Clinical trial NCT07023471: AI-assisted Colonoscopy, Tandem Study
Official title: Effect of an Artificial Intelligence-assisted Colonoscopy on Adenoma Miss Rate of Trainee-performed Colonoscopy; A Four-group Randomized Controlled Tandem Colonoscopy Study
Study type: INTERVENTIONAL
Overall status: ENROLLING_BY_INVITATION
Phase: NA
Conditions: Artificial Intelligence (AI)
Colonoscopy Education
Adenoma Colon Polyp
Keywords: Adenoma miss rate
Artificial intelligence
colonoscopy
tandem colonoscopy
Lead sponsor: Mahidol University
Sponsor class: OTHER
First posted: 2025-06-17
Enrollment: 364
Sex: ALL
Minimum age (years): 40
Maximum age (years): 85
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: DIAGNOSTIC

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 qualityies 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 endoscopists in doing tandem colonoscopy which may still have bias. Only one previous study designed to use trainee endoscopist in the first pass and endoscopist in the second pass, some subgroup used AI-assisted. The result revealed lower 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.

Eligibility criteria: 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

Primary outcomes:
measure: Adenoma miss rate
timeFrame: Untill the end of procedure
Secondary outcomes:
measure: Polyp miss rate
timeFrame: Untill the end of the procedure
measure: Adenoma detection rate of colonoscopy underwent by the trainee
timeFrame: Untill the end of procedure of first pass which will be done by trainee
Other outcomes:
Locations:
city: Bangkok
country: Thailand
facility: Division of Gastroenterology, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
Study officials:
References: