Diagnostic performance of diffusion-weighted magnetic resonance imaging in bladder cancer: potential utility of apparent diffusion coefficient values as a biomarker to predict clinical aggressiveness. Eur Radiol. 2011;21:2178-2186. [PMID: 21688007 DOI: 10.1007/s00330-011-2174-7]

ACR Appropriateness Criteria® Pretreatment Staging of Urothelial Cancer: 2024 Update

Urothelial cancer is the second most common cancer, and cause of cancer death, related to the genitourinary tract. The goals of imaging for pretreatment staging of urothelial cancer are to evaluate for both local and distant spread of the cancer and assessing for synchronous sites of urothelial cancer in the upper tracts and bladder. For pretreatment staging of urothelial carcinoma, patients can be stratified into one of three groups: 1) nonmuscle invasive bladder cancer; 2) muscle invasive bladder cancer; and 3) upper urinary tract urothelial carcinoma. This document is a review of the current literature for urothelial cancer and resulting recommendations for pretreatment staging 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 process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

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.

Alterations of apparent diffusion coefficient from ultra high b-values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy

OBJECTIVE

Subcortical nuclei such as the thalamus and striatum have been shown to be related to seizure modulation and termination, especially in drug-resistant epilepsy. Enhance diffusion-weighted imaging (eDWI) technique and tri-component model have been used in previous studies to calculate apparent diffusion coefficient from ultra high b-values (ADCuh). This study aimed to explore the alterations of ADCuh in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy.

METHODS

Twenty-nine patients with MRI-negative drug-resistant epilepsy and 18 healthy controls underwent eDWI scan with 15 b-values (0-5000 s/mm2). The eDWI parameters including standard ADC (ADCst), pure water diffusion (D), and ADCuh were calculated from the 15 b-values. Regions-of-interest (ROIs) analyses were conducted in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus. ADCst, D, and ADCuh values were compared between the MRI-negative drug-resistant epilepsy patients and controls using multivariate generalized linear models. Inter-rater reliability was assessed using the intra-class correlation coefficient (ICC) and Bland-Altman (BA) analysis. False discovery rate (FDR) method was applied for multiple comparisons correction.

RESULTS

ADCuh values in the bilateral thalamus, caudate nucleus, putamen, and globus pallidus in MRI-negative drug-resistant epilepsy were significantly higher than those in the healthy control subjects (all p < 0.05, FDR corrected).

SIGNIFICANCE

The alterations of the ADCuh values in the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy might reflect abnormal membrane water permeability in MRI-negative drug-resistant epilepsy. ADCuh might be a sensitive measurement for evaluating subcortical nuclei-related brain damage in epilepsy patients.

PLAIN LANGUAGE SUMMARY

This study aimed to explore the alterations of apparent diffusion coefficient calculated from ultra high b-values (ADCuh) in the subcortical nuclei such as the bilateral thalamus and striatum in MRI-negative drug-resistant epilepsy. The bilateral thalamus and striatum showed higher ADCuh in epilepsy patients than healthy controls. These findings may add new evidences of subcortical nuclei abnormalities related to water and ion hemostasis in epilepsy patients, which might help to elucidate the underlying epileptic neuropathophysiological mechanisms and facilitate the exploration of therapeutic targets.

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.

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.

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.

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.

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.

Radiomics nomogram for predicting disease-free survival after partial resection or radical cystectomy in patients with bladder cancer

OBJECTIVES

To create a MRI-derived radiomics nomogram that combined clinicopathological factors and radiomics signature (Rad-score) for predicting disease-free survival (DFS) in patients with bladder cancer (BCa) following partial resection (PR) or radical cystectomy (RC), including lymphadenectomy (LAE).

METHODS

Finally, 80 patients with BCa after PR or RC with LAE were enrolled. Patients were randomly split into training (n = 56) and internal validation (n = 24) cohorts. Radiomic features were extracted from T2-weighted, dynamic contrast-enhanced, diffusion-weighted imaging, and apparent diffusion coefficient sequence. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was applied to choose the valuable features and construct the Rad-score. The DFS prediction model was built using the Cox proportional hazards model. The relationship between the Rad-score and DFS was assessed using Kaplan-Meier analysis. A radiomics nomogram that combined the Rad-score and clinicopathological factors was created for individualized DFS estimation.

RESULTS

In both the training and validation cohorts, the Rad-score was positively correlated with DFS (P < .001). In the validation cohort, the radiomics nomogram combining the Rad-score, tumour pathologic stage (pT stage), and lymphovascular invasion (LVI) achieved better performance in DFS prediction (C-index, 0.807; 95% CI, 0.713-0.901) than either the clinicopathological (C-index, 0.654; 95% CI, 0.467-0.841) or Rad-score-only model (C-index, 0.770; 95% CI, 0.702-0.837).

CONCLUSION

The Rad-score was an independent predictor of DFS for patients with BCa after PR or RC with LAE, and the radiomics nomogram that combined the Rad-score, pT stage, and LVI achieved better performance in individual DFS prediction.

ADVANCES IN KNOWLEDGE

This study provided a non-invasive and simple method for personalized and accurate prediction of DFS in BCa patients after PR or RC.

Significance of Normalized Apparent Diffusion Coefficient in the Vesical Imaging-Reporting and Data System for Diagnosing Muscle-Invasive Bladder Cancer

BACKGROUND

Vesical Imaging-Reporting and Data System (VI-RADS) has been developed for assessing bladder cancer from multiparametric (mp) MRI but its performance in diagnosing muscle-invasive bladder cancer (MIBC) is suboptimal.

PURPOSE

To investigate associations between normalized apparent diffusion coefficient (NADC) and clinicopathological characteristics and to determine whether the inclusion of NADC can improve the performance of VI-RADS in diagnosing MIBC.

STUDY TYPE

Retrospective.

POPULATION

Two hundred seventy-five patients with pathologically confirmed bladder cancer (101 MIBC and 174 non-MIBC [NMIBC]) underwent preoperative mpMRI (233 male, 42 female).

FIELD STRENGTH/SEQUENCE

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

ASSESSMENT

NADC was the mean ADC of tumor divided by that of the iliopsoas muscles in trans caput femoris plane. Associations between NADC and clinicopathological characteristics were evaluated. Models were established for differentiating MIBC and NMIBC: VI-RADS model; VN model (VI-RADS and NADC), Images model (significant variables from imaging associated with MIBC), LN model (Images model without NADC), and Full model (all significant variables associated with MIBC).

STATISTICAL TESTS

Variables for model development were based on logistic regression. Models were evaluated by receiver operating characteristic (ROC) curve. Comparison of the area under the curves (AUCs) for the models used DeLong's test. A P value <0.05 was considered statistically significant.

RESULTS

NADC was significantly lower in lesions with diameter ≥ 3 cm, MIBC, histological high grade, lymph node metastasis, and lymphovascular invasion. Compared with VI-RADS model, the AUCs for VN model (VI-RADS score and NADC), Images model (VI-RADS score, NADC and tumor size) and Full model (VI-RADS score, NADC, tumor size and histological grade) were significantly higher. No significant differences were observed between the AUCs for VN model and Images model (P = 0.051).

DATA CONCLUSION

NADC reflects information about the aggressiveness of bladder cancer. Combining VI-RADS with NADC can improve performance in diagnosing MIBC.

EVIDENCE LEVEL

4 TECHNICAL EFFICACY: Stage 2.

MRI-based radiomics analysis of bladder cancer: prediction of pathological grade and histological variant

AIM

To develop magnetic resonance imaging (MRI)-based radiomics models for the prediction of the pathological grade and histological variant of bladder cancer.

MATERIALS AND METHODS

A total of 227 patients who underwent bladder MRI and had histopathologically confirmed grades and variants were included retrospectively from January 2017 to March 2022. They were assigned to a training set (n=131) and a testing set (n=96) based on the MRI system. MRI-based radiomics features were extracted from manually segmented volumes of interest from high-b-value DWI images and ADC maps. The radiomics models were trained with all possible pipelines in the training set. One optimal model was selected using the fivefold cross-validation method and verified by the testing set according to the pathological results. Univariate and multivariate analyses were performed to identify the significant clinical and imaging factors for developing clinical-radiomics models.

RESULTS

The radiomics model for grade prediction had area under the curve (AUC) values of 0.784, 0.786, and 0.733 in the training, cross-validation, and testing sets, respectively. The radiomics model for variant prediction had AUC values of 0.748, 0.757, and 0.789 in the training, cross-validation, and testing sets, respectively. The performance of the clinical-radiomics model was significantly improved compared with the radiomics models alone for the total dataset (AUC for grade: 0.846 versus 0.756; AUC for variant: 0.810 versus 0.757, p<0.05).

CONCLUSION

MRI-based radiomics models could be used to predict the pathological grade and histological variants of bladder cancer with relatively good performance.

Multiple directional DWI combined with T2WI in predicting muscle layer and Ki-67 correlation in bladder cancer in 3.0-T MRI

OBJECTIVE

To investigate the value of 3.0T MRI multi-directional diffusion-weighted imaging (DWI) combined with T2WI morphological features and lesion distribution in preoperative prediction of muscle layer invasion of bladder cancer (BC) and the correlation with postoperative Ki-67.

MATERIALS AND METHODS

This retrospective study enrolled patients with BC between 2019 and 2021. Patients with muscular invasive bladder cancer (MIBC) or non-muscular invasive BC (NMIBC) were also analyzed by preoperative 3.0T MRI aFostic efficacy.

RESULTS

A total of 186 patients were enrolled. About 27 patients with MIBC (35 lesions in total) and 62 with NMIBC (99 lesions in total). We found the tumor with a larger size, a wide base, and a smaller apparent dispersion coefficient (ADC) value and normalized ADC(nADC) value, without a stalk, presenting a greater risk of muscle invasion. ADC value, nADC value, maximum diameter, and stalk were independently associated with muscle invasion. Lesions located at the bladder fundus or involvement of multiple sites were independently associated with muscle invasion compared to the bladder body. In combination with morphological features, the AUCs of ADC and nADC showed accuracies of 0.925 and 0.947-0.951, respectively. TADC and nTADC showed the best diagnostic efficacy in multiple respects. KI-67 LI was negatively correlated with ADC and nADC values.

CONCLUSIONS

This is the first report in which we found Multi-directional DWI combined with T2WI in 3.0T MRI can be used to predict the muscle layer invasion of bladder cancer. ADC values reflect the muscular invasion of bladder cancer and show a moderate negative correlation with Ki-67. It is especially suitable for bladder cancer patients with renal insufficiency or tumor recurrence.

An artificial intelligence model for the pathological diagnosis of invasion depth and histologic grade in bladder cancer

BACKGROUND

Accurate pathological diagnosis of invasion depth and histologic grade is key for clinical management in patients with bladder cancer (BCa), but it is labour-intensive, experience-dependent and subject to interobserver variability. Here, we aimed to develop a pathological artificial intelligence diagnostic model (PAIDM) for BCa diagnosis.

METHODS

A total of 854 whole slide images (WSIs) from 692 patients were included and divided into training and validation sets. The PAIDM was developed using the training set based on the deep learning algorithm ScanNet, and the performance was verified at the patch level in validation set 1 and at the WSI level in validation set 2. An independent validation cohort (validation set 3) was employed to compare the PAIDM and pathologists. Model performance was evaluated using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value and negative predictive value.

RESULTS

The AUCs of the PAIDM were 0.878 (95% CI 0.875-0.881) at the patch level in validation set 1 and 0.870 (95% CI 0.805-0.923) at the WSI level in validation set 2. In comparing the PAIDM and pathologists, the PAIDM achieved an AUC of 0.847 (95% CI 0.779-0.905), which was non-inferior to the average diagnostic level of pathologists. There was high consistency between the model-predicted and manually annotated areas, improving the PAIDM's interpretability.

CONCLUSIONS

We reported an artificial intelligence-based diagnostic model for BCa that performed well in identifying invasion depth and histologic grade. Importantly, the PAIDM performed admirably in patch-level recognition, with a promising application for transurethral resection specimens.

Does Bladder Cancer with Inchworm Sign Indicate Better Prognosis after TURBT?

Background: Inchworm sign is considered to be a characteristic finding in non-muscle invasive bladder cancer (NMIBC). Nevertheless, pathologically diagnosed muscle invasive bladder cancers (MIBCs) are occasionally diagnosed from tissue obtained by transurethral resection of bladder tumor (TURBT) in patients with inchworm sign. Methods: We retrospectively investigated the factors related to muscle invasive status in bladder cancer associated with inchworm sign and the role of inchworm sign in tumor outcomes following TURBT. Results: Of the 109 patients with inchworm sign, 94 (86.2%) and 15 (13.8%) were NMIBC and MIBC, respectively. Non-papillary tumors (hazard ratio (HR): 9.55, 95% confidence interval (CI): 2.07−44.10; p < 0.01) and tumors located in the bladder neck (HR: 7.73, 95% CI: 1.83−32.76; p < 0.01) were significant predictors of MIBC in bladder cancer with inchworm sign. Furthermore, recurrence-free survival (RFS) and progression-free survival were compared between patients with NMIBC with and without inchworm sign; however, no significant differences were found. In patients with NMIBC with inchworm sign, positive urine cytology was a prognostic factor for RFS (HR: 1.90, 95% CI: 1.04−3.48; p = 0.04). Conclusions: In bladder cancer with inchworm sign, 86.2% were NMIBC. Even in the case of inchworm sign, the presence of a non-papillary tumor or a bladder neck tumor before TURBT should be noted because of the possibility of MIBC. In this study, the inchworm sign was not a prognostic factor in patients with NMIBC.

Diffusion-weighted MRI to determine response and long-term clinical outcomes in muscle-invasive bladder cancer following neoadjuvant chemotherapy

Objective

This study aims to determine local treatment response and long-term survival outcomes in patients with localised muscle-invasive bladder cancer (MIBC) patients receiving neoadjuvant chemotherapy (NAC) using diffusion-weighted MRI (DWI) and apparent diffusion coefficient (ADC) analysis.

Methods

Patients with T2-T4aN0-3M0 bladder cancer suitable for NAC were recruited prospectively. DWI was performed prior to NAC and was repeated following NAC completion. Conventional response assessment was performed with cystoscopy and tumour site biopsy. Response was dichotomised into response (

Results

Forty-eight patients (96 DWI) were evaluated. NAC response was associated with significant increase in mean ΔADC and %ΔADC compared to poor response (ΔADCall 0.32×10-3 versus 0.11×10-3 mm2/s; p=0.009, and %ΔADCall 21.70% versus 8.23%; p=0.013). Highest specificity predicting response was seen at 75th percentile ADC (AUC, 0.8; p=0.01). Sensitivity, specificity, positive predictive power, and negative predictive power of %ΔADCb100 75th percentile was 73.7%, 90.0%, 96.6%, and 52.9%, respectively. %ΔADCb100 75th percentile >15.5% was associated with significant improvement in OS (HR, 0.40; 95% CI, 0.19-0.86; p=0.0179), bCSS (HR, 0.26; 95% CI, 0.08-0.82; p=0.0214), PFS (HR, 0.16; 95% CI, 0.05-0.48; p=0.0012), and time to cystectomy (HR, 0.19; 95% CI, 0.07-0.47; p=0.0004).

Conclusions

Quantitative ADC analysis can successfully identify NAC response and improved long-term clinical outcomes. Multi-centre validation to assess reproducibility and repeatability is required before testing within clinical trials to inform MIBC treatment decision making.

Advances in knowledge

We successfully demonstrated that measured change in DWI can successfully identify NAC response and improved long-term survival outcomes.

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Key Words

• MRI
• diffusion weighted magnetic resonance imaging (DWI)
• imaging biomakers
• muscle invasive bladder cancer (MIBC)
• neoadjuavant chemotherapy

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MESH Headings Collapse

Grants

• 28724 Cancer Research UK

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Affiliation(s)

Shaista Hafeez Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Mu Koh Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Kelly Jones Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Amir El Ghzal Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
James D’Arcy Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom
Pardeep Kumar Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Vincent Khoo Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Susan Lalondrelle Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Fiona McDonald Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom
Alan Thompson Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Erica Scurr Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Aslam Sohaib Department of Diagnostic Radiology, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom
Robert Anthony Huddart Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, United Kingdom Urology Unit, The Royal Marsden National Health Service (NHS) Foundation Trust, London, United Kingdom Department of Radiotherapy, The Royal Marsden NHS Foundation Trust, London, United Kingdom

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Assessing Bladder Radiotherapy Response With Quantitative Diffusion-Weighted Magnetic Resonance Imaging Analysis

AIMS

Radiotherapy with radiosensitisation offers opportunity for cure with organ preservation in muscle-invasive bladder cancer (MIBC). Treatment response assessment and follow-up are reliant on regular endoscopic evaluation of the retained bladder. In this study we aim to determine the role of diffusion-weighted magnetic resonance imaging (DWI) and apparent diffusion coefficient (ADC) analysis to assess bladder radiotherapy response.

MATERIALS AND METHODS

Patients with T2-T4aN0-3M0 MIBC suitable for radical radiotherapy were recruited prospectively to an ethics approved protocol. Following transurethral resection of the bladder tumour and prior to any treatment, magnetic resonance imaging including DWI was performed on a 1.5T system using b values of 0, 100, 150, 250, 500, 750 s/mm2. DWI was repeated 3 months after completing radiotherapy. Cystoscopy and tumour site biopsy were undertaken following this. The response was dichotomised into response (

RESULTS

Thirty-four patients were evaluated. Response was associated with a significant increase in ΔADC mean compared with poor response at ΔADCall (0.57 × 10-3 mm2/s versus -0.01 × 10-3 mm2/s; P < 0.0001) and ΔADCb100 (0.58 × 10-3 mm2/s versus -0.10 x 10-3 mm2/s; P = 0.007). A 48.50% increase in %ΔADCall mean was seen in response compared with a 1.37% decrease in poor response (P < 0.0001). This corresponded to a %ΔADCb100 mean increase of 50.34% in response versus a 7.36% decrease for poor response (P < 0.0001). Significant area under the curve (AUC) values predictive of radiotherapy response were identified at ΔADC and %ΔADC for ADCall and ADCb100 mean, 10th, 25th, 50th, 75th and 90th percentiles (AUC >0.9, P < 0.01). ΔADCall mean of 0.16 × 10-3 mm2/s and ΔADCb100 mean 0.12 × 10-3 mm2/s predicted radiotherapy response with sensitivity/specificity/positive predictive value/negative predictive value of 92.9%/100.0%/100.0%/75.0% and 89.3%/100.0%/100.0%/66.7%, respectively.

CONCLUSIONS

Quantitative DWI analysis can successfully provide non-invasive assessment of bladder radiotherapy response. Multicentre validation is required before prospective testing to inform MIBC radiotherapy follow-up schedules and decision making.

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Key Words

• Bladder cancer
• Diffusion-weighted MRI
• MRI
• Radiotherapy

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MESH Headings

• Diffusion Magnetic Resonance Imaging/methods
• Humans
• Magnetic Resonance Imaging
• Prospective Studies
• ROC Curve
• Urinary Bladder/diagnostic imaging
• Urinary Bladder Neoplasms/diagnostic imaging
• Urinary Bladder Neoplasms/pathology
• Urinary Bladder Neoplasms/radiotherapy

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Grants

• 28724 Cancer Research UK
• C33589/A19727 Cancer Research UK
• Department of Health
• C33589/A28284 Cancer Research UK

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Affiliation(s)

S Hafeez The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK.
M Koh The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
K Jones The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
A El Ghzal The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
J D'Arcy The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
P Kumar The Royal Marsden NHS Foundation Trust, London, UK
V Khoo The Royal Marsden NHS Foundation Trust, London, UK
S Lalondrelle The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
F McDonald The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK
A Thompson The Royal Marsden NHS Foundation Trust, London, UK
E Scurr The Royal Marsden NHS Foundation Trust, London, UK
A Sohaib The Royal Marsden NHS Foundation Trust, London, UK
R Huddart The Institute of Cancer Research, London, UK; The Royal Marsden NHS Foundation Trust, London, UK

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Radiomics Nomogram Based on High-b-Value Diffusion-Weighted Imaging for Distinguishing the Grade of Bladder Cancer

Background: The aim was to evaluate the feasibility of radiomics features based on diffusion-weighted imaging (DWI) at high b-values for grading bladder cancer and to compare the possible advantages of high-b-value DWI over the standard b-value DWI. Methods: Seventy-four participants with bladder cancer were included in this study. DWI sequences using a 3 T MRI with b-values of 1000, 1700, and 3000 s/mm2 were acquired, and the corresponding ADC maps were generated, followed with feature extraction. Patients were randomly divided into training and testing cohorts with a ratio of 8:2. The radiomics features acquired from the ADC1000, ADC1700, and ADC3000 maps were compared between low- and high-grade bladder cancers by using the Wilcox analysis, and only the radiomics features with significant differences were selected. The least absolute shrinkage and selection operator method and a logistic regression were performed for the feature selection and establishing the radiomics model. A receiver operating characteristic (ROC) analysis was conducted to assess the diagnostic performance of the radiomics models. Results: In the training cohorts, the AUCs of the ADC1000, ADC1700, and ADC3000 model for discriminating between low- from high-grade bladder cancer were 0.901, 0.920, and 0.901, respectively. In the testing cohorts, the AUCs of ADC1000, ADC1700, and ADC3000 were 0.582, 0.745, and 0.745, respectively. Conclusions: The radiomics features extracted from the ADC1700 maps could improve the diagnostic accuracy over those extracted from the conventional ADC1000 maps.

Role of multiparametric magnetic resonance imaging in the diagnosis and staging of urinary bladder cancer

Objectives

To assess the role of multiparametric magnetic resonance imaging (mp-MRI) in the diagnosis and staging of urinary bladder cancer (BC).

Materials and methods

Fifty patients diagnosed with bladder masses underwent mp-MRI study. The results of 3 image sets were analyzed 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.

Results

The accuracy of T2WI plus DCE for detecting muscle invasion of BC was 79.5% with a fair agreement with histopathological examination (κ = 0.59); this percentage increased up to 88.6% using T2WI plus DWI, with good agreement with histopathological examination (κ = 0.74), whereas mp-MRI had the highest overall accuracy (95.4%) and excellent agreement with histopathological data (κ = 0.83). Multiparametric MRI can differentiate between low- and high-grade bladder tumors with a high sensitivity and specificity of 93.3% and 98.3%, respectively.

Conclusions

Multiparametric MRI is an acceptable method for the preoperative detection and accurate staging of BC, with reasonable accuracy in differentiating between low- and high-grade BC.

Amide Proton Transfer-weighted MRI in Predicting Histologic Grade of Bladder Cancer

Background Bladder cancer is classified into high and low grades with different clinical treatments and prognoses. Thus, accurate preoperative evaluation of the histologic grade through imaging techniques is essential. Purpose To investigate the potential of amide proton transfer-weighted (APTw) MRI in evaluating the grade of bladder cancer and to evaluate whether APTw MRI can add value to diffusion-weighted imaging (DWI) at MRI. Materials and Methods In this single-center prospective study, participants with pathologic analysis-confirmed bladder cancer with no previous treatment, lesions larger than 10 mm, and adequate MRI quality were enrolled from July 2020 to September 2021 in a university teaching hospital. All participants underwent preoperative multiparametric MRI, including APTw MRI and DWI. The mean APTw and apparent diffusion coefficient (ADC) values of the primary tumor were measured independently by two radiologists. Receiver operating characteristic curves were generated to evaluate the diagnostic performance of these quantitative parameters. Results In total, 83 participants (mean age, 64 years ± 13 [SD]; 72 men) were evaluated: 51 with high-grade and 32 with low-grade bladder cancer. High-grade bladder cancer showed higher APTw values (6% [IQR, 4%-12%] vs 2% [IQR, 1%-3%]; P < .001) and lower ADC values (0.92 × 10^-3 mm²/sec ± 0.17 vs 1.21 × 10^-3 mm²/sec ± 0.25; P < .001) than low-grade bladder cancer. The area under the receiver operating characteristic curve (AUC) of APTw and ADC for differentiating low- and high-grade bladder cancer was similar (0.84 for both; P = .94). Moreover, the combination of the two techniques improved the diagnostic performance (AUC, 0.93; all P = .01). Conclusion The combination of amide proton transfer-weighted and diffusion-weighted MRI has the potential to improve the histologic characterization of bladder cancer by differentiating low- from high-grade cancers. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

Apparent Diffusion Coefficient Map-Based Texture Analysis for the Differentiation of Chromophobe Renal Cell Carcinoma from Renal Oncocytoma

Preoperative imaging differentiation between ChRCC and RO is difficult with conventional subjective evaluation, and the development of quantitative analysis is a clinical challenge. Forty-nine patients underwent partial or radical nephrectomy preceded by MRI and followed by pathological diagnosis with ChRCC or RO (ChRCC: n = 41, RO: n = 8). The whole-lesion volume of interest was set on apparent diffusion coefficient (ADC) maps of 1.5T-MRI. The importance of selected texture features (TFs) was evaluated, and diagnostic models were created using random forest (RF) analysis. The Mean Decrease Gini as calculated through RF analysis was the highest for mean_ADC_value. ChRCC had a significantly lower mean_ADC_value than RO (1.26 vs. 1.79 × 10−3 mm2/s, p < 0.0001). Feature selection by the Boruta method identified the first-quartile ADC value and GLZLM_HGZE as important features. ROC curve analysis showed that there was no significant difference in the classification performances between the mean_ADC_value-only model and the Boruta model (AUC: 0.954 vs. 0.969, p = 0.236). The mean ADC value had good predictive ability for the distinction between ChRCC and RO, comparable to that of the combination of TFs optimized for the evaluated cohort. The mean ADC value may be useful in distinguishing between ChRCC and RO.

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.

Apparent Diffusion Coefficient Value as a Biomarker for Detecting Muscle-Invasive and High-Grade Bladder Cancer: A Systematic Review

Background: Several studies have investigated the potential role of the apparent diffusion coefficient (ADC) value of diffusion-weighted magnetic resonance imaging as a biomarker of high-grade and invasive bladder cancer. Methods: PubMed and the Cochrane Library were systematically searched in September 2021 to extract studies that evaluated the associations between ADC values, pathological T stage, and histological grade bladder cancers. The diagnostic performance of ADC values in detecting muscle-invasive bladder cancer (MIBC) and high-grade disease was systematically reviewed. Results: Six studies were included in this systematic review. MIBC showed significantly lower ADC values than non-muscle-invasive bladder cancer (NMIBC) in all six studies. The median (range) sensitivity, specificity, and area under the curve (AUC) of ADC values to detect MIBC among the four eligible studies were 73.5% (68.8–90.0%), 79.9% (66.7–84.4%), and 0.762 (0.730–0.884), respectively. Similarly, high-grade disease showed significantly lower ADC values than did low-grade disease in all four eligible studies. The median (range) sensitivity, specificity, and AUC of ADC values for detecting high-grade disease among the three eligible studies were 75.0% (73.0–76.5%), 95.8% (76.2–100%), and 0.902 (0.804–0.906), respectively. Conclusions: The ADC value is a non-invasive diagnostic biomarker for discriminating muscle-invasive and high-grade bladder cancer.

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.

Evaluation of a fractional-order calculus diffusion model and bi-parametric VI-RADS for staging and grading bladder urothelial carcinoma

OBJECTIVES

To evaluate the feasibility of high b-value diffusion-weighted imaging (DWI) for distinguishing non-muscle-invasive bladder cancer (NMIBC) from muscle-invasive bladder cancer (MIBC) and low- from high-grade bladder urothelial carcinoma using a fractional-order calculus (FROC) model as well as a combination of FROC DWI and bi-parametric Vesical Imaging-Reporting and Data System (VI-RADS).

METHODS

Fifty-eight participants with bladder urothelial carcinoma were included in this IRB-approved prospective study. Diffusion-weighted images, acquired with 16 b-values (0-3600 s/mm²), were analyzed using the FROC model. Three FROC parameters, D, β, and μ, were used for delineating NMIBC from MIBC and for tumor grading. A receiver operating characteristic (ROC) analysis was performed based on the individual FROC parameters and their combinations, followed by comparisons with apparent diffusion coefficient (ADC) and bi-parametric VI-RADS based on T2-weighted images and DWI.

RESULTS

D and μ were significantly lower in the MIBC group than in the NMIBC group (p = 0.001 for each), and D, β, and μ all exhibited significantly lower values in the high- than in the low-grade tumors (p ≤ 0.011). The combination of D, β, and μ produced the highest specificity (85%), accuracy (78%), and the area under the ROC curve (AUC, 0.782) for distinguishing NMIBC and MIBC, and the best sensitivity (89%), specificity (86%), accuracy (88%), and AUC (0.892) for tumor grading, all of which outperformed the ADC. The combination of FROC parameters with bi-parametric VI-RADS improved the AUC from 0.859 to 0.931.

CONCLUSIONS

High b-value DWI with a FROC model is useful in distinguishing NMIBC from MIBC and grading bladder tumors.

KEY POINTS

• Diffusion parameters derived from a FROC diffusion model may differentiate NMIBC from MIBC and low- from high-grade bladder urothelial carcinomas. • Under the condition of a moderate sample size, higher AUCs were achieved by the FROC parameters D (0.842) and μ (0.857) than ADC (0.804) for bladder tumor grading with p ≤ 0.046. • The combination of the three diffusion parameters from the FROC model can improve the specificity over ADC (85% versus 67%, p = 0.031) for distinguishing NMIBC and MIBC and enhance the performance of bi-parametric VI-RADS.

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.

[French ccAFU guidelines - update 2020-2022: bladder cancer]

OBJECTIVE

- To update French guidelines for the management of bladder cancer specifically non-muscle invasive (NMIBC) and muscle-invasive bladder cancers (MIBC).

METHODS

- A Medline search was achieved between 2018 and 2020, notably regarding diagnosis, options of treatment and follow-up of bladder cancer, to evaluate different references with levels of evidence.

RESULTS

- Diagnosis of NMIBC (Ta, T1, CIS) is based on a complete deep resection of the tumor. The use of fluorescence and a second-look indication are essential to improve initial diagnosis. Risks of both recurrence and progression can be estimated using the EORTC score. A stratification of patients into low, intermediate and high risk groups is pivotal for recommending adjuvant treatment: instillation of chemotherapy (immediate post-operative, standard schedule) or intravesical BCG (standard schedule and maintenance). Cystectomy is recommended in BCG-refractory patients. Extension evaluation of MIBC is based on contrast-enhanced pelvic-abdominal and thoracic CT-scan. Multiparametric MRI can be an alternative. Cystectomy associated with extended lymph nodes dissection is considered the gold standard for non-metastatic MIBC. It should be preceded by cisplatin-based neoadjuvant chemotherapy in eligible patients. An orthotopic bladder substitution should be proposed to both male and female patients with no contraindication and in cases of negative frozen urethral samples; otherwise transileal ureterostomy is recommended as urinary diversion. All patients should be included in an Early Recovery After Surgery (ERAS) protocol. For metastatic MIBC, first-line chemotherapy using platin is recommended (GC or MVAC), when performans status (PS <1) and renal function (creatinine clearance >60 mL/min) allow it (only in 50% of cases). In second line treatment, immunotherapy with pembrolizumab demonstrated a significant improvement in overall survival.

CONCLUSION

- These updated French guidelines will contribute to increase the level of urological care for the diagnosis and treatment of patients diagnosed with NMIBC and MIBC.

Usefulness of texture features of apparent diffusion coefficient maps in predicting chemoradiotherapy response in muscle-invasive bladder cancer

OBJECTIVES

To examine the usefulness of the texture analysis (TA) of apparent diffusion coefficient (ADC) maps in predicting the chemoradiotherapy (CRT) response of muscle-invasive bladder cancer (MIBC).

METHODS

We reviewed 45 MIBC patients who underwent cystectomy after CRT. CRT response was assessed through histologic evaluation of cystectomy specimens. Two radiologists determined the volume of interest for the index lesions on ADC maps of pretherapeutic 1.5-T MRI and performed TA using the LIFEx software. Forty-six texture features (TFs) were selected based on their contribution to the prediction of CRT sensitivity. To evaluate diagnostic performance, diagnostic models from the selected TFs were created using random forest (RF) and support vector machine (SVM), respectively.

RESULTS

Twenty-three patients achieved pathologic complete response (pCR) to CRT. The feature selection identified first quartile ADC (Q1 ADC), gray-level co-occurrence matrix (GLCM) correlation, and GLCM homogeneity as important in predicting CRT response. Patients who achieved pCR showed significantly lower Q1 ADC and GLCM correlation values (0.66 × 10^-3 mm²/s and 0.53, respectively) than those who did not (0.81 × 10^-3 mm²/s and 0.70, respectively; p < 0.05 for both). The AUCs of the RF and SVM models incorporating the selected TFs were 0.82 (95% confidence interval [CI]: 0.67-0.97) and 0.96 (95% CI: 0.91-1.00), respectively, and the AUC of the SVM model was better than that of the mean ADC value (0.76, 95% CI: 0.61-0.90; p = 0.0037).

CONCLUSION

TFs can serve as imaging biomarkers in MIBC patients for predicting CRT sensitivity. TAs of ADC maps can potentially optimize patient selection for CRT.

KEY POINTS

• Texture analysis of ADC maps and feature selection identified important texture features for classifying pathologic tumor response in patients with muscle-invasive bladder cancer. • The machine learning model incorporating the texture features set, which included first quartile ADC, GLCM correlation, and GLCM homogeneity, showed high performance in predicting chemoradiotherapy response. • Texture features could serve as imaging biomarkers that optimize eligible patient selection for chemoradiotherapy in muscle-invasive bladder cancer.

Application of deep learning as a noninvasive tool to differentiate muscle-invasive bladder cancer and non-muscle-invasive bladder cancer with CT

OBJECTIVE

To construct a deep-learning convolution neural network (DL-CNN) system for the differentiation of muscle-invasive bladder cancer (MIBC) and non-muscle-invasive bladder cancer (NMIBC) on contrast-enhanced computed tomography (CT) images in patients with bladder cancer.

MATERIALS AND METHODS

A total of 1200 cross-sectional CT images were obtained from 369 patients with bladder cancer receiving radical cystectomy from January 2015 to June 2018, including 249 non-muscle-invasive bladder cancer (NMIBC) series and 120 muscle-invasive bladder cancer (MIBC) series. All eligible images were distributed randomly into the training, validation, and testing cohorts with ratios of 70 %, 15 %, and 15 %, respectively. We developed one small DL-CNN containing four convolutional and max pooling layers and eight DL-CNNs with pretrained bases from the ImageNet dataset to differentiate NMIBC from MIBC. The intermediate activations were applied on the test dataset to visualize how successive DL-CNN layers transform their input.

RESULTS

The area under the receiver operating characteristic curve (AUROC) of the validation and testing datasets for the small DL-CNN was 0.946 and 0.998, respectively. The AUROCs of eight deep learning algorithms with pretrained bases ranged from 0.762 to 0.997 in the testing dataset. The VGG16 model had the largest AUROC of 0.997 among the eight algorithms with a sensitivity and specificity of 0.889 and 0.989. The independent features encoded by the small DL-CNN filters were displayed as assemblies of individual channels.

CONCLUSION

Based on contrast-enhanced CT images, our DL-CNN system could successfully classify NMIBC and MIBC with favorable AUROC in patients with bladder cancer. The application of our system in early stage might assist the pathological examination for the improvement of diagnostic accuracy.

Apparent Diffusion Coefficient Value can Predict Poor Bacillus Calmette-Guérin Responders in T1HG/NMIBC: Prospective Cohort Study

BACKGROUND

Prediction of recurrence and progression and the choice of type of management are largely based on stage and grade; however, these prognostic features are limited in the prediction of clinical outcomes. The objective was to investigate the relation between the apparent diffusion coefficient (ADC) value and recurrence and progression of T1G3 of urothelial carcinoma after transurethral resection of the bladder tumor (TURBT) and Bacillus Calmette-Guérin instillation.

MATERIALS AND METHODS

This prospective study included 65 patients with single bladder mass T1G3 less than 3 cm without carcinoma in situ or lymphovascular invasion. Mean ADC values of the tumors were compared between patients with and without recurrence and progression following TURBT. The relation of ADC value and other factors were determined by univariate and multivariate analyses. The following tests were used to test differences for significance: difference and association of qualitative variable by χ² test; differences between quantitative independent groups by t-test or Mann-Whitney U test; survival by Kaplan-Meier; Cox regression (or Cox proportional hazards model) was used to analyze the effect of several risk factors on time until event (recurrence and progression); correlation by Pearson or Spearman, and we calculated the most suitable cutoff and validity by receiver operating characteristic curve.

RESULTS

In relation to recurrence, smoking, nonpapillary shape and higher size, and lower ADC were significant predictors for recurrence. In relation to progression, female sex, nonpapillary shape, and lower ADC were significant predictors for progression. Multivariate analysis showed that ADC < 1.09 was the only significant independent predictors for recurrence. Also, it showed that ADC < 0.98 was the only significant independent predictors for progression.

CONCLUSION

Low ADC value group of T1G3 bladder cancer showed significant recurrence and progression than high ADC value group of T1G3 bladder cancer. ADC value in conjunction with other risk stratifications will have a promising role in stratifying patients with T1G3 who need to proceed to early radical cystectomy versus conservative treatment.

Prognostic prediction of resectable colorectal liver metastasis using the apparent diffusion coefficient from diffusion-weighted magnetic resonance imaging

AIM

Diffusion-weighted magnetic resonance imaging (DWI-MRI) is used to predict tumor malignancy. Here we explored the role of apparent diffusion coefficient (ADC) values in the treatment of patients with resectable colorectal liver metastasis (CRLM).

METHODS

Magnetic resonance imaging (MRI) scans were conducted using a Signa HDe or Signa Explorer 1.5-T scanner (GE Healthcare). ADC maps were calculated using DWI with b values of 0, 20, and 800 s/mm2. We enrolled 60 patients who underwent upfront hepatic resection for CRLM and divided them into ADC-high (n = 30) and ADC-low (n = 30) groups. Clinicopathological variables of the groups were compared. Immunohistochemical analysis of HIF-1α expression in tumor tissues was performed, and the relationship between the ADC value and HIF-1α expression was evaluated.

RESULTS

The disease-free survival rate of the ADC-low group was significantly lower than that of the ADC-high group (P < .05). Univariate analysis revealed that tumor number (more than five), synchronous metastasis, and low ADC were prognostic factors. Multivariate analysis identified low ADC as an independent prognostic factor. Furthermore, the ADC-low group more frequently expressed high levels of HIF-1α than the ADC-high group.

CONCLUSION

Low ADC values were an independent prognostic factor of resectable CRLM and correlated with HIF-1α expression.

Imaging of Bladder Cancer: Standard Applications and Future Trends

The evolution in imaging has had an increasing role in the diagnosis, staging and follow up of bladder cancer. Conventional cystoscopy is crucial in the diagnosis of bladder cancer. However, a cystoscopic procedure cannot always depict carcinoma in situ (CIS) or differentiate benign from malignant tumors prior to biopsy. This review will discuss the standard application, novel imaging modalities and their additive role in patients with bladder cancer. Staging can be performed with CT, but distinguishing between T1 and T2 BCa (bladder cancer) cannot be assessed. MRI can distinguish muscle-invasive from non-muscle-invasive tumors with accurate local staging. Vesical Imaging-Reporting and Data System (VI-RADS) score is a new diagnostic modality used for the prediction of tumor aggressiveness and therapeutic response. Bone scintigraphy is recommended in patients with muscle-invasive BCa with suspected bony metastases. CT shows low sensitivity for nodal staging; however, PET (Positron Emission Tomography)/CT is superior and highly recommended for restaging and determining therapeutic effect. PET/MRI is a new imaging technique in bladder cancer imaging and its role is promising. Texture analysis has shown significant steps in discriminating low-grade from high-grade bladder cancer. Radiomics could be a reliable method for quantitative assessment of the muscle invasion of bladder cancer.

Estadificación clínica como factor pronóstico en cáncer de vejiga músculo-invasor

El cáncer de vejiga músculo invasor (CV-MI), requiere de una adecuada estadificación clínica y patológica, ya que eso determina las estrategias terapéuticas y el pronóstico de la enfermedad, caracterizada por una alta morbimortalidad. Este articulo tiene como objetivo realizar una revisión de la literatura sobre la exactitud diagnóstica de las técnicas de imagen disponibles para la estadificación clínica de los pacientes con CV-MI y cómo se debería realizar el seguimiento radiológico en los pacientes llevados a cirugía. Para eso se realizó una búsqueda en la base de datos Pubmed de artículos en inglés y en español, se incluyeron artículos de revisión, metanálisis, guías clínicas, estudios retrospectivos y prospectivos de pronóstico y diagnóstico desde el año 1988 hasta el año 2020.

Multiparametric magnetic resonance imaging for bladder cancer: a comprehensive systematic review of the Vesical Imaging-Reporting and Data System (VI-RADS) performance and potential clinical applications

BACKGROUND

The Vesical Imaging-Reporting and Data System (VI-RADS) score is a novel standardized approach to image and report bladder cancer (BC) with multiparametric MRI (mpMRI).

OBJECTIVES

To describe and evaluate the performance of the VI-RADS score using mpMRI and assess its potential clinical applications and limitations.

METHODS

A systematic review was conducted using the MEDLINE and EMBASE electronic bibliographic databases between June 2020 and December 2020. All reports deemed relevant to describe the VI-RADS score and assess its performance and applications were retrieved. Results presentation stands as narrative, purely descriptive synthesis based on aggregate studies data.

RESULTS

A total of 20 relevant studies were retrieved: three meta-analyses, five prospective studies, and twelve retrospective studies. The retrospective studies covered 1676 patients, while the prospective studies included a total number of 468 patients. Pooled sensitivity, specificity to differentiate muscle-invasive from non-muscle-invasive bladder cancer, ranged from 74.1% to 97.3%, and 77% to 100%, respectively. The chosen VI-RADS score thresholds for this discrimination varied across studies. The interreader agreement ranged from 0.73 to 0.95. Currently, the potential clinical applications of VI-RADS consist of initial BC risk stratification, assessment of neoadjuvant therapies response, and bladder sparing approaches, although further validation is required.

CONCLUSIONS

The VI-RADS score helps to discriminate muscle invasive from non-muscle invasive BC with good performance and reproducibility. A simple algorithm based on four basic questions may enhance its popularization. Further studies are required to validate the clinical applications.

Application of bi-planar reduced field-of-view DWI (rFOV DWI) in the assessment of muscle-invasiveness of bladder cancer

OBJECTIVES

To compare the image quality of the reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) with the full field-of-view (fFOV) DWI in the assessment of bladder cancer (BC); and to explore the possible superiority of bi-planar (axial and sagittal) rFOV DWI over single planar fFOV DWI in predicting muscle-invasiveness of BC.

MATERIALS AND METHODS

This retrospective study analyzed 61 patients with BC who underwent DWI sequences including axial fFOV DWI, axial rFOV DWI, and sagittal rFOV DWI. Qualitative and quantitative image quality assessment were compared between axial fFOV DWI and rFOV DWI sequences. The tumor with its base could be clearly displayed on DWI was defined as the evaluable lesion, and the number of evaluable lesions detected from single axial fFOV DWI, axial rFOV DWI, sagittal rFOV DWI, and bi-planar rFOV DWI sequences was recorded and compared. The apparent diffusion coefficient (ADC) was compared between non-muscular-invasive bladder cancer (NMIBC) and muscular-invasive bladder cancer (MIBC) based on the sequences of axial fFOV DWI and rFOV DWI, respectively. Vesical Imaging-Reporting and Data System (VI-RADS) was introduced to evaluate the overall risk of muscle-invasiveness of BC and receiver operating characteristic (ROC) curve analysis was applied to assess the diagnostic performance.

RESULTS

The contrast-to-noise ratio (CNR) of the rFOV DWI was significantly higher than that of fFOV DWI (p < 0.01), while the signal-to-noise ratio (SNR) was significantly lower than that of fFOV DWI (p < 0.01). The subjective score of rFOV DWI was significantly higher than that of fFOV DWI (p < 0.01). The ADC value of the MIBC group was significantly lower than that of the NMIBC in both rFOV DWI and fFOV DWI (all p < 0.01). The number of evaluable lesions detected from the bi-planar rFOV DWI was significantly higher than that detected from the single axial fFOV DWI, axial rFOV DWI, and sagittal rFOV DWI (all p < 0.01). VI-RADS based on the bi-planar rFOV DWI offered high predictive power (the area under the ROC curve, 0.946) for predicting the presence of muscle-invasiveness of BC.

CONCLUSION

Bi-planar rFOV DWI may provide more diagnostic confidence than the single planar DWI for predicting the presence of muscle-invasiveness in BC, with improved image quality over the fFOV DWI.

Utilization of imaging for staging in bladder cancer: is there a role for MRI or PET-computed tomography?

PURPOSE OF REVIEW

Accurate staging of bladder cancer is essential to guide appropriate management. In this review, we discuss the principles, applications and performance of multiparametric MRI (mpMRI) and PET-computer tomography (PET-CT) for local and distant staging of bladder cancer.

RECENT FINDINGS

Bladder mpMRI has a high diagnostic performance in local staging of bladder cancer, superior to other imaging modalities. It can accurately differentiate muscle invasive bladder cancer (MIBC) from non-MIBC (NMIBC), as well as ≤T2 from ≥T3 stages. mpMRI can be used to assess pelvic lymph nodes, although its sensitivity is relatively low. For the assessment of the upper urinary tract, CT urography is the imaging modality of choice. magnetic resonance urography is a viable alternative to CT in selected cases. Although PET-CT is accurate for nodal and distant staging of bladder cancer, there is no clear evidence on its superior diagnostic performance compared with contrast-enhanced CT.

SUMMARY

mpMRI is the most accurate imaging modality for local staging of bladder cancer, capable to accurately distinguish MIBC from NMIBC. Nodal and distant staging relies primarily on contrast-enhanced CT.

Diagnostic performance of 3-tesla multiparametric MRI for assessment of the bladder cancer T stage and histologic grade

Background

Preoperative staging of urinary bladder carcinomas using TNM system is crucial in the management of bladder cancer which is determined mainly by stage and grade of tumor at diagnosis. We aim to evaluate the diagnostic accuracy of multiparametric MRI (mp-MRI) for assessment of the bladder cancer T stage and histologic grade.

Results

The overall T2-WI diagnostic accuracy for the T stage was 72.3%, increased to be 87.1% for contrast-enhanced images, and 92.6% for DWI, reaching the maximum accuracy 94.5% using the combined multi-parametric MRI technique. Diagnostic accuracies of mp-MRI in differentiating superficial from muscle-invasive (91%) and organ-confined from non-organ confined tumors (92%) were superior to DW-MRI (89% and 87%), DCE-MRI (84% and 83%), and T2W-MRI (74% and 71%), respectively. The agreement between MRI findings and histopathological staging was greater in mp-MRI (k = 0.91; excellent agreement) than in DW-MRI (k = 0.77; moderate agreement), DCE-MRI (k = 0.76; substantial agreement), and T2W-MRI (k = 0.53; fair agreement).

Conclusion

Mp-MRI provides useful information for evaluating the local T stages of bladder cancer and can predict the histological grades of urinary bladder cancers with high diagnostic accuracy.

VI-RADS for Bladder Cancer: Current Applications and Future Developments

Bladder cancer (BCa) is among the ten most frequent cancers globally. It is the tumor with the highest lifetime treatment-associated costs, and among the tumors with the heaviest impacts on postoperative quality of life. The purpose of this article is to review the current applications and future perspectives of the Vesical Imaging Reporting and Data System (VI-RADS). VI-RADS is a newly developed scoring system aimed at standardization of MRI acquisition, interpretation, and reporting for BCa. An insight will be given on the BCa natural history, current MRI applications for local BCa staging with assessment of muscle invasiveness, and clinical implications of the score for disease management. Future applications include risk stratification of nonmuscle invasive BCa, surveillance, and prediction and monitoring of therapy response. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Radiomics nomogram for preoperative prediction of progression-free survival using diffusion-weighted imaging in patients with muscle-invasive bladder cancer

PURPOSE

To develop a radiomics signature using diffusion-weighted imaging (DWI) for predicting progression-free survival (PFS) in muscle-invasive bladder cancer (MIBC) patients and to assess its incremental value over traditional staging system.

METHOD

210 MIBC patients undergoing preoperative DWI were enrolled. A radiomics signature was built using LASSO model. A radiomics nomogram was generated to assess the incremental value of the radiomics signature over existing risk factors in PFS estimation in terms of calibration, discrimination, reclassification and clinical usefulness. Kaplan-Meier analysis was used to assess the association of the radiomics signature with PFS. C-index was used as a discrimination measure. Net reclassification improvement (NRI) was calculated to evaluate the usefulness improvement added by the radiomics signature. Decision curve analysis was performed to evaluate the clinical usefulness of the nomograms.

RESULTS

The radiomics signature was significantly associated with PFS (log-rank P = 0.0073) and was independent with clinicopathological factors (P = 0.0004). The radiomics nomogram achieved better performance in PFS prediction (C-index: 0.702, 95 % confidence interval [CI]: 0.602, 0.802) than either clinicopathological nomogram (C-index: 0.682, 95 % CI: 0.575, 0.788) or radiomics signature (C-index: 0.612, 95 % CI: 0.493, 0.731), and achieved better calibration and classification (NRI: 0.226, 95 % CI: 0.016, 0.415, P = 0.038). Decision curve analysis demonstrated the better clinical usefulness of the radiomics nomogram.

CONCLUSIONS

The DWI-based radiomics signature was an independent predictor of PFS in MIBC patients. Combining the radiomics signature, clinical staging and other clinicopathological factors achieved better performance in individual PFS prediction.

Quantification and correction of distortion in diffusion-weighted MRI at 1.5 and 3 T in a muscle-invasive bladder cancer phantom for radiotherapy planning

OBJECTIVE

Limited visibility of post-resection muscle-invasive bladder cancer (MIBC) on CT hinders radiotherapy dose escalation of the residual tumour. Diffusion-weighted MRI (DW-MRI) visualises areas of high tumour burden and is increasingly used within diagnosis and as a biomarker for cancer. DW-MRI could, therefore, facilitate dose escalation, potentially via dose-painting and/or accommodating response. However, the distortion inherent in DW-MRI could limit geometric accuracy. Therefore, this study aims to quantify DW-MRI distortion via imaging of a bladder phantom.

METHODS

A phantom was designed to mimic MIBC and imaged using CT, DW-MRI and T2W-MRI. Fiducial marker locations were compared across modalities and publicly available software was assessed for correction of magnetic susceptibility-related distortion.

RESULTS

Fiducial marker locations on CT and T2W-MRI agreed within 1.2 mm at 3 T and 1.8 mm at 1.5 T. The greatest discrepancy between CT and apparent diffusion coefficient (ADC) maps was 6.3 mm at 3 T, reducing to 1.8 mm when corrected for distortion. At 1.5 T, these values were 3.9 mm and 1.7 mm, respectively.

CONCLUSIONS

Geometric distortion in DW-MRI of a model bladder was initially >6 mm at 3 T and >3 mm at 1.5 T; however, established correction methods reduced this to <2 mm in both cases.

ADVANCES IN KNOWLEDGE

A phantom designed to mimic MIBC has been produced and used to show distortion in DW-MRI can be sufficiently mitigated for incorporation into the radiotherapy pathway. Further investigation is therefore warranted to enable individually adaptive image-guided radiotherapy of MIBC based upon DW-MRI.

French ccAFU guidelines – Update 2018–2020: Bladder cancer

Objective

To propose updated French guidelines for non-muscle invasive (NMIBC) and muscle-invasive (MIBC) bladder cancers.

Methods

A Medline search was achieved between 2015 and 2018, as regards diagnosis, options of treatment and follow-up of bladder cancer, to evaluate different references with levels of evidence.

Results

Diagnosis of NMIBC (Ta, T1, CIS) is based on a complete deep resection of the tumor. The use of fluorescence and a second-look indication are essential to improve initial diagnosis. Risks of both recurrence and progression can be estimated using the EORTC score. A stratification of patients into low, intermediate and high risk groups is pivotal for recommending adjuvant treatment: instillation of chemotherapy (immediate post-operative, standard schedule) or intravesical BCG (standard schedule and maintenance). Cystectomy is recommended in BCG-refractory patients. Extension evaluation of MIBC is based on contrast-enhanced pelvic-abdominal and thoracic CT-scan. Multiparametric MRI can be an alternative. Cystectomy associated with extended lymph nodes dissection is considered the gold standard for non-metastatic MIBC. It should be preceded by cisplatin-based neoadjuvant chemotherapy in eligible patients. An orthotopic bladder substitution should be proposed to both male and female patients with no contraindication and in cases of negative frozen urethral samples; otherwise transileal ureterostomy is recommended as urinary diversion. All patients should be included in an Early Recovery After Surgery (ERAS) protocol. For metastatic MIBC, first-line chemotherapy using platin is recommended (GC or MVAC), when performans status (PS < 1) and renal function (creatinine clearance > 60 mL/min) allow it (only in 50 % of cases). In second line treatment, immunotherapy with pembrolizumab demonstrated a significant improvement in overall survival.

Conclusion

These updated French guidelines will contribute to increase the level of urological care for the diagnosis and treatment for NMIBC and MIBC.

Detection of Muscle-Invasive Bladder Cancer on Biparametric MRI Using Vesical Imaging-Reporting and Data System and Apparent Diffusion Coefficient Values (VI-RADS/ADC)

BACKGROUND: Vesical Imaging-Reporting And Data System (VI-RADS) was proposed to detect muscle-invasive bladder cancer (MIBC). OBJECTIVE: To evaluate the performance of VI-RADS and additional value of apparent diffusion coefficient (ADC) values measured on diffusion-weighted magnetic resonance imaging (MRI) for detecting MIBC. METHODS: A total of 176 patients undergoing MRI (multiparametric in 97 [55%] and biparametric in 79 [45%]) before transurethral resection of bladder tumor for primary bladder cancer were retrospectively identified. MRI findings were scored according to VI-RADS. The standardized tumor ADC (sT-ADC: tumor ADC/gluteus maximus ADC) was calculated and used to account for the incompatibility among different MRI protocols. The accuracy of VI-RADS, sT-ADC and their combination to detect MIBC was assessed using the AUC of the ROC curve. RESULTS: MIBC was pathologically confirmed in 46 patients (26%). AUC of VI-RADS to detect MIBC was 0.86. When cut-off of VI-RADS was set at≥3 and≥4, sensitivity/specificity were 78% /70% and 63% /96%, respectively. A lower sT-ADC (≤0.894) was significantly associated with muscle invasion (p < 0.01, AUC 0.79) with sensitivity 78% and specificity 79%. Combination of VI-RADS and sT-ADC improved the accuracy (AUC 0.94); sensitivity was 100% when VI-RADS≥3 or sT-ADC≤0.894 was considered positive, and specificity was 99% when VI-RADS≥4 and sT-ADC≤0.894 was considered positive. Incorporation of sT-ADC reduced under-staging of MIBC as VI-RADS < 3 by 100% and over-staging of non-MIBC as VI-RADS≥4 by 80%. CONCLUSIONS: Incorporation of ADC values into VI-RADS improves accuracy to detect MIBC in primary bladder cancer patients.

Association of chromosome 7 aneuploidy measured by fluorescence in situ hybridization assay with muscular invasion in bladder cancer

Background

The preoperative prediction of muscular invasion status is important for adequately treating bladder cancer (BC) but nevertheless, there are some existing dilemmas in the current preoperative diagnostic accuracy of BC with muscular invasion. Here, we investigated the potential association between the fluorescence in situ hybridization (FISH) assay and muscular invasion among patients with BC. A cytogenetic‐clinical nomogram for the individualized preoperative differentiation of muscle‐invasive BC (MIBC) from non‐muscle‐invasive BC (NMIBC) is also proposed.

Methods

All eligible BC patients were preoperatively tested using a FISH assay, which included 4 sites (chromosome‐specific centromeric probe [CSP] 3, 7, and 17, and gene locus‐specific probe [GLP]‐p16 locus). The correlation between the FISH assay and BC muscular invasion was evaluated using the Chi‐square tests. In the training set, univariate and multivariate logistic regression analyses were used to develop a cytogenetic‐clinical nomogram for preoperative muscular invasion prediction. Then, we assessed the performance of the nomogram in the training set with respect to its discriminatory accuracy and calibration for predicting muscular invasion, and clinical usefulness, which were then validated in the validation set. Moreover, model comparison was set to evaluate the discrimination and clinical usefulness between the nomogram and the individual variables incorporated in the nomogram.

Results

Muscular invasion was more prevalent in BC patients with positive CSP3, CSP7 and CSP17 status (OR [95% CI], 2.724 [1.555 to 4.774], P < 0.001; 3.406 [1.912 to 6.068], P < 0.001 and 2.483 [1.436 to 4.292], P = 0.001, respectively). Radiology‐determined tumor size, radiology‐determined clinical tumor stage and CSP7 status were identified as independent risk factors of BC muscular invasion by the multivariate regression analysis in the training set. Then, a cytogenetic‐clinical nomogram incorporating these three independent risk factors was constructed and was observed to have satisfactory discrimination in the training (AUC 0.784; 95% CI: 0.715 to 0.853) and validation (AUC 0.743; 95% CI: 0.635 to 0.850) set. The decision curve analysis (DCA) indicated the clinical usefulness of our nomogram. In models comparison, using the receiver operator characteristic (ROC) analyses, the nomogram showed higher discriminatory accuracy than any variables incorporated in the nomogram alone and the DCAs also identified the nomogram as possessing the highest net benefits at wide range of threshold probabilities.

Conclusion

CSP7 status was identified as an independent factor for predicting muscular invasion in BC patients and was successfully incorporated in a clinical nomogram combining the results of the FISH assay with clinical risk factors.

Accuracy of diffusion-weighted magnetic resonance imaging in evaluation of muscle invasion and histologic grading of the urinary bladder carcinoma

Background

Carcinoma of the urinary bladder is a common malignant tumor of the urinary tract in both men and women. Proper management of the urinary bladder cancer depends on the stage of the lesions. The aim of this prospective study was to determine the accuracy of diffusion-weighted images in early detection of muscle invasion, local tumor staging of urinary bladder carcinoma, and to measure the correlation between apparent diffusion coefficient (ADC) and histologic grade. Sixty patients with urinary bladder mass lesions underwent transurethral cystoscopy and biopsy after MR imaging. Radical cystectomy was done for lesions infiltrating muscularis propria. Different MR image sets (T2WIs, DWIs images) were interpreted; ADC values of tumors were calculated.

Results

Kappa agreement was better in DWI than T2WI (Kappa was 0.756 and 0.484) and the overall agreement was (83.6% and 63.6%) among both respectively. Accuracy of DWI in diagnosis of tumor stages were 80%, 43%, 96%, and 100% while in T2WI were 55%, 43%, 74%, and 80% for T1, T2, T3, and T4 stages respectively. ANOVA test showed statistically significant difference between mean ADC values of different tumor grades.

Conclusion

DWI showed higher accuracy than T2WI in detection of the degree of muscle invasion of the urinary bladder carcinoma, so it can be added to the routine protocol of MRI examination especially in patients with renal impairment. ADC value can predict the histological grade of the tumor.

Validation of vesical imaging reporting and data system for assessing muscle invasion in bladder tumor

PURPOSE

To retrospectively determine the diagnostic values of vesical imaging reporting and data system (VI-RADS) score for detecting muscle-invasive bladder tumors.

METHODS

This study included 297 consecutive patients with 339 tumors who previously diagnosed and subsequently underwent multiparametric MR imaging between January 2015 and March 2019. Two radiologists assessed the scores of muscle-invasive tumors using cutoff values of ≥ 4 and ≥ 3. Cutoff values for VI-RADS scores were estimated from the best operating points of the areas under the receiver operating characteristic curve analyses using the Youden J statistic. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were calculated to assess the utility of VI-RADS for diagnosing muscle-invasive tumors.

RESULTS

Inter-observer agreement was excellent for three different MR imaging type at lesion level (k = 0.89 for T2W, k = 0.82 for DW, and k = 0.85 for DCE). At a cutoff value of 4, T2W and DW imaging had a diagnostic accuracy of 79.3% (269/339) for tumor lesions with muscle invasion, which was similar to an overall score of 80.2% (272/339). The overall VI-RAD score showed 80.2% accuracy (272/339), with a cutoff value of ≥ 4, yielding 91.3% sensitivity (85/93), 76.0% specificity (187/246), 83.3% PPV (85/102), and 78.9% NPV (187/237). When we considered an arbitrary overall score of ≥ 3 as the cutoff value, the accuracy was 63.7% (216/339); sensitivity, 94.6% (125/132); specificity, 43.9% (91/207); PPV, 51.6% (125/242); and NPV, 63.7% (91/97).

CONCLUSION

VI-RADS has an overall good performance in the diagnosis of muscle-invasive tumors.

T1-Staging for Urinary Bladder Cancer with the Stalk and Inchworm Signs with 3.0 Tesla MRI

Purpose

To evaluate the diagnostic utility of the stalk and the inchworm sign on preoperative MRI for detecting superficial bladder cancers, and to compare the diagnostic performance between the stalk and the inchworm sign.

Materials and Methods

We retrospectively reviewed 240 patients (505 tumors) who had undergone radical cystectomy. The tumors were classified as follows: superficial or invasive tumors indicated by the stalk or inchworm sign on 3.0 Tesla MRI. We evaluated the diagnostic accuracy of the stalk and inchworm signs, by comparing each finding with the postoperative pathologic T stage. We compared diagnostic performance between them statistically.

Results

The stalk and inchworm signs showed high specificity (93% and 91%, respectively), positive predictive values (89% and 90%, respectively), and acceptable accuracy (70% and 74%, respectively), but low sensitivity (54% and 61%, respectively) and negative predictive values (60% and 63%, respectively). There was no statistically significant difference between the two signs (p > 0.05).

Conclusion

Superficial bladder cancers could be differentiated from invasive tumors using the stalk or inchworm sign on MRI.

Rectal Cancer Invasiveness: Whole-Lesion Diffusion-Weighted Imaging (DWI) Histogram Analysis by Comparison of Reduced Field-of-View and Conventional DWI Techniques

To explore the role of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) for discriminating between T stages of rectal carcinoma by comparison of reduced field-of-view (FOV) and conventional DWI techniques. 102 patients with rectal cancer were enrolled in this retrospective study. All patients received preoperative MR scan at 3 T, including reduced and full FOV DWI sequences. Histogram parameters from two DWI methods were calculated and correlated with histological T stage of rectal cancer. The diagnostic performance of individual parameter for differentiating stage pT1-2 and pT3-4 tumors from both DWI techniques was assessed by receiver operating characteristic curve analysis. There were significant differences for the parameters of ADCmean, 50th, 75th, 90th, 95th percentiles, skewness and kurtosis of both DWI sequences in patients with pT1-2 as compared to those with pT3-4 tumors (P < 0.05), in addition to parameters including ADCmin (P = 0.015) and 25th percentile (P = 0.006) from rFOV DWI. Correlations were noted between T staging and above histogram parameters from rFOV DWI (r: −0.741–0.682) and fFOV DWI (r: −0.449–0.449), besides parameters of ADCmin (0.370) and 25th percentile (−0.425) from rFOV DWI. The AUCs of 75th and 90th percentiles from rFOV DWI were significantly higher than that from fFOV DWI (P = 0.0410 and P = 0.0208). The whole-lesion histogram analysis based on rFOV DWI was overall more advantageous than the one based on fFOV DWI in differentiating T staging of rectal cancer and the 90th percentile ADC from rFOV DWI was the value with the highest AUC (0.932).

Multiparametric MRI in differentiation between muscle invasive and non-muscle invasive urinary bladder cancer with vesical imaging reporting and data system (VI-RADS) application

OBJECTIVE

To evaluate role of multiparametric MRI (mp-MRI) in differentiation between invasive and non-invasive bladder cancer and accuracy of vesical imaging reporting and data system (VI-RADS) score.

METHODS AND MATERIALS

50 patients diagnosed as cancer bladder were enrolled in this study, mp-MRI including conventional (T₁ weighted imaging and high resolution T₂ weighted imaging) and functional sequences (diffusion-weighted imaging and dynamic contrast enhanced-MRI) were done, all data were regrouped to evaluate the accuracy of each separate sequence and mp-MRI in distinguishing non-muscle invasive from muscle-invasive tumors, with VI-RADS score application and comparison with pathological findings, then interobserver agreement for detection of muscle invasion according to mp-MRI and VI-RADS scoring system findings was calculated.

RESULTS

Diagnostic accuracy of mp-MRI in differentiation between muscle invasive and non-muscle invasive bladder cancer was (84%) with highest sensitivity (78%), very good agreement between mp-MRI and histopathological data (k = 0.87), and highest area under curve (AUC) reaching 0.83, dynamic contrast enhanced-MRI sequence showed the highest accuracy in muscle invasion detection by (88%), with highest AUC 0.83. Diagnostic accuracy of VI-RADS score in detection of muscle invasion was 84%, with specificity and negative predictive value of 88% and AUC was 0.83. Interobserver agreement was strong as regard diagnostic performance of mp-MRI and VI-RADS scoring for detection of muscle invasion reaching (K = 0.82, p < 0.001) and (K = 0.87, p < 0.001) respectively.

CONCLUSION

mp-MRI is considered as comprehensive and effective tool for determination of muscle invasion in cases of urinary bladder cancer. Also VI-RADS scoring system can accurately differentiate between invasive and non-invasive bladder cancer.

ADVANCES IN KNOWLEDGE

The VI-RADS system was recently suggested for the uniform evaluation of muscle invasion in cancer bladder by mp-MRI. In this paper, we applied this system to 50 cases to evaluate its ease and compared the results with the histopathological findings for evaluation of its accuracy.

Diagnostic Accuracy of Multi-Parametric Magnetic Resonance Imaging for Tumor Staging of Bladder Cancer: Meta-Analysis

Purpose: Evaluate the diagnostic accuracy of multi-parametric magnetic resonance imaging (mp-MRI) for local staging of bladder cancer (BCa).

Materials and Methods: The databases of PubMed, Web of Science, Wanfang, and CNKI were searched for related literatures about BCa diagnosed by mp-MRI from January 1, 2000 to April 12, 2019. The strict inclusion and exclusion criteria were set up to extract records. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 was used to evaluate quality of the candidate studies. The pooled sensitivity, specificity, positive likelihood ratio (+LR), negative likelihood ratio (−LR), and diagnostic odds ratio (DOR) were calculated to assess the diagnostic authenticity of mp-MRI. The summarized receiver operating characteristic (SROC) curve corresponding with the area under the curve (AUC) were analyzed to comprehensively evacuate the diagnostic value of mp-MRI.

Results: A total of 140 studies were retrieved by computer-based searching. After quality control, 4 studies with 259 patients were enrolled for meta-analysis. The pooled results showed 0.84 of sensitivity [95% confidence interval (CI) = 0.79-0.89], 0.91 of specificity (95% CI = 0.87–0.93), 8.24 of +LR (95% CI = 4.87–13.92), 0.18 of –LR (95% CI = 0.10–0.31), 49.42 of DOR (95% CI = 19.07–128.09), and 0.946 of AUC. The Spearman correlation analysis found no threshold effect (p = 0.684). A significant heterogeneity existed among 4 included studies with sensitivity (I² = 65.7%), specificity (I² = 60.0%) and diagnostic OR (I² = 67.5%). The Begg's test (p = 0.497) and the egger's test (p = 0.337) found no publication bias.

Conclusion: mp-MRI acts a good diagnostic performance for bladder cancer. It is plausible that mpMRIs can be used as an important method for bladder cancer staging.