Multiparametric Magnetic Resonance Imaging for Bladder Cancer: Development of VI-RADS (Vesical Imaging-Reporting And Data System)

Role of Additional MRI-Based Morphologic Measurements on the Performance of VI-RADS for Muscle-Invasive Bladder Cancer

BACKGROUND

Vesical Imaging-Reporting and Data System (VI-RADS) is a pathway for the standardized imaging and reporting of bladder cancer staging using multiparametric (mp) MRI.

PURPOSE

To investigate additional role of morphological (MOR) measurements to VI-RADS for the detection of muscle-invasive bladder cancer (MIBC) with mpMRI.

STUDY TYPE

Retrospective.

POPULATION

A total of 198 patients (72 MIBC and 126 NMIBC) underwent bladder mpMRI was included.

FIELD STRENGTH/SEQUENCE

3.0 T/T2-weighted imaging with fast-spin-echo sequence, spin-echo-planar diffusion-weighted imaging and dynamic contrast-enhanced imaging with fast 3D gradient-echo sequence.

ASSESSMENT

VI-RADS score and MOR measurement including tumor location, number, stalk, cauliflower-like surface, type of tumor growth, tumor-muscle contact margin (TCM), tumor-longitudinal length (TLL), and tumor cellularity index (TCI) were analyzed by three uroradiologists (3-year, 8-year, and 15-year experience of bladder MRI, respectively) who were blinded to histopathology.

STATISTICAL TESTS

Significant MOR measurements associated with MIBC were tested by univariable and multivariable logistic regression (LR) analysis with odds ratio (OR). Area under receiver operating characteristic curve (AUC) with DeLong's test and decision curve analysis (DCA) were used to compared the performance of unadjusted vs. adjusted VI-RADS. A P-value <0.05 was considered statistically significant.

RESULTS

TCM (OR 9.98; 95% confidence interval [CI] 4.77-20.8), TCI (OR 5.72; 95% CI 2.37-13.8), and TLL (OR 3.35; 95% CI 1.40-8.03) were independently associated with MIBC at multivariable LR analysis. VI-RADS adjusted by three MORs achieved significantly higher AUC (reader 1 0.908 vs. 0.798; reader 2 0.906 vs. 0.855; reader 3 0.907 vs. 0.831) and better clinical benefits than unadjusted VI-RADS at DCA. Specially in VI-RADS-defined equivocal lesions, MOR-based adjustment resulted in 55.5% (25/45), 70.4% (38/54), and 46.4% (26/56) improvement in accuracy for discriminating MIBC in three readers, respectively.

DATA CONCLUSION

MOR measurements improved the performance of VI-RADS in detecting MIBC with mpMRI, especially for equivocal lesions.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Preoperative Prediction of Muscle Invasiveness in Bladder Cancer: The Role of 3D Volumetric Radiomics Using Diffusion-Weighted MRI, the VI-RADS Score, or a Combination of Both

BACKGROUND

Bladder cancer treatment decisions hinge on detecting muscle invasion. The 2018 "Vesical Imaging Reporting and Data System" (VI-RADS) standardizes multiparametric MRI (mp-MRI) use. Radiomics, an analysis framework, provides more insightful information than conventional methods.

PURPOSE

To determine how well MIBC (Muscle Invasive Bladder Cancer) and NMIBC (Non-Muscle Invasive Bladder Cancer) can be distinguished using mp-MRI radiomics features.

METHODS

We conducted a study with 73 bladder cancer patients diagnosed pathologically, who underwent preoperative mp-MRI from January 2020 to July 2022. Utilizing 3D Slicer (version 4.8.1) and Pyradiomics, we manually extracted radiomic features from apparent diffusion coefficient (ADC) maps created from diffusion-weighted imaging. The LASSO approach identified optimal features, and we addressed sample imbalance using SMOTE. We developed a classification model using textural features alone or combined with VI-RADS, employing a random forest classifier with 10-fold cross-validation. Diagnostic performance was assessed using the area under the ROC curve analysis.

RESULTS

Among 73 patients (63 men, 10 women; median age: 63 years), 41 had muscle-invasive and 32 had superficial bladder cancer. Muscle invasion was observed in 25 of 41 patients with VI-RADS 4 and 5 scores and 12 of 32 patients with VI-RADS 1, 2, and 3 scores (accuracy: 77.5%, sensitivity: 67.7%, specificity: 88.8%). The combined VI-RADS score and radiomics model (AUC = 0.92 ± 0.12) outperformed the single radiomics model using ADC MRI (AUC = 0.83 ± 0.22 with 10-fold cross-validation) in this dataset.

CONCLUSION

Before undergoing surgery, bladder cancer invasion in muscle might potentially be predicted using a radiomics signature based on mp-MRI.

Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer

BACKGROUND

Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive bladder carcinoma (NMIBC). However, the European Organization for Research and Treatment of Cancer (EORTC) model exhibits poor performance.

PURPOSE

To investigate whether integrating multiparametric MRI (mp-MRI) with clinical factors improves NMIBC 5-year recurrence risk assessment.

STUDY TYPE

Retrospective.

POPULATION

One hundred ninety-one patients (median age, 65 years; age range, 54-73 years; 27 females) underwent mp-MRI between 2011 and 2017, and received ≥5-year follow-ups. They were divided into a training cohort (N = 115) and validation/testing cohorts (N = 38 in each). Recurrence rates were 23.5% (27/115) in the training cohort and 23.7% (9/38) in both validation and testing cohorts.

FIELD STRENGTH/SEQUENCE

3-T, fast spin echo T2-weighted imaging (T2WI), single-shot echo planar diffusion-weighted imaging (DWI), and volumetric spoiled gradient echo dynamic contrast-enhanced (DCE) sequences.

ASSESSMENT

Radiomics and deep learning (DL) features were extracted from the combined region of interest (cROI) including intratumoral and peritumoral areas on mp-MRI. Four models were developed, including clinical, cROI-based radiomics, DL, and clinical-radiomics-DL (CRDL) models.

STATISTICAL TESTS

Student's t-tests, DeLong's tests with Bonferroni correction, receiver operating characteristics with the area under the curves (AUCs), Cox proportional hazard analyses, Kaplan-Meier plots, SHapley Additive ExPlanations (SHAP) values, and Akaike information criterion for clinical usefulness. A P-value <0.05 was considered statistically significant.

RESULTS

The cROI-based CRDL model showed superior performance (AUC 0.909; 95% CI: 0.792-0.985) compared to other models in the testing cohort for assessing 5-year recurrence in NMIBC. It achieved the highest Harrell's concordance index (0.804; 95% CI: 0.749-0.859) for estimating recurrence-free survival. SHAP analysis further highlighted the substantial role (22%) of the radiomics features in NMIBC recurrence assessment.

DATA CONCLUSION

Integrating cROI-based radiomics and DL features from preoperative mp-MRI with clinical factors could improve 5-year recurrence risk assessment in NMIBC.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 3.

[Can muscle invasive bladder cancer be treated without cystectomy in the future? : New data on trimodal therapy and bladder preservation after systemic therapy alone]

Muscle invasive bladder cancer is generally an aggressive disease. Radical cystectomy (RC) is traditionally the treatment of choice. Due to possible advantages in morbidity, peri-interventional mortality, and quality of life, bladder-preserving treatment strategies are of interest. Here, trimodal therapy (TMT) consisting of maximum transurethral resection and subsequent radiochemotherapy with subsequent cystoscopic follow-up plays an important role. Current cohort analyses indicate equivalent oncological results of TMT to RC in selected patients. However, the use of systemic therapy alone with combined chemo-/immunotherapy or cytotoxic combination therapy also shows promising efficacy both in early surrogate parameters and in oncological endpoints. Overall, studies to date suggest that bladder preservation is possible without compromising oncologic outcomes. Future developments aim to refine patient selection by combining different risk factors and biomarkers to further improve outcomes.

Recent trends in AI applications for pelvic MRI: a comprehensive review

Magnetic resonance imaging (MRI) is an essential tool for evaluating pelvic disorders affecting the prostate, bladder, uterus, ovaries, and/or rectum. Since the diagnostic pathway of pelvic MRI can involve various complex procedures depending on the affected organ, the Reporting and Data System (RADS) is used to standardize image acquisition and interpretation. Artificial intelligence (AI), which encompasses machine learning and deep learning algorithms, has been integrated into both pelvic MRI and the RADS, particularly for prostate MRI. This review outlines recent developments in the use of AI in various stages of the pelvic MRI diagnostic pathway, including image acquisition, image reconstruction, organ and lesion segmentation, lesion detection and classification, and risk stratification, with special emphasis on recent trends in multi-center studies, which can help to improve the generalizability of AI.

CT and MRI features of sarcomatoid urothelial carcinoma of the bladder and its differential diagnosis with conventional urothelial carcinoma

BACKGROUND

Sarcomatoid urothelial carcinoma (SUC) is a rare and highly malignant form of bladder cancer with a poor prognosis. Currently, there is limited information on the imaging features of bladder SUC and reliable indicators for distinguishing it from conventional urothelial carcinoma (CUC). The objective of our study was to identify the unique imaging characteristics of bladder SUC and determine factors that aid in its differential diagnosis.

MATERIALS AND METHODS

This retrospective study enrolled 22 participants with bladder SUC and 61 participants with CUC. The clinical, pathologic, and CT/MRI data from both groups were recorded, and a comparison was conducted using univariate analysis and multinomial logistic regression for distinguishing SUC from CUC.

RESULTS

The majority of SUCs were located in the trigone of the bladder and exhibited large tumor size, irregular shape, low ADC values, Vesical Imaging-Reporting and Data System (VI-RADS) score ≥ 4, the presence of necrosis, and an invasive nature. Univariate analysis revealed significant differences in terms of tumor location, shape, the maximum long-axis diameter (LAD), the short-axis diameter (SAD), ADC-value, VI-RADS scores, necrosis, extravesical extension (EVE), pelvic peritoneal spread (PPS), and hydronephrosis/ureteral effusion (p < .001 ~ p = .037) between SUCs and CUCs. Multinomial logistic regression found that only SAD (p = .014) and necrosis (p = .003) emerged as independent predictors for differentiating between SUC and CUC. The model based on these two factors achieved an area under curve (AUC) of 0.849 in ROC curve analysis.

CONCLUSION

Bladder SUC demonstrates several distinct imaging features, including a high incidence of trigone involvement, large tumor size, and obvious invasiveness accompanied by necrosis. A bladder tumor with a large SAD and evidence of necrosis is more likely to be SUC rather than CUC.

Tumor necrosis in magnetic resonance imaging predicts urothelial carcinoma with squamous differentiation in muscle-invasive bladder carcinoma

PURPOSE

This study investigated radiologic features on preoperative MRI to differentiate urothelial carcinoma with squamous differentiation (UCSD) from conventional urothelial carcinoma (UC) in muscle-invasive bladder carcinoma.

METHODS

Ninety-nine patients who underwent radical cystectomy and a preoperative bladder MRI scan within three months before surgery were retrospectively enrolled. Various MRI features, including tumor length, location, multiplicity, long-to-short axis ratio, morphology, radiologic stage, and degree of severe necrosis, were analyzed. Univariable and multivariable logistic regression analyses were performed to identify MRI features predictive of UCSD. The diagnostic performance of a significant MRI feature was assessed using 5-fold cross-validation.

RESULTS

Among the MRI features, significant radiologic findings associated with UCSD in the univariable analysis included heterogeneous tumor signal intensity in T2-weighted images (odds ratio [OR], 3.365; 95% confidence interval [CI], 1.213-9.986; P = 0.022) and contrast-enhanced T1-weighted images (OR, 4.428; 95% CI, 1.519-12.730; P = 0.007), as well as marked (≥ 50%) severe necrosis (OR, 17.100; 95% CI, 4.699-73.563; P < 0.001). In the multivariable analysis, marked (≥ 50%) severe necrosis (odds ratio [OR], 13.755; 95% confidence interval [CI], 2.796-89.118; P = 0.004) was a significant predictor of UCSD. Marked (≥ 50%) severe necrosis showed a high specificity of 95.0% with a precision of 65.0% for diagnosing UCSD based on 5-fold cross-validation.

CONCLUSION

Preoperative bladder MRI revealing marked severe necrosis may be indicative of UCSD and can assist in distinguishing it from conventional UC.

CT and MRI findings of small cell neuroendocrine carcinoma of the urinary bladder: comparison with urothelial carcinoma

OBJECTIVE

This study aimed to evaluate the efficacy of CT and MRI findings to differentiate small cell neuroendocrine carcinoma (SCNEC) from urothelial carcinoma (UC) of the urinary bladder.

MATERIALS AND METHODS

This study included 90 patients with histopathologically confirmed bladder cancer (10 SCNECs and 80 UCs). Eight patients with bladder SCNEC and 80 with UC underwent CT and MRI, whereas the remaining two patients with SCNEC underwent CT alone before treatment. CT and MRI findings were retrospectively evaluated and compared between the two pathologies.

RESULTS

The maximum diameter (36.5 mm vs. 19.0 mm, p < 0.01) and height (22.0 mm vs. 14.0 mm, p < 0.01) of the tumor in bladder SCNEC were higher than in UC. The pedunculated configuration (20% vs. 61%, p < 0.05) and irregular tumor margins (20% vs. 76%, p < 0.01) in bladder SCNEC were less common than in UC. The CT attenuation of the solid component in unenhanced CT images was higher in bladder SCNEC than in UC (37 Hounsfield unit [HU] vs. 34 HU, p < 0.01). The apparent diffusion coefficient (ADC) of the solid component in bladder SCNEC was lower than in UC (0.49 × 10-3 mm2/s vs. 1.02 × 10-3 mm2/s, p < 0.01).

CONCLUSION

In comparison with UC, bladder SCNEC was larger, had higher unenhanced CT attenuation, and had a lower ADC value. The pedunculated configuration and irregular tumor margins were typical of bladder UC.

Development and Validation of an MRI-Based Nomogram for Preoperative Detection of Muscle Invasion in VI-RADS 3

BACKGROUND

The relationship between tumor and muscle layer in the vesical imaging-reporting and data system (VI-RADS) 3 is ambiguous, and there is a lack of preoperative and non-invasive procedures to detect muscle invasion in VI-RADS 3.

PURPOSE

To develop a nomogram based on MRI features for detecting muscle invasion in VI-RADS 3.

STUDY TYPE

Retrospective.

POPULATION

235 cases (Age: 67.5 ± 11.5 years) with 11.9% females were randomly divided into a training cohort (n = 164) and a validation cohort (n = 71).

FIELD STRENGTH/SEQUENCE

3T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin echo), and dynamic contrast-enhanced imaging (gradient echo).

ASSESSMENT

3 features were selected from the training cohort, including tumor contact length greater than maximum tumor diameter (TCL > Dmax), flat tumor morphology, and lower standard deviation of apparent diffusion coefficient (ADCSD). Three readers assessed VI-RADS scores and the tumor morphology.

STATISTICAL TESTS

Interobserver agreement was assessed by Kappa analysis. Features for final analysis were selected by logistic regression. The performance of the nomogram was evaluated by the receiver operating characteristic curve, decision curve analysis, and calibration curve.

RESULTS

TCL > Dmax, flat morphology, and lower ADCSD were the independent risk factors for muscle invasive in VI-RADS 3. The AUCs, accuracy, sensitivity, and specificity of the nomogram 1 composed of three features for detecting muscle invasion were 0.852 (95% CI: 0.793-0.912), 0.756, 0.917, and 0.663 in the training cohort, and 0.885 (95% CI: 0.801-0.969), 0.817, 0.900, and 0.784 in the validation cohort. The nomogram 2 without ADCSD has nearly the same performance as the nomogram 1.

DATA CONCLUSION

Nomogram can be an efficient tool for preoperative detection of muscle invasion in VI-RADS 3.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Pictorial review of multiparametric MRI in bladder urothelial carcinoma with variant histology: pearls and pitfalls

Bladder cancer (BC), predominantly comprising urothelial carcinomas (UCs), ranks as the tenth most common cancer worldwide. UCs with variant histology (variant UC), including squamous differentiation, glandular differentiation, plasmacytoid variant, micropapillary variant, sarcomatoid variant, and nested variant, accounting for 5-10% of cases, exhibit more aggressive and advanced tumor characteristics compared to pure UC. The Vesical Imaging-Reporting and Data System (VI-RADS), established in 2018, provides guidelines for the preoperative evaluation of muscle-invasive bladder cancer (MIBC) using multiparametric magnetic resonance imaging (mpMRI). This technique integrates T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE)-MRI, and diffusion-weighted imaging (DWI) to distinguish MIBC from non-muscle-invasive bladder cancer (NMIBC). VI-RADS has demonstrated high diagnostic performance in differentiating these two categories for pure UC. However, its accuracy in detecting muscle invasion in variant UCs is currently under investigation. These variant UCs are associated with a higher likelihood of disease recurrence and require precise preoperative assessment and immediate surgical intervention. This review highlights the potential value of mpMRI for different variant UCs and explores the clinical implications and prospects of VI-RADS in managing these patients, emphasizing the need for careful interpretation of mpMRI examinations including DCE-MRI, particularly given the heterogeneity and aggressive nature of variant UCs. Additionally, the review addresses the fundamental MRI reading procedures, discusses potential causes of diagnostic errors, and considers future directions in the use of artificial intelligence and radiomics to further optimize the bladder MRI protocol.

Comparison of golden-angle radial sparse parallel (GRASP) and conventional cartesian sampling in 3D dynamic contrast-enhanced mri for bladder cancer: a preliminary study

PURPOSE

To compare the image quality, inter-reader agreement, and diagnostic capability for muscle-invasive bladder cancer (MIBC) of the reconstructed images in sections orthogonal to the bladder tumor obtained by 3D Dynamic contrast-enhanced (DCE)-MRI using the Golden-angle Radial Sparse Parallel (GRASP) technique with the images directly captured using the Cartesian sampling.

MATERIALS AND METHODS

This study involved 68 initial cases of bladder cancer examined with DCE-MRI (GRASP: n = 34, Cartesian: n = 34) at 3 Tesla. Four radiologists conducted qualitative evaluations (overall image quality, absence of motion artifact, absence of streak artifact, and tumor conspicuity) using a five-point Likert scale (5 = Excellent/None) and quantitative signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements. The areas under the receiver-operating characteristic curves (AUCs) for the Vesical Imaging-Reporting and Data System (VI-RADS) DCE score for MIBC assessment were calculated. Inter-reader agreement was also assessed.

RESULTS

GRASP notably enhanced overall image quality (pooled score: GRASP 4 vs. Cartesian 3, P < 0.0001), tumor conspicuity (5 vs. 3, P < 0.05), SNR (Median 38.2 vs. 19.0, P < 0.0001), and CNR (7.9 vs. 6.0, P = 0.005), with fewer motion artifacts (5 vs. 3, P < 0.0001) and minor streak artifacts (5 vs. 5, P > 0.05). Although no significant differences were observed, the GRASP group tended to have higher AUCs for MIBC (pooled AUCs: 0.92 vs. 0.88) and showed a trend toward higher inter-reader agreement (pooled kappa-value: 0.70 vs. 0.63) compared to the Cartesian group.

CONCLUSIONS

Using the GRASP for 3D DCE-MRI, the reconstructed images in sections orthogonal to the bladder tumor achieved higher image quality and improve the clinical work flow, compared to the images directly captured using the Cartesian. GRASP tended to have higher diagnostic ability for MIBC and showed a trend toward higher inter-reader agreement compared to the Cartesian.

The role of VI-RADS scoring criteria for predicting oncological outcomes in bladder cancer

PURPOSE

Our purpose was to evaluate the prognostic value of Vesical Imaging Reporting and Data System (VI-RADS) in bladder cancer (BCa) staging and predicting recurrence or progression.

METHODS

We retrospectively analyzed the prospectively collected data from 96 patients with bladder tumors who underwent VI-RADS-based multiparametric magnetic resonance imaging (mpMRI) before endourological treatment from April 2021 to December 2022. Diagnostic performance was evaluated by comparing mpMRI reports with final pathology, using logistic regression for muscle-invasive bladder cancer (MIBC) predictors. Follow-up until May 2023 included Kaplan-Meier and Cox regression analysis to assess VI-RADS predictive roles for recurrence-free survival (RFS) and progression-free survival (PFS).

RESULTS

A total of 96 patients (19.8% women, 80.2% men; median age 68.0 years) were included, with 71% having primary tumors and 29% recurrent BCa. Multiparametric MRI exhibited high sensitivity (92%) and specificity (79%) in predicting MIBC, showing no significant differences between primary and recurrent cancers (AUC: 0.96 vs. 0.92, P = .565). VI-RADS emerged as a key predictor for MIBC in both univariate (OR: 40.3, P < .001) and multivariate (OR: 54.6, P < .001) analyses. Primary tumors with VI-RADS ≥ 3 demonstrated significantly shorter RFS (P = .02) and PFS (P = .04).

CONCLUSIONS

In conclusion, mpMRI with VI-RADS has a high diagnostic value in predicting MIBC in both primary and recurrent BCa. A VI-RADS threshold ≥ 3 is a strong predictor for MIBC, and in primary tumors predicts early recurrence and progression.

Prospective Comparison of 2D and 3D T2-Weighted Imaging in Multiparametric MRI for Assessing Muscle Invasion Accuracy Using VI-RADS in Bladder Cancer

RATIONALE AND OBJECTIVES

T2-weighted imaging (T2WI) is an essential sequence for assessing the staging of bladder cancer. This study aimed to compare the image quality and diagnostic performance of three-dimensional (3D) and two-dimensional (2D) T2WI in diagnosing muscle invasion of bladder cancer using Vesical Imaging Reporting and Data System (VI-RADS).

MATERIALS AND METHODS

Between August 2022 and May 2023, 101 participants with bladder cancer underwent multiparametric MRI including 3D and 2D T2WI. Two radiologists independently reviewed 2D and 3D T2WI, evaluating image quality and muscle invasion based on VI-RADS scoring. The paired Wilcoxon signed-rank test assessed the differences between 2D and 3D T2WI. The areas under the receiver operating characteristic curve (AUCs) were utilized to compare the diagnostic performance.

RESULTS

3D T2WI demonstrated significantly superior overall image quality scores with less artifacts than 2D T2WI. Compared to 2D T2WI, 3D T2WI categories had significantly higher AUC for both readers (reader 1: 0.937 vs. 0.909, p = .02; reader 2: 0.923 vs.0.884, p = .04). The VI-RADS score of 3D MR protocol had higher accuracy than 2D MR protocol (reader 1: 0.931 vs. 0.921, p = .02; reader 2: 0.931 vs. 0.911, p = .02). However, there were no significant differences in AUC values of VI-RADS categories between 2D and 3D MR protocol (all p > 0.05).

CONCLUSION

In assessing muscle invasion of bladder cancer, 3D T2WI exhibited superior overall image quality and diagnostic performance than 2D T2WI. However, 3D T2WI did not significantly improve the diagnostic performance of VI-RADS.

Novel bladder-sparing approaches in patients with muscle-invasive bladder cancer

The pursuit of surgeons and oncologists in fulfilling the inherent desire of patients to retain their urinary bladder despite having muscle-invasive bladder cancer (MIBC) has sparked years of research and multiple debates, given its aggressive nature and the high risk of fatal metastatic recurrence. Historically, several approaches to bladder-sparing treatment have been explored, ranging from radical transurethral resection to concurrent chemoradiation. A less well-established approach involves a risk-adapted approach with local therapy deferred based on the clinical response to transurethral resection followed by systemic therapy. Each approach is associated with potential risks, benefits, and trade-offs. In this review, we aim to understand, navigate, and suggest future perspectives on bladder-sparing approaches in patients with 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.

Multiparametric MR characterization for human epithelial growth factor receptor 2 expression in bladder cancer: an exploratory study

PURPOSE

To investigate the application value of multiparametric MRI in evaluating the expression status of human epithelial growth factor receptor 2 (HER2) in bladder cancer (BCa).

METHODS

From April 2021 to July 2023, preoperative imaging manifestations of 90 patients with pathologically confirmed BCa were retrospectively collected and analyzed. All patients underwent multiparametric MRI including synthetic MRI, DWI, from which the T1, T2, proton density (PD) and apparent diffusion coefficient (ADC) values were obtained. The clinical and imaging characteristics as well as quantitative parameters (T1, T2, PD and ADC values) between HER2-positive and -negative BCa were compared using student t test and chi-square test. The diagnostic efficacy of parameters in predicting HER2 expression status was evaluated by calculating the area under ROC curve (AUC).

RESULTS

In total, 76 patients (mean age, 63.59 years ± 12.84 [SD]; 55 men) were included: 51 with HER2-negative and 25 with HER2-positive BCa. HER2-positive group demonstrated significantly higher ADC, T1, and T2 values than HER2-negative group (all P < 0.05). The combination of ADC values and tumor grade yielded the best diagnostic performance in evaluating HER2 expression level with an AUC of 0.864.

CONCLUSION

The multiparametric MR characterization can accurately evaluate the HER2 expression status in BCa, which may further guide the determination of individualized anti-HER2 targeted therapy strategies.

Detecting Muscle Invasion of Bladder Cancer: An Application of Diffusion Kurtosis Imaging Ratio and Vesical Imaging-Reporting and Data System

BACKGROUND

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).

PURPOSE

To assess the correlation between MIBC and diffusion kurtosis imaging (DKI) ratio, VI-RADS, and other factors (such as tumor location).

STUDY TYPE

Retrospective.

POPULATION

Sixty-eight patients (50 males and 18 females; age: 70.1 ± 9.5 years) with bladder urothelial carcinoma.

FIELD STRENGTH/SEQUENCE

1.5 T, conventional diffusion-weighted imaging (DWI), and DKI (single shot echo-planar sequence).

ASSESSMENT

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.

STATISTICAL TESTS

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.

RESULTS

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.

DATA CONCLUSIONS

MKratio has potential to assist the assessment of MIBC. MKratio can be used as a supplement to VI-RADS for detecting MIBC.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Evaluation of magnetic resonance imaging for bladder cancer detection following transurethral resection of bladder tumour (TURBT)

PURPOSE

To evaluate the performance of MRI for detection of bladder cancer following transurethral resection of bladder tumour (TURBT).

METHODS

This single-centre retrospective study included forty-one consecutive patients with bladder cancer who underwent bladder MRI after TURBT. Two uroradiologists retrospectively assessed the presence of tumour using bladder MRI with and without DWI (diffusion weighted imaging) using a five-point Likert scale. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated and inter-reader agreement was assessed. Histopathology was used as the reference standard.

RESULTS

24 out of 41 patients (58.5%) had no residual tumour or Tis (carcinoma in situ) after TURBT. Sensitivity, specificity, PPV and NPV for detection of tumour using T1WI (T1-weighted imaging) and T2WI (T2-weighted imaging) was 50.0%, 54.6%, 21.1%, and 81.8%, respectively and for T1WI, T2WI and DWI combined was 100%, 76.5%, 50.0% and 100%, respectively. Overestimation of tumour was more common than underestimation. MRI showed high accuracy for patients in whom there was no residual tumour (78.9%). Inter-reader agreement for tumour detection improved from fair (κ = 0.54) to moderate (κ = 0.70) when DWI was included.

CONCLUSION

Non-contrast MRI with DWI showed high sensitivity and relatively high specificity for detection of residual tumour after TURBT. Inter-reader agreement improved from fair to moderate with the addition of DWI. MRI can be useful after TURBT in order to guide further management.

Clinical Upstaging After Neoadjuvant Chemotherapy Impacting Eligibility for Vaginal-sparing Cystectomy: Identifying Bladder Cancer Patients Who May Benefit From Interim Imaging

OBJECTIVE

Limited data exist on the frequency with which clinical progression during neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) impacts eligibility for a vaginal-sparing surgical approach or on the utility of interim imaging assessment. We sought to evaluate the incidence of clinical upstaging following NAC that would render a patient ineligible for a vaginal-sparing cystectomy.

METHODS

Eighty-nine female patients with non-metastatic MIBC treated with NAC and radical cystectomy (RC) (2012-2023) were retrospectively reviewed. Tumor location(s) was determined from transurethral resection of bladder tumor operative reports. Pre- and post-NAC clinical staging was determined from imaging. Outcomes of interest included clinical upstaging and upstaging to vaginal invasion after NAC.

RESULTS

75/89 patients had pre- and post-NAC imaging. Fifty-five had no change in clinical staging, 6 patients were upstaged (4 cT2→cT3, 2 cT3→cT4), and 14 patients were downstaged (13 cT3→cT2, 1 cT4→cT2). Of the 75 patients with pre- and post-NAC imaging, 39 had trigone tumors. Of these, 28 had no change in clinical staging, 2 were upstaged (1 cT2→cT3, 1 cT3→cT4) and 9 were downstaged (8 cT3→cT2, 1 cT4→cT2). Overall, 6/75 (8%) of patients demonstrated clinical upstaging after NAC. 2/39 (5%) of patients with trigone tumors clinically progressed after NAC and both had vaginal invasion (pT4) on final pathology.

CONCLUSION

Although clinical upstaging after NAC was infrequent, 5% of patients with trigonal MIBC were rendered ineligible for vaginal-sparing cystectomy following NAC due to progression. Interim imaging assessment may identify non-responders and preserve eligibility for vaginal-sparing RC.

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.

Compressed sensing 3D T2WI radiomics model: improving diagnostic performance in muscle invasion of bladder cancer

BACKGROUND

Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time.

METHODS

This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves.

RESULTS

In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model.

CONCLUSION

The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.

Reduced field-of-view DWI based on deep learning reconstruction improving diagnostic accuracy of VI-RADS for evaluating muscle invasion

OBJECTIVES

To investigate whether reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with deep learning reconstruction (DLR) can improve the accuracy of evaluating muscle invasion using VI-RADS.

METHODS

Eighty-six bladder cancer participants who were evaluated by conventional full field-of-view (fFOV) DWI, standard rFOV (rFOVSTA) DWI, and fast rFOV with DLR (rFOVDLR) DWI were included in this prospective study. Tumors were categorized according to the vesical imaging reporting and data system (VI-RADS). Qualitative image quality scoring, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC value were evaluated. Friedman test with post hoc test revealed the difference across the three DWIs. Receiver operating characteristic analysis was performed to calculate the areas under the curve (AUCs).

RESULTS

The AUC of the rFOVSTA DWI and rFOVDLR DWI were higher than that of fFOV DWI. rFOVDLR DWI reduced the acquisition time from 5:02 min to 3:25 min, and showed higher scores in overall image quality with higher CNR and SNR, compared to rFOVSTA DWI (p < 0.05). The mean ADC of all cases of rFOVSTA DWI and rFOVDLR DWI was significantly lower than that of fFOV DWI (all p < 0.05). There was no difference in mean ADC value and the AUC for evaluating muscle invasion between rFOVSTA DWI and rFOVDLR DWI (p > 0.05).

CONCLUSIONS

rFOV DWI with DLR can improve the diagnostic accuracy of fFOV DWI for evaluating muscle invasion. Applying DLR to rFOV DWI reduced the acquisition time and improved overall image quality while maintaining ADC value and diagnostic accuracy.

CRITICAL RELEVANCE STATEMENT

The diagnostic performance and image quality of full field-of-view DWI, reduced field-of-view (rFOV) DWI with and without DLR were compared. DLR would benefit the wide clinical application of rFOV DWI by reducing the acquisition time and improving the image quality.

KEY POINTS

Deep learning reconstruction (DLR) can reduce scan time and improve image quality. Reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with DLR showed better diagnostic performances than full field-of-view DWI. There was no difference of diagnostic accuracy between rFOV DWI with DLR and standard rFOV DWI.

Non-Gaussian diffusion metrics with whole-tumor histogram analysis for bladder cancer diagnosis: muscle invasion and histological grade

PURPOSE

To investigate the performance of histogram features of non-Gaussian diffusion metrics for diagnosing muscle invasion and histological grade in bladder cancer (BCa).

METHODS

Patients were prospectively allocated to MR scanner1 (training cohort) or MR2 (testing cohort) for conventional diffusion-weighted imaging (DWIconv) and multi-b-value DWI. Metrics of continuous time random walk (CTRW), diffusion kurtosis imaging (DKI), fractional-order calculus (FROC), intravoxel incoherent motion (IVIM), and stretched exponential model (SEM) were simultaneously calculated using multi-b-value DWI. Whole-tumor histogram features were extracted from DWIconv and non-Gaussian diffusion metrics for logistic regression analysis to develop diffusion models diagnosing muscle invasion and histological grade. The models' performances were quantified by area under the receiver operating characteristic curve (AUC).

RESULTS

MR1 included 267 pathologically-confirmed BCa patients (median age, 67 years [IQR, 46-82], 222 men) and MR2 included 83 (median age, 65 years [IQR, 31-82], 73 men). For discriminating muscle invasion, CTRW achieved the highest testing AUC of 0.915, higher than DWIconv's 0.805 (p = 0.014), and similar to the combined diffusion model's AUC of 0.885 (p = 0.076). For differentiating histological grade of non-muscle-invasion bladder cancer, IVIM outperformed a testing AUC of 0.897, higher than DWIconv's 0.694 (p = 0.020), and similar to the combined diffusion model's AUC of 0.917 (p = 0.650). In both tasks, DKI, FROC, and SEM failed to show diagnostic superiority over DWIconv (p > 0.05).

CONCLUSION

CTRW and IVIM are two potential non-Gaussian diffusion models to improve the MRI application in assessing muscle invasion and histological grade of BCa, respectively.

CRITICAL RELEVANCE STATEMENT

Our study validates non-Gaussian diffusion imaging as a reliable, non-invasive technique for early assessment of muscle invasion and histological grade in BCa, enhancing accuracy in diagnosis and improving MRI application in BCa diagnostic procedures.

KEY POINTS

Muscular invasion largely determines bladder salvageability in bladder cancer patients. Evaluated non-Gaussian diffusion metrics surpassed DWIconv in BCa muscle invasion and histological grade diagnosis. Non-Gaussian diffusion imaging improved MRI application in preoperative diagnosis of BCa.

Amide Proton Transfer-Weighted Imaging in Assessing the Aggressive and Proliferative Potential of Bladder Cancer

BACKGROUND

Ki-67 and human epidermal growth factor receptor 2 (HER2) are known oncogenes involved in bladder cancer (BCa) patient risk stratification. Preoperative assessment of their expression level can assist in clinical treatment decision-making. Recently, amide proton transfer-weighted (APTw) MRI has shown promising potential in the diagnosis of several malignancies. However, few studies reported the value of APTw imaging in evaluating Ki-67 and HER2 status of BCa.

PURPOSE

To investigate the feasibility of APTw MRI in assessing the aggressive and proliferative potential regarding the expression levels of Ki-67 and HER2 in BCa.

STUDY TYPE

Retrospective.

SUBJECTS

114 patients (mean age, 64.78 ± 11.93 [SD] years; 97 men) were studied.

FIELD STRENGTH/SEQUENCE

APTw MRI acquired by a three-dimensional fast-spin-echo sequence at 3.0 T MRI system.

ASSESSMENT

Patient pathologic findings, included histologic grade and the expression status of Ki-67 and HER2, were reviewed by one uropathologist. The APTw values of BCa were independently measured by two radiologists and were compared between high-/low-tumor grade group, high-/low-Ki-67 expression group, and high-/low-HER2 expression group.

STATISTICAL TESTS

The interclass correlation coefficient, independent sample t-test, Mann-Whitney U test, Spearman's rank correlation, and receiver operating characteristic curve (ROC) analysis were used. P < 0.05 was considered statistically significant.

RESULTS

Significantly higher APTw values were found in high-grade BCa patients (7.72% vs. 4.29%, P < 0.001), high-Ki-67 expression BCa patients (8.40% vs. 3.25%, P < 0.001) and HER2 positive BCa patients (8.24% vs. 5.40%, P = 0.001). APTw values were positively correlated with Ki-67 (r = 0.769) and HER2 (r = 0. 356) expression status. The area under the ROC curve of the APTw values for detecting Ki-67 and HER2 expression status were 0.883 (95% CI: 0.790-0.945) and 0.713 (95% CI: 0.592-0.816), respectively.

DATA CONCLUSIONS

APTw MRI is a potential method to assess the biological and proliferation potential of BCa.

LEVEL OF EVIDENCE: 4

TECHNICAL EFFICACY

Stage 2.

Management of patients with muscle-invasive bladder cancer with clinical evidence of pelvic lymph node metastases

Identification of clinically positive pelvic lymph node metastases (cN+) in patients with muscle-invasive bladder cancer is currently challenging, as the diagnostic accuracy of available imaging modalities is limited. Conventional CT is still considered the gold-standard approach to diagnose lymph node metastases in these patients. The development of innovative diagnostic methods including radiomics, artificial intelligence-based models and molecular biomarkers might offer new perspectives for the diagnosis of cN+ disease. With regard to the treatment of these patients, multimodal strategies are likely to provide the best oncological outcomes, especially using induction chemotherapy followed by radical cystectomy and pelvic lymph node dissection in responders to chemotherapy. Additionally, the use of adjuvant nivolumab has been shown to decrease the risk of recurrence in patients who still harbour ypT2-T4a and/or ypN+ disease after surgery. Alternatively, the use of avelumab maintenance therapy can be offered to patients with unresectable cN+ tumours who have at least stable disease after induction chemotherapy alone. Lastly, patients with cN+ tumours who are not responding to induction chemotherapy are potential candidates for receiving second-line treatment with pembrolizumab.

Prediction of histopathologic grades of bladder cancer with radiomics based on MRI: Comparison with traditional MRI

PURPOSE

To compare biparametric magnetic resonance imaging (bp-MRI) radiomics signatures and traditional MRI model for the preoperative prediction of bladder cancer (BCa) grade.

MATERIALS AND METHODS

This retrospective study included 255 consecutive patients with pathologically confirmed 113 low-grade and 142 high-grade BCa. The traditional MRI nomogram model was developed using univariate and multivariate logistic regression by the mean apparent diffusion coefficient (ADC), vesical imaging reporting and data system, tumor size, and the number of tumors. Volumes of interest were manually drawn on T2-weighted imaging (T2WI) and ADC maps by 2 radiologists. Using one-way analysis of variance, correlation, and least absolute shrinkage and selection operator methods to select features. Then, a logistic regression classifier was used to develop the radiomics signatures. Receiver operating characteristic (ROC) analysis was used to compare the diagnostic abilities of the radiomics and traditional MRI models by the DeLong test. Finally, decision curve analysis was performed by estimating the clinical usefulness of the 2 models.

RESULTS

The area under the ROC curves (AUCs) of the traditional MRI model were 0.841 in the training cohort and 0.806 in the validation cohort. The AUCs of the 3 groups of radiomics model [ADC, T2WI, bp-MRI (ADC and T2WI)] were 0.888, 0.875, and 0.899 in the training cohort and 0.863, 0.805, and 0.867 in the validation cohort, respectively. The combined radiomics model achieved higher AUCs than the traditional MRI model. decision curve analysis indicated that the radiomics model had higher net benefits than the traditional MRI model.

CONCLUSION

The bp-MRI radiomics model may help distinguish high-grade and low-grade BCa and outperforming the traditional MRI model. Multicenter validation is needed to acquire high-level evidence for its clinical application.

Multiparametric MRI-based VI-RADS: can it predict 1- to 5-year recurrence of bladder cancer?

OBJECTIVES

To evaluate whether Vesical Imaging-Reporting And Data System (VI-RADS) scores based on multiparametric MRI (mp-MRI) can predict bladder cancer (BCa) recurrence.

METHODS

In this retrospective study, 284 patients with pathologically confirmed bladder neoplasms from November 2011 to October 2020 were included. Two radiologists blindly and independently scored mp-MRI scans according to VI-RADS. Scoring inconsistency was resolved in consensus. The latest follow-up was completed in December 2022. Pearson's correlation analyses, independent-sample t-tests, and receiver operating characteristic analyses were performed to assess the efficacy of VI-RADS score for the 1- to 5-year recurrence prognostication.

RESULTS

Based on the latest follow-up, 37 (of 284, 13.0%), 69 (of 284, 24.3%), 70 (of 234, 29.9%), 72 (of 190, 37.9%), and 63 (of 135, 46.7%) patients had cancer recurrence at 1- to 5-year follow-up, respectively. VI-RADS scores showed significantly intergroup differences between recurrent and nonrecurrent cases during 1- to 4-year surveillance (p < 0.05). The recurrence-free survival was significantly higher in patients with VI-RADS scores of 1 or 2, compared to those with scores of 3, 4, or 5 (p < 0.05). Areas under the receiver operating characteristic curves for 1- to 5-year recurrence prediction were 0.744, 0.686, 0.656, 0.595, and 0.536, respectively. VI-RADS score of 3 or more was the threshold for 1-year recurrence assessment, and VI-RADS more than 3 was the cutoff for 2-year recurrence prediction.

CONCLUSION

VI-RADS score has potential in preoperative prognostication of BCa recurrence, but its predictive power decreases over time.

CLINICAL RELEVANCE STATEMENT

VI-RADS has potential in bladder cancer recurrence assessment, but its prognostic value decreases over time. Patients with VI-RADS ≥ 3 may be more likely to recur in 1 or 2 years postoperatively, thus should be performed with intensive surveillances.

KEY POINTS

• VI-RADS scores had significant differences in 1- to 4-year recurrent and nonrecurrent patient groups. • Patients with VI-RADS scores of ≤ 2 showed more favorable recurrence-free survival outcomes. • The prognostic value of VI-RADS score decreased over time for bladder cancer recurrence prediction.

Vesical Imaging-Reporting and Data System (VI-RADS) as a grouping imaging biomarker combined with a decision-tree mode to preoperatively predict the pathological grade of bladder cancer

AIM

To investigate whether the Vesical Imaging-Reporting and Data System (VI-RADS) could be used to develop a new non-invasive preoperative grade-prediction system to partially predict high-grade bladder cancer (HG-BC).

MATERIALS AND METHODS

The present study enrolled 89 primary BC patients prospectively from March 2022 to June 2023. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance of VI-RADS for predicting HG-BC and muscle-invasive bladder cancer (MIBC) in the entire group. In the low VI-RADS (≤2) group, the decision tree-based method was used to obtain significant predictors and construct the decision-tree model (DT model). The performance of the DT model and low VI-RADS scores for predicting HG-BC was determined using ROC, calibration, and decision curve analyses.

RESULTS

At a cut-off of ≥3, the specificity and positive predictive value of VI-RADS for predicting HG-BC in the entire group was 100%, and the area under the ROC curve (AUC) was 0.697. Among 65 patients with low VI-RADS scores, the DT model showed an AUC of 0.884 in predicting HG-BC compared to 0.506 for low VI-RADS scores. Calibration and decision curve analyses showed that the DT model performed better than the low VI-RADS scores.

CONCLUSION

Most VI-RADS scores ≥3 correspond to HG-BCs. VI-RADS could be used as a grouping imaging biomarker for a pathological grade-prediction procedure, which in combination with the DT model for low VI-RADS (≤2) populations, would provide a potential preoperative non-invasive method of predicting HG-BC.

Performance of VI-RADS in predicting muscle-invasive bladder cancer after transurethral resection: a single center retrospective analysis

PURPOSE

To assess VIRADS performance and inter-reader agreement for detecting muscle-invasive bladder cancer (MIBC) following transurethral resection of bladder tumor (TURBT).

METHODS

An IRB-approved, HIPAA-compliant, retrospective study from 2016 to 2020 included patients with bladder urothelial carcinoma who underwent MRI after TURBT, and cystectomy within 3 months without post-MRI treatments. Three radiologists blinded to pathology results independently reviewed MR images and assigned a VI-RADS score. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of VI-RADS were assessed for diagnosing MIBC using VI-RADS scores ≥ 3 and ≥ 4. Inter-reader agreement was assessed using Gwet's agreement coefficient (AC) and percent agreement.

RESULTS

The cohort consisted of 70 patients (mean age, 68 years ± 11 [SD]; range 39-85; 58 men) and included 32/70 (46%) with MIBC at cystectomy. ROC analysis revealed an AUC ranging from 0.67 to 0.77 and no pairwise statistical difference between readers (p-values, 0.06, 0.08, 0.97). Percent sensitivity, specificity, PPV, NPV and accuracy for diagnosing MIBC for the three readers ranged from 81.3-93.8, 36.8-55.3, 55.6-60.5, 77.3-87.5, and 62.9-67.1 respectively for VI-RADS score ≥ 3, and 78.1-81.3, 47.4-68.4, 55.6-67.6, 72.0-78.8 and 61.4-72.9 respectively for VI-RADS score ≥ 4. Gwet's AC was 0.63 [95% confidence interval (CI): 0.49,0.78] for VI-RADS score ≥ 3 with 79% agreement [95% CI 72,87] and 0.54 [95%CI 0.38,0.70] for VI-RADS score ≥ 4 with 76% agreement [95% CI 69,84]. VIRADS performance was not statistically different among 31/70 (44%) patients who received treatments prior to MRI (p ≥ 0.16).

CONCLUSION

VI-RADS had moderate sensitivity and accuracy but low specificity for detection of MIBC following TURBT, with moderate inter-reader agreement.

Bladder MRI with deep learning-based reconstruction: a prospective evaluation of muscle invasiveness using VI-RADS

PURPOSE

To investigate the influence of deep learning reconstruction (DLR) on bladder MRI, specifically examination time, image quality, and diagnostic performance of vesical imaging reporting and data system (VI-RADS) within a prospective clinical cohort.

METHODS

Seventy participants with bladder cancer who underwent MRI between August 2022 and February 2023 with a protocol containing standard T2-weighted imaging (T2WIS), standard diffusion-weighted imaging (DWIS), fast T2WI with DLR (T2WIDL), and fast DWI with DLR (DWIDL) were enrolled in this prospective study. Imaging quality was evaluated by measuring signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and qualitative image quality scoring. Additionally, the apparent diffusion coefficient (ADC) of bladder lesions derived from DWIS and DWIDL was measured and VI-RADS scoring was performed. Paired t-test or paired Wilcoxon signed-rank test were performed to compare image quality score, SNR, CNR, and ADC between standard sequences and fast sequences with DLR. The diagnostic performance for VI-RADS was assessed using the area under the receiver operating characteristic curve (AUC).

RESULTS

Compared to T2WIS and DWIS, T2WIDL and DWIDL reduced the acquisition time from 5:57 min to 3:13 min and showed significantly higher SNR, CNR, qualitative image quality score of overall image quality, image sharpness, and lesion conspicuity. There were no significant differences in ADC and AUC of VI-RADS between standard sequences and fast sequences with DLR.

CONCLUSIONS

The application of DLR to T2WI and DWI reduced examination time and significantly improved image quality, maintaining ADC and the diagnostic performance of VI-RADS for evaluating muscle invasion in bladder cancer.

MRI evaluation of vesical imaging reporting and data system for bladder cancer after neoadjuvant chemotherapy

BACKGROUND

The Vesical Imaging-Reporting and Data System (VI-RADS) has demonstrated effectiveness in predicting muscle invasion in bladder cancer before treatment. The urgent need currently is to evaluate the muscle invasion status after neoadjuvant chemotherapy (NAC) for bladder cancer. This study aims to ascertain the accuracy of VI-RADS in detecting muscle invasion post-NAC treatment and assess its diagnostic performance across readers with varying experience levels.

METHODS

In this retrospective study, patients with muscle-invasive bladder cancer who underwent magnetic resonance imaging (MRI) after NAC from September 2015 to September 2018 were included. VI-RADS scores were independently assessed by five radiologists, consisting of three experienced in bladder MRI and two inexperienced radiologists. Comparison of VI-RADS scores was made with postoperative histopathological diagnosis. Receiver operating characteristic curve analysis (ROC) was used for evaluating diagnostic performance, calculating sensitivity, specificity, and area under ROC (AUC)). Interobserver agreement was assessed using the weighted kappa statistic.

RESULTS

The final analysis included 46 patients (mean age: 61 years ± 9 [standard deviation]; age range: 39-70 years; 42 men). The pooled AUC for predicting muscle invasion was 0.945 (95% confidence interval (CI): 0.893-0.977) for experienced readers, and 0.910 (95% CI: 0.831-0.959) for inexperienced readers, and 0.932 (95% CI: 0.892-0.961) for all readers. At an optimal cut-off value ≥ 4, pooled sensitivity and specificity were 74.1% (range: 66.0-80.9%) and 94.1% (range: 88.6-97.7%) for experienced readers, and 63.9% (range: 59.6-68.1%) and 86.4% (range: 84.1-88.6%) for inexperienced readers. Interobserver agreement ranged from substantial to excellent between all readers (k = 0.79-0.92).

CONCLUSIONS

VI-RADS accurately assesses muscle invasion in bladder cancer patients after NAC and exhibits good diagnostic performance across readers with different experience levels.

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.

A Nomogram of MRI Features to Assess Muscle Invasion in VI-RADS 2 Tumors With Stalk

BACKGROUND

Vesical Imaging-Reporting and Data System (VI-RADS) is widely used to assess the muscle-invasive status of bladder cancer. However, the current classification efficacy of VI-RASD 2 tumors of stalk is unsatisfactory.

PURPOSE

To develop a nomogram to assess muscle-invasive bladder cancer (MIBC) in VI-RADS 2 tumors with stalk.

STUDY TYPE

Retrospective.

POPULATION

A total of 186 patients (age: 67.8 ± 12.7 years) with 15.1% females, divided randomly into a training cohort (N = 130) and validation cohort (N = 56).

FIELD STRENGTH/SEQUENCE

3-T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin-echo), and dynamic contrast-enhanced imaging (gradient-echo).

ASSESSMENT

Twenty-one MRI features of tumors and stalks were developed from training cohort. The mean apparent diffusion coefficient (ADC) values of the tumor, stalk, and psoas muscles were calculated from the three circular regions of interest. The normalized T value = mean ADC tumor mean ADC muscle . The normalized ST value = mean ADC stalk mean ADC tumor . Three readers assessed the morphology of tumors and stalks.

STATISTICAL TESTS

The final features of nomogram were selected by univariable logistic and the least absolute shrinkage and selection operator (LASSO) regression. The performance of the nomogram was assessed by the receiver operating characteristic (ROC) curve, calibration, and decision curve analysis.

RESULTS

In VI-RADS 2 tumors with stalk, tumor size over 3 cm, increased stalk width, stalk morphology, decreased normalized T value, and increased normalized ST value were selected as the risk factors for MIBC. The AUC, accuracy, sensitivity, and specificity of the nomogram to assess MIBC were 0.969 (95% CI: 0.941-0.997), 92.3%, 94.1%, and 92.0% in training cohort and 0.940 (95% CI: 0.859-1.000), 89.3%, 75.0%, and 91.7% in validation cohort.

DATA CONCLUSION

This study constructed a nomogram for preoperative assessment of MIBC and modifying the current VI-RADS.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

Multiparametric Magnetic Resonance Imaging in the follow-up of non-muscle-invasive bladder tumors after intravesical instillations: a promising tool

PURPOSE

The standard follow-up for non-muscle-invasive bladder cancer is based on cystoscopy. Unfortunately, post-instillation inflammatory changes can make the interpretation of this exam difficult, with lower specificity. This study aimed to evaluate the interest of bladder MRI in the follow-up of patients following intravesical instillation.

METHODS

Data from patients who underwent cystoscopy and bladder MRI in a post-intravesical instillation setting between February 2020 and March 2023 were retrospectively collected. Primary endpoint was to evaluate and compare the diagnostic performance of cystoscopy and bladder MRI in the overall cohort (n = 67) using the pathologic results of TURB as a reference. The secondary endpoint was to analyze the diagnostic accuracy of cystoscopy and bladder MRI according to the appearance of the lesion on cystoscopy [flat (n = 40) or papillary (n = 27)].

RESULTS

The diagnostic performance of bladder MRI was better than that of cystoscopy, with a specificity of 47% (vs. 6%, p < 0.001), a negative predictive value of 88% (vs. 40%, p = 0.03), and a positive predictive value of 66% (vs. 51%, p < 0.001), whereas the sensitivity did not significantly differ between the two exams. In patients with doubtful cystoscopy and negative MRI findings, inflammatory changes were found on TURB in most cases (17/19). The superiority in MRI bladder performance prevailed for "flat lesions", while no significant difference was found for "papillary lesions".

CONCLUSIONS

In cases of doubtful cystoscopy after intravesical instillations, MRI appears to be relevant with good performance in differentiating post-therapeutic inflammatory changes from recurrent tumor lesions and could potentially allow avoiding unnecessary TURB.

Determining the clinicopathological significance of the VI-RADS ≧4 group: a retrospective study

BACKGROUND

The Vesical Imaging Reporting and Data System (VI-RADS) is widely used for predicting muscle-invasive bladder cancer (MIBC). This study aimed to determine the clinicopathological significance of the VI-RADS ≧4 (VI≧4) group.

METHODS

Patients who underwent transurethral resections of bladder tumors during the study period and preoperative magnetic resonance imaging were considered. The patients were pathologically diagnosed with urothelial carcinoma (UC). We first compared the results of patients with VI-RADS scores of 3 and 4 to determine the cut-off score for MIBC; thereafter, the patients were divided into the VI≧4 and VI-RADS ≦3 (VI≦3) groups using VI-RADS. The clinicopathological significance of the VI≧4 group was examined retrospectively by comparing the characteristics of each group.

RESULTS

In total, 121 cases were examined, of which 28 were pathologically diagnosed with MIBC. Of the 28 MIBC cases, three (10.7%) had a VI-RADS score of ≦3, and 25 (89.3%) had a VI-RADS score of ≧4. Of the 93 NMIBC cases, 86 (92.5%) had a VI-RADS score of ≦3, and seven (7.5%) had a VI-RADS score of ≧4. The diagnostic performance of the VI-RADS with a cut-off score of 4 was 89.3% for sensitivity, 92.5% for specificity, and an area under the curve (AUC) of 0.91. Contrastingly, for a cut-off score of 3, the sensitivity was 89.3%, specificity was 62.0%, and AUC was 0.72. A VI-RADS score of ≥ 4 could predict MIBC. In the VI≧4 group, 30 of 32 (93.8%) patients had high-grade tumors. The VI≧4 group had significantly more high-grade bladder cancers than the VI≦3 group (p < 0.001 OR = 31.77 95%CI:8.47-1119.07). In addition, the VI≧4 group had more tumor necrosis (VI≧4 vs VI≦3, p < 0.001 OR = 7.46 95%CI:2.61-21.34) and more UC variant cases (VI≧4 vs VI≦3, p = 0.034 OR = 3.28 95%CI:1.05-10.25) than the VI≦3 group.

CONCLUSIONS

This study suggests that VI-RADS has a high diagnostic performance in predicting MIBC and that VI-RADS could diagnose high-grade tumors, necrosis, and UC variants.

SMMF: a self-attention-based multi-parametric MRI feature fusion framework for the diagnosis of bladder cancer grading

Background

Multi-parametric magnetic resonance imaging (MP-MRI) may provide comprehensive information for graded diagnosis of bladder cancer (BCa). Nevertheless, existing methods ignore the complex correlation between these MRI sequences, failing to provide adequate information. Therefore, the main objective of this study is to enhance feature fusion and extract comprehensive features from MP-MRI using deep learning methods to achieve an accurate diagnosis of BCa grading.

Methods

In this study, a self-attention-based MP-MRI feature fusion framework (SMMF) is proposed to enhance the performance of the model by extracting and fusing features of both T2-weighted imaging (T2WI) and dynamic contrast-enhanced imaging (DCE) sequences. A new multiscale attention (MA) model is designed to embed into the neural network (CNN) end to further extract rich features from T2WI and DCE. Finally, a self-attention feature fusion strategy (SAFF) was used to effectively capture and fuse the common and complementary features of patients' MP-MRIs.

Results

In a clinically collected sample of 138 BCa patients, the SMMF network demonstrated superior performance compared to the existing deep learning-based bladder cancer grading model, with accuracy, F1 value, and AUC values of 0.9488, 0.9426, and 0.9459, respectively.

Conclusion

Our proposed SMMF framework combined with MP-MRI information can accurately predict the pathological grading of BCa and can better assist physicians in diagnosing BCa.

MRI-based automated machine learning model for preoperative identification of variant histology in muscle-invasive bladder carcinoma

OBJECTIVES

It is essential yet highly challenging to preoperatively diagnose variant histologies such as urothelial carcinoma with squamous differentiation (UC w/SD) from pure UC in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. We developed a non-invasive automated machine learning (AutoML) model to preoperatively differentiate UC w/SD from pure UC in patients with MIBC.

METHODS

A total of 119 MIBC patients who underwent baseline bladder MRI were enrolled in this study, including 38 patients with UC w/SD and 81 patients with pure UC. These patients were randomly assigned to a training set or a test set (3:1). An AutoML model was built from the training set, using 13 selected radiomic features from T2-weighted imaging, semantic features (ADC values), and clinical features (tumor length, tumor stage, lymph node metastasis status), and subsequent ten-fold cross-validation was performed. A test set was used to validate the proposed model. The AUC of the ROC curve was then calculated for the model.

RESULTS

This AutoML model enabled robust differentiation of UC w/SD and pure UC in patients with MIBC in both training set (ten-fold cross-validation AUC = 0.955, 95% confidence interval [CI]: 0.944-0.965) and test set (AUC = 0.932, 95% CI: 0.812-1.000).

CONCLUSION

The presented AutoML model, that incorporates the radiomic, semantic, and clinical features from baseline MRI, could be useful for preoperative differentiation of UC w/SD and pure UC.

CLINICAL RELEVANCE STATEMENT

This MRI-based automated machine learning (AutoML) study provides a non-invasive and low-cost preoperative prediction tool to identify the muscle-invasive bladder cancer patients with variant histology, which may serve as a useful tool for clinical decision-making.

KEY POINTS

• It is important to preoperatively diagnose variant histology from urothelial carcinoma in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. • An automated machine learning (AutoML) model based on baseline bladder MRI can identify the variant histology (squamous differentiation) from urothelial carcinoma preoperatively in patients with MIBC. • The developed AutoML model is a non-invasive and low-cost preoperative prediction tool, which may be useful for clinical decision-making.

Practical Guide to VI-RADS: MRI Protocols, Lesion Characterization, and Pitfalls

Urothelial carcinoma is the most common type of bladder cancer (BC), accounting for approximately 90% of all cases. Evaluating the depth of tumor invasion in the bladder wall (tumor staging) is essential for determining the treatment and prognosis in patients with BC. Neoadjuvant therapy followed by radical cystectomy is the most common treatment of localized muscle-invasive BC (MIBC). Therefore, it is vital to differentiate non-MIBC from MIBC. Transurethral resection of bladder tumor (TURBT) is the reference standard to determine the extent of tumor invasion into the bladder wall through tissue sampling. However, this diagnostic and therapeutic method may not adequately sample the muscularis propria, leading to a higher risk of residual disease, early recurrence, and tumor understaging in approximately 50% of patients during the initial TURBT. Multiparametric MRI can overcome some of the limitations of TURBT when evaluating BC, particularly regarding tumor staging. In this context, the Vesical Imaging Reporting and Data System (VI-RADS) classification was developed to establish standards for bladder multiparametric MRI and interpretation. It uses a 5-point scale to assess the likelihood of detrusor muscle invasion. T2-weighted MR images are particularly useful as an initial guide, especially for categories 1-3, while the presence of muscular invasion is determined with diffusion-weighted and dynamic contrast-enhanced sequences. Diffusion-weighted imaging takes precedence as the dominant method when optimal image quality is achieved. The presence of a stalk or a thickened inner layer and no evidence of interruption of the signal intensity of the muscular layer are central for predicting a low likelihood of muscle invasion. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Hoegger in this issue.

A novel predict method for muscular invasion of bladder cancer based on 3D mp-MRI feature fusion

Objective. To assist urologist and radiologist in the preoperative diagnosis of non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), we proposed a combination models strategy (CMS) utilizing multiparametric magnetic resonance imaging.Approach. The CMS includes three components: image registration, image segmentation, and multisequence feature fusion. To ensure spatial structure consistency of T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCE), a registration network based on patch sampling normalized mutual information was proposed to register DWI and DCE to T2WI. Moreover, to remove redundant information around the bladder, we employed a segmentation network to obtain the bladder and tumor regions from T2WI. Using the coordinate mapping from T2WI, we extracted these regions from DWI and DCE and integrated them into a three-branch dual-channel input. Finally, to fully fuse low-level and high-level features of T2WI, DWI, and DCE, we proposed a distributed multilayer fusion model for preoperative MIBC prediction with five-fold cross-validation.Main results. The study included 436 patients, of which 404 were for the internal cohort and 32 for external cohort. The MIBC was confirmed by pathological examination. In the internal cohort, the area under the curve, accuracy, sensitivity, and specificity achieved by our method were 0.928, 0.869, 0.753, and 0.929, respectively. For the urologist and radiologist, Vesical Imaging-Reporting and Data System score >3 was employed to determine MIBC. The urologist demonstrated an accuracy, sensitivity, and specificity of 0.842, 0.737, and 0.895, respectively, while the radiologist achieved 0.871, 0.803, and 0.906, respectively. In the external cohort, the accuracy of our method was 0.831, which was higher than that of the urologist (0.781) and the radiologist (0.813).Significance. Our proposed method achieved better diagnostic performance than urologist and was comparable to senior radiologist. These results indicate that CMS can effectively assist junior urologists and radiologists in diagnosing preoperative MIBC.

Progress of Multiparameter Magnetic Resonance Imaging in Bladder Cancer: A Comprehensive Literature Review

Magnetic resonance imaging (MRI) has been proven to be an indispensable imaging method in bladder cancer, and it can accurately identify muscular invasion of bladder cancer. Multiparameter MRI is a promising tool widely used for preoperative staging evaluation of bladder cancer. Vesical Imaging-Reporting and Data System (VI-RADS) scoring has proven to be a reliable tool for local staging of bladder cancer with high accuracy in preoperative staging, but VI-RADS still faces challenges and needs further improvement. Artificial intelligence (AI) holds great promise in improving the accuracy of diagnosis and predicting the prognosis of bladder cancer. Automated machine learning techniques based on radiomics features derived from MRI have been utilized in bladder cancer diagnosis and have demonstrated promising potential for practical implementation. Future work should focus on conducting more prospective, multicenter studies to validate the additional value of quantitative studies and optimize prediction models by combining other biomarkers, such as urine and serum biomarkers. This review assesses the value of multiparameter MRI in the accurate evaluation of muscular invasion of bladder cancer, as well as the current status and progress of its application in the evaluation of efficacy and prognosis.

Diagnostic Accuracy of Contrast-Enhanced Ultrasound (CEUS) in the Detection of Muscle-Invasive Bladder Cancer: A Systematic Review and Diagnostic Meta-Analysis

BACKGROUND

Contrast-enhanced ultrasound (CEUS) is a diagnostic tool that is gaining popularity for its ability to improve overall diagnostic accuracy in bladder cancer (BC) staging. Our aim is to determine the cumulative diagnostic performance of CEUS in predicting preoperative muscle invasiveness using a comprehensive systematic review and pooled meta-analysis.

METHODS

A systematic review until October 2023 was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Patients with BC suspicion were offered CEUS before the transurethral resection of the bladder tumor (TURBT). The diagnostic performance of CEUS was evaluated based on non-muscle-invasive bladder cancer (NMIBC) vs. muscle-invasive bladder cancer (MIBC) confirmed at the final histopathological examination after TURBT. The outcomes were determined through pooled sensitivity, specificity, pooled positive likelihood ratio (PLR+), negative likelihood ratio (PLR-), and area under the summary receiver operating characteristic (SROC) along with their respective 95% confidence intervals (CI).

RESULTS

Overall, five studies were included. In these studies, a total of 362 patients underwent CEUS prior to TURBT. The pooled sensitivity and specificity were 0.88 (95% CI: 0.81-0.93) and 0.88 (95% CI: 0.82-0.92), respectively. SROC curve depicted a diagnostic accuracy of 0.94 (95% CI: 0.81-0.98). The pooled PLR+ and PLR- were 7.3 (95% CI: 4.8-11.2) and 0.14 (95% CI: 0.08-0.23), respectively.

CONCLUSIONS

Our meta-analysis indicates that CEUS is highly accurate in the diagnosis and staging for BC. Beyond its accuracy, CEUS offers the advantage of being a cost-effective, safe, and versatile imaging tool.

Vesical Imaging-Reporting and Data System use predicting the outcome of neoadjuvant pembrolizumab in muscle-invasive bladder cancer

OBJECTIVE

To evaluate the predictive capability of the pre- and post-pembrolizumab Vesical Imaging-Reporting and Data System (VI-RADS) to identify ypT0N0 or ypT≤1N0 response in muscle-invasive bladder cancer (MIBC) within the PURE-01 trial (ClinicalTrials.gov identifier: NCT02736266).

PATIENTS AND METHODS

Patients were staged with bladder multiparametric magnetic resonance imaging (mpMRI) before and after treatment (three cycles of pembrolizumab) prior to radical cystectomy (RC). Logistic regression models were used to analyse the pre- and post- pembrolizumab VI-RADS against ypT≤1N0 and ypT0N0 response. The VI-RADS scores were dichotomised between 0 and 3 (0 = no evidence of disease) and 4-5. Event-free survival (EFS) and overall survival (OS) analyses were performed. Comprehensive genomic profiling and transcriptome-wide expression profiling data were matched with the VI-RADS scores.

RESULTS

In total, 110 patients underwent centrally reviewed scans (N = 220 mpMRI), treated between February 2017 and July 2020. Both pre- and post-pembrolizumab VI-RADS 0-3 scores were the only significant covariates that predicted the ypT≤1N0 endpoint in multivariable analyses, and the strongest effect was seen with post-pembrolizumab VI-RADS 0-3 predicting the ypT≤1N0 response (P < 0.001). The area under the curve for this model was 0.90. Post-pembrolizumab VI-RADS 0-3 also predicted a longer EFS (P < 0.001) and OS (P = 0.044). The scores of several gene signatures from baseline tumours differed between the pre-pembrolizumab VI-RADS 0-3 and 4-5 categories.

CONCLUSION

Post-pembrolizumab VI-RADS scores are strongly associated with pathological downstaging and survival. VI-RADS scores were also characterised by distinct biomarker features. These results indicate that the VI-RADS is emerging as an important tool for designing next-generation trials for MIBC.

Role of multiparametric MRI in predicting muscle invasiveness in urinary bladder neoplasms with pathological correlations

Urinary bladder cancer (BC) is one of the most frequent malignancies and the ninth most common malignancy worldwide. The objective of this study is to assess the role of multiparametric magnetic resonance imaging (mp-MRI) in predicting the invasiveness of urinary bladder space occupying lesions. Thirty-five patients diagnosed with bladder masses underwent an mp-MRI study. The results of three image sets were analysed and compared with the histopathological results as a reference standard: T2-weighted image (T2WI) plus dynamic contrast-enhanced (DCE), T2WI plus diffusion-weighted images (DWI), and mp-MRI, including T2WI plus DWI and DCE. The diagnostic accuracy of mp-MRI was evaluated using receiver operating characteristic curve analysis. We discovered a highly significant correlation between muscle invasiveness as staged by HPE (Histopathological examination) and mp-MRI utilising a VI-RADS score >3 (p 0.001) with a sensitivity of 100% and a specificity of 85.7%. With a diagnostic accuracy of 77.14%, a sensitivity of 92.31%, a specificity of 72.72%, a positive predictive value of 66.67%, and a negative predictive value of 94.11%, In terms of muscle invasiveness, there is good concordance between HPE staging and mp-MRI utilising the VI-RADS score. The mean apparent diffusion coefficient (ADC) values were higher in low grades than in high grades. The ROC curve study revealed a very strong correlation between HPE grade and ADC (p = 0.045). In 77.14% of patients, Mp-MRI correctly identified the local T stage. Mp-MRI is imaging biomarker for invasiveness and grade of tumour. The tumours with high grade are more invasive. However, the diagnostic accuracy of mp-MRI in determining muscle invasiveness is not very high and it overstages the disease in some cases (33.3%). Its clinical usefulness in determining muscle invasiveness before TURBT and histopathological examination can be questioned.

Amide Proton Transfer-Weighted MRI and Diffusion-Weighted Imaging in Bladder Cancer: A Complementary Tool to the VI-RADS

RATIONALE AND OBJECTIVES

To investigate the feasibility of amide proton transfer-weighted (APTw) and diffusion-weighted Magnetic Resonance Imaging (MRI) as a means by which to add value to the Vesical Imaging Reporting and Data System (VI-RADS) for discriminating muscle invasive bladder cancer (MIBC) from nonmuscle invasive bladder cancer (NMIBC).

MATERIALS AND METHODS

This prospective study enrolled participants with pathologically confirmed bladder cancer (BCa) who underwent preoperative multiparametric MRI, including APTw and diffusion-weighted MRI, from July 2020 to January 2023. The exclusion criteria were lesions smaller than 10 mm, missing smooth muscle layer in the operation specimen, neoadjuvant therapy before MRI, inadequate image quality, and malignancy other than urothelial neoplasm. Two radiologists independently assigned the VI-RADS score for each participant. Quantitative parameters derived from APTw and diffusion-weighted MRI were obtained by another two radiologists. Receiver operating characteristic (ROC) curve analysis with the area under the ROC curve (AUC) was performed to evaluate the diagnostic performances of quantitative parameters for discriminating BCa detrusor muscle invasion status.

RESULTS

A total of 106 participants were enrolled (mean age, 64 ± 12 years [SD]; 90 men): 32 with MIBC and 74 with NMIBC. Lower apparent diffusion coefficient (ADC) values (0.88 × 10-3 mm2/s ± 0.12 vs. 1.08 × 10-3 mm2/s ± 0.25; P < 0.001) and higher APTw values (6.89% [interquartile range {IQR}, 5.05%-12.17%] vs. 3.61% [IQR, 2.23%-6.83%]; P < 0.001) were observed in the MIBC group. Compared to VI-RADS alone, both APTw (P = 0.003) and ADC (P = 0.020) values could improve the diagnostic performance of VI-RADS in differentiating MIBC from NMIBC. The combination of the three yielded the highest diagnostic performance (AUC, 0.93; 95% CI:0.87,0.97) for evaluating muscle invasion status. The addition of the APTw values to the combination of VI-RADS and ADC values notably improved the diagnostic performance for differentiating NMIBC from MIBC (VI-RADS+ADC vs. VI-RADS+APTw+ADC, P = 0.046).

CONCLUSION

MRI parameters derived from APTw and diffusion-weighted MRI can be used to accurately assess muscle invasion status in BCa and provide additional value to VI-RADS.