Artificial Intelligence-assisted Colonoscopy on Detection of Missed Proximal Lesions

• Sponsor: The University of Hong Kong (Other)
• Overall Status: Completed
• CT.gov ID: NCT04294355
• Collaborator: Tan Tock Seng Hospital (Other), Institute of Gastroenterology and Hepatology, Vietnam (Other)
• Enrollment: 216
• Locations: 3
• Arms: 2
• Actual Duration (Months): 13.5
• Patients Per Site: 72
• Patients Per Site Per Month: 5.3

Study Details

Study Description

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

Condition or Disease	Intervention/Treatment	Phase
Colon Adenoma; Colon Polyp	Device: Artificial intelligence-Assisted colonoscopy; Procedure: Conventional colonoscopy	N/A

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.

Study Design

• Study Type: Interventional
• Actual Enrollment: 216 participants
• Allocation: Randomized
• Intervention Model: Parallel Assignment
• Intervention Model Description: Prospective randomized designProspective randomized design
• Masking: Single (Participant)
• Primary Purpose: Diagnostic
• Official Title: Artificial Intelligence-assisted Colonoscopy Versus Conventional Colonoscopy for Missed Lesions in the Proximal Colon: A Prospective Multi-center Randomized Study in Asia
• Actual Study Start Date: Mar 1, 2021
• Actual Primary Completion Date: Mar 31, 2022
• Actual Study Completion Date: Apr 15, 2022

Arms and Interventions

Arm	Intervention/Treatment
Experimental: Artificial intelligence-Assisted colonoscopy Tandem colonoscopy of proximal colon assisted with artificial intelligence followed by conventional colonoscopy	Device: Artificial intelligence-Assisted colonoscopy; Artificial intelligence-Assisted colonoscopy for detection of colonic polyp; Procedure: Conventional colonoscopy; Conventional colonoscopy
Active Comparator: Conventional colonoscopy Tandem conventional colonoscopy of proximal colon followed by usual conventional colonoscopy	Procedure: Conventional colonoscopy; Conventional colonoscopy

Outcome Measures

Primary Outcome Measures

1. Proximal adenoma missed rate [One day]

   The proportion of patients with missed adenomas detected in the second examination only

Secondary Outcome Measures

1. Proximal polyp missed rate [One day]

   The proportion of patients with missed adenomas detected in the second examination only

2. Proximal adenoma detection rate [One day]

   The proportion of patients with at least one adenoma

3. Proximal polyp detection [One day]

   The proportion of patients with at least one polyp

Eligibility Criteria

Criteria

• Ages Eligible for Study: 40 Years and Older
• Sexes Eligible for Study: All
• Accepts 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.

Contacts and Locations

Locations

	Site	City	State	Country	Postal Code
1	Queen Mary Hospital	Hong Kong		China
2	Tan Tock Seng Hospital	Singapore		Singapore
3	Institute of Gastroenterology and Hepatology	Hanoi		Vietnam	0

Sponsors and Collaborators

• The University of Hong Kong
• Tan Tock Seng Hospital
• Institute of Gastroenterology and Hepatology, Vietnam

Investigators

• Principal Investigator: Ka Luen, Thomas Lui, MBBS, Queen Mary Hospital, the University of Hong Kong
• Study Director: Wai Keung Leung, MD, Queen Mary Hospital, the University of Hong Kong

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

• Responsible Party: The University of Hong Kong
• ClinicalTrials.gov Identifier: NCT04294355
• Other Study ID Numbers: UW 19-713
• First Posted: Mar 4, 2020
• Last Update Posted: Apr 21, 2022
• Last Verified: Apr 1, 2022

• Individual Participant Data (IPD) Sharing Statement: No
• Plan to Share IPD: No
• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No
• Keywords provided by The University of Hong Kong: Colonoscopy; Artificial intelligence
• Additional relevant MeSH terms: Adenoma

Study Results

No Results Posted as of Apr 21, 2022