Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
Recruiting now · Not applicable
Conditions studied: Colonic Neoplasms
In brief
This three parallel-arms, randomized, multicenter trial is aimed at investigating the value of AI-assisted optical biopsy for differentiating between neoplastic and non-neoplastic polyps which will lead to the implementation of cost-saving strategies in screening programs. A cost-effectiveness analyses with the use of modern trial emulation analyses of large observational and clinical trial datasets and real-cost data will be conducted. To improve personalized treatment with a novel colonoscopy CADx risk-prediction tool, the investigators will even develop a novel deep learning algorithm for the optical biopsy of the alternative pathway of colorectal cancer carcinogenesis, namely the serrated pathway and develop cost-effectiveness models of AI-assisted optical biopsy in colorectal cancer screening that provides reliable information to identify cancer risk regardless of physicians' skill.
Key facts
- Study ID
- NCT06041945
- Run by
- Istituto Clinico Humanitas
- People needed
- 1800
- Starts
- 2023-09-21
- Expected to finish
- 2027-09-01
- Last updated by the study team
- 2023-10-04
Who can join
Age: 40 and older. Sex: any. Healthy volunteers: accepted.
You may qualify if…
- All >40 years-old patients undergoing colonoscopy for selected indications
You may not qualify if…
- patients with personal history of CRC, or IBD
- patients affected with Lynch syndrome or Familiar Adenomatous Polyposis.
- patients with inadequate bowel preparation (defined as Boston Bowel Preparation Scale <2 in any colonic segment).
- patients with previous colonic resection.
- patients on antithrombotic therapy, precluding polyp resection.
- patients who were not able or refused to give informed written consent.
Where it is running
- Istituto Clinico Humanitas — Rozzano, Milano, Italy (enrolling)
- Istituto Clinico Humanitas — Rozzano, Milano, Italy (enrolling)
Full record on ClinicalTrials.gov
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