Development and Validation of an Artificial Intelligence-assisted System for Bowel Cleanliness Assessment Based on Withdrawal Distance Weighting
1 other identifier
observational
700
1 country
1
Brief Summary
To address the limitations of current AI-based systems that rely on the assumption of a "constant withdrawal speed," this study proposes the integration of the UPD-3 endoscopic positioning system. By using colonoscope withdrawal videos in combination with UPD-3 imaging data as training samples, we aim to develop an AI-powered bowel cleanliness assessment system that incorporates "withdrawal distance" as a weighting factor. This approach is expected to yield a more reliable, objective, and clinically applicable intelligent assessment system that better aligns with real-world clinical practice and endoscopists' operational habits.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Oct 2025
Typical duration 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
First Submitted
Initial submission to the registry
August 25, 2025
CompletedFirst Posted
Study publicly available on registry
September 2, 2025
CompletedStudy Start
First participant enrolled
October 1, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
October 1, 2028
ExpectedStudy Completion
Last participant's last visit for all outcomes
October 1, 2028
September 2, 2025
August 1, 2025
3 years
August 25, 2025
August 25, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Prediction accuracy of the models
Immediately after models development
Study Arms (4)
Cohort for Module 1
Development and Validation of Module for Exclusion of Unqualified Frames in Colonoscopy Videos
Cohort for Module 2
Development and Validation of Module for BBPS 0-3 Scoring for Qualified Colonoscopy Images
Cohort for Module 3
Development and Validation of Module for Prediction of Hepatic and Splenic Flexure Locations
Cohort for Module 4
Development and Validation of Module for Real-Time Prediction of Withdrawal Distance
Interventions
No Intervention: Observational Cohort
Eligibility Criteria
Colonoscopy images, colonoscopy videos, and colonoscopy videos with the UPD-3 positioning system from the electronic database of our hospital
You may qualify if:
- Clear colonoscopy images suitable for BBPS scoring
- Complete and clear colonoscopy videos suitable for BBPS scoring
- Clear colonoscopy videos with a stable UPD-3 positioning system, without signal drift, disappearance, or other disruptions
You may not qualify if:
- Blurred colonoscopy images
- Colonoscopy images taken from the small intestine or outside the patient's body
- Colonoscopy images captured during irrigation or instrument manipulation
- Colonoscopy images obtained during chromoendoscopy
- Colonoscopy videos that do not contain the complete withdrawal process
- Videos in which the UPD-3 colonoscopic positioning system exhibited signal drift, disappearance, or other instability
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Fudan Universitylead
Study Sites (1)
Huadong hospital, Fudan university
Shanghai, 200040, China
Study Officials
- STUDY DIRECTOR
Danian Ji, M.D.
Huadong Hospital
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Director
Study Record Dates
First Submitted
August 25, 2025
First Posted
September 2, 2025
Study Start
October 1, 2025
Primary Completion (Estimated)
October 1, 2028
Study Completion (Estimated)
October 1, 2028
Last Updated
September 2, 2025
Record last verified: 2025-08
Data Sharing
- IPD Sharing
- Will not share