Use of Quantitative T2-Weighted and Apparent Diffusion Coefficient Texture Features of Bladder Cancer and Extravesical Fat for Local Tumor Staging After Transurethral Resection

Intravesical BCG therapy: implications for radiologists in abdominal imaging follow-up

This study reviews the intravesical Bacillus Calmette-Guérin therapy for treatment of non-muscle invasive bladder cancer including mechanism of action, dosing considerations, treatment success and surveillance. A variety of common and uncommon adverse effects are reviewed with a focus on abdominal -pelvic complications stratified into genitourinary and systemic categories. The complications included more common entities such as chemical cystitis, which has been reported to be present in approximately 35% of the patients to more serious but rare complications such as vascular involvement with only a few reported cases in the literature. For each complication, the pertinent imaging findings and available examples are provided. Additionally, it is important to consider the potential for recurrence or progression of bladder cancer in this patient population, with reported rates of 38.2% and 9.8%, respectively. This underscores the necessity of a thorough differential diagnosis when interpreting imaging findings related to these complications.

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.

MRI-Based Radiomics in Bladder Cancer: A Systematic Review and Radiomics Quality Score Assessment

(1): Background: With the recent introduction of vesical imaging reporting and data system (VI-RADS), magnetic resonance imaging (MRI) has become the main imaging method used for the preoperative local staging of bladder cancer (BCa). However, the VI-RADS score is subject to interobserver variability and cannot provide information about tumor cellularity. These limitations may be overcome by using a quantitative approach, such as the new emerging domain of radiomics. (2) Aim: To systematically review published studies on the use of MRI-based radiomics in bladder cancer. (3) Materials and Methods: We performed literature research using the PubMed MEDLINE, Scopus, and Web of Science databases using PRISMA principles. A total of 1092 papers that addressed the use of radiomics for BC staging, grading, and treatment response were retrieved using the keywords "bladder cancer", "magnetic resonance imaging", "radiomics", and "textural analysis". (4) Results: 26 papers met the eligibility criteria and were included in the final review. The principal applications of radiomics were preoperative tumor staging (n = 13), preoperative prediction of tumor grade or molecular correlates (n = 9), and prediction of prognosis/response to neoadjuvant therapy (n = 4). Most of the developed radiomics models included second-order features mainly derived from filtered images. These models were validated in 16 studies. The average radiomics quality score was 11.7, ranging between 8.33% and 52.77%. (5) Conclusions: MRI-based radiomics holds promise as a quantitative imaging biomarker of BCa characterization and prognosis. However, there is still need for improving the standardization of image preprocessing, feature extraction, and external validation before applying radiomics models in the clinical setting.

Evaluation of Whole-Tumor Texture Analysis Based on MRI Diffusion Kurtosis and Biparametric VI-RADS Model for Staging and Grading Bladder Cancer

BACKGROUND

to evaluate the feasibility of texture analysis (TA) based on diffusion kurtosis imaging (DKI) in staging and grading bladder cancer (BC) and to compare it with apparent diffusion coefficient (ADC) and biparametric vesical imaging reporting and data system (VI-RADS).

MATERIALS AND METHODS

In this retrospective study, 101 patients with pathologically confirmed BC underwent MRI with multiple-b values ranging from 0 to 2000 s/mm². ADC- and DKI-derived parameters, including mean kurtosis (MK) and mean diffusivity (MD), were obtained. First-order texture histogram parameters of MK and MD, including the mean; 5th, 25th, 50th, 75th, and 90th percentiles; inhomogeneity; skewness: kurtosis; and entropy; were extracted. The VI-RADS score was evaluated based on the T2WI and DWI. The Mann-Whitney U-test was used to compare the texture parameters and ADC values between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), as well as between low and high grades. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of each significant parameter and their combinations.

RESULTS

The NMIBC and low-grade group had higher MDmean, MD5th, MD25th, MD50th, MD75th, MD90th, and ADC values than those of the MIBC and the high-grade group. The NMIBC and low-grade group yielded lower MKmean, MK25th, MK50th, MK75th, and MK90th than the MIBC and high-grade group. Among all histogram parameters, MD75th and MD90th yielded the highest AUC in differentiating MIBC from NMIBC (both AUCs were 0.87), while the AUC for ADC was 0.86. The MK75th and MK90th had the highest AUC (both 0.79) in differentiating low- from high-grade BC, while ADC had an AUC of 0.68. The AUC (0.92) of the combination of DKI histogram parameters (MD75th, MD90th, and MK90th) with biparametric VI-RADS in staging BC was higher than that of the biparametric VI-RADS (0.89).

CONCLUSIONS

Texture-analysis-derived DKI is useful in evaluating both the staging and grading of bladder cancer; in addition, the histogram parameters of the DKI (MD75th, MD90th, and MK90th) can provide additional value to VI-RADS.

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.

Radiomic assessment as a method for predicting tumor mutation burden (TMB) of bladder cancer patients: a feasibility study

Background

Tumor mutation burden (TMB) is an emerging prognostic biomarker of immunotherapy for bladder cancer (BLCA). We aim at investigating radiomic features’ value in predicting the TMB status of BLCA patients.

Methods

Totally, 75 patients with BLCA were enrolled. Radiomic features extracted from the volume of interest of preoperative pelvic contrast-enhanced computed tomography (CECT) were obtained for each case. Unsupervised hierarchical clustering analysis was performed based on radiomic features. Sequential univariate Logistic regression, the least absolute shrinkage and selection operator (LASSO) regression and the backward stepwise regression were used to develop a TMB-predicting model using radiomic features.

Results

The unsupervised clustering analysis divided the total cohort into two groups, i.e., group A (32.0%) and B (68.0%). Patients in group A had a significantly larger proportion of having high TMB against those in group B (66.7% vs. 41.2%, p = 0.039), indicating the intrinsic ability of radiomic features in TMB-predicting. In univariate analysis, 27 radiomic features could predict TMB. Based on six radiomic features selected by logistic and LASSO regression, a TMB-predicting model was built and visualized by nomogram. The area under the ROC curve of the model reached 0.853. Besides, the calibration curve and the decision curve also revealed the good performance of the model.

Conclusions

Our work firstly proved the feasibility of using radiomics to predict TMB for patients with BLCA. The predictive model based on radiomic features from pelvic CECT has a promising ability to predict TMB. Future study with a larger cohort is needed to verify our findings.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08569-y.

Recommendations for planning and delivery of radical radiotherapy for localized urothelial carcinoma of the bladder

PURPOSE

Curative radio-chemotherapy is recognized as a standard treatment option for muscle-invasive bladder cancer (MIBC). Nevertheless, the technical aspects for MIBC radiotherapy are heterogeneous with a lack of practical recommendations.

METHODS AND MATERIALS

In 2018, a workshop identified the need for two cooperative groups to develop consistent, evidence-based guidelines for irradiation technique in the delivery of curative radiotherapy. Two radiation oncologists performed a review of the literature addressing several topics relative to radical bladder radiotherapy: planning computed tomography acquisition, target volume delineation, radiation schedules (total dose and fractionation) and dose delivery (including radiotherapy techniques, image-guided radiotherapy (IGRT) and adaptive treatment modalities). Searches for original and review articles in the PubMed and Google Scholar databases were conducted from January 1990 until March 2020. During a meeting conducted in October 2020, results on 32 topics were presented and discussed with a working group involving 15 radiation oncologists, 3 urologists and one medical oncologist. We applied the American Urological Association guideline development's method to define a consensus strategy.

RESULTS

A consensus was obtained for all 34 except 4 items. The group did not obtain an agreement on CT enhancement added value for planning, PTV margins definition for empty bladder and full bladder protocols, and for pelvic lymph-nodes irradiation. High quality evidence was shown in 6 items; 8 items were considered as low quality of evidence.

CONCLUSION

The current recommendations propose a homogenized modality of treatment both for routine clinical practice and for future clinical trials, following the best evidence to date, analyzed with a robust methodology. The XXX group formulates practical guidelines for the implementation of innovative techniques such as adaptive radiotherapy.

Radiomics and Bladder Cancer: Current Status

PURPOSE: To systematically review the current literature and discuss the applications and limitations of radiomics and machine-learning augmented radiomics in the management of bladder cancer. METHODS: Pubmed ®, Scopus ®, and Web of Science ® databases were searched systematically for all full-text English-language articles assessing the impact of Artificial Intelligence OR Radiomics OR Machine Learning AND Bladder Cancer AND (staging OR grading OR prognosis) published up to January 2020. RESULTS: Of the 686 articles that were identified, 13 studies met the criteria for quantitative analysis. Staging, Grading and Tumor Classification, Prognosis, and Therapy Response were discussed in 7, 3, 2 and 7 studies, respectively. Data on cost of implementation were not reported. CT and MRI were the most common imaging approaches. CONCLUSION: Radiomics shows potential in bladder cancer detection, staging, grading, and response to therapy, thereby supporting the physician in personalizing patient management. Extension and validation of this promising technology in large multisite prospective trials is warranted to pave the way for its clinical translation.

Preoperative imaging for locoregional staging of bladder cancer

Bladder cancer is the ninth most common cancer, expected to lead to an estimated 17,670 deaths in the United States in 2019. Clinical management and prognosis of bladder cancer mainly depend on the extent of locoregional disease, particularly whether bladder muscle is involved. Therefore, bladder cancer is often divided into superficial, non-muscle-invasive bladder cancer and muscle-invasive bladder cancer; the latter often prompts consideration for cystectomy. While precise staging prior to cystectomy is crucial, the optimal preoperative imaging modality used to stage the disease remains controversial. Transurethral resection of bladder tumor (TURBT) followed by computed tomography (CT) urography is the current recommended approach for staging bladder cancer but suffers from a high rate of understaging. We review the recent literature and compare different imaging modalities for assessing the presence of muscle invasion and lymph node involvement prior to cystectomy and highlight the advantages of each modality.

Application of R2* and Apparent Diffusion Coefficient in Estimating Tumor Grade and T Category of Bladder Cancer

OBJECTIVE. The objective of our study was to compare the feasibility of R2* and apparent diffusion coefficient (ADC) for differentiating tumor grade and T category of bladder cancer. SUBJECTS AND METHODS. In this prospective study, 58 patients with pathologically confirmed bladder cancers underwent pretreatment T2*-weighted imaging and DWI on a 3-T MRI unit. The apparent transverse relaxation rate R2*, which is derived from T2*-weighted imaging, and ADC, which is derived from DWI, were calculated and compared between low- and high-grade bladder cancers as well as between non-muscle-invasive bladder cancers (NMIBCs) and muscle-invasive bladder cancers (MIBCs) using the Mann-Whitney U test. The diagnostic performances of R2*, ADC, and the combination of R2* and ADC were evaluated through an ROC analysis. RESULTS. Significant differences were found in R2* (mean ± SD, 16.55 ± 5.54 vs 20.96 ± 7.75 s^-1; p = 0.001) and ADC (1.62 ± 0.31 vs 1.33 ± 0.21 × 10^-3 mm²/s; p < 0.001) between lowand high-grade bladder cancers. R2* was significantly higher (22.56 ± 8.41 vs 18.06 ± 6.46 s^-1; p = 0.008) and ADC was considerably lower (1.21 ± 0.18 vs 1.53 ± 0.27 × 10^-3 mm²/s; p < 0.001) in MIBCs than in NMIBCs. The AUCs for differentiating low-from high-grade groups were 0.714 using R2* and 0.779 using ADC. AUCs for distinguishing between NMIBC and MIBC groups using R2* and ADC were 0.682 and 0.850, respectively. CONCLUSION. In addition to ADC, R2* can be used as a quantitative imaging biomarker to provide additional information for tumor characterization of bladder cancer.