95% CI 0.88-0.99), and 0.92 (95% CI 0.89-0.94) for VI-RADS 4 as the cutoff value. Meta-regression analysis revealed that study design (p value 0.01) and surgical pattern of reference standard (p value 0.02) were source of the heterogeneity of pooled sensitivity. No publication bias was observed. The VI-RADS score can provide a good predictive ability for detecting the muscle invasiveness of primary bladder cancer with VI-RADS 3 or VI-RADS 4 as the cutoff value. • VI-RADS score has high sensitivity and specificity for predicting muscle invasion. • The diagnostic efficiencies of VI-RADS 3 and VI-RADS 4 as the cutoff value are similar. • VI-RADS score could be used for detecting muscle invasion of bladder cancer in clinical practice.

Background Contrast-enhanced US (CEUS) can be used preoperatively for evaluating muscle invasion in bladder cancer, which is important for determining appropriate treatment. However, diagnostic criteria for assessing this at CEUS have not been standardized. Purpose To develop and validate a CEUS Vesical Imaging Reporting and Data System (VI-RADS) for evaluating muscle invasion in bladder cancer. Materials and Methods This single-center prospective study consecutively enrolled patients with suspected bladder cancer. Participants underwent transabdominal or intracavity CEUS between July 2021 and May 2023. Participants were divided into a training set and a validation set at a 2:1 ratio based on the chronologic order of enrollment. The training set was used to identify major imaging features to include in CEUS VI-RADS, and the likelihood of muscle invasion per category was determined using a pathologic reference standard. The optimal VI-RADS category cutoff for muscle invasion was determined with use of the maximum Youden index. The validation set was assessed by novice and expert readers and used to validate the diagnostic performance and interreader agreement of the developed system. Results Overall, 126 participants (median age, 64 years [IQR, 57-71 years]; 107 male) and 67 participants (median age, 64 years [IQR, 56-69 years]; 49 male) were included in the training and validation set, respectively. In the training set, the optimal CEUS VI-RADS category cutoff for muscle invasion was VI-RADS 4 or higher (Youden index, 0.77). In the validation set, CEUS VI-RADS achieved good performance for both novice and expert readers (area under the receiver operating characteristic curve, 0.80 [95% CI: 0.70, 0.90] vs 0.88 [95% CI: 0.80, 0.97]; P = .09). The interreader agreement regarding the evaluation of CEUS VI-RADS category was 0.77 (95% CI: 0.65, 0.85) for novice readers, 0.87 (95% CI: 0.79, 0.92) for expert readers, and 0.78 (95% CI: 0.70, 0.84) for all readers. Conclusion The developed CEUS VI-RADS showed good performance and interreader agreement for the assessment of muscle invasion in bladder cancer. Chinese Clinical Trial Registry no. ChiCTR2100049435 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Morrell in this issue.

Background Multiparametric magnetic resonance imaging (mp-MRI) of urinary bladder (UB) is a novel imaging to predict detrusor muscle invasion in Bladder cancer (BC). The Vesical Imaging–Reporting and Data System (VI-RADS) was introduced in 2018 to standardize the reporting of BC with mp-MRI and to diagnose muscle invasion. This study was performed to evaluate the role of mp-MRI using VI-RADS to predict muscle invasive BC.Methods This prospective study was carried from June 2020 to May 2021 in a tertiary care institute. Thirty-six patients with untreated BC underwent mp-MRI followed by transuretheral resection of the tumor (TURBT). Mp-MRI findings were evaluated by two radiologists and BC was categorized according to VI-RADS scoring system. Resected tumors along with separate biopsy from the base were reported by two pathologists. Histopathological findings were compared with VI-RADS score and the performance of VI-RADS for determining detrusor muscle invasion was analyzed.Results VI-RADS scores of 4 and 5 were assigned to 9 (25%) and 15 (41.7%) cases, respectively, while 4 (13.3%) cases had VI-RADS score 3 on mp-MRI. VI-RADS 1 and 2 lesions were observed in six (16.7%) and two (5.5%) cases, respectively. On histopathology, 23 cases (63.9%) had muscle-invasive cancer and 13 cases (36.1%) had non–muscle-invasive cancer. The sensitivity and diagnostic accuracy of mp-MRI in predicting muscle invasive BC was 95.6 and 80.6%, respectively.Conclusion Mp-MRI has high sensitivity and diagnostic accuracy in predicting muscle invasive BC and should be advocated for evaluation of BC prior to surgery.

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. 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. 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). VIRADS is a good predictor of muscle layer invasion. As an independent quantitative indicator, tumor-wall interface may complement VIRADS to enhance prediction. • 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.

The purpose of the present study was to assess the diagnostic accuracy of the Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in predicting muscle infiltration of bladder cancer (BC) on a pre-operative multiparametric magnetic resonance imaging (mpMRI). The prospective study enrolled patients with bladder lesions detected on a preliminary ultrasonography or cystoscopy. The patients underwent mpMRI on a 3T MRI scanner followed by surgery within 2 weeks. The tumours were assigned a VI-RADS score by 2 experienced abdominal radiologists. The VI-RADS score was compared with postoperative histopathological findings to confirm detrusor muscle infiltration. The diagnostic performance of VI-RADS for predicting muscle invasion was assessed by calculating sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy. A total of 60 patients were included in the study with a male: female ratio of 4.4 : 1. Transurethral resection of bladder tumour (TURBT) was performed in 47 (78.4%) and radical cystectomy in 13 (21.6%) patients. 19 (31.7%) had non-muscle invasive invasive BC (NMIBCa) and 41 (68.3%) had muscle invasive BC (MIBCa) on histopathology. There was a significant association between VI-RADS score and its components with muscle invasion (p < 0.05). A VI-RADS score of ≥ 3 had a sensitivity of 97.56% (95% CI: 0.87-0.99%), specificity of 73.68% (95% CI: 0.49-0.91), positive predictive value of 88.9% (95% CI: 0.79-0.94), negative predictive value of 93.33% (95% CI: 0.66-0.99), and diagnostic accuracy of 90% (95% CI: 0.80-0.96) for prediction of muscle invasion. VI-RADS scoring system pre-operatively predicts the likelihood of muscle invasion in BC with a satisfactory diagnostic performance, and it should be incorporated in the diagnostic work-up of BC patients.

Integrating radiomics with the vesical imaging-reporting and data system to predict muscle invasion of bladder cancer.

Background The Vesical Imaging-Reporting and Data System (VI-RADS) scoring system was created in 2018 to standardize imaging and reporting of bladder cancer staging with multiparametric MRI. The system provides a five-point VI-RADS score, which suggests the likelihood of detrusor muscle invasion. Muscle-invasive disease carries a worse prognosis and requires radical surgery. Purpose To determine the performance of the VI-RADS score in detecting muscle-invasive bladder cancer in a cohort of patients undergoing multiparametric MRI before surgery. Materials and Methods In this retrospective study, a total of 340 patients with bladder cancer were identified from a database of consecutive patients undergoing multiparametric MRI from November 2011 to August 2018. The tumor with the largest burden was selected in those patients with multifocal tumors. Bladder tumors were retrospectively categorized according to the VI-RADS five-point scoring system by two readers, independently and in consensus, who were blinded to histologic findings. The VI-RADS score was compared with postoperative pathology for each tumor, and the performance of VI-RADS for determining detrusor muscle invasion was analyzed by using the Cochran-Armitage test. Results Among the 340 patients, there were 296 men and 44 women; the median age was 64.0 years (interquartile range [IQR], 57.0-87.0 years). Of 340 tumors, 255 (75.0%) were verified as non-muscle-invasive and 85 (25.0%) as muscle-invasive bladder cancer. Both the VI-RADS score and its components were associated with muscle-invasive condition (P < .001). The area under the receiver operating characteristic curve for VI-RADS for muscle invasion was 0.94 (95% confidence interval [CI]: 0.90, 0.98). The sensitivity and specificity of a VI-RADS score of 3 or greater were 87.1% (95% CI: 78%, 93%) and 96.5% (95% CI: 93%, 98%), respectively. Conclusion The Vesical Imaging-Reporting and Data System score effectively defines the likelihood of detrusor muscle invasion in bladder cancer and should be considered for evaluation of tumors prior to surgery. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Margolis and Hu in this issue.

Preoperative differentiation of muscle-invasive bladder cancer (MIBC) is challenging. This study explores the application of the Dual-Energy CT (DECT) model and the vesical imaging reporting and data system (VI-RADS) in assessing MIBC and compares their diagnostic performance. This single-center prospective study included 105 patients (33 MIBC and 72 non-MIBC cases). Two radiologists independently performed DECT morphological assessment, and evaluated quantitative DECT parameters and VI-RADS scores, blinded to the pathological findings. A DECT-based model was constructed by integrating independent quantitative predictors with tumor diameter (D). Diagnostic performance was compared using the area under the receiver operating characteristic curve (AUC). Subgroup analyses were performed for equivocal VI-RADS 3-4 cases and small lesions (D < 3 cm). VI-RADS achieved an AUC of 0.926 (sensitivity 0.970) but low specificity (0.542). The DECT model showed moderate performance (AUC = 0.761). However, the DECT + D model achieved an AUC of 0.925, comparable to VI-RADS (p > 0.05), with improved specificity (0.833). Crucially, in equivocal VI-RADS 3-4 cases, DECT + D (AUC = 0.904) significantly outperformed VI-RADS (AUC = 0.652, p < 0.05), while standalone DECT achieved an AUC of 0.824. For D < 3 cm, DECT + D (AUC = 0.895) and DECT (AUC = 0.857) were comparable to VI-RADS (AUC = 0.866), but DECT maintained high specificity (0.934). A nomogram and web-based risk calculator were developed. The DECT-based model achieves diagnostic accuracy comparable to VI-RADS and demonstrates superior stability in clinically challenging subgroups. It serves as a robust, objective alternative for preoperative bladder cancer staging, particularly beneficial for patients with MRI contraindications. This study demonstrates that a quantitative DECT-based model provides an accurate, objective alternative to MRI for preoperative bladder cancer staging, mitigating diagnostic ambiguity in clinically equivocal cases and ensuring accurate risk stratification in small lesions. Preoperative differentiation of muscle invasion is critical for bladder cancer management. The DECT-based model yields diagnostic accuracy statistically comparable to VI-RADS. The DECT-based model improves diagnostic confidence in VI-RADS 3-4 lesions.

BackgroundTo investigate the accuracy of using the Vesical Imaging-Reporting and Data System (VI-RADS) scoring system in prediction preoperative muscle invasion of bladder cancer.MethodsThe study retrospectively reviewed consecutive patients with bladder cancer who received multiparametric magnetic resonance imaging (MRI) between January 2017 and June 2019. Clinical and pathological parameters were collected. Bladder tumors were re-evaluated with 5-point VI-RADS scoring system by two experienced radiologists independently. The VI-RADS score was compared with postoperative pathology for each tumor for determining muscle invasion. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated for each VI-RADS cutoff.ResultsA total of 126 patients were included in analysis, with 82 patients received transurethral resection of bladder tumor (TURBt) while 44 underwent radical cystectomy. Fifty patients were muscle-invasive bladder cancer and 76 were non-muscle invasive tumor confirmed pathologically. VI-RADS score was only predictive factor to muscle invasion in multivariate analysis. Setting VI-RADS score greater than or equal to 4 reached the best sensitivity and specificity of 94.00% and 92.11%, with PPV and NPV value of 88.68% and 95.89%.ConclusionsVI-RADS score system is a promising and effective modality in determining detrusor muscle invasion of bladder cancer preoperatively.

Bladder cancer (BCa) diagnosis relies on distinguishing muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC) forms. Transurethral resection of the bladder tumor (TURBT) is a standard procedure for initial staging and treatment. The Vesical Imaging-Reporting and Data System (VI-RADS) enhances diagnostic accuracy for muscle invasiveness through advanced imaging techniques, potentially reducing reliance on repeat TURBT and improving patient management. We aimed to evaluate the role of VI-RADS in predicting muscle invasiveness in BCa and its potential to predict adverse pathology in high-risk NMIBC to avoid unnecessary repeat TURBT procedures. In this prospective study, we included 62 patients over the age of 18years who underwent TURBT. In a secondary phase, patients selected for restaging TURBT (re-TURBT) were included, but those with T2 tumors or low-risk NMIBC were excluded. Multiparametric magnetic resonance imaging (MRI) examinations were scored by a radiologist using the VI-RADS 5 method, while a pathologist analyzed TURBT and re-TURBT samples for accurate staging. Statistical analysis evaluated the role of VI-RADS in BCa staging. The VI-RADS score was the only predictive factor for muscle invasion in multivariate analysis. Setting the VI-RADS score at >3 resulted in the highest sensitivity, specificity, and diagnostic accuracy, with values of 67.0%, 89.0%, and 78%, respectively. The receiver operating characteristic area under the curve score for VI-RADS for muscle invasion was 85% for stage Ta, 61% for stage T1, and 88% for stage T2, which shows the utility of VI-RADS in the predictiveness of MIBC/NMIBC. VI-RADS is effective in stratifying BCa patients by predicting muscle invasiveness and identifying NMIBC cases that may not need repeat TURBT.

To compare the diagnostic performance of a novel deep learning (DL) method based on T2-weighted imaging with the vesical imaging-reporting and data system (VI-RADS) in predicting muscle invasion in bladder cancer (MIBC). A total of 215 tumours (129 for training and 31 for internal validation, centre 1; 55 for external validation, centre 2) were included. MIBC was confirmed by pathological examination. VI-RADS scores were provided by two groups of radiologists (readers 1 and readers 2) independently. A deep convolutional neural network was constructed in the training set, and validation was conducted on the internal and external validation sets. ROC analysis was performed to evaluate the performance for MIBC diagnosis. The AUCs of the DL model, readers 1, and readers 2 were as follows: in the internal validation set, 0.963, 0.843, and 0.852, respectively; in the external validation set, 0.861, 0.808, and 0.876, respectively. The accuracy of the DL model in the tumours scored VI-RADS 2 or 3 was higher than that of radiologists in the external validation set: for readers 1, 0.886 vs. 0.600, p = 0.006; for readers 2, 0.879 vs. 0.636, p = 0.021. The average processing time (38 s and 43 s in two validation sets) of the DL method was much shorter than the readers, with a reduction of over 100 s in both validation sets. Compared to radiologists using VI-RADS, the DL method had a better diagnostic performance, shorter processing time, and robust generalisability, indicating good potential for diagnosing MIBC. • The DL model shows robust performance for MIBC diagnosis in both internal and external validation. • The diagnostic performance of the DL model in the tumours scored VI-RADS 2 or 3 is better than that obtained by radiologists using VI-RADS. • The DL method shows potential in the preoperative assessment of MIBC.

PurposeTo investigate the diagnostic performance of the overall Vesical Imaging Reporting and Data System (VI-RADS) score and its individual magnetic resonance imaging (MRI) parameters in assessing grade and muscle invasiveness of bladder cancer (BC). MethodsThis IRB-approved retrospective, single-center, cross-sectional study included patients with BC wo underwent 3 Tesla preoperative multiparametric (mp)-MRI including T2-weighted (T2w), diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) sequences. An independent evaluation according to VI-RADS was performed by two radiologists in separate sessions, blinded to histological findings. ResultsThe mean age of 59 included patients was 68.2 (±13.6 standard deviation) years. Among bladder cancer patients, 26 (51%) were identified as high grade and 14 (27.5%) as muscle invasive urothelial carcinomas in histological sections. The area under the curve (AUC) for the overall VI-RADS score to predict muscle invasion was 0.986 (R1) and 0.992 (R2). The AUC to diagnose high grade bladder cancer was 0.908 (R1) and 0.905 (R2). There was no significance difference between the AUC of single parameters (T2w, DWI and DCE) compared to the total VI-RADS score (P > 0.05, respectively). Upon multivariate logistic regression, only the T2w VI-RADS score contributed independently to the diagnosis of high grade and muscle invasive bladder cancer (P = 0.001 (R1) and P = 0.0022 (R2) for high grade cancer; P = 0.0007 (R1) and P = 0.0019 (R2) for muscle invasiveness). ConclusionVI-RADS provides high diagnostic accuracy to diagnose high grade and muscle invasive BC. Our results suggest, that mp-MRI parameters provide overlapping information and for sake of clinical simplicity, a biparametric, contrast free image acquisition may be approached without sacrificing diagnostic accuracy.

Evaluating the concordance between Vesical Imaging Reporting and Data System scores and bladder tumor histopathology

Independent factors are needed to supplement vesical imaging-reporting and data system (VI-RADS) to improve its ability to identify muscle invasive bladder cancer (MIBC). To assess the correlation between MIBC and diffusion kurtosis imaging (DKI) ratio, VI-RADS, and other factors (such as tumor location). Retrospective. Sixty-eight patients (50 males and 18 females; age: 70.1 ± 9.5 years) with bladder urothelial carcinoma. 1.5 T, conventional diffusion-weighted imaging (DWI), and DKI (single shot echo-planar sequence). Three radiologists independently measured the diffusion parameters of each bladder cancer (BCa) and obturator internus, including the mean apparent diffusion coefficient (ADCmean), mean kurtosis (MK), and mean diffusion (MD). And the ratio of diffusion parameters between BCa and obturator internus was calculated (diffusion parameter ratio = bladder cancer:obturator internus). Based on the VI-RADS, the target lesions were independently scored. Furthermore, the actual tumor-wall contact length (ACTCL) and absolute tumor-wall contact length (ABTCL) were measured. Multicollinearity among independent variables was evaluated using the variance inflation factor (VIF). Multivariable logistic regression analysis was used to determine the independent risk factors of MIBC. The receiver operating characteristic curve was used to evaluate the efficacy of each variable in detecting MIBC. The DeLong test was used to compare the area under the curve (AUC). A P < 0.05 was considered statistically significant. MKratio (median: 0.62) and VI-RADS were independent risk factors for MIBC. AUCs for MKratio, VI-RADS, and MKratio combined with VI-RADS in assessing MIBC were 0.895, 0.871, and 0.973, respectively. MKratio combined with VI-RADS was more effective in diagnosing MIBC than VI-RADS alone. MKratio has potential to assist the assessment of MIBC. MKratio can be used as a supplement to VI-RADS for detecting MIBC. 4 TECHNICAL EFFICACY: Stage 2.