Actively Recruiting
Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound
Led by Peking University First Hospital · Updated on 2025-08-17
400
Participants Needed
1
Research Sites
4 weeks
Total Duration
On this page
AI-Summary
What this Trial Is About
Researchers are developing a deep learning system based on ultrasound images to improve the diagnosis of bladder tumors. This system aims to automatically segment tumors, determine their stage (T-staging), and predict pathological grading. The goal is to make bladder cancer diagnosis more objective, accurate, and efficient by reducing reliance on physician experience and supporting precision medicine and resource optimization. The study focuses on creating and testing this diagnostic model using ultrasound images from patients suspected of having bladder tumors. It is an observational study conducted across multiple centers, starting in May 2025 and continuing through May 2027, during which the overall diagnostic accuracy of the deep learning system will be evaluated. Participants will be patients aged 18 to 85 years who have a suspected bladder mass detected by abdominal ultrasound and are scheduled for surgical treatment of bladder tumors. Researchers will collect ultrasound data and surgical pathology results to assess the model's performance. The primary outcome measure is the overall diagnostic accuracy of the system, with safety and other assessments conducted as part of routine care. Participation will last as long as needed to complete the diagnostic evaluation and surgery within the study period.
CONDITIONS
Brief Title
Construction of a Deep Learning-Based Precise Diagnostic Framework for Bladder Tumors Using Ultrasound: A Multicenter, Ambispective Cohort Study
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Suspected bladder mass detected by abdominal ultrasound in patients aged 18 years or older
- Patients scheduled for surgical treatment of bladder tumors
You will not qualify if you...
- Age over 85 years
- Unable to undergo abdominal or transrectal ultrasound due to uncooperativeness or poor image quality
- History of bladder tumor surgery, radiotherapy, chemotherapy, or systemic therapy within the past 3 months
- Presence of indwelling medical devices such as double-J ureteral stents or urinary catheters
- Failure to undergo bladder tumor surgery within 2 weeks after ultrasound examination
- Diagnosis of non-urothelial carcinoma or pathologically unconfirmed bladder tumors
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Your Study Journey
Duration - 2 to 4 weeks
Participants are screened for eligibility to participate in the trial.
1 visit (in-person)
Duration - Up to 2 weeks
Participants undergo ultrasound examinations and diagnostic assessments to evaluate bladder tumors as part of the observational study.
1 to 2 visits depending on diagnostic procedures
Duration - From May 2025 to May 2027
Participants are followed over time to assess diagnostic accuracy and outcomes related to bladder tumor detection.
Periodic visits as per clinical care
Trial Site Locations
Total: 1 location
1
Department of Urology, Peking University First Hospital
Beijing, China, 100034
Actively Recruiting
Research Team
Z
Zheng Zhang
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
0
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