AI Detection of Bladder Tumors Under Endoscopy
Artificial Intelligence Detection of Bladder Tumors Under Endoscopy
1 other identifier
observational
1,000
1 country
1
Brief Summary
The goal of this clinical trial is to learn if the AI algorithm can detect bladder tumors better than urologists under cystoscopy. It will also train the AI algorithm for bladder tumor detection. The main question it aims to answer is: Can AI algorithm achieve IOU value, precision, recall, false negative rate of bladder tumor detection similar to that of urologists? The cystoscopy video will be annotated by AI and urologists. Researchers will compare AI algorithm to urologists to see if Al algorithm has a similar capability as urologists do.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Jan 2024
Longer than P75 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
January 1, 2024
CompletedFirst Submitted
Initial submission to the registry
June 19, 2024
CompletedFirst Posted
Study publicly available on registry
June 25, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2033
ExpectedStudy Completion
Last participant's last visit for all outcomes
December 31, 2034
June 25, 2024
June 1, 2024
10 years
June 19, 2024
June 19, 2024
Conditions
Outcome Measures
Primary Outcomes (1)
intersection over union
The overlapping area of the actual bladder lesion and detected bladder lesion divided by their combined areas.
From Jan 1st 2024 to Dec 31st 2033
Study Arms (2)
detection by artificial intelligence
The patient with bladder lesion confirmed by cystoscopy, these bladder lesion(s) are detected by artificial intelligence algorithm.
detection by urologists.
The patient with bladder lesion confirmed by cystoscopy, these bladder lesion(s) are detected by urologist.
Interventions
The bladder lesion(s) are detected by artificial intelligence algorithm.
The bladder lesion(s) are detected by urologists.
Eligibility Criteria
The patients with benign or malignant bladder lesion.
You may qualify if:
- The patient who receives cystoscopy and the cystoscopy video is available, and one or multiple bladder lesions can be observed in the cystoscopy.
You may not qualify if:
- The patient whose cystoscopy is not clear enough to analyze.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Peking Union Medical College Hospital
Beijing, Beijing Municipality, China
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Zixing Ye
Peking Union Medical College Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- CASE ONLY
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 19, 2024
First Posted
June 25, 2024
Study Start
January 1, 2024
Primary Completion (Estimated)
December 31, 2033
Study Completion (Estimated)
December 31, 2034
Last Updated
June 25, 2024
Record last verified: 2024-06