Assessing AI's Role in Colonoscopy Withdrawal Time and Adenoma Detection
Official title: A Prospective Evaluation of the Correlation Between Real Time Artificial Intelligence-derived Effective Withdrawal Time and Adenoma Detection Rate
Run by The University of Hong Kong · NCT06345105 · Data updated 2026-05-14
This study is no longer in our active list. It may have stopped recruiting or finished. The details below are as of 2026-05-14 and are kept for reference. Check ClinicalTrials.gov for its current status, or see similar studies below.
This study is testing if using artificial intelligence during colonoscopy can help doctors find more polyps and improve the time they spend checking the colon in people aged 40 and older.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 40 Years and up |
| Sex | All |
| Enrollment | 198 (estimated) |
| Sponsor | The University of Hong Kong Academic / other |
| Locations | 1 site (Hong Kong) |
| Trial ID | NCT06345105 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates are adults aged 40 or older who are scheduled for outpatient colonoscopy.
✕Probably not a fit
Patients with a history of inflammatory bowel disease, colorectal cancer, or other significant gastrointestinal conditions may not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This observational study aims to evaluate the relationship between artificial intelligence-derived effective withdrawal time (EWT) during colonoscopy and the adenoma detection rate (ADR) of endoscopists. Participants aged 40 and above will undergo outpatient colonoscopy, where their bowel preparation will be monitored, and the colonoscopy video will be analyzed by AI to determine the EWT. The study will compare the AI-derived EWT with standard withdrawal times and assess various colonoscopy outcomes, including polyp detection rates. The goal is to enhance the effectiveness of colonoscopy procedures through real-time AI monitoring.
Why it matters
Potential benefit: If successful, this study could improve adenoma detection rates during colonoscopy, leading to better early detection of colorectal cancer.
How similar studies have gone: While the use of AI in colonoscopy is a growing field, this specific approach to measuring withdrawal time and its correlation with adenoma detection rates is relatively novel.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * All adult patients, aged 40 or above, undergoing outpatient colonoscopy will be recruited Exclusion Criteria: * history of inflammatory bowel disease * history of colorectal cancer * previous bowel resection (apart from appendectomy) * Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes * bleeding tendency or severe comorbid illnesses for which polypectomy is considered unsafe. * Cecum could not be intubated for various reasons * Poor bowel preparation with Boston Bowel Preparation Scale (BBPS) \< 6
Where it's running
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Queen Mary Hospital, the University of Hong Kong
Hong Kong, Hong Kong Recruiting
Study contacts
- Principal investigator: Thomas Ka-Luen Lui — The University of Hong Kong
- Study coordinator: Thomas Ka-Luen Lui
- Email: tkllui@hku.hk
- Phone: +85297360997
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.