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NCT Number: NCT04294355

Artificial Intelligence-assisted Colonoscopy on Detection of Missed Proximal Lesions

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

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Key information

Age range

40 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Queen Mary Hospital, Hong Kong, China

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About this study

Centers

  • Queen Mary Hospital, Hong Kong, China (Co-ordinating Center)
  • Tan Tock Seng Hospital, Singapore, Singapore
  • 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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

Artificial intelligence-Assisted colonoscopy

Device

Artificial intelligence-Assisted colonoscopy for detection of colonic polyp

Conventional colonoscopy

Procedure

Conventional colonoscopy

Primary outcomes

  1. Proximal adenoma missed rate

    Time frame: One day

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

Secondary outcomes

  1. Proximal polyp missed rate

    Time frame: One day

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

  2. Proximal adenoma detection rate

    Time frame: One day

    The proportion of patients with at least one adenoma

  3. Proximal polyp detection

    Time frame: One day

    The proportion of patients with at least one polyp

Sponsors and collaborators

Lead sponsor

The University of Hong Kong

Other

Collaborators

  • Institute of Gastroenterology and Hepatology, Vietnam
  • Tan Tock Seng Hospital

Registry information

Official study title

Artificial Intelligence-assisted Colonoscopy Versus Conventional Colonoscopy for Missed Lesions in the Proximal Colon: A Prospective Multi-center Randomized Study in Asia

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Mar 4, 2020
Registry last updated
Apr 21, 2022

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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