Diagnostic accuracy of vesical imaging-reporting and data system (VI-RADS) for the detection of muscle-invasive bladder cancer: a meta-analysis

Prediction of muscular-invasive bladder cancer using multi-view fusion self-distillation model based on 3D T2-Weighted images

OBJECTIVES

Accurate preoperative differentiation between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is crucial for surgical decision-making in bladder cancer (BCa) patients. MIBC diagnosis relies on the Vesical Imaging-Reporting and Data System (VI-RADS) in clinical using multi-parametric MRI (mp-MRI). Given the absence of some sequences in practice, this study aims to optimize the existing T2-weighted imaging (T2WI) sequence to assess MIBC accurately.

METHODS

We analyzed T2WI images from 615 BCa patients and developed a multi-view fusion self-distillation (MVSD) model that integrates transverse and sagittal views to classify MIBC and NMIBC. This 3D image classification method leverages z-axis information from 3D MRI volume, combining information from adjacent slices for comprehensive features extraction. Multi-view fusion enhances global information by mutually complementing and constraining information from the transverse and sagittal planes. Self-distillation allows shallow classifiers to learn valuable knowledge from deep layers, boosting feature extraction capability of the backbone and achieving better classification performance.

RESULTS

Compared to the performance of MVSD with classical deep learning methods and the state-of-the-art MRI-based BCa classification approaches, the proposed MVSD model achieves the highest area under the curve (AUC) 0.927 and accuracy (Acc) 0.880, respectively. DeLong's test shows that the AUC of the MVSD has statistically significant differences with the VGG16, Densenet, ResNet50, and 3D residual network. Furthermore, the Acc of the MVSD model is higher than that of the two urologists.

CONCLUSIONS

Our proposed MVSD model performs satisfactorily distinguishing between MIBC and NMIBC, indicating significant potential in facilitating preoperative BCa diagnosis for urologists.

Current Status of Magnetic Resonance Imaging Use in Bladder Cancer

ABSTRACT

Bladder cancer (BC) is a significant global health concern, with over 500,000 new cases and 200,000 deaths annually, emphasizing the need for accurate staging and effective management. Traditional diagnostic techniques, such as cystoscopy and transurethral resection, are fundamental but have limitations in accurately assessing the depth of invasion. These limitations include the possibility of understaging and procedural variability, which can significantly impact treatment decisions. This review focuses on the role of multiparametric magnetic resonance imaging (mpMRI) in the diagnosis and staging of BC, particularly emphasizing the Vesical Imaging-Reporting and Data System (VI-RADS) framework. By enhancing interpretive consistency and diagnostic accuracy, mpMRI and VI-RADS offer detailed visualization of tumor characteristics and depth of invasion, while reducing the need for more invasive traditional methods. These advancements not only improve staging accuracy but also enhance treatment planning, underscoring the importance of advanced imaging in evolving BC management and positively influencing patient outcomes.

Pictorial review of the diagnosis of muscle-invasive bladder cancer using vesical imaging-reporting and data system (VI-RADS)

The Vesical Imaging-Reporting and Data System (VI-RADS) is a standard magnetic resonance imaging (MRI) and diagnostic method for muscle-invasive bladder cancer that was published in 2018. Several studies have demonstrated that VI-RADS has high diagnostic power and reproducibility. However, reading VI-RADS requires a certain amount of expertise, and radiologists need to be aware of the various pitfalls. MRI of the bladder includes T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI). T2WI is excellent for understanding anatomy. DWI and DCEI show high contrast between the tumor and normal anatomical structures and are suitable for staging local tumors. Bladder tumors are classified into five categories according to their size and morphology and their positional relationship to the bladder wall based on the VI-RADS diagnostic criteria. If the T2WI, DWI, and DCEI categories are the same, the category is the VI-RADS category. If the categories do not match, the DWI category is the VI-RADS category. If image quality of DWI is not evaluable, the DCEI category is the final category. In many cases, DWI is dominant, but this does not mean that T2WI and DCEI can be omitted from the reading of the bladder. In this educational review, typical and atypical teaching cases are demonstrated, and how to resolve misdiagnosis and the limitations of VI-RADS are discussed. The most important aspect of VI-RADS reading is to practice multiparametric reading with a solid understanding of the characteristics and role of each sequence and an awareness of the various pitfalls.

The Role of Maximal TURBT in Muscle-Invasive Bladder Cancer: Balancing Benefits in Bladder Preservation and Beyond

Radical cystectomy with lymph node dissection and urinary diversion is the gold-standard treatment for non-metastatic muscle-invasive bladder cancer (MIBC). However, in patients who refuse cystectomy, or in whom cystectomy carries a high risk, bladder-preserving therapies remain potential options. Bladder preservation therapies can include maximal debulking transurethral resection of bladder tumor (TURBT), concurrent chemoradiation therapy, followed by cystoscopy to assess response. At this time, maximal TURBT is recommended for patients prior to the initiation of chemoradiation therapy or in patients with residual bladder tumors after the completion of chemoradiation therapy. That being said, TURBT carries significant risks such as bladder perforation, bleeding, and infection, ultimately risking delayed systemic treatment. Hence, understanding its role within trimodal therapy is crucial to avoid undue suffering in patients. Herein, we review the current literature on the impact of debulking TURBT in non-metastatic MIBC.

Comparison of staging MRI to re-resection for localised bladder cancer: Narrative review

Introduction

Bladder cancer (BCa) is characterised by high prevalence, multifocality, and frequent recurrence, imposing significant clinical and economic burdens. Accurate staging, particularly distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC) disease, is crucial for guiding treatment decisions. This narrative review explores the potential implications of incorporating multiparametric magnetic resonance imaging (mpMRI) and the Vesical Imaging Reporting Data System (VI-RADS) into BCa staging, focusing on repeat transurethral resection of bladder tumour (re-TURBT).

Methods

A comprehensive search of PubMed, EMBASE, and MEDLINE databases identified studies published from 2018 to 2023 discussing mpMRI or VI-RADS in the context of re-TURBT for BCa staging. Studies meeting inclusion criteria underwent qualitative analysis.

Results

Six recent studies met inclusion criteria. VI-RADS scoring, accurately predicted muscle invasion, aiding in NMIBC/MIBC differentiation. VI-RADS scores of ≥3 indicated MIBC with high sensitivity and specificity. VI-RADS potentially identified patients benefiting from re-TURBT and those for whom it could be safely omitted.

Discussion

mpMRI and VI-RADS offer promising prospects for BCa staging, potentially correlating more closely with re-TURBT and radical cystectomy histopathology than initial TURBT. However, validation and careful evaluation of clinical integration are needed. Future research should refine patient selection and optimise mpMRI's role in BCa management.

Conclusion

VI-RADS scoring could revolutionise BCa staging, especially regarding re-TURBT. There is potential that VI-RADS correlates more with the histopathology of re-TURBT and radical cystectomy than initial TURBT. While promising, ongoing research is essential to validate utility, refine selection criteria, and address economic considerations. Integration of VI-RADS into BCa staging holds potential benefits for patients and health care systems.

Clinical application of bladder MRI and the Vesical Imaging-Reporting and Data System

Diagnostic work-up and risk stratification in patients with bladder cancer before and after treatment must be refined to optimize management and improve outcomes. MRI has been suggested as a non-invasive technique for bladder cancer staging and assessment of response to systemic therapy. The Vesical Imaging-Reporting And Data System (VI-RADS) was developed to standardize bladder MRI image acquisition, interpretation and reporting and enables accurate prediction of muscle-wall invasion of bladder cancer. MRI is available in many centres but is not yet recommended as a first-line test for bladder cancer owing to a lack of high-quality evidence. Consensus-based evidence on the use of MRI-VI-RADS for bladder cancer care is needed to serve as a benchmark for formulating guidelines and research agendas until further evidence from randomized trials becomes available.

Computed tomography-based prediction model for identifying patients with high probability of non-muscle-invasive bladder cancer

PURPOSE

To investigate computed tomography (CT)-based prediction model for identifying patients with high probability of non-muscle-invasive bladder cancer (NMIBC).

METHODS

This retrospective study evaluated 147 consecutive patients who underwent contrast-enhanced CT and surgery for bladder cancer. Using corticomedullary-to-portal venous phase images, two independent readers analyzed bladder muscle invasion, tumor stalk, and tumor size, respectively. Three-point scale (i.e., from 0 to 2) was applied for assessing the suspicion degree of muscle invasion or tumor stalk. A multivariate prediction model using the CT parameters for achieving high positive predictive value (PPV) for NMIBC was investigated. The PPVs from raw data or 1000 bootstrap resampling and inter-reader agreement using Gwet's AC1 were analyzed, respectively.

RESULTS

Proportion of patients with NMIBC was 81.0% (119/147). The CT criteria of the prediction model were as follows: (a) muscle invasion score < 2; (b) tumor stalk score > 0; and (c) tumor size < 3 cm. From the raw data, PPV of the model for NMIBC was 92.7% (51/55; 95% confidence interval [CI] 82.4-98.0) in reader 1 and 93.3% (42/45; 95% CI 81.7-98.6) in reader 2. From the bootstrap data, PPV was 92.8% (95% CI 85.2-98.3) in reader 1 and 93.4% (95% CI 84.9-99.9) in reader 2. The model's AC1 was 0.753 (95% CI 0.647-0.859).

CONCLUSION

The current CT-derived prediction model demonstrated high PPV for identifying patients with NMIBC. Depending on CT findings, approximately 30% of patients with bladder cancer may have a low need for additional MRI for interpreting vesical imaging-reporting and data system.

Tumor contact length with bladder wall provides effective risk stratification for lesions with a VIRADS score of 2-3

OBJECTIVES

To evaluate the diagnostic performance of the tumor contact length (TCL) in the prediction of MIBC (muscle-invasive bladder cancer) in lesions corresponding to the vesical imaging-reporting and data system (VIRADS) score 2-3.

METHODS

This is a single institution, retrospective study targeting 191 consecutive patients assigned of VIRADS score 2-3, who had pre-transurethral resection MRI from July 2019 to September 2021. Logistic regression analyses were performed to determine meaningful predictors of MIBC for this score group, and a nomogram was plotted with those variables. The diagnostic performance of each predictor was compared at predefined thresholds (VIRADS score 3 and TCL 3 cm) using the generalized linear model and ROC analysis.

RESULTS

Both VIRADS score and TCL remained independent predictors of MIBC for this score group (odds ratio 7.3 for VIRADS score, and 1.3 for TCL, p < 0.01 for both). The contribution of TCL to the probability of MIBC in the nomogram was greater than that of the VIRADS score. VIRADS score had a sensitivity of 0.54 (14/26), specificity of 0.92 (203/221), and diagnostic accuracy of 0.88 (217/247), and TCL showed a sensitivity of 0.89 (23/26), specificity of 0.95 (209/221), and diagnostic accuracy of 0.94 (232/247). The difference in sensitivity (p = 0.03) and accuracy (p = 0.04) was statistically significant. The AUC was also significantly wider for TCL than for VIRADS (0.97 vs. 0.73, p < 0.01).

CONCLUSION

A simple index, TCL, may be helpful in further risk stratification for MIBC in patients with a score of VIRADS 2-3.

CLINICAL RELEVANCE STATEMENT

For bladder cancer patients with insufficient qualitative evidence of muscle layer invasion using VIRADS categorization, TCL, a simple quantitative indicator defined as the curvilinear contact length between the bladder wall and the tumor, may be helpful in risk stratification.

KEY POINTS

• Even when only lesions with score 2-3 were targeted, VIRADS was still a meaningful indicator of MIBC. • With a predefined threshold of 3 cm applied, TCL outperformed VIRADS in the score 2-3 group, in predicting MIBC. • A longer TCL for a lesion with a VIRADS score 2 may warrant an additional warning for MIBC, whereas a shorter TCL for a lesion with a score 3 may indicate a lower risk of MIBC.