Teaching doctors to tell Paris-class polyps apart using real and AI-generated colon images
Official title: Training Physicians to Differentiate the Paris Classification Using Artificial Colon Polyp Images
Run by Wuerzburg University Hospital · NCT06550908 · Data updated 2026-11-12
This trial tests if training doctors with AI-generated colon polyp images helps them learn to classify polyps by the Paris system better than training with real images.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 70 (estimated) |
| Sponsor | Wuerzburg University Hospital Academic / other |
| Locations | 1 site (Würzburg) |
| Status | Recruiting |
| Started | April 15, 2025 |
| Main results expected | August 31, 2025 |
| Study ends | August 31, 2025 |
| Registry record updated | August 12, 2025 |
| Trial ID | NCT06550908 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Physicians, with or without prior colonoscopy experience, who can attend and complete the image-based training sessions at the University Hospital Würzburg are ideal candidates.
✕Probably not a fit
Individual patients will not directly benefit from this educational intervention, and clinicians who do not perform endoscopy or cannot apply the training in practice are unlikely to gain practical benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Investigators will train physicians using the Lutetia Training Platform with either collections of real colon polyp images or AI-generated (synthetic) images and then compare classification performance for the Paris system. The generative AI images are designed to be realistic, compliant with data protection rules, and can be modified to show different precancerous stages in the same lesion. Participants include physicians with and without colonoscopy experience who complete the image-based training at the University Hospital Würzburg. The primary comparison is which image source leads to more accurate polyp classification after the training.
Why it matters
Potential benefit: If successful, this approach could improve clinicians' ability to detect and correctly classify precancerous colon polyps earlier, potentially improving colorectal cancer prevention.
How similar studies have gone: Previous work shows image-based and AI-assisted training can improve polyp recognition, but using fully synthetic, generative images for clinician training is a relatively new approach.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Physicians with or without experience in colonoscopy
Where it's running
-
University hospital Würzburg
Würzburg, Germany Recruiting
Study contacts
- Principal investigator: Alexander Hann — Wuerzburg University Hospital
- Study coordinator: Alexander Hann, MD
- Email: hann_a@ukw.de
- Phone: 0049931201
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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.