AI system to detect and describe small-bowel mucosal damage in celiac and other enteropathies
Development and Validation of an Artificial Intelligence System for Detection and Characterization of Small Bowel Mucosal Atrophy in Celiac Disease and Non-Celiac Enteropathies: A Multicenter Observational Study
This project will test if an artificial intelligence system can find and describe small-bowel mucosal atrophy and other lesions in adults having small-bowel endoscopy or capsule endoscopy.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 380 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Istituti Clinici Scientifici Maugeri SpA Academic / other |
| Locations | 1 site (Pavia, PV) |
| Trial ID | NCT07387185 on ClinicalTrials.gov |
What this trial studies
This multicenter observational project will develop a deep-learning AI using anonymized retrospective endoscopy images and videos, then prospectively validate its performance on recorded procedures. In the retrospective phase, algorithms are trained to recognize mucosal atrophy and other lesions such as angiodysplasia, ulcers, and polyps. In the prospective phase, adult patients undergoing small-bowel endoscopy or capsule endoscopy will have their recorded videos analyzed offline by the AI and compared to standard human interpretation and biopsy results where available. The aim is to reduce missed lesions and decrease inter-observer variability in endoscopic characterization.
Who should consider this trial
Good fit: Adults aged 18 and older who are undergoing small-bowel endoscopy or capsule endoscopy for suspected celiac disease or other enteropathies and who can give informed consent are ideal candidates.
Not a fit: Children under 18, patients who do not undergo endoscopic imaging or cannot provide informed consent, and cases where diagnosis depends solely on non-endoscopic tests are unlikely to benefit.
Why it matters
Potential benefit: If successful, the AI could help endoscopists detect and characterize small-bowel lesions more reliably, reducing missed diagnoses and improving diagnostic confidence.
How similar studies have performed: AI and deep-learning tools have shown promise in detecting gastrointestinal lesions and capsule endoscopy abnormalities, but application specifically for celiac-related mucosal atrophy is relatively novel and still being validated.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Adult patients (age ≥18 years). * Patients undergoing endoscopic investigation of the small bowel (endoscopy or capsule endoscopy) Exclusion Criteria: * Inability to provide informed consent.
Where this trial is running
Pavia, PV
- ICS Maugeri IRCCS — Pavia, Pv, Italy (Recruiting)
Study contacts
- Study coordinator: Federico Biagi, MD
- Email: federico.biagi@icsmaugeri.it
- Phone: 0382592695
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.