Clinical trial NCT04294355: Artificial Intelligence-assisted Colonoscopy on Detection of Missed Proximal Lesions
Official title: Artificial Intelligence-assisted Colonoscopy Versus Conventional Colonoscopy for Missed Lesions in the Proximal Colon: A Prospective Multi-center Randomized Study in Asia
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Colon Adenoma
Colon Polyp
Keywords: Colonoscopy
Artificial intelligence
Lead sponsor: The University of Hong Kong
Sponsor class: OTHER
Collaborators: name: Tan Tock Seng Hospital
name: Institute of Gastroenterology and Hepatology, Vietnam
First posted: 2020-03-04
Enrollment: 216
Sex: ALL
Minimum age (years): 40
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Intervention model description: Prospective randomized design
Primary purpose: DIAGNOSTIC

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.

Eligibility criteria: 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.

Primary outcomes:
measure: Proximal adenoma missed rate
timeFrame: One day
Secondary outcomes:
measure: Proximal polyp missed rate
timeFrame: One day
measure: Proximal adenoma detection rate
timeFrame: One day
measure: Proximal polyp detection
timeFrame: One day
Other outcomes:
Locations:
city: Hong Kong
country: China
facility: Queen Mary Hospital
city: Singapore
country: Singapore
facility: Tan Tock Seng Hospital
city: Hanoi
country: Vietnam
facility: Institute of Gastroenterology and Hepatology
Study officials:
affiliation: Queen Mary Hospital, the University of Hong Kong
name: Ka Luen, Thomas Lui, MBBS
role: PRINCIPAL_INVESTIGATOR
affiliation: Queen Mary Hospital, the University of Hong Kong
name: Wai Keung Leung, MD
role: STUDY_DIRECTOR
References: