Longterm Effectiveness of Artificial Intelligence-assisted Colonoscopy on Adenoma Recurrence

Between April 2021 and July 2022, our group completed a parallel-group, randomized controlled trial in Hong Kong. [ENDOAID-TRAIN study; NCT04838951] 856 subjects undergoing colonoscopies were randomized 1:1 to receive colonoscopies with CADe (ENDO-AID, Olympus Co., Japan) or standard colonoscopies (control). Our study proved that AI-assisted colonoscopies could increase the overall ADR, especially small-to-medium size adenomas. It remains questionable whether the increased detection and removal of these non-advanced adenomas can be translated into any sustained long-term benefit. The impact of this AI-driven intensive surveillance on general population and healthcare system is also largely unknown. In this research project, we aim to assess the long-term effectiveness of AI-assisted colonoscopy on adenoma recurrence and PCCRC prevention, by conducting a real-world, prospective study with longitudinal extension from a randomized trial.

Inclusion criteria

Subjects are eligible if:

(i) They underwent randomization to receive colonoscopy with/without CADe in ENDOAID-TRAIN study [NCT04838951]; (ii) They are fit and willing to undergo surveillance colonoscopy at year 3; (iii) Written informed consent obtained.

Exclusion criteria

Subjects will be excluded from the study if they have any of the followings:

(i) Incomplete colonoscopy during index procedure; (ii) Known residual colorectal neoplasia not removed (except hyperplastic polyps); (iii) Underwent unscheduled interval colonoscopy before year 3; (iv) Contraindications to surveillance colonoscopy at year 3; (v) Advanced comorbid (American Society of Anesthesiologists grade 4 or above); (vi) History of CRC, hereditary polyposis syndrome or inflammatory bowel disease; (vii) History of colectomy at any time point.