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To investigate the feasibility of a radiomics model for the detection of bladder invasion (BI) by colorectal cancer (CRC) on CT images. Ninety-six patients with CRC and a suspicion of BI who underwent tumor resection with partial or total cystectomy were reviewed. The 96 patients were randomly assigned to the training dataset ( n = 68) or test dataset ( n = 28) at a ratio of 7:3. The CT images were reviewed by two experienced radiologists, who provided a CT impression of the invasion of the bladder by CRC. A region of interest (ROI) on the CT images for each case was manually labeled by two radiologists. A radiomics model was constructed using a Categorical Boosting (CatBoost) classifier. The predicted probability by CatBoost was used to evaluate the efficacy of the radiomics model. The areas under the curve (AUCs) of the receiver operating characteristic were compared between the radiomics model and the CT impression. In the training dataset, the AUC of the radiomic model [0.864 (95% CI: 0.778, 0.951)] was significantly greater than that of CT impression [0.678 (95% CI: 0.569. 0.786), P = 0.007]. In the test dataset, the AUC of the radiomic model [0.883 (95% CI: 0.699, 1.000)] was also significantly greater than that of CT impression [0.570 (95% CI: 0.370, 0.770), P = 0.040]. It is feasible to use radiomics models for the prediction of BI by CRC, which might perform better than human radiologists.

IntroductionMuscle-invasive bladder cancer (MIBC) is an aggressive type of cancer. About 50% of patients will die from the disease within 5 years despite radical treatment. This implies that in many patients, the disease has already spread at the time of radical treatment, even though imaging shows no signs of metastasis. We hypothesise that the standard local staging method, transurethral resection of the bladder tumour (TURBT), is partly responsible for tumour cell spread. Furthermore, TURBT (and re-TURBT in many patients) contributes to a significant delay to definitive therapy. The aim of this randomised study is to determine whether multiparametric MRI (mpMRI) of the bladder, in combination with a single outpatient bladder tumour biopsy for histological confirmation, is a safer, faster, less costly and, therefore, more cost-effective diagnostic pathway than TURBT to detect or rule out MIBC.Methods and analysisBladParadigm is a two-arm multicentre randomised controlled trial (RCT) conducted in the Netherlands. Over a 3-year period, patients with clinically suspected MIBC without evidence of metastases will be recruited and randomised 1:1 to either TURBT or 3-Tesla mpMRI with same-day outpatient bladder biopsy. The Vesical Imaging Reporting and Data System (VI-RADS) will be used to standardise mpMRI reporting. Patients will undergo definitive treatment based on the results of the TURBT or mpMRI. The study is powered to demonstrate that the mpMRI-based strategy is at least non-inferior to standard TURBT in patients treated with radical cystectomy alone, assuming a relative hazard of 0.55. The required sample size is 360 patients (180 TURBT, 180 mpMRI). The primary outcome is 2-year progression-free survival. Progression will be assessed by imaging, according to the current standard of care. Secondary outcome measures are time to definitive treatment, quality of life (EuroQol 5D-5L), healthcare costs and cost-effectiveness.Ethics and disseminationThis study has received ethical approval from the Medical Ethical Committee Oost-Nederland (NL83685.091.23). All participants will provide written informed consent prior to inclusion. Findings of this study will be disseminated through peer-reviewed, open-access publications, presentations at scientific conferences and stakeholder briefings.Trial registration numberNCT05779631.

Purpose The aim of the current study was to evaluate the diagnostic accuracy of transvaginal ultrasound measurement of bladder wall thickness (BWT) in diagnosis of over active bladder (OAB). Methods The current prospective study was conducted at Ain Shams University Maternity Hospital over 2 years. Patients presented to the urogynecology outpatient clinic with symptoms of urinary frequency, urgency, nocturia and/or urge incontinence were included in this study. The allocated patients were divided into two groups; Group 1(study group): fifty (50) patients with urodynamic diagnosis of detrusor instability (OAB) were included. Group 2 (control): fifty (50) patients with urodynamic diagnosis of stress incontinence were included. Using a transvaginal probe, BWT was measured in three sites at the thickest part of (a) the dome of the bladder (b) the trigone, and (c) the anterior wall of the bladder. An average of the three measurements was considered as the mean bladder thickness. Results A total of 100 patients with lower urinary symptoms were finally analyzed. There were no statistical significant differences between both groups regarding age, parity and body mass index, while there was statistically longer disease duration in group 2. Excluding urgency, there was statistical significant difference ( P  < 0.001) regarding lower urinary tract symptoms namely frequency, urgency incontinence, coital incontinence and nocturia. Patients in group 1 were more positive to symptoms of frequency, urgency incontinence, and nocturia, while patients in group 2 were more positive regarding coital incontinence. The thickness of trigon, dome, anterior wall and mean BWT was significantly higher in group 1 when compared to group 2. Receiver operator characteristics curve was constructed for estimating the association between mean BWT and prediction of OAB in patients with lower urinary tract symptoms. Mean BWT at 4.78 mm was considered as best cut-off value for prediction of OAB with sensitivity of 90 % and specificity of 78 %. Mean BWT was significantly associated with OAB > 4.78 mm as denoted by the significantly large area under the curve [AUC], AUC was 0.905. Conclusion In women with lower urinary tract symptom, transvaginal ultrasounds measured mean BWT seems to be an effective non invasive diagnostic tool for prediction of OAB.

This comprehensive review examines recent advancements in the integration of multiparametric ultrasound for diagnostic imaging of the urinary bladder. It not only highlights the current state of ultrasound imaging but also projects its potential to further elevate standards of care in managing urinary bladder pathologies. Specifically, contrast-enhanced ultrasound (CEUS) and elastography show significant improvements in detecting bladder tumors and assessing bladder wall mechanics compared to traditional methods. The review also explores the future potential of ultrasound-mediated nanobubble destruction (UMND) as an investigational targeted cancer therapy, showcasing a novel approach that utilizes nanobubbles to deliver therapeutic genes into tumor cells with high precision. Emerging AI-driven innovations and novel techniques, such as microvascular ultrasonography (MVUS), are proving to be powerful tools for the non-invasive and precise management of bladder conditions, offering detailed insights into bladder structure and function. These advancements collectively underscore their transformative impact on the field of urology.

Aims: Ultrasound-estimated bladder weight (UEBW), is an emerging diagnostic tool, which has been used in both males and females with lower urinary tract dysfunction. The currently acknowledged UEBW calculation methods rely on the accurate measurement of bladder wall thickness (BWT). We aim to identify if subtle errors in BWT measurement have a significant impact on UEBW calculations.Materials and methods: Twenty patients were randomly selected from an overactive bladder patient cohort. The primary endpoint was to identify the range of false BWT measurements outside which significant changes in UEBW calculation occur. We used the Kojima method and a semi-automatic 3-D model that is based on Chalana’s principle. Measurements were performed using the correct BWT and a series of faulty calculations from +0.5 mm to -0.5 mm using steps of 0.05 mm from true BWT. The effect of a fixed 0.5 mm BWT error was checked in bladder volumes above and below 250 ml and in three UEBW groups (<35 gr; 36-50 gr; >51gr).Results: BWT measurement errors above 0.25 mm cause statistically significant changes in UEWB calculation when a 3-D model is used and errors above 0.15 mm when Kojima’s method is used. At a fixed BWT error of 0.5 mm and bladder volume <250 ml, there is a 23.76% deviation from true UEBW, while at volumes >250 ml the deviation is 32.72%. The deviation is inversely proportional to the UEBW result, and heavier bladders deviate less.Conclusions: UEBW is a promising diagnostic tool, but small errors in BWT measurement might cause significant deviation from the true values. A 3-D calculation model appears to minimize such risks.

IntroductionTo investigate the risk factors for febrile genito-urinary tract infection (GUTI) in spinal cord injury-associated neurogenic lower urinary tract dysfunction (NLUTD) patients who perform routine clean intermittent catheterization (CIC) evaluated by urodynamic study (UDS) and cystography.Patients and methodsOver a 3-year period, we retrospectively assessed risk factors for febrile UTI in 141 spinal cord injury patients diagnosed as NLUTD and performing routine CIC, regarding gender, UDS findings such as bladder compliance, maximum cystometric capacity, and cystography.ResultsA total of 41 patients had febrile GUTI in the follow-up period as along with 32 cases of pyelonephritis, 10 cases of epididymitis, and 1 case of prostatitis, including patients with multiple infectious diseases. The causative bacteria were Escherichia coli (14 cases) followed by Pseudomonas aeruginosa (n = 5), Klebsiella pneumoniae (n = 4), and Klebsiella oxytoca (n = 4). Antibiotic-resistant E. coli were seen, with 36.4% instances of extended-spectrum beta-lactamase production in whole of E. coli. Male gender (p = 0.018), ASIA Impairment Scale (AIS) C or more severe (p = 0.031), the number of CIC (p = 0.034), use of quinolones (p < 0.001) and severe bladder deformity (DG 2 or more, p = 0.004) were significantly associated with febrile GUTI occurrence.ConclusionsOur data demonstrated that male gender, severe bladder deformity (DG 2 or more), AIS C or more, the number of CIC, and use of quinolones were significantly associated with febrile GUTI occurrence in NLUTD patients employing routine CIC. Further prospective studies are necessary to define the full spectrum of possible risk factors for febrile GUTI in these patients.

We report an approach in diagnostic imaging based on nanoscale-resolution scanning of surfaces of cells collected from body fluids using a recent modality of atomic force microscopy (AFM), subresonance tapping, and machine-leaning analysis. The surface parameters, which are typically used in engineering to describe surfaces, are used to classify cells. The method is applied to the detection of bladder cancer, which is one of the most common human malignancies and the most expensive cancer to treat. The frequent visual examinations of bladder (cytoscopy) required for follow-up are not only uncomfortable for the patient but a serious cost for the health care system. Our method addresses an unmet need in noninvasive and accurate detection of bladder cancer, which may eliminate unnecessary and expensive cystoscopies. The method, which evaluates cells collected from urine, shows 94% diagnostic accuracy when examining five cells per patient’s urine sample. It is a statistically significant improvement (P < 0.05) in diagnostic accuracy compared with the currently used clinical standard, cystoscopy, as verified on 43 control and 25 bladder cancer patients.

PurposeTo determine through a comprehensive systematic review and meta-analysis the cumulative diagnostic performance of vesical imaging-reporting and data system (VIRADS) to predict preoperative muscle-invasiveness among different institutions, readers, and optimal scoring accuracy thresholds.MethodsPubMed, Cochrane and Embase were searched from inception up to May 2021. Sensitivity (Sn), Specificity (Sp) were first estimated and subsequently pooled using hierarchical summary receiver operating characteristics (HSROC) modeling for both cut-off ≥ 3 and ≥ 4 to predict muscle-invasive bladder cancer (MIBC). Further sensitivity analysis, subgroup analysis and meta-regression were conducted to investigate contribution of moderators to heterogeneity.ResultsIn total, n = 20 studies from 2019 to 2021 with n = 2477 patients by n = 53 genitourinary radiologists met the inclusion criteria. Pooled weighted Sn and Sp were 0.87 (95% CI 0.82–0.91) and 0.86 (95% CI 0.80–0.90) for cut-off ≥ 3 while 0.78 (95% CI 0.74–0.81) and 0.94 (95% CI 0.91–0.96) for cut-off ≥ 4. The area under the HSROC curve was 0.93 (95% CI 0.90–0.95) and 0.91 (95% CI 0.88–0.93) for cut-off ≥ 3 and ≥ 4, respectively. Meta-regression analyses showed no influence of clinical characteristics nor cumulative reader’s experience while study design and radiological characteristics were found to influence the estimated outcome.ConclusionWe demonstrated excellent worldwide diagnostic performance of VI-RADS to determine pre-trans urethral resection of bladder tumor (TURBT) staging. Our findings corroborate wide reliability of VI-RADS accuracy also between different centers with varying experience underling the importance that standardization and reproducibility of VI-RADS may confer to multiparametric magnetic resonance imaging (mpMRI) for preoperative BCa discrimination.

Objectives It is essential yet highly challenging to preoperatively diagnose variant histologies such as urothelial carcinoma with squamous differentiation (UC w/SD) from pure UC in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly. We developed a non-invasive automated machine learning (AutoML) model to preoperatively differentiate UC w/SD from pure UC in patients with MIBC. Methods A total of 119 MIBC patients who underwent baseline bladder MRI were enrolled in this study, including 38 patients with UC w/SD and 81 patients with pure UC. These patients were randomly assigned to a training set or a test set (3:1). An AutoML model was built from the training set, using 13 selected radiomic features from T2-weighted imaging, semantic features (ADC values), and clinical features (tumor length, tumor stage, lymph node metastasis status), and subsequent ten-fold cross-validation was performed. A test set was used to validate the proposed model. The AUC of the ROC curve was then calculated for the model. Results This AutoML model enabled robust differentiation of UC w/SD and pure UC in patients with MIBC in both training set (ten-fold cross-validation AUC = 0.955, 95% confidence interval [CI]: 0.944–0.965) and test set (AUC = 0.932, 95% CI: 0.812–1.000). Conclusion The presented AutoML model, that incorporates the radiomic, semantic, and clinical features from baseline MRI, could be useful for preoperative differentiation of UC w/SD and pure UC. Clinical relevance statement This MRI-based automated machine learning (AutoML) study provides a non-invasive and low-cost preoperative prediction tool to identify the muscle-invasive bladder cancer patients with variant histology, which may serve as a useful tool for clinical decision-making. Key Points •  It is important to preoperatively diagnose variant histology from urothelial carcinoma in patients with muscle-invasive bladder carcinoma (MIBC), as their treatment strategy varies significantly . •  An automated machine learning (AutoML) model based on baseline bladder MRI can identify the variant histology (squamous differentiation) from urothelial carcinoma preoperatively in patients with MIBC . •  The developed AutoML model is a non-invasive and low-cost preoperative prediction tool, which may be useful for clinical decision-making .

PurposeThe Vesical Imaging-Reporting and Data System (VI-RADS) criteria are expanding, providing fine differentiation of bladder wall layers involvement. We aimed to explore the feasibility of a novel categorical scoring, the Neoadjuvant chemotherapy VI-RADS (nacVI-RADS) for radiologic assessment of response (RaR), to define the spectrum of treatment response among patients with muscle invasive bladder cancer (MIBC).MethodsTen consecutive patients diagnosed with non-metastatic MIBC were prospectively enrolled and addressed to NAC and underwent mpMRI before staging resection and after the chemotherapy cycles. The follow-up MRI assessment was performed using the nacVI-RADS algorithm for evaluation of response to therapy. NacVI-RADS categorically define complete RaR, based on prior VI-RADS score, presence of residual disease, tumor size, and infiltration of the muscularis propria.ResultsNacVI-RADS categories were able to match all the final radical cystectomy pathology both for complete pT0 responders and for the patients defined as partial or minimal responders, who only showed some RaR inter-scoring class downstaging.ConclusionThis report is the preliminary evidence of the feasibility of nacVI-RADS criteria. These findings might lead to possible paradigmatic shifts for cancer-specific survival risk assessment and to possibly drive the therapeutic decision through active surveillance programs, bladder-sparing modalities, or to the standard of care.