Artificial Intelligence-assisted Colonoscopy, Tandem Study

Not Applicable

• Conditions: Artificial Intelligence (AI); Colonoscopy Education; Adenoma Colon Polyp

• Registration Number: NCT07023471
• Lead Sponsor: Mahidol University

Brief Summary

The goal of this clinical trial is to evaluate effect of artifial intelligent (AI) system, Endoscopy as AI-powered Device (ENAD) on adenoma miss rate from colonoscopy underwent by trainee endoscopist. It will also evaluate effect of AI on adenoma and polyp detection rate from colonoscopy underwent by trainee endoscopist. The main questions it aims to answer are:

• Does AI-system lower adenoma miss rate in colonoscopy underwent by trainee endoscopist?

Researchers will do the tandem colonoscopy and devided the participant in 4 groups as follows:

A. First pass: trainee; Second pass: expert B. First pass: trainee + AI; Second pass: expert C. First pass: trainee; Second pass: expert + AI D. First pass: trainee+AI; Second pass: expert+AI Participants will take bowel preparation in split dose regimen and nothing per oral for 4 hours. They will underwent colonoscopy as above, with sedation by anesthesiologist. Details on qualities of colonoscopy, polyps detection and pathology results will be recorded.

Detailed Description

Colon cancer accounts for one of the most common cancer worldwide and also cancer-related death. Colonoscopy is accepted to be an effective tool in colon cancer screening since the polypectomy of small adenoma can prevent colon cancer. Missed adenoma is one of the causes of interval cancer between routine colonoscopy screening. Nonvisualization is the cause of missed adenoma during colonoscopy. Artificial intelligence (AI)-assisted colonoscopy was superior then routine colonoscopy from parallel study and tandem study. Previous studies often used one same endoscopist in doing tandem colonoscopy which may still have bias. Only one previous study designed to use trainee endoscopist in the first pass and expert endoscopist in the second pass, some subgroups used AI-assisted. The result revealed the lower of adenoma miss rate (AMR) in AI-assisted colonoscopy in the first pass. This study designed to evaluate AMR of AI-assisted colonoscopy in trainee endoscopist compared to expert endoscopist, the trainee will do colonoscopy in the first pass (with or without AI) and the expert will do colonoscopy in the second pass (with or without AI). The present study aimed to evaluate effect of AI-assisted colonoscopy in trainee endoscopist.

Study Timeline

• Study Start: 2025-05-13
• Primary Completion: 2025-05-13
• Status Verified: 2025-06
• Study First Submitted: 2025-06-07
• Study First Submitted QC: 2025-06-07
• Study First Posted: 2025-06-17
• Last Update Submitted: 2025-06-18
• Last Update Posted: 2025-06-24
• Study Completion: 2026-12-31

Recruitment & Eligibility

• Status: ENROLLING_BY_INVITATION
• Sex: All
• Target Recruitment: 364

Inclusion Criteria

• Age 40 - 85 years old
• Appointment for colonoscopy for colorectal cancer screening

Exclusion Criteria

• Previous history of bowel obstruction or perforation
• Presence of coagulopathy (Prothrombin time >, = 3 second ULN; Platelet < 50,000)
• Previously diagnosed with inflammatory bowel disease or polyposis syndrome
• Pregnancy or lactation
• Severe comorbities or American Society of Anesthesiologist classification >, = 3
• Unable to sign informed consent

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
Adenoma miss rate	Untill the end of procedure	Compare adenoma miss rate (AMR) in each groups including Non-AI/ Non-AI, Non-AI/ AI, AI/ Non-AI, and AI/ AI

Secondary Outcome Measures

Name	Time	Method
Polyp miss rate	Untill the end of the procedure	Compare polyp miss rate (PMR) in each groups
Adenoma detection rate of colonoscopy underwent by the trainee	Untill the end of procedure of first pass which will be done by trainee	Compare adenoma detection rate (ADR) of colonoscopy underwent by trainee with or without AI

Trial Locations

Locations (1)

Division of Gastroenterology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand; 🇹🇭 Bangkok, Thailand