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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., (Copyright © 2024 American College of Radiology. Published by Elsevier Inc. All rights reserved.)

Purpose: The incomplete resection of non-muscle invasive bladder cancer (NMIBC) augments the risk of disease recurrence. Imaging-guided surgery by molecular probes represents a pivotal strategy for mitigating postoperative recurrence. Traditional optical molecular probes, primarily composed of antibodies/peptides targeting tumour cells and fluorescent groups, are challenged by the high heterogeneity of NMIBC cells, leading to inadequate probe sensitivity. We have developed a collagen-adhesive probe (CA-P) to target the collagen within the tumour microenvironment, aiming to address the issue of insufficient imaging sensitivity., Methods: The distribution characteristics of collagen in animal bladder cancer models and human bladder cancer tissues were explored. The synthesis and properties of CA-P were validated. In animal models, the imaging performance of CA-P was tested and compared with our previously reported near-infrared probe PLSWT7-DMI. The clinical translational potential of CA-P was assessed using human ex vivo bladder tissues., Results: The distribution of collagen on the surface of tumour cells is distinct from its expression in normal urothelium. In vitro studies have demonstrated the ability of the CA-P to undergo a "sol-gel" transition upon interaction with collagen. In animal models and human ex vivo bladder specimens, CA-P exhibits superior imaging performance compared to PLSWT7-DMI. The sensitivity of this probe is 94.1%, with a specificity of 81%., Conclusion: CA-P demonstrates the capability to overcome tumour cell heterogeneity and enhance imaging sensitivity, exhibiting favorable imaging outcomes in preclinical models. These findings provide a theoretical basis for the application of CA-P in intraoperative navigation for NMIBC., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: The purpose of this study was to investigate the impact of different low-energy virtual monochromatic images (VMIs) in dual-energy CT on the performance of radiomics models for predicting muscle invasive status in bladder cancer (BCa)., Materials and Methods: A total of 127 patients with pathologically proven muscle-invasive BCa (n = 49) and non-muscle-invasive BCa (n = 78) were randomly allocated into the training and test cohorts at a ratio of 7:3. Feature extraction was performed on the venous phase images reconstructed at 40, 50, 60 and 70-keV (single-energy analysis) or in combination (multi-energy analysis). Recursive feature elimination (RFE) and the least absolute shrinkage and selection operator (LASSO) were employed to select the most relevant features associated with BCa. Models were built using a support vector machine (SVM) classifier. Diagnostic performance was assessed through receiver operating characteristic curves, evaluating sensitivity, specificity, accuracy, precision, and the area-under-the curve (AUC) values., Results: In the test cohort, the multi-energy model achieved the best diagnostic performance with AUC, sensitivity, specificity, accuracy, and precision of 0.917, 0.800, 0.833, 0.821, and 0.750, respectively. Conversely, the single-energy model exhibited lower AUC and sensitivity in predicting the muscle invasion status., Conclusions: By combining information from VMIs of various energies, the multi-energy model displays superior performance in preoperatively predicting the muscle invasion status of bladder cancer., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Bladder cancer (BCa), as the most common malignant tumor of the urinary system, has received significant attention in research on the clinical application of artificial intelligence algorithms. Nevertheless, it has been observed that certain investigations use data from various medical facilities to train models for BCa, which may pose a privacy risk. Given this concern, protecting patient privacy during machine learning algorithm training is a crucial aspect that requires substantial attention. One emerging machine learning paradigm that addresses this concern is federated learning (FL). FL enables multiple entities to collaboratively build machine learning models while preserving data privacy and security. In this study, we present a multicenter BCa magnetic resonance imaging (MRI) dataset. The dataset comprises 275 three-dimensional bladder T2-weighted MRI scans collected from four medical centers, and each scan includes diagnostic pathological labels for muscle invasion and pixel-level annotations of tumor contours. Four FL methods are used to assess the baseline of the dataset for both the task of diagnosing muscle-invasive bladder cancer and automatic bladder tumor lesion segmentation., (© 2024. The Author(s).)

We report the case of a 79-year-old woman with primary lymphoma of mucosa-associated lymphoid tissue (MALT) in the urinary bladder. The patient, with urinary frequency, urgency and suprapubic pain had several emergency room visits due to recurrent urinary tract infection. Both sonogram and cystoscopy identified bladder tumors near the bladder neck. An abdominal contrast-enhanced computed tomography scan revealed a polypoid lesion on the anterior bladder wall without enlarged lymph nodes. Transurethral resection of the bladder tumor was conducted. The pathology report confirmed extranodal marginal zone MALT lymphoma. The clinical stage was IEA. Follow-up imaging reported residual bladder tumors, prompting adjuvant radiotherapy. The patient was treated successfully and was disease-free at the 9-month follow-up visit. Primary lymphoma is an uncommon pathological subtype. Its clinical and radiological differentiation from urothelial carcinoma (UC) can be challenging, but treatment strategies differ significantly. A definitive diagnosis relies on histopathology and immunohistochemistry. Typically, bladder lymphoma has a favorable prognosis, but further research is required to identify the optimal treatment., (© 2024. The Author(s).)

Background: Muscle invasive bladder cancer (MIBC) treatment combines systemic therapy and radical cystectomy (RC) or local (chemo-)radiotherapy. Response to systemic therapy is an important outcome predictor but is difficult to assess pre-operatively., Methods: We analyzed multiparametric MRI (mpMRI) in consecutive MIBC patients receiving cisplatin-based neo-adjuvant chemotherapy at our institution. Two readers, blinded for pathological outcome, independently scored mpMRI before and after 2 and 4 cycles using both a qualitative 3-step method and nacVI-RADS. We analyzed accuracy of mpMRI scores to predict pathologic complete response (pCR) and inter-observer agreement., Results: We analyzed 46 patients receiving NAC, 6 patients did not undergo RC after NAC and were excluded. Eleven out of 40 (28%) patients showed a pCR. mpMRI could be assessed in over 90% of patients. Radiologic complete response (rCR) using both methods was significantly associated with pCR, with an overall specificity of 96% and sensitivity of 36% and a high inter-observer agreement. rCR as assessed by the 3-step score was significantly associated with disease free survival (DFS) benefit., Conclusion: The use of nacVI-RADS can predict pCR after NAC with high specificity but low sensitivity and a high inter-observer agreement. A 3-step score adds value in determining local residual disease, rCR assessed by this method could correlate with DFS benefit. mpMRI scores should be prospectively assessed in future trials of multimodal management of MIBC and can be a predictive asset in routine clinical management., (© 2024. The Author(s).)

Purpose: MRI-based VI-RADS score aids in differentiating MIBC and NMIBC, but the experience's impact remains unexplored. We aimed to determine the effect of accumulating experience in the diagnostic performance of VI-RADS., Methods: In our previously published series 71 primary bladder cancer patients who underwent multiparametric MRI before the transurethral resection were analyzed. The radiologist who assessed the VI-RADS scores at the time the study was performed, re-evaluated all cases after 3 years, in a blinded fashion. During these three years, more than 300 additional bladder MRIs were performed for VI-RADS assessment. The diagnostic performances of the initial and subsequent VI-RADS analyses were compared. Moreover, VIRADS results obtained by a newly trained abdominal radiologist was also compared with experienced radiologist's results. For this study, VI-RADS ≥3 was accepted for predicting MIBC., Results: Overall 71 patients [62 (87.3 %) males, 67.4 ± 10.2 years] who underwent bladder MRI before TURBT were included. Histopathology revealed MIBC in 16 (26.2 %) cases. The initial MRI analysis revealed VI-RADS score ≥ 3 in 36 (50.7 %) cases. The sensitivity and specificity for depicting MIBC were 75 % and 56.4 % respectively. The subsequent MRI analysis revealed VI-RADS score ≥ 3 in 23 (32.4 %) cases. The sensitivity and specificity were 93.8 % and 85.5 % respectively. The MRI analysis performed by the recently trained abdominal radiologist revealed VI-RADS score ≥ 3 in 24 (33.8 %) cases. The sensitivity and specificity were 87.5 % and 56.4 % respectively., Conclusion: The diagnostic performance of VI-RADS for the interpretation of bladder MRI can improve over time by increasing the experience of the urogenital radiologist., Competing Interests: Declaration of competing interest The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Rationale and Objectives: To evaluate the potential of Synthetic Magnetic Resonance Imaging (SynMRI) in identifying muscular invasion in bladder cancer (BCa), and explore whether there is additional value in combination with the Vesical Imaging-Reporting and Data System (VI-RADS)., Methods: In this prospective single-center study, pathologically-confirmed BCa were enrolled between May 2023 and November 2023. All participants underwent preoperative multiparametric MRI, including T1/T2 weighted, SynMRI and diffusion-weighted imaging. T1/T2/PD values and apparent diffusion coefficient (ADC) values were compared between muscle invasive (MIBC) and non-invasive (NMIBC) groups. Receiver operating characteristic (ROC) analysis with the variables and their combination was performed to explore the performance of distinguishing the MIBC from NMIBC, and the ROC curves were compared using DeLong's test., Results: A total of 54 BCa patients were enrolled (38 males; NMIBC/MIBC=37/19) and all assessed with VI-RADS without dynamic enhanced imaging (DCE). Compared to NMIBC group, MIBC group had significantly larger diameter, higher VI-RADS score, lower T2 and ADC values (P < 0.05). VI-RADS score and T2 showed independent predictive value in differentiating NMIBC and MIBC. The combined model (T2 + VI-RADS+Diameter) resulted in significantly improved specificity (0.842), sensitivity (0.914), and AUC (0.943), in comparison to VI-RADS or ADC alone (P < 0.05)., Conclusion: T2 relaxation time can be easily obtained from SynMRI in routine clinical protocol and assist VI-RADS score system without DCE to improve differentiation performance in identifying NMIBC and MIBC., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Jinxia Guo is an employee of GE Healthcare but he had no control over the inclusion of any data or information that might have presented a conflict of interest. There are no actual or potential conflicts of interest to declare about this article. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Granulomatous prostatitis is a medical condition that may mimic prostate cancer., Purpose: Granulomatous prostatitis resulting from BCG-exposure can confound the diagnosis of prostate cancer based on prostate imaging and data system (PI-RADS) classification observed on multiparametric prostate magnetic resonance imaging (mpMRI)., Study Type, Population, Assessment and Statistical Tests: A cohort study was conducted, enrolling consecutive males at risk for prostate cancer who underwent an mpMRI-targeted prostate biopsy between February 2016 and August 2023. The focus of the study was on prior BCG-exposure as adjuvant treatment for non-muscle-invasive urothelial carcinoma within the 3 years prior the magnetic resonance imaging (MRI). Exclusion criteria were a prior androgen deprivation therapy, prostate surgery or radiation, and BCG-exposure occurring more than 3 years and less than 3 months before the MRI. Chi-square, logistic-regression, statistical association, and homogeneity tests were used., Results: Total 712 patients, 899 biopsied lesions (218 PI-RADS 3, 521 PI-RADS 4 and 160 PI-RADS 5) and 20 patients with 30 lesions within the BCG-exposed cohort. Chi-square and logistic-regression tests showed an association between PI-RADS with malignancy and significant tumor (ST), considering PI-RADS3 as the reference (OR: 4.9 [95% CI, 3.4-7.1] for PI-RADS4 and OR: 21.7 [95% CI, 12.4-37.8] for PI-RADS5 for malignancy, and OR: 5.3 [95% CI, 3.2-8.7] for PI-RADS4 and OR: 16.5 [95% CI, 9.4-28.9] for PI-RADS5 regarding ST). A statistically significant negative association was demonstrated between malignancy and ST with respect to BCG-exposure (OR: 0.15 [95% CI, 0.06-0.39] and OR: 0.39 [95% CI, 0.15-1.0], respectively). Statistically significant risk-difference for malignancy in patients nonexposed to BCG regarding those exposed was 45% (61.6% vs. 16.7%) for PI-RADS4, and 68.5% (90.7% vs. 22.2%) and 42.7% (64.9% vs. 22.2%) concerning malignancy and ST for PI-RADS5, respectively., Data Conclusions: Granulomatous prostate reaction caused by BCG-exposure acts as confounding factor for prostate MRI interpretation. The risk of malignancy and significant tumor on targeted biopsy to PI-RADS 3, 4 and 5 is notably lower in exposed patients., Competing Interests: Disclosure The authors have stated that they have no conflicts of interest., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: To assess the diagnostic performance of 18F-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomograpy (PET)/computed tomography (CT) in nodal staging before radical cystectomy (RC) and pelvic lymph node dissection (PLND) for bladder cancer (BCa)., Materials and Methods: This analysis was based on a cohort of 199 BCa patients undergoing RC and bilateral PLND between 2015 and 2022. Neoadjuvant chemotherapy (NAC) or immunotherapy (NAI) was administered after oncological evaluation. All patients received preoperative 18F-FDG PET/CT to assess extravesical disease. Point estimates for true negative, false negative, false positive, true positive, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy of conventional imaging and PET/CT were calculated. Subgroup analysis in patients receiving neoadjuvant treatment was performed., Results: At preoperative evaluation, 30 patients (15.1%) had 48 suspicious nodal spots on 18F-FDG PET/CT. At RC and bilateral PLND, a total of 4871 lymph nodes (LNs) were removed with 237 node metastases corresponding to 126 different regions. Pathological node metastases were found in 17/30 (57%) vs 39/169 patients (23%) with suspicious vs negative preoperative 18F-FDG PET/CT, respectively (sensitivity = 0.30, specificity = 0.91, PPV = 0.57, NPV = 0.77, accuracy = 0.74). On per-region analysis including 1367 nodal regions, LN involvement was found in 19/48 (39%) vs 105/1319 (8%) suspicious vs negative regions at PET/CT, respectively (sensitivity = 0.15, specificity = 0.98, PPV = 0.40, NPV = 0.92, ACC = 0.90). Similar results were observed for patients receiving NAC (n = 44, 32.1%) and NAI (n = 93, 67.9% [per-patient: sensitivity = 0.36, specificity = 0.91, PPV = 0.59, NPV = 0.80, accuracy = 0.77; per-region: sensitivity = 0.12, specificity = 0.98, PPV = 0.32, NPV = 0.93, ACC = 0.91]). Study limitations include its retrospective design and limited patient numbers., Conclusions: In eight out of 10 patients with negative preoperative 18F-FDG PET/CT, pN0 disease was confirmed at final pathology. No differences were found based on NAC vs NAI treatment. These findings suggest that 18F-FDG PET/CT could play a role in the preoperative evaluation of nodal metastases in BCa patients, although its cost-effectiveness is uncertain., (© 2024 The Authors. BJU International published by John Wiley & Sons Ltd on behalf of BJU International.)

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., (© 2023 International Society for Magnetic Resonance in Medicine.)

Purpose: An investigation of various convolutional neural network (CNN)-based deep learning algorithms was conducted to select the appropriate artificial intelligence (AI) model for calculating the diagnostic performance of bladder tumor classification on cystoscopy images, with the performance of the selected model to be compared against that of medical students and urologists. Methods: A total of 3,731 cystoscopic images that contained 2,191 tumor images were obtained from 543 bladder tumor cases and 219 normal cases were evaluated. A total of 17 CNN models were trained for tumor classification with various hyperparameters. The diagnostic performance of the selected AI model was compared with the results obtained from urologists and medical students by using the receiver operating characteristic (ROC) curve graph and metrics. Results: EfficientNetB0 was selected as the appropriate AI model. In the test results, EfficientNetB0 achieved a balanced accuracy of 81%, sensitivity of 88%, specificity of 74%, and an area under the curve (AUC) of 92%. In contrast, human-derived diagnostic statistics for the test data showed an average balanced accuracy of 75%, sensitivity of 94%, and specificity of 55%. Specifically, urologists had an average balanced accuracy of 91%, sensitivity of 95%, and specificity of 88%, while medical students had an average balanced accuracy of 69%, sensitivity of 94%, and specificity of 44%. Conclusions: Among the various AI models, we suggest that EfficientNetB0 is an appropriate AI classification model for determining the presence of bladder tumors in cystoscopic images. EfficientNetB0 showed the highest performance among several models and showed high accuracy and specificity compared to medical students. This AI technology will be helpful for less experienced urologists or nonurologists in making diagnoses. Image-based deep learning classifies bladder cancer using cystoscopy images and shows promise for generalized applications in biomedical image analysis and clinical decision making.

Competing Interests: Disclosure The authors have stated that they have no conflicts of interest.

Objective: To verify by retrospective analysis the performance of applying dual-parametric (T2 weighted image [T2WI] and diffusion weighted image [DWI]) and multi-parametric (T2WI, DWI, and dynamic contrast enhance [DCE]) evaluation systems of Vesical Imaging-Reporting and Data System (VI-RADS) in the magnetic resonance imaging (MRI) diagnosis of bladder cancer., Methods: The imaging and clinical data of bladder cancer patients who underwent bladder MRI examination in the Department of Urology of our hospital between January 2020 and December 2021 were collected. A total of 215 bladder cancer patients, among whom there were 183 males and 32 females with an average age of (67.60±11.42) years, were included. The bladder cancer diagnosis of all the cases was verified by pathology analysis of tissue samples. Two radiologists, who were double-blinded, scored multiple sequences separately. Then, a comparative analysis was made on the diagnostic performance of dual-parametric and multi-parametric VI-RADS diagnostic scores. The diagnostic test with receiver operator characteristic (ROC) curves and Cohen's Kappa were used to evaluate the diagnostic efficacy and consistency., Results: The area under the curve (AUC) and 95% confidence interval (CI) of the multi-parametric VI-RADS evaluation system by the two radiologists in the overall population were 0.878 (0.830-0.925) and 0.856 (0.805-0.907), while those for the bi-parametric VI-RADS evaluation system were 0.889 (0.844-0.934) and 0.856 (0.805-0.907), showing no statistically significant difference. No significant difference was observed in the subgroup analysis of patients who underwent transurethral resection of bladder tumor (TURBT). Furthermore, the Kappa values for inter-rater agreement between of the two radiologists were 0.694 and 0.546 (with the VI-RADS score≥3 defined as being positive) and 0.693 and 0.712 (with the VI-RADS score≥4 defined as being positive) in multi-parametric and bi-parametric evaluation, respectively (all P <0.001)., Conclusion: The bi-parametric VI-RADS scoring system can achieve a diagnostic efficacy comparable to that of the multi-parametric scoring system, offering an alternative to patients who are unable to undergo contrast-enhanced MRI due to allergic reaction to contrasts., Competing Interests: 利益冲突　所有作者均声明不存在利益冲突, (© 2024《四川大学学报（医学版）》编辑部 版权所有Copyright ©2024 Editorial Office of Journal of Sichuan University (Medical Sciences).)

The poor 5-year survival rate for bladder cancers is associated with the lack of efficient diagnostic and treatment techniques. Despite cystoscopy-assisted photomedicine and external radiation being promising modalities to supplement or replace surgery, they remain invasive or fail to provide real-time navigation. Here, we report non-invasive fractionated photodynamic therapy of bladder cancer with full-course real-time near-infrared-II imaging based on engineered X-ray-activated nanotransducers that contain lanthanide-doped nanoscintillators with concurrent emissions in visible and the second near-infrared regions and conjugated photosensitizers. Following intravesical instillation in mice with carcinogen-induced autochthonous bladder tumours, tumour-homing peptide-labelled nanotransducers realize enhanced tumour regression, robust recurrence inhibition, improved survival rates, and restored immune homeostasis under X-ray irradiation with accompanied near-infrared-II imaging. On-demand fractionated photodynamic therapy with customized doses is further achieved based on quantifiable near-infrared-II imaging signal-to-background ratios. Our study presents a promising non-invasive strategy to confront the current bladder cancer dilemma from diagnosis to treatment and prognosis., (© 2024. The Author(s).)

Objective: To evaluate the prediction value of Dual-energy CT (DECT)-based quantitative parameters and radiomics model in preoperatively predicting muscle invasion in bladder cancer (BCa)., Materials and Methods: A retrospective study was performed on 126 patients with BCa who underwent DECT urography (DECTU) in our hospital. Patients were randomly divided into training and test cohorts with a ratio of 7:3. Quantitative parameters derived from DECTU were identified through univariate and multivariate logistic regression analysis to construct a DECT model. Radiomics features were extracted from the 40, 70, 100 keV and iodine-based material-decomposition (IMD) images in the venous phase to construct radiomics models from individual and combined images using a support vector machine classifier, and the optimal performing model was chosen as the final radiomics model. Subsequently, a fusion model combining the DECT parameters and the radiomics model was established. The diagnostic performances of all three models were evaluated through receiver operating characteristic (ROC) curves and the clinical usefulness was estimated using decision curve analysis (DCA)., Results: The normalized iodine concentration (NIC) in DECT was an independent factor in diagnosing muscle invasion of BCa. The optimal multi-image radiomics model had predictive performance with an area-under-the-curve (AUC) of 0.867 in the test cohort, better than the AUC = 0.704 with NIC. The fusion model showed an increased level of performance, although the difference in AUC (0.893) was not statistically significant. Additionally, it demonstrated superior performance in DCA. For lesions smaller than 3 cm, the fusion model showed a high predictive capability, achieving an AUC value of 0.911. There was a slight improvement in model performance, although the difference was not statistically significant. This improvement was observed when comparing the AUC values of the DECT and radiomics models, which were 0.726 and 0.884, respectively., Conclusion: The proposed fusion model combing NIC and the optimal multi-image radiomics model in DECT showed good diagnostic capability in predicting muscle invasiveness of BCa., (© 2024. The Author(s).)

Residual nonvisible bladder cancer after proper treatment caused by technological and therapeutic limitations is responsible for tumor relapse and progression. This study aimed to demonstrate the feasibility of a solution for simultaneous detection and treatment of bladder cancer lesions smaller than one millimeter. The α5β1 integrin was identified as a specific marker in 81% of human high-grade nonmuscle invasive bladder cancers and used as a target for the delivery of targeted gold nanorods (GNRs). In a preclinical model of orthotopic bladder cancer expressing the α5β1 integrin, the photoacoustic imaging of targeted GNRs visualized lesions smaller than one millimeter, and their irradiation with continuous laser was used to induce GNR-assisted hyperthermia. Necrosis of the tumor mass, improved survival, and computational modeling were applied to demonstrate the efficacy and safety of this solution. Our study highlights the potential of the GNR-assisted theranostic strategy as a complementary solution in clinical practice to reduce the risk of nonvisible residual bladder cancer after current treatment. Further validation through clinical studies will support the findings of the present study., Competing Interests: Competing interests statement:F.C., A.C., M.A., I.L., E.A., M. Maturi, E.L., and M.C.F. are inventors of patents regarding GNRs functionalized with peptide Iso4.

Molecular imaging of muscle-invasive bladder cancer (MBC) is restricted to its locoregional and distant metastases, since most radiopharmaceuticals have a urinary excretion that limits the visualization of the primary tumor. 64 CuCl 2 , a positron-emitting radiotracer with nearly exclusive biliary elimination, could be well suited to exploring urinary tract neoplasms. In this study, we evaluated the feasibility of 64 CuCl 2 -based staging of patients with MBC; furthermore, we compared the diagnostic capability of this method with those of the current gold standards, that is, contrast-enhanced CT (ceCT) and 18 F-FDG PET/CT. Methods: We prospectively enrolled patients referred to our institution for pathology-confirmed MBC staging/restaging between September 2021 and January 2023. All patients underwent ceCT, 18 F-FDG, and 64 CuCl 2 PET/CT within 2 wk. Patient-based analysis and lesion-based analysis were performed for all of the potentially affected districts (overall, bladder wall, lymph nodes, skeleton, liver, lung, and pelvic soft tissue). Results: Forty-two patients (9 women) were enrolled. Thirty-six (86%) had evidence of disease, with a total of 353 disease sites. On patient-based analysis, ceCT and 64 CuCl 2 PET/CT showed higher sensitivity than 18 F-FDG PET/CT in detecting the primary tumor ( P < 0.001); moreover, 64 CuCl 2 PET/CT was slightly more sensitive than 18 F-FDG PET/CT in disclosing soft-tissue lesions ( P < 0.05). Both PET methods were more specific and accurate than ceCT in classifying nodal lesions ( P < 0.05). On lesion-based analysis, 64 CuCl 2 PET/CT outperformed 18 F-FDG PET/CT and ceCT in detecting disease localizations overall ( P < 0.001), in the lymph nodes ( P < 0.01), in the skeleton ( P < 0.001), and in the soft tissue ( P < 0.05). Conclusion: 64 CuCl 2 PET/CT appears to be a sensitive modality for staging/restaging of MBC and might represent a "one-stop shop" diagnostic method in these scenarios., (© 2024 by the Society of Nuclear Medicine and Molecular Imaging.)

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

Background/aim: Positron emission tomography (PET) is an important imaging modality, especially in oncology. [ 18 F]fluorodeoxyglucose PET (FDG-PET) is the most used cancer PET imaging. However, since the elevated glucose use by cancers, termed the Warburg effect, is usually only moderate, FDG often does not provide a strong or well-delineated signal. Malignancies have a stronger addiction to methionine, known as the Hoffman effect, and thus [ 11 C]methionine PET (MET-PET) has demonstrated superiority over FDG-PET in gliomas and other brain tumors. Our team is pioneering the use of MET-PET for tumors of the trunk for both better detection of cancer and to determine candidates for methionine-restriction therapy. The present study provides examples of cancers of organs in the trunk in which MET-PET outperforms FDG-PET in detecting and delineating primary and metastatic cancer., Patients and Methods: In all cases, MET-PET and FDG-PET were performed simultaneously. An evaluation of the images was conducted by a nuclear medicine physician., Results: Four cases, including prostate, bladder, esophageal, and breast cancer demonstrated the superiority of MET-PET compared to FDG-PET., Conclusion: MET-PET can out-perform FDG PET for accurate detection of primary and metastatic cancer in the trunk and can determine the extent of methionine addiction of cancer, thereby indicating whether cancer patients can benefit from methionine-restriction therapy., (Copyright © 2024 International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

Non-invasive screening for bladder cancer is crucial for treatment and postoperative follow-up. This study combines digital microfluidics (DMF) technology with fluorescence lifetime imaging microscopy (FLIM) for urine analysis and introduces a novel non-invasive bladder cancer screening technique. Initially, the DMF was utilized to perform preliminary screening and enrichment of urine exfoliated cells from 54 participants, followed by cell staining and FLIM analysis to assess the viscosity of the intracellular microenvironment. Subsequently, a deep learning residual convolutional neural network was employed to automatically classify FLIM images, achieving a three-class prediction of high-risk (malignant), low-risk (benign), and minimal risk (normal) categories. The results demonstrated a high consistency with pathological diagnosis, with an accuracy of 91% and a precision of 93%. Notably, the method is sensitive for both high-grade and low-grade bladder cancer cases. This highly accurate non-invasive screening method presents a promising approach for bladder cancer screening with significant clinical application potential., (© 2024 Wiley‐VCH GmbH.)

Rationale and Objectives: The role of Programmed death-ligand 1 (PD-L1) expression is crucial in guiding immunotherapy selection. This study aims to develop and evaluate a radiomic model, leveraging Computed Tomography (CT) imaging, with the objective of predicting PD-L1 expression status in patients afflicted with bladder cancer., Materials and Methods: The study encompassed 183 subjects diagnosed with histologically confirmed bladder cancer, among which the PD-L1(+) cohort constituted 60.1% of the total population. Stratified random sampling was utilized at a 7:3 ratio. We employed five diverse machine learning algorithms-Decision Tree, Random Forest, Linear Support Vector Classification, Support Vector Machine, and Logistic Regression-to establish radiomic models on the training dataset. These models endeavored to predict PD-L1 expression status premised on radiomic features derived from region-of-interest segmentation. Subsequent to this, the predictive performance of these models was examined on a validation set employing the receiver operating characteristic (ROC) curve. The DeLong test was utilized to contrast ROC curves, thereby pinpointing the model with superior predictive accuracy., Results: 16 features were chosen for the model construction. All five models revealed strong performance in the training set (AUC, 0.920-1) and commendable predictive ability in the validation set (AUC, 0.753-0.766). As per the DeLong test, no statistically significant disparities were observed among any of the models (P > 0.05) in the validation set. Additional verification through the calibration curve and decision curve analysis indicated that the Logistic Regression model exhibited extraordinary precision and practicality., Conclusion: Our machine learning model, grounded on radiomic features, demonstrated its proficiency in accurately distinguishing bladder cancer patients with high PD-L1 expression. Future research, incorporating more exhaustive datasets, could potentially augment the predictive efficiency of radiomic algorithms, thereby advancing their clinical utility., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Objective: Limited data exist on the frequency with which clinical progression during neoadjuvant chemotherapy (NAC) for muscle-invasive bladder cancer (MIBC) impacts eligibility for a vaginal-sparing surgical approach or on the utility of interim imaging assessment. We sought to evaluate the incidence of clinical upstaging following NAC that would render a patient ineligible for a vaginal-sparing cystectomy., Methods: Eighty-nine female patients with non-metastatic MIBC treated with NAC and radical cystectomy (RC) (2012-2023) were retrospectively reviewed. Tumor location(s) was determined from transurethral resection of bladder tumor operative reports. Pre- and post-NAC clinical staging was determined from imaging. Outcomes of interest included clinical upstaging and upstaging to vaginal invasion after NAC., Results: 75/89 patients had pre- and post-NAC imaging. Fifty-five had no change in clinical staging, 6 patients were upstaged (4 cT2→cT3, 2 cT3→cT4), and 14 patients were downstaged (13 cT3→cT2, 1 cT4→cT2). Of the 75 patients with pre- and post-NAC imaging, 39 had trigone tumors. Of these, 28 had no change in clinical staging, 2 were upstaged (1 cT2→cT3, 1 cT3→cT4) and 9 were downstaged (8 cT3→cT2, 1 cT4→cT2). Overall, 6/75 (8%) of patients demonstrated clinical upstaging after NAC. 2/39 (5%) of patients with trigone tumors clinically progressed after NAC and both had vaginal invasion (pT4) on final pathology., Conclusion: Although clinical upstaging after NAC was infrequent, 5% of patients with trigonal MIBC were rendered ineligible for vaginal-sparing cystectomy following NAC due to progression. Interim imaging assessment may identify non-responders and preserve eligibility for vaginal-sparing RC., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Conventional magnetic resonance imaging (MRI) has certain limitations in distinguishing between malignant and benign urinary bladder (UB) lesions. Amide proton transfer (APT) imaging may provide more diagnostic information than diffusion-weighted imaging (DWI) to distinguish between malignant and benign UB., Purpose: To investigate the potential of APT imaging in the diagnosis of malignant and benign UB lesions and to compare its diagnostic efficacy with that of conventional DWI., Study Type: Prospective., Subjects: Eighty patients with UB lesions., Field Strength/sequence: A 3.0 T/turbo spin echo (TSE) T1-weighted and T2-weighted imaging, single-shot echo planar DWI, and three-dimensional TSE APT imaging., Assessment: Patients underwent radical cystectomy or transurethral resection of the bladder lesions within 2 weeks after CT urography and MRI examination. APT signal intensity in UB lesions was quantified by the asymmetric magnetization transfer ratio (MTR asym ). MTR asym and apparent diffusion coefficient (ADC) values were measured and compared between malignant and benign UB lesions., Statistical Tests: Kolmogorov-Smirnov test, Student's t test or Mann-Whitney U test, Spearman rank correlation coefficient, area under the receiver operating characteristic (ROC) curve (AUC), Delong test, and intraclass correlation coefficient (ICC). The significance threshold was set at P < 0.05., Results: Thirty-two patients had pathologically confirmed benign UB lesions, including 2 bladder leiomyomas, 1 submucosal amyloidosis, 1 inflammatory myofibroblastic tumor, and 28 inflammatory lesions, and 48 patients had pathologically confirmed urothelial carcinoma. Urothelial carcinomas showed significantly higher MTR asym values (1.53% [0.74%] vs. 0.85% [0.23%]) and significantly lower ADC values (1.24 ± 0.34 × 10 -3  mm 2 /s vs. 1.43 ± 0.22 × 10 -3  mm 2 /s) than benign UB lesions. The MTR asym value (AUC = 0.928) was significantly better in differentiating urothelial carcinoma from benign UB lesions than the ADC value (AUC = 0.722)., Data Conclusion: APT imaging may have value in discriminating malignant from benign UB lesions and has better diagnostic performance than DWI., Level of Evidence: 3 TECHNICAL EFFICACY: Stage 2., (© 2024 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Bladder cancer treatment decisions hinge on detecting muscle invasion. The 2018 "Vesical Imaging Reporting and Data System" (VI-RADS) standardizes multiparametric MRI (mp-MRI) use. Radiomics, an analysis framework, provides more insightful information than conventional methods., Purpose: To determine how well MIBC (Muscle Invasive Bladder Cancer) and NMIBC (Non-Muscle Invasive Bladder Cancer) can be distinguished using mp-MRI radiomics features., Methods: We conducted a study with 73 bladder cancer patients diagnosed pathologically, who underwent preoperative mp-MRI from January 2020 to July 2022. Utilizing 3D Slicer (version 4.8.1) and Pyradiomics, we manually extracted radiomic features from apparent diffusion coefficient (ADC) maps created from diffusion-weighted imaging. The LASSO approach identified optimal features, and we addressed sample imbalance using SMOTE. We developed a classification model using textural features alone or combined with VI-RADS, employing a random forest classifier with 10-fold cross-validation. Diagnostic performance was assessed using the area under the ROC curve analysis., Results: Among 73 patients (63 men, 10 women; median age: 63 years), 41 had muscle-invasive and 32 had superficial bladder cancer. Muscle invasion was observed in 25 of 41 patients with VI-RADS 4 and 5 scores and 12 of 32 patients with VI-RADS 1, 2, and 3 scores (accuracy: 77.5%, sensitivity: 67.7%, specificity: 88.8%). The combined VI-RADS score and radiomics model (AUC = 0.92 ± 0.12) outperformed the single radiomics model using ADC MRI (AUC = 0.83 ± 0.22 with 10-fold cross-validation) in this dataset., Conclusion: Before undergoing surgery, bladder cancer invasion in muscle might potentially be predicted using a radiomics signature based on mp-MRI., (© 2024. Society of Surgical Oncology.)

Background: Vesical Imaging-Reporting and Data System (VI-RADS) is a pathway for the standardized imaging and reporting of bladder cancer staging using multiparametric (mp) MRI., Purpose: To investigate additional role of morphological (MOR) measurements to VI-RADS for the detection of muscle-invasive bladder cancer (MIBC) with mpMRI., Study Type: Retrospective., Population: A total of 198 patients (72 MIBC and 126 NMIBC) underwent bladder mpMRI was included., Field Strength/sequence: 3.0 T/T2-weighted imaging with fast-spin-echo sequence, spin-echo-planar diffusion-weighted imaging and dynamic contrast-enhanced imaging with fast 3D gradient-echo sequence., Assessment: VI-RADS score and MOR measurement including tumor location, number, stalk, cauliflower-like surface, type of tumor growth, tumor-muscle contact margin (TCM), tumor-longitudinal length (TLL), and tumor cellularity index (TCI) were analyzed by three uroradiologists (3-year, 8-year, and 15-year experience of bladder MRI, respectively) who were blinded to histopathology., Statistical Tests: Significant MOR measurements associated with MIBC were tested by univariable and multivariable logistic regression (LR) analysis with odds ratio (OR). Area under receiver operating characteristic curve (AUC) with DeLong's test and decision curve analysis (DCA) were used to compared the performance of unadjusted vs. adjusted VI-RADS. A P-value <0.05 was considered statistically significant., Results: TCM (OR 9.98; 95% confidence interval [CI] 4.77-20.8), TCI (OR 5.72; 95% CI 2.37-13.8), and TLL (OR 3.35; 95% CI 1.40-8.03) were independently associated with MIBC at multivariable LR analysis. VI-RADS adjusted by three MORs achieved significantly higher AUC (reader 1 0.908 vs. 0.798; reader 2 0.906 vs. 0.855; reader 3 0.907 vs. 0.831) and better clinical benefits than unadjusted VI-RADS at DCA. Specially in VI-RADS-defined equivocal lesions, MOR-based adjustment resulted in 55.5% (25/45), 70.4% (38/54), and 46.4% (26/56) improvement in accuracy for discriminating MIBC in three readers, respectively., Data Conclusion: MOR measurements improved the performance of VI-RADS in detecting MIBC with mpMRI, especially for equivocal lesions., Level of Evidence: 3 TECHNICAL EFFICACY: Stage 2., (© 2024 International Society for Magnetic Resonance in Medicine.)

Background: Predicting the accurate preoperative staging of bladder cancer (BLCA), which markedly affects treatment decisions and patient outcomes, using traditional clinical parameters is challenging. Nevertheless, emerging studies in radiomics, especially machine learning-based computed tomography (CT) image-based radiomics, hold promise in improving stage prediction accuracy in various tumors. However, the comparative performance and clinical utility of models for BLCA are under investigation., Purpose: We aimed to investigate the application value of machine learning-based CT radiomics in preoperative staging prediction by comparing the performance of clinical, radiomics, and clinical-radiomics combined models., Methods: A retrospective cohort of 105 patients with initial BLCA was randomized into training (70%) and testing (30%) cohorts. Radiomics features were extracted from CT images using the optimal feature filter, followed by the application of the least absolute shrinkage and selection operator algorithm for optimum feature selection. Furthermore, machine learning algorithms were used to establish a radiomics model within the training cohort. Independent risk factors for muscle-invasive BLCA (MIBC) obtained by multivariate logistic regression (LR) analysis were separately used to construct a clinical model. For a clinical-radiomics fusion model, radiomics features were combined with clinical parameters. Performance was evaluated based on receiver operating characteristic curves, calibration curves, decision curve analysis (DCA), and standard performance metrics., Results: Patients exhibited a significantly higher age (p = 0.029), larger tumor size (p = 0.01), and an increased neutrophil-to-lymphocyte ratio (NLR; p = 0.045) in the MIBC group than in the NMIBC group. LR analysis revealed age (p = 0.026), tumor size (p = 0.007), and NLR (p = 0.019) as significant predictors for constructing the clinical model. In the testing cohort, the radiomics model, which used an Support Vector Machine classifier, achieved the highest area under the curve (AUC) value of 0.857. The clinical-radiomics model outperformed the remaining two models, with AUC values of 0.958 and 0.893 in the training and testing cohorts, respectively. DeLong's test indicated significant differences between the three models. Calibration curves showed good agreement, and DCA confirmed the superior clinical utility of the clinical-radiomics model., Conclusions: Machine learning-based CT radiomics combined with clinical parameters was a promising approach in staging BLCA accurately, which outperformed the individual models. Integrating radiomics features with clinical information holds the potential to improve personalized treatment planning and patient outcomes in BLCA., (© 2024 American Association of Physicists in Medicine.)

Bladder cancer (BC) represents a significant global health challenge with notable incidence and mortality rates. Despite treatment advancements, its management remains complex, requiring a multidisciplinary approach. Imaging techniques play a pivotal role in diagnosis, staging, and treatment planning by aiding lesion localization, differentiation, and assessment of tumor extent. Primary modalities like computed tomography and MRI offer detailed anatomic insights. Imaging provides valuable insights into tumor biology, vascular patterns, and molecular profiles, enabling personalized medicine strategies to optimize therapeutic efficacy and minimize adverse effects, crucial for improving BC management and prognosis., Competing Interests: Disclosures F. Alessandrino–Subinvestigator, Ascelia Pharma. B. Dabiri, H. Amirian and F.B. Franco have nothing to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Objective: To investigate the effect of radiomics models obtained from dual-energy CT (DECT) material decomposition images and virtual monoenergetic images (VMIs) in predicting the pathological grading of bladder urothelial carcinoma (BUC)., Materials and Methods: A retrospective analysis of preoperative DECT examination was conducted on 112 patients diagnosed with BUC. This cohort included 76 cases of high-grade urothelial carcinoma and 36 cases of low-grade urothelial carcinoma. DECT can provide material decomposition images of venous phase Iodine maps and Water maps based on the differences in attenuation of substances, as well as VMIs at 40 to 140 keV (interval 10 keV). A total of 13 image sets were obtained, and radiomics features were extracted and analyzed from each set to achieve preoperative prediction of BUC. The best features related to BUC were identified by recursive feature elimination (RFE), the Minimum Redundancy Maximum Relevance (mRMR), and the Least Absolute Shrinkage and Selection Operator (LASSO) in order. A five-fold cross-validation method was used to divide the samples into training and testing sets, and models for pathological prediction of BUC grading were constructed by a random forest (RF) classifier. Receiver operating curves (ROC) were plotted to evaluate the performance of 13 models obtained from each image set., Results: Despite the notable differences in the best radiomics features chosen from each image set, all the features selected from 40 to 100 keV VMIs included the Dependence Variance of the GLDM feature set. There were no statistically significant differences in the area under the curve (AUC) between the training set and the testing set for all 13 models. In the testing set, the AUCs of the models established through 40 keV to 140 keV (interval of 10 keV) image sets were 0.895, 0.874, 0.855, 0.889, 0.841, 0.868, 0.852, 0.847, 0.889, 0.887 and 0.863 respectively. The AUCs for the models established using the Iodine maps and Water maps image sets were 0.873 and 0.852, respectively., Conclusion: Despite the differences in the selected radiomic features from DECT multi-parameter images, the performance of radiomics models in predicting the pathological grading of BUC was not affected by the variations in the types of images used for model training., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The human epidermal growth factor receptor 2 (HER2) has recently emerged as hotspot in targeted therapy for urothelial bladder cancer (UBC). The HER2 status is mainly identified by immunohistochemistry (IHC), preoperative and noninvasive methods for determining HER2 status in UBC remain in searching., Purposes: To investigate whether radiomics features extracted from MRI using machine learning algorithms can noninvasively evaluate the HER2 status in UBC., Study Type: Retrospective., Population: One hundred ninety-five patients (age: 68.7 ± 10.5 years) with 14.3% females from January 2019 to May 2023 were divided into training (N = 156) and validation (N = 39) cohorts, and 43 patients (age: 67.1 ± 13.1 years) with 13.9% females from June 2023 to January 2024 constituted the test cohort (N = 43)., Field Strength/sequence: 3 T, T2-weighted imaging (turbo spin-echo), diffusion-weighted imaging (breathing-free spin echo)., Assessment: The HER2 status were assessed by IHC. Radiomics features were extracted from MRI images. Pearson correlation coefficient and the least absolute shrinkage and selection operator (LASSO) were applied for feature selection, and six machine learning models were established with optimal features to identify the HER2 status in UBC., Statistical Tests: Mann-Whitney U-test, chi-square test, LASSO algorithm, receiver operating characteristic analysis, and DeLong test., Results: Three thousand forty-five radiomics features were extracted from each lesion, and 22 features were retained for analysis. The Support Vector Machine model demonstrated the best performance, with an AUC of 0.929 (95% CI: 0.888-0.970) and accuracy of 0.859 in the training cohort, AUC of 0.886 (95% CI: 0.780-0.993) and accuracy of 0.846 in the validation cohort, and AUC of 0.712 (95% CI: 0.535-0.889) and accuracy of 0.744 in the test cohort., Data Conclusion: MRI-based radiomics features combining machine learning algorithm provide a promising approach to assess HER2 status in UBC noninvasively and preoperatively., Evidence Level: 2 TECHNICAL EFFICACY: Stage 3., (© 2024 International Society for Magnetic Resonance in Medicine.)

Purpose: This study investigated radiologic features on preoperative MRI to differentiate urothelial carcinoma with squamous differentiation (UCSD) from conventional urothelial carcinoma (UC) in muscle-invasive bladder carcinoma., Methods: Ninety-nine patients who underwent radical cystectomy and a preoperative bladder MRI scan within three months before surgery were retrospectively enrolled. Various MRI features, including tumor length, location, multiplicity, long-to-short axis ratio, morphology, radiologic stage, and degree of severe necrosis, were analyzed. Univariable and multivariable logistic regression analyses were performed to identify MRI features predictive of UCSD. The diagnostic performance of a significant MRI feature was assessed using 5-fold cross-validation., Results: Among the MRI features, significant radiologic findings associated with UCSD in the univariable analysis included heterogeneous tumor signal intensity in T2-weighted images (odds ratio [OR], 3.365; 95% confidence interval [CI], 1.213-9.986; P = 0.022) and contrast-enhanced T1-weighted images (OR, 4.428; 95% CI, 1.519-12.730; P = 0.007), as well as marked (≥ 50%) severe necrosis (OR, 17.100; 95% CI, 4.699-73.563; P < 0.001). In the multivariable analysis, marked (≥ 50%) severe necrosis (odds ratio [OR], 13.755; 95% confidence interval [CI], 2.796-89.118; P = 0.004) was a significant predictor of UCSD. Marked (≥ 50%) severe necrosis showed a high specificity of 95.0% with a precision of 65.0% for diagnosing UCSD based on 5-fold cross-validation., Conclusion: Preoperative bladder MRI revealing marked severe necrosis may be indicative of UCSD and can assist in distinguishing it from conventional UC., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objectives: To systematically assess the current available literature concerning advanced optical imaging methods for the detection and diagnosis of bladder cancer (BCa), focusing particularly on the sensitivity and specificity of these techniques., Methods: First a scoping search was performed to identify all available optical techniques for BCa detection and diagnosis. The optical imaging techniques used for detecting BCa are: the Storz professional image enhancement system (IMAGE1 S), narrow-band imaging (NBI), photoacoustic imaging (PAI), autofluorescence imaging (AFI), photodynamic diagnosis (PDD), and scanning fibre endoscopy (SFE). The staging and grading techniques for BCa are: optical coherence tomography (OCT), confocal laser endomicroscopy (CLE), Raman spectroscopy, endocytoscopy, and non-linear optical microscopy (NLO). Then a systematic literature search was conducted using MEDLINE, EMBASE and Web of Science from inception to 21 November 2023. Articles were screened and selected by two independent reviewers. Inclusion criteria were: reporting on both the sensitivity and specificity of a particular technique and comparison to histopathology, and in the case of a detection technique comparison to white light cystoscopy (WLC)., Results: Out of 6707 articles, 189 underwent full-text review, resulting in 52 inclusions. No articles met criteria for IMAGE1 S, PAI, SFE, Raman spectroscopy, and endocytoscopy. All detection techniques showed higher sensitivity than WLC, with NBI leading (87.8-100%). Overall, detection technique specificity was comparable to WLC, with PDD being most specific (23.3-100%). CLE and OCT varied in sensitivity and specificity, with OCT showing higher specificity for BCa diagnosis, notably for carcinoma in situ (97-99%) compared to CLE (62.5-81.3%). NLO demonstrated high sensitivity and specificity (90-97% and 77-100%, respectively) based on limited data from two small ex vivo studies., Conclusions: Optical techniques with the most potential are PDD for detecting and OCT for staging and grading BCa. Further research is crucial to validate their integration into routine practice and explore the value of other imaging techniques., (© 2024 The Author(s). BJU International published by John Wiley & Sons Ltd on behalf of BJU International.)

The Vesical Imaging-Reporting and Data System (VI-RADS) is a standard magnetic resonance imaging (MRI) and diagnostic method for muscle-invasive bladder cancer that was published in 2018. Several studies have demonstrated that VI-RADS has high diagnostic power and reproducibility. However, reading VI-RADS requires a certain amount of expertise, and radiologists need to be aware of the various pitfalls. MRI of the bladder includes T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and dynamic contrast-enhanced imaging (DCEI). T2WI is excellent for understanding anatomy. DWI and DCEI show high contrast between the tumor and normal anatomical structures and are suitable for staging local tumors. Bladder tumors are classified into five categories according to their size and morphology and their positional relationship to the bladder wall based on the VI-RADS diagnostic criteria. If the T2WI, DWI, and DCEI categories are the same, the category is the VI-RADS category. If the categories do not match, the DWI category is the VI-RADS category. If image quality of DWI is not evaluable, the DCEI category is the final category. In many cases, DWI is dominant, but this does not mean that T2WI and DCEI can be omitted from the reading of the bladder. In this educational review, typical and atypical teaching cases are demonstrated, and how to resolve misdiagnosis and the limitations of VI-RADS are discussed. The most important aspect of VI-RADS reading is to practice multiparametric reading with a solid understanding of the characteristics and role of each sequence and an awareness of the various pitfalls., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Sarcomatoid urothelial carcinoma (SUC) is a rare and highly malignant form of bladder cancer with a poor prognosis. Currently, there is limited information on the imaging features of bladder SUC and reliable indicators for distinguishing it from conventional urothelial carcinoma (CUC). The objective of our study was to identify the unique imaging characteristics of bladder SUC and determine factors that aid in its differential diagnosis., Materials and Methods: This retrospective study enrolled 22 participants with bladder SUC and 61 participants with CUC. The clinical, pathologic, and CT/MRI data from both groups were recorded, and a comparison was conducted using univariate analysis and multinomial logistic regression for distinguishing SUC from CUC., Results: The majority of SUCs were located in the trigone of the bladder and exhibited large tumor size, irregular shape, low ADC values, Vesical Imaging-Reporting and Data System (VI-RADS) score ≥ 4, the presence of necrosis, and an invasive nature. Univariate analysis revealed significant differences in terms of tumor location, shape, the maximum long-axis diameter (LAD), the short-axis diameter (SAD), ADC-value, VI-RADS scores, necrosis, extravesical extension (EVE), pelvic peritoneal spread (PPS), and hydronephrosis/ureteral effusion (p < .001 ~ p = .037) between SUCs and CUCs. Multinomial logistic regression found that only SAD (p = .014) and necrosis (p = .003) emerged as independent predictors for differentiating between SUC and CUC. The model based on these two factors achieved an area under curve (AUC) of 0.849 in ROC curve analysis., Conclusion: Bladder SUC demonstrates several distinct imaging features, including a high incidence of trigone involvement, large tumor size, and obvious invasiveness accompanied by necrosis. A bladder tumor with a large SAD and evidence of necrosis is more likely to be SUC rather than CUC., (© 2024. The Author(s).)

Background: Transurethral resection of bladder tumour has been the mainstay of bladder cancer staging for > 60 years. Staging inaccuracies are commonplace, leading to delayed treatment of muscle-invasive bladder cancer. Multiparametric magnetic resonance imaging offers rapid, accurate and non-invasive staging of muscle-invasive bladder cancer, potentially reducing delays to radical treatment., Objectives: To assess the feasibility and efficacy of the introducing multiparametric magnetic resonance imaging ahead of transurethral resection of bladder tumour in the staging of suspected muscle-invasive bladder cancer., Design: Open-label, multistage randomised controlled study in three parts: feasibility, intermediate and final clinical stages. The COVID pandemic prevented completion of the final stage., Setting: Fifteen UK hospitals., Participants: Newly diagnosed bladder cancer patients of age ≥ 18 years., Interventions: Participants were randomised to Pathway 1 or 2 following visual assessment of the suspicion of non-muscle-invasive bladder cancer or muscle-invasive bladder cancer at the time of outpatient cystoscopy, based upon a 5-point Likert scale: Likert 1-2 tumours considered probable non-muscle-invasive bladder cancer; Likert 3-5 possible muscle-invasive bladder cancer. In Pathway 1, all participants underwent transurethral resection of bladder tumour. In Pathway 2, probable non-muscle-invasive bladder cancer participants underwent transurethral resection of bladder tumour, and possible muscle-invasive bladder cancer participants underwent initial multiparametric magnetic resonance imaging. Subsequent therapy was determined by the treating team and could include transurethral resection of bladder tumour., Main Outcome Measures: Feasibility stage: proportion with possible muscle-invasive bladder cancer randomised to Pathway 2 which correctly followed the protocol. Intermediate stage: time to correct treatment for muscle-invasive bladder cancer., Results: Between 31 May 2018 and 31 December 2021, of 638 patients approached, 143 participants were randomised; 52.1% were deemed as possible muscle-invasive bladder cancer and 47.9% probable non-muscle-invasive bladder cancer. Feasibility stage: 36/39 [92% (95% confidence interval 79 to 98%)] muscle-invasive bladder cancer participants followed the correct treatment by pathway. Intermediate stage: median time to correct treatment was 98 (95% confidence interval 72 to 125) days for Pathway 1 versus 53 (95% confidence interval 20 to 89) days for Pathway 2 [hazard ratio 2.9 (95% confidence interval 1.0 to 8.1)], p = 0.040. Median time to correct treatment for all participants was 37 days for Pathway 1 and 25 days for Pathway 2 [hazard ratio 1.4 (95% confidence interval 0.9 to 2.0)]., Limitations: For participants who underwent chemotherapy, radiotherapy or palliation for multiparametric magnetic resonance imaging-diagnosed stage T2 or higher disease, it was impossible to conclusively know whether these were correct treatments due to the absence of histopathologically confirmed muscle invasion, this being confirmed radiologically in these cases. All patients had histological confirmation of their cancers. Due to the COVID-19 pandemic, we were unable to realise the final stage., Conclusion: The multiparametric magnetic resonance imaging-directed pathway led to a substantial 45-day reduction in time to correct treatment for muscle-invasive bladder cancer, without detriment to non-muscle-invasive bladder cancer participants. Consideration should be given to the incorporation of multiparametric magnetic resonance imaging ahead of transurethral resection of bladder tumour into the standard pathway for all patients with suspected muscle-invasive bladder cancer. The improved decision-making accelerated time to treatment, even though many patients subsequently needed transurethral resection of bladder tumour. A proportion of patients can avoid transurethral resection of bladder tumour completely, reducing costs and morbidity, given the much lower cost of magnetic resonance imaging and biopsy compared to transurethral resection of bladder tumour., Future Work: Further work to cross-correlate with the recently developed Vesical Imaging-Reporting and Data System will improve accuracy and aid dissemination. Longer follow-up to examine the effect of the pathway on outcomes is also required. Incorporation of liquid deoxyribonucleic acid-based biomarkers may further improve the quality of decision-making and should also be investigated further., Study Registration: This study is registered as ISRCTN 35296862., Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR135775) and is published in full in Health Technology Assessment ; Vol. 28, No. 42. See the NIHR Funding and Awards website for further award information.

Rationale and Objectives: This study explored the clinical value of dual time-point 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography (PET) imaging for differentiating lymph node metastasis from lymph nodes with reactive hyperplasia., Methods: 250 lymph nodes from 153 bladder cancer patients who underwent 18 F-FDG PET/computed tomography (CT) delayed diuretic imaging were analyzed. The maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), metabolic tumor volume (MTV), and related delay indices before and after PET delayed imaging were obtained. Relationships with outcomes were analyzed using nonparametric and multivariate analyses. Receiver operating characteristic curves and nomograms were drawn to predict lymph node metastasis., Results: Delayed PET/CT imaging showed better detection of hyperplasia and metastatic lymph nodes. Delayed imaging with a cutoff SUVmax of 2.0 or 2.5 increased the detection rate of metastatic lymph nodes by 4.1%, and 6.9%, respectively. Delayed imaging often showed speckle-like radioactive foci in lymph nodes with reactive hyperplasia and increased FDG uptake throughout the nodes in metastatic lymph nodes. The lymph node short-axis diameter, SUVmean, and delayed index of MTV (DIMTV) were independent predictors for differentiating metastatic lymph nodes from reactive hyperplasia, and their combination showed better differentiation performance than the individual predictors. In high-risk patients, the probability of lymph node metastasis was as high as 97.6%., Conclusion: Dual time-point imaging can detect more metastatic lymph nodes. Some lymph nodes with hyperplasia show speckle-like radioactive foci on delayed imaging. The lymph node short-axis diameter, SUVmean, and DIMTV are three important parameters for predicting lymph node metastasis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

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 (ADC SD ). 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 ADC SD 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 ADC SD 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., (© 2023 International Society for Magnetic Resonance in Medicine.)

Bladder cancer (BC), predominantly comprising urothelial carcinomas (UCs), ranks as the tenth most common cancer worldwide. UCs with variant histology (variant UC), including squamous differentiation, glandular differentiation, plasmacytoid variant, micropapillary variant, sarcomatoid variant, and nested variant, accounting for 5-10% of cases, exhibit more aggressive and advanced tumor characteristics compared to pure UC. The Vesical Imaging-Reporting and Data System (VI-RADS), established in 2018, provides guidelines for the preoperative evaluation of muscle-invasive bladder cancer (MIBC) using multiparametric magnetic resonance imaging (mpMRI). This technique integrates T2-weighted imaging (T2WI), dynamic contrast-enhanced (DCE)-MRI, and diffusion-weighted imaging (DWI) to distinguish MIBC from non-muscle-invasive bladder cancer (NMIBC). VI-RADS has demonstrated high diagnostic performance in differentiating these two categories for pure UC. However, its accuracy in detecting muscle invasion in variant UCs is currently under investigation. These variant UCs are associated with a higher likelihood of disease recurrence and require precise preoperative assessment and immediate surgical intervention. This review highlights the potential value of mpMRI for different variant UCs and explores the clinical implications and prospects of VI-RADS in managing these patients, emphasizing the need for careful interpretation of mpMRI examinations including DCE-MRI, particularly given the heterogeneity and aggressive nature of variant UCs. Additionally, the review addresses the fundamental MRI reading procedures, discusses potential causes of diagnostic errors, and considers future directions in the use of artificial intelligence and radiomics to further optimize the bladder MRI protocol., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The diagnostic accuracy of cystoscopy varies according to the knowledge and experience of the performing physician. In this study, we evaluated the difference in cystoscopic gaze location patterns between medical students and urologists and assessed the differences in their eye movements when simultaneously observing conventional cystoscopic images and images with lesions detected by artificial intelligence (AI). Methodology: Eye-tracking measurements were performed, and observation patterns of participants (24 medical students and 10 urologists) viewing images from routine cystoscopic videos were analyzed. The cystoscopic video was captured preoperatively in a case of initial-onset noninvasive bladder cancer with three low-lying papillary tumors in the posterior, anterior, and neck areas (urothelial carcinoma, high grade, and pTa). The viewpoint coordinates and stop times during observation were obtained using a noncontact type of gaze tracking and gaze measurement system for screen-based gaze tracking. In addition, observation patterns of medical students and urologists during parallel observation of conventional cystoscopic videos and AI-assisted lesion detection videos were compared. Results: Compared with medical students, urologists exhibited a significantly higher degree of stationary gaze entropy when viewing cystoscopic images ( p  < 0.05), suggesting that urologists with expertise in identifying lesions efficiently observed a broader range of bladder mucosal surfaces on the screen, presumably with the conscious intent of identifying pathologic changes. When the participants observed conventional and AI-assisted lesion detection images side by side, contrary to urologists, medical students showed a higher proportion of attention directed toward AI-detected lesion images. Conclusion: Eye-tracking measurements during cystoscopic image assessment revealed that experienced specialists efficiently observed a wide range of video screens during cystoscopy. In addition, this study revealed how lesion images detected by AI are viewed. Observation patterns of observers' gaze may have implications for assessing and improving proficiency and serving educational purposes. To the best of our knowledge, this is the first study to utilize eye tracking in cystoscopy. University of Tsukuba Hospital, clinical research reference number R02-122.

Achieving accurate bladder wall and tumor segmentation from MRI is critical for diagnosing and treating bladder cancer. However, automated segmentation remains challenging due to factors such as comparable density distributions, intricate tumor morphologies, and unclear boundaries. Considering the attributes of bladder MRI images, we propose an efficient multiscale hierarchical hybrid attention with a transformer (MH2AFormer) for bladder cancer and wall segmentation. Specifically, a multiscale hybrid attention and transformer (MHAT) module in the encoder is designed to adaptively extract and aggregate multiscale hybrid feature representations from the input image. In the decoder stage, we devise a multiscale hybrid attention (MHA) module to generate high-quality segmentation results from multiscale hybrid features. Combining these modules enhances the feature representation and guides the model to focus on tumor and wall regions, which helps to solve bladder image segmentation challenges. Moreover, MHAT utilizes the Fast Fourier Transformer with a large kernel (e.g., 224 × 224) to model global feature relationships while reducing computational complexity in the encoding stage. The model performance was evaluated on two datasets. As a result, the model achieves relatively best results regarding the intersection over union (IoU) and dice similarity coefficient (DSC) on both datasets (Dataset A: IoU = 80.26%, DSC = 88.20%; Dataset B: IoU = 89.74%, DSC = 94.48%). These advantageous outcomes substantiate the practical utility of our approach, highlighting its potential to alleviate the workload of radiologists when applied in clinical settings.

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 mm 2 /s vs. 1.02 × 10 -3 mm 2 /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., (© 2024. The Author(s).)

Accurate segmentation of the tumor area is crucial for the treatment and prognosis of patients with bladder cancer. Cystoscopy is the gold standard for diagnosing bladder tumors. However, The vast majority of current work uses deep learning to identify and segment tumors from CT and MRI findings, and rarely involves cystoscopy findings. Accurately segmenting bladder tumors remains a great challenge due to their diverse morphology and fuzzy boundaries. In order to solve the above problems, this paper proposes a medical image segmentation network with boundary guidance called boundary guidance network. This network combines local features extracted by CNNs and long-range dependencies between different levels inscribed by Parallel ViT, which can capture tumor features more effectively. The Boundary extracted module is designed to extract boundary features and utilize the boundary features to guide the decoding process. Foreground-background dual-channel decoding is performed by boundary integrated module. Experimental results on our proposed new cystoscopic bladder tumor dataset (BTD) show that our method can efficiently perform accurate segmentation of tumors and retain more boundary information, achieving an IoU score of 91.3%, a Hausdorff Distance of 10.43, an mAP score of 85.3%, and a F1 score of 94.8%. On BTD and three other public datasets, our model achieves the best scores compared to state-of-the-art methods, which proves the effectiveness of our model for common medical image segmentation., (© 2024. The Author(s).)

Purpose: Our purpose was to evaluate the prognostic value of Vesical Imaging Reporting and Data System (VI-RADS) in bladder cancer (BCa) staging and predicting recurrence or progression., Methods: We retrospectively analyzed the prospectively collected data from 96 patients with bladder tumors who underwent VI-RADS-based multiparametric magnetic resonance imaging (mpMRI) before endourological treatment from April 2021 to December 2022. Diagnostic performance was evaluated by comparing mpMRI reports with final pathology, using logistic regression for muscle-invasive bladder cancer (MIBC) predictors. Follow-up until May 2023 included Kaplan-Meier and Cox regression analysis to assess VI-RADS predictive roles for recurrence-free survival (RFS) and progression-free survival (PFS)., Results: A total of 96 patients (19.8% women, 80.2% men; median age 68.0 years) were included, with 71% having primary tumors and 29% recurrent BCa. Multiparametric MRI exhibited high sensitivity (92%) and specificity (79%) in predicting MIBC, showing no significant differences between primary and recurrent cancers (AUC: 0.96 vs. 0.92, P = .565). VI-RADS emerged as a key predictor for MIBC in both univariate (OR: 40.3, P < .001) and multivariate (OR: 54.6, P < .001) analyses. Primary tumors with VI-RADS ≥ 3 demonstrated significantly shorter RFS (P = .02) and PFS (P = .04)., Conclusions: In conclusion, mpMRI with VI-RADS has a high diagnostic value in predicting MIBC in both primary and recurrent BCa. A VI-RADS threshold ≥ 3 is a strong predictor for MIBC, and in primary tumors predicts early recurrence and progression., (© 2024. The Author(s).)

Perineural spread (PNS) from pelvic carcinoma has been regarded as a pathway to muscle and bone metastasis. However, few cases have been reported, especially in patients with bladder carcinoma. In the present report, we discuss a case of diffuse cancer involvement in the muscle 5 years after radical cystectomy for advanced bladder carcinoma. Careful observation of temporal changes on medical images confirmed PNS as the pathway to muscle metastasis (i.e., primary PNS). Our report presents early and post-treatment CT, MRI and FDG-PET/CT findings of PNS from the bladder carcinoma.

Efforts on bladder cancer treatment have been shifting from extensive surgery to organ preservation in the past decade. To this end, we herein develop a multifunctional nanoagent for bladder cancer downstaging and bladder-preserving therapy by integrating mucosa penetration, reduced off-target effects, and internal irradiation therapy into a nanodrug. Specifically, an iron oxide nanoparticle was used as a carrier that was coated with hyaluronic acid (HA) for facilitating mucosa penetration. Dibenzocyclooctyne (DBCO) was introduced into the HA coating layer to react through bioorthogonal reaction with azide as an artificial receptor of bladder cancer cells, to improve the cellular internalization of the nanoprobe labeled with 177 Lu. Through magnetic resonance imaging, the targeted imaging of both nonmuscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) was realized after intravesical instillation of the multifunctional probe, both NMIBC and MIBC were found downstaged, and the metastasis was inhibited, which demonstrates the potential of the multifunctional nanoprobe for bladder preservation in bladder cancer treatment.