AI detection of bladder tumors during cystoscopy
Artificial Intelligence Detection of Bladder Tumors Under Endoscopy
This study is testing whether an AI tool can find bladder tumors during cystoscopy better than doctors can.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 1000 (estimated) |
| Ages | 18 Years to 100 Years |
| Sex | All |
| Sponsor | Peking Union Medical College Hospital Academic / other |
| Locations | 1 site (Beijing, Beijing Municipality) |
| Trial ID | NCT06474338 on ClinicalTrials.gov |
What this trial studies
This clinical trial aims to evaluate whether an AI algorithm can detect bladder tumors more effectively than urologists during cystoscopy. The study will involve annotating cystoscopy videos with both AI and urologist input to compare their detection capabilities. The primary focus is on achieving similar performance metrics, such as precision and recall, between the AI and human observers. By leveraging advanced deep learning techniques, the research seeks to enhance the accuracy of bladder tumor detection, which is critical for effective patient management.
Who should consider this trial
Good fit: Ideal candidates for this study are patients undergoing cystoscopy with observable bladder lesions.
Not a fit: Patients whose cystoscopy results are unclear and cannot be analyzed will not benefit from this study.
Why it matters
Potential benefit: If successful, this approach could lead to improved detection rates of bladder tumors, potentially reducing recurrence and progression of the disease.
How similar studies have performed: While the application of AI in medical imaging is gaining traction, this specific approach to bladder tumor detection is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: The patient who receives cystoscopy and the cystoscopy video is available, and one or multiple bladder lesions can be observed in the cystoscopy. Exclusion Criteria: The patient whose cystoscopy is not clear enough to analyze.
Where this trial is running
Beijing, Beijing Municipality
- Peking Union Medical College Hospital — Beijing, Beijing Municipality, China (Recruiting)
Study contacts
- Principal investigator: Zixing Ye — Peking Union Medical College Hospital
- Study coordinator: Zixing Ye
- Email: yezixing@pumch.cn
- Phone: +86-18611385866
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.