Assessing AI's impact on gaze patterns during colonoscopy
The Influence of Artificial Intelligence (AI) Assisted Polyp Detection (Discovery System) on Visual Gaze Patterns During Real-time Colonoscopy
This study tests how using AI during colonoscopy affects where doctors look while searching for polyps to see if it helps them find more of them.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 50 (estimated) |
| Sex | All |
| Sponsor | Radboud University Medical Center Academic / other |
| Locations | 1 site (Nijmegen, Gelderland) |
| Trial ID | NCT05619614 on ClinicalTrials.gov |
What this trial studies
This observational study evaluates how an artificial intelligence-assisted polyp detection system influences the visual gaze patterns of endoscopists during real-time colonoscopy procedures. By utilizing eye-tracking glasses, the study aims to gather data on the endoscopists' focus and attention while performing colonoscopies. The findings could provide insights into the effectiveness of AI in enhancing polyp detection rates and improving overall colonoscopy outcomes.
Who should consider this trial
Good fit: Ideal candidates for this study are patients referred for diagnostic, screening, or surveillance colonoscopy.
Not a fit: Patients undergoing therapeutic procedures or those with a Boston Bowel Prep Score of less than 6 may not benefit from this study.
Why it matters
Potential benefit: If successful, this study could lead to improved polyp detection rates during colonoscopy, enhancing early diagnosis of colonic neoplasms.
How similar studies have performed: While the use of AI in medical imaging is gaining traction, this specific approach to assessing gaze patterns during colonoscopy is relatively novel and has not been extensively tested in prior studies.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria of patients: * Referred for diagnostic, screening or surveillance colonoscopy Exclusion Criteria of patients: * Therapeutic procedure * Boston Bowel Prep Score (BBPS) score of \<6
Where this trial is running
Nijmegen, Gelderland
- Radboud university medical center Nijmegen — Nijmegen, Gelderland, Netherlands (Recruiting)
Study contacts
- Study coordinator: Michiel HJ Maas, Drs.
- Email: Michiel.maas@radboudumc.nl
- Phone: 3629647175
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.