Diagnostic Accuracy and Interobserver Agreement for the Vesical Imaging-Reporting and Data System for Muscle-invasive Bladder Cancer: A Multireader Validation Study

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.

VI-RADS-based Algorithm for Bladder Cancer Management Randomized Retrospective Study

OBJECTIVE

To evaluate if VI-RADS can distinguish between nonmuscle-invasive bladder cancers (NMIBC), muscle-invasive bladder cancer (MIBC), and high-risk nonmuscle-invasive bladder cancers (HR-NMIBCs). It is unclear if the Vesical Imaging-Reporting and Data System (VI-RADS) can replace repeated transurethral resection of bladder tumor (Re-TURBT) as in the new VI-RADS-based algorithm.

METHODS

Sensitivity, specificity, and positive (PPV) and negative (NPV) predictive values of the VI-RADS score were calculated for mpMRI performance in patients undergoing TURBT and HR-NMIBC patients for only Re-TURBT.

RESULTS

Of 283 cases, when VI-RADS ≥3 lesions were considered muscle-invasive, its sensitivity was 95.7% and specificity was 92.5%. PPV and NPV were 86.6% and 97.7%, respectively. The area under the curve (AUC) was 0.942 (P <.001). Of 89 patients undergoing post-Re-TURBT, 41 (46%) were tumor-free, 47 (50.5%) showed permanent HR-NMIBC, and 3 (2.2%) were upgraded to MIBC. Per the new VI-RADS-based approach, 73 (41%) of the 178 HR-NMIBCs with VI-RADS ≤2 would not undergo Re-TURBT. Of the 75 patients with VI-RADS ≥4, 6 (6) with HR-NMIBCs (8%) would not undergo Re-TURBT. When incomplete resections were excluded, 35 (60.3%) of the patients had complete resection, 23 (39.7%) had residual disease, and complete resection would not have been performed in these patients, and 2 (100%) still had residual disease.

CONCLUSION

The new VI-RADS-based algorithm helped VI-RADS ≥4 patients by switching to radical treatment. Since the residual disease is high in cases with VI-RADS ≤2, even if incomplete resections are excluded, TURBT should be continued.

Effect of accumulating experience on diagnostic performance of VI-RADS in bladder cancer

PURPOSE

MRI-based VI-RADS score aids in differentiating MIBC and NMIBC, but the experience's impact remains unexplored. We aimed to determine the effect of accumulating experience in the diagnostic performance of VI-RADS.

METHODS

In our previously published series 71 primary bladder cancer patients who underwent multiparametric MRI before the transurethral resection were analyzed. The radiologist who assessed the VI-RADS scores at the time the study was performed, re-evaluated all cases after 3 years, in a blinded fashion. During these three years, more than 300 additional bladder MRIs were performed for VI-RADS assessment. The diagnostic performances of the initial and subsequent VI-RADS analyses were compared. Moreover, VIRADS results obtained by a newly trained abdominal radiologist was also compared with experienced radiologist's results. For this study, VI-RADS ≥3 was accepted for predicting MIBC.

RESULTS

Overall 71 patients [62 (87.3 %) males, 67.4 ± 10.2 years] who underwent bladder MRI before TURBT were included. Histopathology revealed MIBC in 16 (26.2 %) cases. The initial MRI analysis revealed VI-RADS score ≥ 3 in 36 (50.7 %) cases. The sensitivity and specificity for depicting MIBC were 75 % and 56.4 % respectively. The subsequent MRI analysis revealed VI-RADS score ≥ 3 in 23 (32.4 %) cases. The sensitivity and specificity were 93.8 % and 85.5 % respectively. The MRI analysis performed by the recently trained abdominal radiologist revealed VI-RADS score ≥ 3 in 24 (33.8 %) cases. The sensitivity and specificity were 87.5 % and 56.4 % respectively.

CONCLUSION

The diagnostic performance of VI-RADS for the interpretation of bladder MRI can improve over time by increasing the experience of the urogenital radiologist.

Development and Validation of a Contrast-Enhanced US VI-RADS for Evaluating Muscle Invasion in Bladder Cancer

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

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.

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.

Deep Learning Algorithms for Bladder Cancer Segmentation on Multi-Parametric MRI

BACKGROUND

Bladder cancer (BC) segmentation on MRI images is the first step to determining the presence of muscular invasion. This study aimed to assess the tumor segmentation performance of three deep learning (DL) models on multi-parametric MRI (mp-MRI) images.

METHODS

We studied 53 patients with bladder cancer. Bladder tumors were segmented on each slice of T2-weighted (T2WI), diffusion-weighted imaging/apparent diffusion coefficient (DWI/ADC), and T1-weighted contrast-enhanced (T1WI) images acquired at a 3Tesla MRI scanner. We trained Unet, MAnet, and PSPnet using three loss functions: cross-entropy (CE), dice similarity coefficient loss (DSC), and focal loss (FL). We evaluated the model performances using DSC, Hausdorff distance (HD), and expected calibration error (ECE).

RESULTS

The MAnet algorithm with the CE+DSC loss function gave the highest DSC values on the ADC, T2WI, and T1WI images. PSPnet with CE+DSC obtained the smallest HDs on the ADC, T2WI, and T1WI images. The segmentation accuracy overall was better on the ADC and T1WI than on the T2WI. The ECEs were the smallest for PSPnet with FL on the ADC images, while they were the smallest for MAnet with CE+DSC on the T2WI and T1WI.

CONCLUSIONS

Compared to Unet, MAnet and PSPnet with a hybrid CE+DSC loss function displayed better performances in BC segmentation depending on the choice of the evaluation metric.

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.

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.

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.

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.

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.

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.

Biparametric versus Multiparametric Magnetic Resonance Imaging for Assessing Muscle Invasion in Bladder Urothelial Carcinoma with Variant Histology Using the Vesical Imaging-Reporting and Data System

BACKGROUND

The diagnostic performance of contrast medium-free biparametric magnetic resonance imaging (bpMRI; combining T2-weighted imaging [T2WI] and diffusion-weighted imaging [DWI]) for evaluating variant-histology urothelial carcinoma (VUC) remains unknown.

OBJECTIVE

To compare the diagnostic performance of bpMRI and multiparametric MRI (mpMRI; combining T2WI, DWI, and dynamic contrast-enhanced MRI]) for assessing muscle invasion of VUC.

DESIGN, SETTING, AND PARTICIPANTS

This multi-institution retrospective analysis included 118 patients with pathologically verified VUC who underwent bladder mpMRI before transurethral bladder tumor resection between 2010 and 2019.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Three board-certified radiologists separately evaluated two sets of images, set 1 (bpMRI) and set 2 (mpMRI), in accordance with the Vesical Imaging Reporting and Data System (VI-RADS). The histopathology results were utilized as a reference standard. Receiver operating characteristic curve analysis, Z test, and Wald test were used to assess diagnostic abilities.

RESULTS AND LIMITATIONS

Sixty-six (55.9%) and 52 (44.1%) of the 118 patients with VUC included in the analysis (mean age, 71 ± 10 yr; 88 men) had muscle-invasive bladder cancer (MIBC) and non-MIBC, respectively. For the diagnosis of MIBC, the areas under the curve for bpMRI were significantly smaller than those for mpMRI (0.870-0.884 vs 0.902-0.923, p < 0.05). The sensitivity of bpMRI was significantly lower than that of mpMRI for all readers with a VI-RADS cutoff score of 4 (65.2-66.7% vs 77.3-80.3%, p < 0.05). The specificity of bpMRI and mpMRI did not differ significantly for all readers (88.5-90.4 vs 88.5-92.3, p > 0.05). A limitation of the study is the limited sample size because of the rarity of VUC.

CONCLUSIONS

In patients with VUC, on applying VI-RADS, the diagnostic results of bpMRI were inferior to those of mpMRI for evaluating muscle invasion. Therefore, mpMRI-based methods are recommended for evaluating muscle invasiveness of VUC.

PATIENT SUMMARY

Contrast medium-free biparametric magnetic resonance imaging (bpMRI)-based Vesical Imaging Reporting and Data System (VI-RADS) can accurately diagnose pure urothelial carcinomas, similar to conventional multiparametric magnetic resonance imaging-based VI-RADS. However, bpMRI-based VI-RADS may misdiagnose muscle invasiveness of urothelial carcinoma with variant histology, particularly when its cutoff score is 4.

A machine learning model based on MRI for the preoperative prediction of bladder cancer invasion depth

OBJECTIVES

To construct and validate a prediction model based on full-sequence MRI for preoperatively evaluating the invasion depth of bladder cancer.

METHODS

A total of 445 patients with bladder cancer were divided into a seven-to-three training set and test set for each group. The radiomic features of lesions were extracted automatically from the preoperative MRI images. Two feature selection methods were performed and compared, the key of which are the Least Absolute Shrinkage and Selection Operator (LASSO) and the Max Relevance Min Redundancy (mRMR). The classifier of the prediction model was selected from six advanced machine-learning techniques. The receiver operating characteristic (ROC) curves and the area under the curve (AUC) were applied to assess the efficiency of the models.

RESULTS

The models with the best performance for pathological invasion prediction and muscular invasion prediction consisted of LASSO as the feature selection method and random forest as the classifier. In the training set, the AUC of the pathological invasion model and muscular invasion model were 0.808 and 0.828. Furthermore, with the mRMR as the feature selection method, the external invasion model based on random forest achieved excellent discrimination (AUC, 0.857).

CONCLUSIONS

The full-sequence models demonstrated excellent accuracy for preoperatively predicting the bladder cancer invasion status.

CLINICAL RELEVANCE STATEMENT

This study introduces a full-sequence MRI model for preoperative prediction of the depth of bladder cancer infiltration, which could help clinicians to recognise pathological features associated with tumour infiltration prior to invasive procedures.

KEY POINTS

• Full-sequence MRI prediction model performed better than Vesicle Imaging-Reporting and Data System (VI-RADS) for preoperatively evaluating the invasion status of bladder cancer. • Machine learning methods can extract information from T1-weighted image (T1WI) sequences and benefit bladder cancer invasion prediction.

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.

Construction of 3D and 2D contrast-enhanced CT radiomics for prediction of CGB3 expression level and clinical prognosis in bladder cancer

Objective

The purpose of this study was to construct a 3D and 2D contrast-enhanced computed tomography (CECT) radiomics model to predict CGB3 levels and assess its prognostic abilities in bladder cancer (Bca) patients.

Methods

Transcriptome data and CECT images of Bca patients were downloaded from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA) database. Clinical data of 43 cases from TCGA and TCIA were used for radiomics model evaluation. The Volume of interest (VOI) (3D) and region of interest (ROI) (2D) radiomics features were extracted. For the construction of predicting radiomics models, least absolute shrinkage and selection operator regression were used, and the filtered radiomics features were fitted using the logistic regression algorithm (LR). The model's effectiveness was measured using 10-fold cross-validation and the area under the receiver operating characteristic curve (AUC of ROC).

Result

CGB3 was a differential expressed prognosis-related gene and involved in the immune response process of plasma cells and T cell gamma delta. The high levels of CGB3 are a risk element for overall survival (OS). The AUCs of VOI and ROI radiomics models in the training set were 0.841 and 0.776, while in the validation set were 0.815 and 0.754, respectively. The Delong test revealed that the AUCs of the two models were not statistically different, and both models had good predictive performance.

Conclusion

The CGB3 expression level is an important prognosis factor for Bca patients. Both 3D and 2D CECT radiomics are effective in predicting CGB3 expression levels.

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

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

DHCR7 promotes tumorigenesis via activating PI3K/AKT/mTOR signalling pathway in bladder cancer

Bladder cancer (BCa) is a common malignancy with uncertain molecular mechanism. 7-dehydrocholesterol reductase (DHCR7), the enzyme of mammalian sterol biosynthesis, plays important roles in several types of cancers but its specific function in BCa is still unknown. The current study aimed to determine the bioinformatic characteristics and biological functions of DHCR7 in BCa. Sequencing results and clinical data from online public databases, human BCa tissues and matched noncancerous tissues, xenograft nude mice, DHCR7 deficiency and overexpression BCa cell (T24 and EJ) models were used. Several bioinformatics analyses were made, qRT-PCR, Western-blotting, flow cytometry, immunohistochemistry (IHC), MTT assay, wound healing and cell invasion assays were performed. It was found that DHCR7 was upregulated in BCa as an independent risk factor, and the expression of DHCR7 was associated with BCa grade and stage, finally resulted in poor prognosis. We further demonstrated that DHCR7 overexpression could accelerate the G0/G1 phase to accelerate the growth of tumor cells, antagonize cell apoptosis, and enhance the invasion and migration capacity, as well as EMT process via PI3K/AKT/mTOR signalling pathway, which could be completely reversed by DHCR7 knockdown. Finally, DHCR7 deficiency significantly decreased tumorigenesis in vivo. Our novel data demonstrated that DHCR7 could modulate BCa tumorigenesis in vitro and in vivo via PI3K/AKT/mTOR signalling pathway. It is suggested that DHCR7 might become a molecular target for the diagnosis and treatment of BCa.

The Additional Value of Tri-parametric MRI in Identifying Muscle-invasive Status in Bladder Cancer

RATIONALE AND OBJECTIVES

Identification of muscle-invasive status (MIS) of bladder cancer (BCa) is critical for treatment decisions. The Vesical Imaging-Reporting and Data System (VI-RADS) has been widely used in preoperatively predicting MIS using tri-parametric MR imaging including T2-weighted (T2W), diffusion-weighted (DW), and dynamic contrast-enhanced (DCE) sequences. While the diagnostic values of radiomics features from bi-parametric MRI such as T2W + DW to identification of MIS have been reported, whether the tri-parametric MRI could provide additional diagnostic value to the radiomics prediction task, and how to integrate DCE features into the radiomics model, which is the objectives of this study, remain unknown.

MATERIALS AND METHODS

Patients with postoperatively confirmed BCa lesions (150 in non-muscle-invasive BCa and 56 in muscle-invasive BCa groups) were retrospectively included. Their T2W, DW with apparent diffusion coefficient (ADC) maps, and DCE sequences were acquired using a 3.0T MR system. Regions of interest were manually depicted and VI-RADS scores were assessed by three radiologists. Three predictive models were developed by the radiomics features extracted from sequence combinations of T2W + DW (Model one), T2W + DCE (Model two), and T2W + DW + DCE (Model three), respectively, using the least absolute shrinkage and selection operator. The performance of each model was quantitatively assessed on both the training (n = 165) and testing (n = 41) cohorts. Then a 10 times five-fold cross validation was conducted to assess the overall performance.

RESULTS

Three models achieved area under the curve of 0.888, 0.869, and 0.901 in the cross validation, respectively. The tri-parametric model performed significantly superior than the two bi-parametric models and VI-RADS. The analysis of feature coefficients derived from least absolute shrinkage and selection operator algorithm showed features from the tri-parametric MRI are effective in MIS discrimination.

CONCLUSION

The tri-parametric MRI provides additional value to the radiomics-based identification of MIS.

Inter-reader reliability of the vesical imaging-reporting and data system (VI-RADS) for muscle-invasive bladder cancer: a systematic review and meta-analysis

To evaluate the diagnostic agreement between readers in VI-RADS interpretation to detect muscle-invasive bladder cancer (MIBC) preoperatively, we conducted a systematic review and meta-analysis of the available data. Scopus, PubMed, Web of Science, and Embase databases were systematically searched up to November 13, 2021. Case reports, review articles, editorials, and studies with insufficient data were eliminated. The Quality Appraisal of the Diagnostic Reliability Checklist was used to assess the risk of bias. The degree of agreement was determined by Cohen's kappa coefficient (κ) for comparison of data. The heterogeneity of these studies was explored using subgroup analysis and meta-regression analysis. The level of confidence was set at 0.05. All analyses were conducted in STATA 16.0. Overall, 19 eligible studies, consisting of 2439 participants, were included in this meta-analysis. The inter-reader agreement for VI-RADS in MIBC detection ranged from κ of 0.45 to 0.96 among included studies. The pooled inter-reader reliability was calculated as 0.76 [95% CI 0.73-0.80; I² = 92.13%, Q(50) = 635.08, p < 0.01]. Sources of heterogeneity included magnetic strength, T2WI slice thickness, number of readers, sample size, study design, number of centers, year of publication, proportion of male patients, and mean age. There is substantial reliability in VI-RADS interpretation for MIBC among radiologists with various levels of expertise. The high degree of inter-reader agreement for MIBC detection supports the implementation of VI-RADS in routine clinical practice for the staging paradigm of bladder cancer.

Comparison between biparametric and multiparametric MRI in predicting muscle invasion by bladder cancer based on the VI-RADS

This study aimed to compare the diagnostic validity of biparametric magnetic resonance imaging (bpMRI) with that of multiparametric MRI (mpMRI) based on the Vesicle Imaging-Reporting and Data System (VI-RADS) in predicting muscle invasion by bladder cancer (BCa). We retrospectively examined 357 patients with an initial diagnosis of BCa who underwent preoperative MRI; 257 and 100 patients underwent mpMRI and bpMRI, respectively. Two urogenital radiologists evaluated all bpMRI and mpMRI scans using VI-RADS, and the diagnostic validity of VI-RADS for predicting muscle invasion by BCa was analyzed based on histopathology of the first and/or second transurethral resection of bladder tumors and radical cystectomy. Receiver operating characteristic (ROC) curves were plotted with the calculation of area under the curves (AUCs), and the level of significance was P < 0.05. Both groups showed optimal performance with a VI-RADS score ≥ 3. BpMRI showed comparable diagnostic performance to mpMRI (reader 1: AUC, 0.903 [0.827-0.954] vs. 0.935 [0.884-0.968], p = 0.510; and reader 2: AUC, 0.901 [0.814-0.945] vs. 0.915 [0.874-0.946]; p = 0.655). The inter-reader agreement between both readers was excellent (Cohen's kappa value = 0.942 and 0.905 for bpMRI and mpMRI, respectively). This comparative study suggests that bpMRI has comparable diagnostic performance to mpMRI and may be an alternative option to predict muscle invasion by BCa.

The role of radiomics with machine learning in the prediction of muscle-invasive bladder cancer: A mini review

Bladder cancer is a common malignant tumor in the urinary system. Depending on whether bladder cancer invades muscle tissue, it is classified into non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC). It is crucial to accurately diagnose the muscle invasion of bladder cancer for its clinical management. Although imaging modalities such as CT and multiparametric MRI play an important role in this regard, radiomics has shown great potential with the development and innovation of precision medicine. It features outstanding advantages such as non-invasive and high efficiency, and takes on important significance in tumor assessment and laor liberation. In this article, we provide an overview of radiomics in the prediction of muscle-invasive bladder cancer and reflect on its future trends and challenges.

Comparison of reduced field-of-view DWI and full field-of view DWI for the differentiation between non-muscle invasive bladder cancer and muscle invasive bladder cancer using VI-RADS

Purpose

To evaluate whether reduced field-of-view (rFOV) DWI sequence improves the differentiation between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) using VI-RADS.

Material and methods

Eighty-nine patients underwent bladder MRI with full field-of-view (fFOV) DWI and rFOV DWI sequence. Images were independently evaluated by 2 radiologists. The sensitivities, specificities, accuracies, and areas under the curve (AUCs) for the differentiation between NMIBC and MIBC with fFOV DWI and with rFOV DWI sequence were calculated using VI-RADS. Apparent diffusion coefficients (ADC) values were measured for each patient and averaged.

Results

The sensitivity, specificity, accuracy, and AUC by reader 1 were 92%, 78%, 82% and 0.905 with fFOV DWI, and 92%, 86%, 88% and 0.916 with rFOV DWI sequence, respectively. The sensitivity, specificity, accuracy and AUC by reader 2 were 96%, 76%, 82% and 0.900 with conventional DWI, and 96%, 81%, 85% and 0.907 with rFOV DWI sequence, respectively. The specificity and accuracy of reader 1 were significantly better with rFOV DWI sequence than with fFOV DWI, in contrast there was no significant difference for the others. The average of ADC values of fFOV DWI and rFOV DWI sequence were 1.004×10⁻⁶ mm²/s and 1.003×10⁻⁶ mm²/s, respectively.

Conclusion

The diagnostic ability of rFOV DWI sequence may be better than that of fFOV DWI using VI-RADS for the differentiation between NMIBC and MIBC regardless of image-reading experience, it is controversial.

The application value of multi-parameter cystoscope in improving the accuracy of preoperative bladder cancer grading

PURPOSE

To develop and validate a preoperative cystoscopic-based predictive model for predicting postoperative high-grade bladder cancer (BCa), which could be used to guide the surgical selection and postoperative treatment strategies.

MATERIALS AND METHODS

We retrospectively recruited 366 patients with cystoscopy biopsy for pathology and morphology evaluation between October 2010 and January 2021. A binary logistic regression model was used to assess the risk factors for postoperative high-grade BCa. Diagnostic performance was analyzed by plotting receiver operating characteristic curve and calculating area under the curve (AUC), sensitivity, specificity. From January 2021 to July 2021, we collected 105 BCa prospectively to validate the model's accuracy.

RESULTS

A total of 366 individuals who underwent transurethral resection of bladder tumor (TURBT) or radical cystectomy following cystoscopy biopsy were included for analysis. 261 (71.3%) had a biopsy pathology grade that was consistent with postoperative pathology grade. We discovered five cystoscopic parameters, including tumor diameter, site, non-pedicled, high-grade biopsy pathology, morphology, were associated with high-grade BCa. The established multi-parameter logistic regression model ("JSPH" model) revealed AUC was 0.917 (P < 0.001). Sensitivity and specificity were 86.2% and 84.0%, respectively. And the consistency of pre- and post-operative high-grade pathology was improved from biopsy-based 70.5% to JSPH model-based 85.2%. In a 105-patients prospective validation cohort, the consistency of pre- and post-operative high-grade pathology was increased from 63.1 to 84.2% after incorporation into JSPH model for prediction.

CONCLUSION

The cystoscopic parameters based "JSPH model" is accurate at predicting postoperative pathological high-grade tumors prior to operations.

VI-RADS score system - A primer for urologists

Bladder cancer (BCa) is one of the most common cancers worldwide and is also considered to be one of the most relapsing and aggressive neoplasms. About 30% of patients will present with muscle invasive disease, which is associated with a higher risk for metastatic disease. The aim of this article is to review the state of art imaging in Radiology, while providing a complete guide to urologists, with case examples, for the rationale of the development of the Vesical Imaging Reporting and Data System (VI-RADS), a scoring system emphasizing a standardized approach to multiparametric Magnetic Resonance Imaging (mpMRI) acquisition, interpretation, and reporting for BCa. Also, we examine relevant external validation studies and the consolidated literature of mpMRI for bladder cancer. In addition, this article discusses some of the potential clinical implications of this scoring system for disease management and follow-up.

Feasibility Study on Predicting Recurrence Risk of Bladder Cancer Based on Radiomics Features of Multiphase CT Images

Background

Predicting the recurrence risk of bladder cancer is crucial for the individualized clinical treatment of patients with bladder cancer.

Objective

To explore the radiomics based on multiphase CT images combined with clinical risk factors, and to further construct a radiomics-clinical model to predict the recurrence risk of bladder cancer within 2 years after surgery.

Methods

Patients with bladder cancer who underwent surgical treatment at the First Affiliated Hospital of Soochow University from January 2016 to December 2019 were retrospectively included and followed up to record the disease recurrence. A total of 183 patients were included in the study, and they were randomly divided into training group and validation group in a ratio of 7: 3. The three basic models which are plain scan, corticomedullary phase, and nephrographic phase as well as two combination models, namely, corticomedullary phase + nephrographic phase and plain scan + corticomedullary phase + nephrographic phase, were built with the logistic regression algorithm, and we selected the model with higher performance and calculated the Rad-score (radiomics score) of each patient. The clinical risk factors and Rad-score were screened by Cox univariate and multivariate proportional hazard models in turn to obtain the independent risk factors, then the radiomics-clinical model was constructed, and their performance was evaluated.

Results

Of the 183 patients included, 128 patients constituted the training group and 55 patients constituted the validation group. In terms of the radiomics-clinical model constructed by three independent risk factors—number of tumors, tumor grade, and Rad-score—the AUCs of the training group and validation group were 0.813 (95% CI 0.740–0.886) and 0.838 (95% CI 0.733–0.943), respectively. In the validation group, the diagnostic accuracy, sensitivity, and specificity were 0.727, 0.739, and 0.719, respectively.

Conclusion

Combining with radiomics based on multiphase CT images and clinical risk factors, the radiomics-clinical model constructed to predict the recurrence risk of bladder cancer within 2 years after surgery had a good performance.

Multiparametric MRI Evaluation of VI-RADS for Bladder Tumors Located at the Ureteral Orifice

Background The Vesical Imaging Reporting and Data System (VI-RADS) based on multiparametric MRI scans standardizes preoperative bladder cancer staging. However, limitations have been reported for VI-RADS, particularly for ureteral orifice tumors. Purpose To investigate the diagnostic performance and interobserver agreement of VI-RADS in evaluating muscle invasion for bladder tumors located at the ureteral orifice. Materials and Methods In this retrospective study, patients with histopathologically confirmed bladder cancer occurring at the ureteral orifice from January 2012 to November 2021 were analyzed. Two blinded radiologists independently scored multiparametric MRI scans according to VI-RADS. Interobserver agreement of the VI-RADS scores was evaluated with weighted κ analysis. Receiver operating characteristic curve analysis was used to evaluate the diagnostic performance of the VI-RADS scores in the prediction of muscle invasion. Results A total of 78 patients (mean age, 67 years ± 7 [SD]; age range, 46-90 years; 67 men) were included in the final analysis: 25 with non-muscle-invasive bladder cancer and 53 with muscle-invasive bladder cancer (MIBCa). At consensus reading, one (1%) case was scored as VI-RADS 1, 27 cases (35%) were scored as VI-RADS 2, six (8%) were scored as VI-RADS 3, 10 (13%) were scored as VI-RADS 4, and 34 (44%) were scored as VI-RADS 5. On comparison of the VI-RADS score with histopathologic findings, it was confirmed that the presence of muscle invasion was 0% (zero of one) for VI-RADS 1, 15% (four of 27) for VI-RADS 2, 83% (five of six) for VI-RADS 3, 100% (10 of 10) for VI-RADS 4, and 100% (34 of 34) for VI-RADS 5. The area under the receiver operating characteristic curve of VI-RADS in the detection of MIBCa was 0.96 (95% CI: 0.92, 1.00). Conclusion The Vesical Imaging Reporting and Data System could be used to accurately predict muscle invasion for bladder tumors occurring at the ureteral orifice. © RSNA, 2022 Online supplemental material is available for this article.

What is the impact of dynamic contrast-enhancement sequence in the Vesical Imaging, Reporting and Data System (VI-RADS)? A subgroup analysis

Background

A scoring system focusing on the risk of muscle layer invasion by Bladder cancer (BCa) has been released, Vesical Imaging - Radiological and Data System (VI-RADS), with a growing interest in evaluating its diagnostic accuracy.

Our goal was to assess the accuracy and reproducibility of the VI-RADS score for assessment of the vesical muscular layer with (multiparametric-mp) and without (biparametric-bp) a dynamic-contrast enhancement (DCE) sequence.

Methods

Retrospective study conducted from July 2018 to July 2020. All patients had suspicions of BCa and underwent Magnetic Resonance Imaging (MRI) before any intervention. MRI was interpreted by two radiologists with different levels of experience, and a VI-RADS score assigned in two different sessions (3 months apart) without and with DCE. After exclusions, 44 patients with 50 lesions were enrolled. The standard of reference was transurethral resection in 18 patients (40.9%) and cystectomy in 26 patients (59.1%).

Results

Twenty-five lesions (50%) were muscle-invasive. There was no significant difference between the two groups for gender and presence of a stalk, but mean age of NMIBCa group was significantly higher (p = 0.01). The sizes of lesions were significantly different between groups for both readers at 2.42+/− 1.58 vs. 5.70+/− 2.67 cm for reader 1 (p < 0.0001) and 2.37+/− 1.50 vs. 5.44 +/− 2.90 cm for reader 2 (p = 0.001). The area under the curve (AUC) for muscle invasion with mpVI-RADS, considering all lesions, was 0.885 +/− 0.04 (95% CI-0.79-0.98) for reader 1 and 0.924 +/− 0.04 (0.84–0.99) for reader 2, and for bpVI-RADS was 0.879+/− 0.05 and 0.916 +/− 0.04 (0.85–0.99), respectively, both differences not statistically significant (p = 0.24 and 0.07, respectively). When considering only small lesions (< 3.0 cm), the accuracy for mpVI-RADS was 0.795 +/− 0.11 (0.57–1.0) for reader1, and 0.80 +/− 0.11(0.57–1.0) for reader 2, a non-significant difference (p = 0.56) and for bpVI-RADS was 0.747 +/− 0.12 (0.50–0.99) for reader 1 and 0.80 +/− 0.11(0.57–1.0) for reader 2, a significant difference (p = 0.04). The intraclass correlation coefficient for the final score was 0.81 (0.60–1.0) for mpVI-RADS and 0.85 (0.63–1.0) for bpVI-RADS.

Conclusion

The VI-RADS system was accurate in demonstrating muscle-invasive BCa, for both experienced and less experienced reader, regardless of the use of a DCE sequence. However, when only small lesions were assessed the difference between the two readers was significant only for the biparametric analysis. The reproducibility was similar between multiparametric and biparametric approach.

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

PURPOSE

Vesical Imaging-Reporting and Data System (VI-RADS) was proposed and considered as a standardized reporting criterion for bladder magnetic resonance imaging (MRI). VI-RADS could suggest the likelihood of muscle invasion based on the multiparametric MRI (mp-MRI) findings which contain five-point scores. The current study is designed to comprehensively and systematically evaluate the diagnostic performance of VI-RADS (score 3 and 4) for predicting muscle invasion.

METHODS

The Cochrane Library, Embase, and PubMed were searched comprehensively from inception to October 2021.

RESULTS

Finally, 19 studies incorporating 2900 patients were enrolled. The pooled sensitivity and specificity of VI-RADS 3 for predicting muscle invasion were 0.92 (95%CI 0.89-0.94) and 0.82 (95%CI 0.76-0.87), respectively. The pooled sensitivity and specificity of VI-RADS 4 were 0.78 (95%CI 0.72-0.83) and 0.96 (95%CI 0.93-0.97), respectively. And the area under the curve (AUCs) of VI-RADS 3 and 4 were all 0.94 (95%CI 0.92-0.96). No significant publication biases were not observed for VI-RADS 3 (P = 0.74) and 4 (P = 0.57).

CONCLUSION

The VI-RADS reveals a good diagnostic performance for predicting muscle invasive in bladder cancer, which also has good clinical utilities and applicability. And VI-RADS 3 and 4 as cutoff values provide similar overall diagnostic and could be selectively applied individually. Prospective studies with a large scale are further required to validate the accuracy of the VI-RADS score.

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

Purpose

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

Methods

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

Results

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

Conclusion

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

Supplementary Information

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

Accuracy of Inchworm Sign on Diffusion-Weighted MRI in Differentiating Muscle-Invasive Bladder Cancer

BACKGROUND

Inchworm sign is a finding on diffusion-weighted magnetic resonance imaging (DWI-MRI) and is used to better stratify T-staging in muscle invasive (MIBC) and non-muscle-invasive bladder cancer (NMIBC). An uninterrupted low submucosal signal on DWI, defined as inchworm sign (IS), indicates NMIBC.

OBJECTIVE

We aimed to define the diagnostic accuracy of IS in primary bladder cancer, as well as find agreement between the urologists and the radiologist.

METHODS

Between December 2018 and December 2020, we retrospectively analyzed 95 primary bladder cancer patients who had undergone multiparametric-MRI before transurethral resection. Patients with former bladder cancer history, tumors smaller than 10 mm, and MRI without proper protocol, as well as patients who did not attend follow-up, were excluded. In total, 71 patients' images were evaluated by a genitourinary specialist radiologist and two urologists. Sensitivity, specificity, positive and negative predictive values of IS and VI-RADS in differentiating MIBC and NMIBC, and interreader agreement between the radiologist and urologists were analyzed.

RESULTS

During follow-up, 38 patients (53.5%) were IS-positive, while 33 patients (46.5%) were negative. Among the 33 patients with negative IS, 14 patients (42.4%) had MIBC. Meanwhile, two out of the 38 IS-positive patients (5.3%) had MIBC (p = 0.00). Sensitivity, specificity, and positive and negative predictive values of IS in predicting MIBC were 87.5%, 63.6%, 41.2%and 94.6%, respectively. The interobserver agreement between the urologists and radiologist was almost perfect ( K  = 0.802 and K  = 0.745).

CONCLUSION

The absence of IS on DWI is useful in differentiating MIBC from NMIBC. It is a simple finding that can be interpreted by urologists.

Accuracy and Challenges in the Vesical Imaging-Reporting and Data System for Staging Bladder Cancer

BACKGROUND

The Vesical Imaging-Reporting and Data System (VI-RADS) scoring system has been widely used to stage bladder cancer (BCa) since 2018.

PURPOSE

To describe the characteristics of cases with discordant T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) scores in patients with BCa and further verify the accuracy of the VI-RADS scoring system and the necessity of dynamic contrast-enhanced (DCE) sequence.

STUDY TYPE

Retrospective.

SUBJECTS

A total of 106 patients (include 16.5% female) with bladder cancer.

SEQUENCE

T2WI (fast spin echo), DWI (echo planer imaging), and DCE (gradient echo).

ASSESSMENT

Some cases are difficult to score according to the system, mainly when the T2WI (category 4) and DWI (category 2) sequence scores are discordant, termed the discordant group below. The complementary group will be termed concordant group. Each MRI sequence was reviewed respectively according to the 5-point VI-RADS scoring system by three observers. The diagnostic ability of sequences for evaluating muscle invasion by BCa was calculated using histopathology as the reference standards.

STATISTICAL TESTS

Receiver operating characteristic (ROC) curve, DeLong test, intraclass correlation coefficient. A P value of 0.05 or less was considered statistically significant.

RESULTS

Fourteen cases (13.2%) had discordant VI-RADS scoring system. In the discordant group, the area under the ROC curve (AUC) of DCE was 0.875, while the T2WI and DWI showed limited diagnostic performance (AUCs = 0.50). In the concordant group, there was no significant difference in diagnostic efficacy between the overall VI-RADS (AUC: 0.950) and the combination of T2WI and DWI (AUC: 0.946) (P = 0.56). Among all patients, the AUC of overall VIRADS was 0.939 with a 3 or greater cutoff value.

DATA CONCLUSION

The DCE was crucial in the discordant group for evaluating muscle-invasiveness, while DCE may not be necessary for the concordant group. The VI-RADS scoring system performed with overall good diagnostic performance in evaluating muscle-invasiveness in BCa patients.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 3.

Clinical validity of non-contrast-enhanced VI-RADS: prospective study using 3-T MRI with high-gradient magnetic field

OBJECTIVES

To develop a modified Vesical Imaging Reporting and Data System (VI-RADS) without dynamic contrast-enhanced imaging (DCEI), termed "non-contrast-enhanced VI-RADS (NCE-VI-RADS)", and to assess the additive impact of denoising deep learning reconstruction (dDLR) on NCE-VI-RADS.

METHODS

From January 2019 through December 2020, 163 participants who underwent high-gradient 3-T MRI of the bladder were prospectively enrolled. In total, 108 participants with pathologically confirmed bladder cancer by transurethral resection were analyzed. Tumors were evaluated based on VI-RADS (scores 1-5) by two readers independently: an experienced radiologist (reader 1) and a senior radiology resident (reader 2). Conventional VI-RADS assessment included all three imaging types (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI], and dynamic contrast-enhanced imaging [DCEI]). Also evaluated were NCE-VI-RADS comprising only non-contrast-enhanced imaging types (T2WI and DWI), and "NCE-VI-RADS with dDLR" comprising T2WI processed with dDLR and DWI. All systems were assessed using receiver-operating characteristic curve analysis and simple and/or weighted κ statistics.

RESULTS

Muscle invasion was identified in 23/108 participants (21%). Area under the curve (AUC) values for diagnosing muscle invasion were as follows: conventional VI-RADS, 0.94 and 0.91; NCE-VI-RADS, 0.93 and 0.91; and "NCE-VI-RADS with dDLR", 0.96 and 0.93, for readers 1 and 2, respectively. Simple κ statistics indicated substantial agreement for NCE-VI-RADS and almost perfect agreement for conventional VI-RADS and "NCE-VI-RADS with dDLR" between the two readers.

CONCLUSION

NCE-VI-RADS achieved predictive accuracy for muscle invasion comparable to that of conventional VI-RADS. Additional use of dDLR improved the diagnostic accuracy of NCE-VI-RADS.

KEY POINTS

• Non-contrast-enhanced Vesical Imaging Reporting and Data System (NCE-VI-RADS) was developed to avoid risk related to gadolinium-based contrast agent administration. • NCE-VI-RADS had predictive accuracy for muscle invasion comparable to that of conventional VI-RADS. • The additional use of denoising deep learning reconstruction (dDLR) might further improve the diagnostic accuracy of NCE-VI-RADS.

Role of Vesical Imaging-Reporting and Data System in predicting muscle-invasive bladder cancer: A diagnostic meta-analysis

The objective of this study is to systematically evaluate the diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer. Embase, PubMed and Web of Science were systematically searched from 1 September 2018 to 30 July 2021 to include proper studies. We included studies that included data on Vesical Imaging-Reporting and Data System and their associated pathological findings, and we assessed their quality using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. The pooled sensitivity and specificity were calculated and plotted using hierarchical summary receiver operating characterisijutic modeling. Meta-regression analysis was carried out to detect heterogeneity. A total of 20 studies with 2725 patients were included. When the cut-off point was 3, the pooled sensitivity and specificity were 0.92 (0.89-0.94) and 0.85 (0.78-0.90), respectively, and 0.82 (0.75-0.88) and 0.95 (0.91-0.97), respectively, when the cut-off point was 4. The area under the curve was 0.95 and 0.95, respectively. Heterogeneity was substantially considerable in sensitivity and specificity. All subgroup variables, including patient number, study design, magnetic resonance imaging field strength, number of radiologists, surgery pattern, diffusion-weighted imaging, and dynamic contrast-enhanced magnetic resonance imaging, contributed to sensitivity heterogeneity when the cut-off point was 3 and specificity heterogeneity when the cut-off point was 4. Multiple image acquisition plane of diffusion-weighted imaging achieved a higher sensitivity than single image acquisition plane of diffusion-weighted imaging in both the Vesical Imaging-Reporting and Data System 3 and 4 groups, and higher specificity in the Vesical Imaging-Reporting and Data System 4 group. Another significant source of heterogeneity was the cut-off point. The diagnostic performance of the Vesical Imaging-Reporting and Data System for predicting muscle-invasive bladder cancer was excellent in both cut-off points of the Vesical Imaging-Reporting and Data System 3 and 4. Multiple image acquisition planes of diffusion-weighted imaging should be given more attention in the Vesical Imaging-Reporting and Data System.

Diagnostic accuracy of vesical imaging-reporting and data system (VI-RADS) in suspected muscle invasive bladder cancer: A systematic review and diagnostic meta-analysis

OBJECTIVE

To investigate the accuracy of Vesical Imaging-Reporting and Data System (VI-RADS) in detection of muscle-invasive bladder cancer (MIBC) we performed a systematic review and meta-analysis of the available literature.

MATERIALS AND METHODS

Scopus, Web of Science, PubMed, and EMBASE were searched up to 8 March 2021 for the studies evaluating the diagnostic performance of VI-RADS for the detection of MIBC. Inclusion criteria were patients with bladder cancer; index test of VI-RADS based on multiparametric MRI; reference test of histopathological findings from TURBT, re-TURBT, or cystectomy and study design of cohort. Case reports, review articles, and editorials were eliminated, as well as studies with insufficient knowledge to acquire TP, FP, FN, and TN values of VI-RADS. The MIDAS module of STATA was for statistical analysis. The heterogeneity was explored using subgroup analysis and meta-regression analysis.

RESULTS

Overall, 22 eligible studies, consisting of 2,576 participants and 5,414 MRI reports, were included in this meta-analysis. The area under curve (AUC) of VI-RADS at cut-point values of 3 and 4 were 0.93 (95%CI: 0.91, 0.95), 0.93 (95%CI: 0.90, 0.95), respectively. Based on Youden's J statistic, the optimal VI-RADS cutoff value for predicting MIBC was determined as 3 which granted a pooled sensitivity of 89% (95%CI: 87%, 91%; I²=48%) and a specificity of 84% (95%CI: 80%, 87%; I²=90%). Based on meta-regression, the sources of inter-study heterogeneity for VI-RADS ≥ 3 were the sample size > 70, study design, single-center vs multi-center, patient population characteristics (i.e., gender, age), reference standard, histology, magnetic strength, T2WI slice thickness, and the number of radiologists reporting the MRI results (P value ≤ 0.01).

CONCLUSION

The VI-RADS demonstrates consistently high diagnostic accuracy to predict MIBC. This scoring system could be applied in standard staging MRI reports of bladder cancer and can be incorporated into future MIBC work up guidelines.

The efficacy and reliability of VI-RADS in determining candidates for repeated transurethral resection in patients with high-risk non-muscle invasive bladder cancer

OBJECTIVE

Our study aims to evaluate the efficiency and reliability of Vesical Imaging Reporting Data System (VI-RADS) in prospectively identifying the patients to undergo RE-TURBT in the management of patients with high-risk non-muscle invasive Bladder Cancer(HR-NMIBC).The secondary objective was to evaluate the performance of the VI-RADS scoring system in differentiating between muscle-invasive bladder cancer (MIBC) and non-muscle invasive bladder cancer(NMIBC) prospectively.

METHODS

The study included 330 patients who underwent transurethral resection of bladder tumour(TURBT) for Bladder Cancer (BC) in our clinic. All patients underwent multiparametric-magnetic resonance imaging (Mp-MRI) before the operation and VI-RADS scoring was administered. The cut-off value of VI-RADS was accepted as three and above. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the differentiation between NMIBC and MIBC distinction in all patients. Receiver operating characteristic (ROC) analysis was performed to evaluate the performance of the VI-RADS scoring system. In the second phase of the study, patients with MIBC and low-risk NMIBC (LR-NMBIC) were excluded and 158 patients with HR-NMIBC were included, and their sensitivity, specificity, PPV and NPV values were measured. ROC analysis was performed.

RESULTS

In all patients, sensitivity, specificity, PPV and NPV values of the VI-RADS scoring in the differentiation of MIBC and NMIBC were 91.3, 91.8, 81.7 and 96.3 respectively. The AUC value was 0.934 (95%CI: 0.903-0.964). Sensitivity, specificity, PPV and NPV values were found to be 87, 91.8, 74.1, 95.2 in the evaluation specifically made for patients with HR-NMIBC. The AUC value was 0.900 (95% CI:0.843-0.957). Inter-reader agreement was excellent (Ƙ = 0.90, 95% CI:0.71-0.95).

CONCLUSIONS

The VI-RADS scoring system is an effective and reliable method in determining the patients who will undergo RE-TURBT and in differentiating MIBC and NMIBC.

Combining volumetric apparent diffusion coefficient histogram analysis with vesical imaging reporting and data system to predict the muscle invasion of bladder cancer

OBJECTIVE

The objective of this study was to explore whether volumetric apparent diffusion coefficient (ADC) histogram analysis can provide additional value to Vesical Imaging Reporting and Data System (VI-RADS) in differentiating muscle-invasive bladder cancer (MIBC) from non-muscle-invasive bladder cancer (NMIBC).

MATERIALS AND METHODS

80 patients were retrospectively reviewed with pathologically proven NMIBC (n = 53) or MIBC (n = 27). All patients underwent MRI including diffusion-weighted imaging (DWI) (b = 0, 800 s/mm²), and the VI-RADS score was evaluated based on DWI. Volumetric ADC histogram parameters were calculated from the volumetric of interest (VOI) on DWI, including the min ADC, mean ADC, median ADC, max ADC, 10th, 25th, 75th, 90th percentiles ADC, skewness, kurtosis, and entropy. The Mann-Whitney U-test was used to compare histogram parameters between NMIBC and MIBC. Receiver operating characteristic analysis was used to evaluate the diagnostic value of each significant parameter.

RESULTS

Among all parameters, the VI-RADS yield the highest Area Under the Curve (AUC, 0.88; sensitivity, 88.89%; specificity, 83.61%). MIBC had significantly lower min ADC, mean ADC, median ADC, 10th, 25th, 75th, and 90th percentiles ADC than NMIBC (p = 0.002, p < 0.001, p < 0.001, p = 0.003, p = 0.004, p < 0.001, p < 0.001). Skewness and kurtosis of MIBC were significantly higher than those of NMIBC (p < 0.001, p < 0.001). The combination of VI-RADS and skewness showed significantly higher AUC (AUC 0.923; 95% CI 0.847-0.969) than only with VI-RADS (AUC 0.880; 95% CI 0.793-0.940).

CONCLUSION

Volumetric ADC histogram analysis and VI-RADS are both useful methods in differentiating MIBC from NMIBC, and the volumetric ADC histogram analysis can provide additional value to VI-RADS.

Accuracy of the Vesical Imaging-Reporting and Data System (VIRADS) for pre-treatment staging of bladder cancer in an Australian cohort

INTRODUCTION

To evaluate the performance of the Vesical Imaging-Reporting and Data System (VIRADS) in differentiating muscle-invasive and non-muscle-invasive bladder cancer and whether this reporting system improves inter-reader agreement.

METHODS

Sixty-four cases of multiparametric 3 tesla bladder MRI from January 2014 to May 2020 were reviewed retrospectively. T2-weighted, diffusion and post-contrast images were reviewed. All magnetic resonance images were reported by a radiologist with 15 years' experience (Reader 1) and a final year radiology trainee with a special interest in urogenital imaging with 3 years of experience (Reader 2). Both readers were blinded to clinical history and histopathology results when scoring each lesion.

RESULTS

The sensitivity and specificity for differentiating MIBC and NMIBC were 91% and 68%, respectively, for Reader 1 and 91% and 63%, respectively, for Reader 2. The inter-reader agreement for assigning VIRADS scores was 0.79. The area under the receiver operator curve for Reader 1 and 2 were not significantly different (Reader 1 = 0.79, Reader 2 = 0.77, P = 0.83).

CONCLUSIONS

Staging of bladder cancer prior to treatment can be accurately and reliably diagnosed using VIRADS, a novel, standardised reporting system for bladder MRI.

Diagnostic performance of the vesical imaging-reporting and data system for detecting muscle-invasive bladder cancer in real clinical settings: Comparison with diagnostic cystoscopy

PURPOSE

We herein compared the diagnostic performance of Vesical Imaging-Reporting and Data System (VI-RADS) scoring with diagnostic cystoscopy and evaluated diagnostic accuracies based on tumor locations.

MATERIALS AND METHODS

Among 112 bladder cancer patients who underwent multiparametric magnetic resonance imaging and diagnostic cystoscopy preoperatively to detect bladder cancer, 61 were analyzed. VI-RADS was categorized into 5 stages by 2 radiologists (R1 and R2). Cut-off values ≥3 indicated muscle-invasive bladder cancer (MIBC). Muscle invasion (MI) was visually evaluated using diagnostic cystoscopy by 2 urologists (U1 and U2). The sensitivity and specificity of VI-RADS scores and diagnostic cystoscopy for diagnosing MI were compared.

RESULTS

16 patients (26.2%) were pathologically diagnosed with MIBC. Regarding MI diagnostic accuracy, the sensitivity/specificity of VI-RADS scores were 93.8/88.9% by R1 and 87.5/86.7% by R2, while those of diagnostic cystoscopy were 56.3/68.9% by U1 and 68.8/84.4% by U2. Therefore, the diagnostic accuracy of VI-RADS was significantly higher than that of cystoscopy, particularly for tumors located on the bladder neck, trigone, dome, and posterior and anterior walls. Over- and under-diagnosis rates were higher with VI-RADS than with diagnostic cystoscopy (25.9% vs. 14.8%) for tumors located on the lateral wall or ureteral orifice.

CONCLUSION

VI-RADS had superior diagnostic performance for detecting MI, especially in tumors located at the bladder neck/trigone/dome/posterior and anterior wall. However, VI-RADS was inferior to cystoscopy in terms of MI detection for tumors located on the lateral wall or ureteral orifice. Therefore, a combination of diagnostic tools is recommended for the accurate staging of these tumors.

Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer

Urinary bladder cancer (BCa) is a highly prevalent disease among aged males. Precise diagnosis of tumor phenotypes and recurrence risk is of vital importance in the clinical management of BCa. Although imaging modalities such as CT and multiparametric MRI have played an essential role in the noninvasive diagnosis and prognosis of BCa, radiomics has also shown great potential in the precise diagnosis of BCa and preoperative prediction of the recurrence risk. Radiomics-empowered image interpretation can amplify the differences in tumor heterogeneity between different phenotypes, i.e., high-grade vs. low-grade, early-stage vs. advanced-stage, and nonmuscle-invasive vs. muscle-invasive. With a multimodal radiomics strategy, the recurrence risk of BCa can be preoperatively predicted, providing critical information for the clinical decision making. We thus reviewed the rapid progress in the field of medical imaging empowered by the radiomics for decoding the phenotype and recurrence risk of BCa during the past 20 years, summarizing the entire pipeline of the radiomics strategy for the definition of BCa phenotype and recurrence risk including region of interest definition, radiomics feature extraction, tumor phenotype prediction and recurrence risk stratification. We particularly focus on current pitfalls, challenges and opportunities to promote massive clinical applications of radiomics pipeline in the near future.

ACR Appropriateness Criteria® Post-Treatment Surveillance of Bladder Cancer: 2021 Update

Urothelial cancer is the second most common cancer, and cause of cancer death, related to the genitourinary tract. The goals of surveillance imaging after the treatment of urothelial cancer of the urinary bladder are to detect new or previously undetected urothelial tumors, to identify metastatic disease, and to evaluate for complications of therapy. For surveillance, patients can be stratified into one of three groups: 1) nonmuscle invasive bladder cancer with no symptoms or additional risk factors; 2) nonmuscle invasive bladder cancer with symptoms or additional risk factors; and 3) muscle invasive bladder cancer. This document is a review of the current literature for urothelial cancer and resulting recommendations for surveillance imaging. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Preliminary Exploration of the Application of Vesical Imaging-Reporting and Data System (VI-RADS) in Post-treatment Patients With Bladder Cancer: A Prospective Single-Center Study

BACKGROUND

Vesical Imaging-Reporting and Data System (VI-RADS) has been shown to be effective in diagnosing muscle invasion of bladder cancer (BC) in primary patients.

PURPOSE

To evaluate the diagnostic efficacy of VI-RADS in a BC target population which included post-treatment patients, and to determine the repeatability.

STUDY TYPE

Prospective.

POPULATION

Seventy-three patients (42 with primary BC, 31 with post-treatment BC).

FIELD STRENGTH/SEQUENCE

3.0 T MRI with propeller fast spin-echo T₂ WI, echo planer imaging diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI).

ASSESSMENT

VI-RADS scores were independently assessed by five radiologists with different levels of experience. The diagnostic efficiency in each group (primary and post-treatment) and of each radiologist was assessed.

STATISTICAL TESTS

Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), and area under the curve (AUC) in receiver operating characteristic curve analysis were calculated to evaluate VI-RADS diagnostic performance. Interobserver agreement was assessed using weighted Kappa statistics. A P value <0.05 was considered statistically significant.

RESULTS

At the corresponding cut-off, AUC values of three groups range from 0.936 to 0.947 and AUC values of five observers range from 0.901 to 0.963. There was no significant difference between the AUCs in the primary and post-treatment groups (P = 0.870). The cut-off of the whole group and the post-treatment group was ≥4, and the cut-off of the primary group was ≥3. The Kappa values of interobserver agreements range from 0.709 to 0.923.

CONCLUSIONS

After expanding the target population to include post-treatment patients, VI-RADS still has good diagnostic efficacy and repeatability. VI-RADS could potentially be a preoperative staging tool for post-treatment patients.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2.

Vesical Imaging Reporting and Data System (VI-RADS): Are the individual MRI sequences equivalent in diagnostic performance of high grade NMIBC and MIBC?

PURPOSE

To investigate the diagnostic performance of the overall Vesical Imaging Reporting and Data System (VI-RADS) score and its individual magnetic resonance imaging (MRI) parameters in assessing grade and muscle invasiveness of bladder cancer (BC).

METHODS

This IRB-approved retrospective, single-center, cross-sectional study included patients with BC wo underwent 3 Tesla preoperative multiparametric (mp)-MRI including T2-weighted (T2w), diffusion weighted imaging (DWI) and dynamic contrast enhanced (DCE) sequences. An independent evaluation according to VI-RADS was performed by two radiologists in separate sessions, blinded to histological findings.

RESULTS

The mean age of 59 included patients was 68.2 (±13.6 standard deviation) years. Among bladder cancer patients, 26 (51%) were identified as high grade and 14 (27.5%) as muscle invasive urothelial carcinomas in histological sections. The area under the curve (AUC) for the overall VI-RADS score to predict muscle invasion was 0.986 (R1) and 0.992 (R2). The AUC to diagnose high grade bladder cancer was 0.908 (R1) and 0.905 (R2). There was no significance difference between the AUC of single parameters (T2w, DWI and DCE) compared to the total VI-RADS score (P > 0.05, respectively). Upon multivariate logistic regression, only the T2w VI-RADS score contributed independently to the diagnosis of high grade and muscle invasive bladder cancer (P = 0.001 (R1) and P = 0.0022 (R2) for high grade cancer; P = 0.0007 (R1) and P = 0.0019 (R2) for muscle invasiveness).

CONCLUSION

VI-RADS provides high diagnostic accuracy to diagnose high grade and muscle invasive BC. Our results suggest, that mp-MRI parameters provide overlapping information and for sake of clinical simplicity, a biparametric, contrast free image acquisition may be approached without sacrificing diagnostic accuracy.