Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
Saving by Artificial Intelligence for Virtual Endoscopy Biopsy Artificial Intelligence to Implement Cost-saving Strategies for Colonoscopy Screening Based on in Vivo Prediction of Polyp Histology
About This Trial
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.
Who May Be Eligible (Plain English)
Original Eligibility Criteria
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Treatments Being Tested
Standard, high-definition colonoscopy with the use of CADe assistance
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
Standard, high-definition colonoscopy with the use of CADe/CADx assistance, no leave-in-situ
All detected polyps regardless of size and optical diagnosis will be resected and sent to pathology.
Standard, high-definition colonoscopy with the use of CADe/CADx assistance, leave-in-situ
Polyps will be left in situ if diminutive (≤5 mm) in size, located in the rectum or sigma and optically diagnosed by the endoscopist using the system to be hyperplastic with high confidence, otherwise resected and sent to pathology.