Colon Adenoma, Colon Polyp
Conditions
Keywords
Colonoscopy, Artificial intelligence
Brief summary
This is a prospective multi-center randomized study is to determine whether the use of artificial intelligence (AI)-assistance could reduce the miss rates of polyps and adenomas in the proximal colon during tandem examination
Detailed description
Centers 1. Queen Mary Hospital, Hong Kong, China (Co-ordinating Center) 2. Tan Tock Seng Hospital, Singapore, Singapore 3. Institute of Gastroenterology and Hepatology, Vietnam Union of Science and Technology Association, Hanoi, Vietnam Study population Inclusion: All adult patients, aged 40 or above, undergoing outpatient colonoscopy in the participating centers will be recruited. Exclusion: * history of inflammatory bowel disease * history of colorectal cancer * previous bowel resection (apart from appendectomy) * Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes * bleeding tendency or severe comorbid illnesses for which polypectomy is considered unsafe. Post-randomization exclusion: * Cecum could not be intubated for various reasons * Boston Bowel Preparation Scale (BBPS) score of the proximal colon is \<2 Study design This is a prospective randomized trial comparing the miss rates of proximal colonic lesions by AI assisted colonoscopy or conventional colonoscopy (Fig. 1). The study will be conducted in the Endoscopy Centre of the participating hospitals. Randomization Eligible patients in each center will be randomly allocated in a 1:1 ratio to undergo tandem colonoscopy of the proximal colon first with AI-assistance and follow by conventional white light colonoscopy (Group 1) or conventional white light colonoscopy without AI assistance follow by conventional colonoscopy (Group 2). Proximal colon refers to colonic segment proximal to the splenic flexure. Randomization will be conducted in blocks of 4 by computer generated random sequences and stratified according to indications of colonoscopy (symptomatic vs screening/surveillance). Patients will be blinded to the group assignment.
Interventions
Artificial intelligence-Assisted colonoscopy for detection of colonic polyp
PROCEDUREConventional colonoscopy
Conventional colonoscopy
Sponsors
Tan Tock Seng Hospital
Institute of Gastroenterology and Hepatology, Vietnam
The University of Hong Kong
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
SINGLE (Subject)
Intervention model description
Prospective randomized design
Eligibility
Sex/Gender
ALL
Age
40 Years to No maximum
Healthy volunteers
Yes
Inclusion criteria
* All adult patients, aged 40 or above, undergoing outpatient colonoscopy in the participating centers will be recruited
Exclusion criteria
* history of inflammatory bowel disease * history of colorectal cancer * previous bowel resection (apart from appendectomy) * Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes * bleeding tendency or severe comorbid illnesses for which polypectomy is considered unsafe.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Proximal adenoma missed rate | One day | The proportion of patients with missed adenomas detected in the second examination only |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Proximal polyp missed rate | One day | The proportion of patients with missed adenomas detected in the second examination only |
| Proximal adenoma detection rate | One day | The proportion of patients with at least one adenoma |
| Proximal polyp detection | One day | The proportion of patients with at least one polyp |
Countries
China, Singapore, Vietnam
Outcome results
None listed