Bladder Disorders Clinical Trials
A listing of Bladder Disorders medical research trials actively recruiting patient volunteers. Search for closest city to find more detailed information on a research study in your area.
Found 279 clinical trials
Urinary Microbiome Differences in Bladder Cancer, Benign Urinary Diseases and Healthy Counterparts in Adult Male Population
The study aims to investigate alterations in the bladder microbiome in adult men with bladder cancer, healthy men, and men with benign urinary disease
A Novel Multiplex ELISA Assay for Surveilling Patients with History of Bladder Cancer
Voided urinary cytology (VUC) is the most widely used urine-based assay for detecting bladder cancer (BCa); however, it fails to detect approximately 50% of low-grade or early stage BCa when it is most curable. Furthermore, the detection rate of VUC for recurrent BCa is not much better. Because of this …
A Research Protocol for Evaluating the Efficacy of Perfused Chemotherapeutic Agents for Bladder Cancer Based on Organoid Technology
The investigators are here to invite participants to participate in a medical research project, and this informed consent form provides participants with information to decide whether or not to participate in this study. Please read the following carefully and discuss any questions and terms that are not clear with the …
Analysis of Urinary Methylation Patterns Via Liquid Biopsy as an Early Diagnosis Tool
Multicenter, observational, prospective, biological pilot study on liquid biopsy, aimed at investigating methylation profiles in relation to the early diagnosis of bladder cancer, to validate the potential of commercially available tests (e.g. BladderCARE, Bladder EpiCheck), to apply and validate tests based on targeted multi-marker or genome wide analyzes via NGS …
Deep Learning Radiomics Model for Predicting Post-cystectomy Outcome in Muscle Invasive Bladder Cancer
Muscle invasive bladder cancer (MIBC) has a poor prognosis even after radical cystectomy. Postoperative survival stratification based on radiomics and deep learning may be useful for treatment decisions to improve prognosis. This study was aimed to develop and validate a deep learning radiomics model based on preoperative enhanced CT to …
Role of Microbiome in BCG Responsiveness Prediction
Our primary aim is to investigate the use of microbial profile from the bladder and the feces of NMIBC patients as a predicting tool for therapy response prior to BCG administration. Our second aim is to collect additional samples (blood, instrumented urine, bladder tissue, feces) to establish a local biobank …
Bladder Cancer Staging and Prediction of New Adjuvant Chemotherapy Efficacy Based on Deep Learning and Transfer Learning in Ultrasound-Magnetic Resonance-Pathology Multimodal Multiscale
Bladder cancer is the most common malignant tumor of the urinary system. The presence or absence of muscle invasion in early bladder cancer is an independent prognostic factor. The involvement of muscle invasion affects the choice of surgical methods and treatment. Preoperatively, the precise assessment of bladder cancer staging has …
Augmented Bladder Tumor Detection Using Real Time Based Artificial Intelligence
Today the standard for the diagnosis and monitoring of bladder tumors is bladder endoscopy. The performance of this exam is not perfect. With this work, based on artificial intelligence, the investigators wish to combine endoscopy with a complementary diagnostic tool in order to improve patient care. The main objective will …
The Guiding Value of Liquid Biopsy Based on Urinary Tumor DNA/RNA in the Second Transurethral Resection of High-risk Non-muscle Invasive Bladder Cancer
High-risk non-muscle-invasive bladder cancer (NMIBC) carries a substantial risk of residual disease after initial transurethral resection of bladder tumor (TURBT). Current guidelines recommend a second TURBT (re-TURBT) within 2-6 weeks for patients with stage T1 disease to remove residual tumor, confirm staging, and obtain additional pathological information. However, the actual …
Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study
This study aims to develop an ultrasound image-based deep learning system to enable automatic segmentation, T-staging, and pathological grading prediction of bladder tumors. It seeks to enhance the objectivity, accuracy, and efficiency of bladder cancer diagnosis, reduce reliance on physician experience, and provide support for precision medicine and resource optimization.
