Actively Recruiting

Phase Not Applicable
Age: 40Years +
All Genders
NCT05863208

Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision

Led by E-DA Hospital · Updated on 2025-06-27

1000

Participants Needed

1

Research Sites

191 weeks

Total Duration

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Sponsors

E

E-DA Hospital

Lead Sponsor

C

Chung Shan Medical University

Collaborating Sponsor

AI-Summary

What this Trial Is About

Adenoma detection rate (ADR) is considered the single most important quality measure in colonoscopy and a higher ADR can reduce the risk of interval colorectal cancer (CRC). Several kinds of new endoscopes and accessories have been accessed to investigate the abilities of improving the ADR. Artificial intelligence (AI) and Endocuff vision are promising new devices to improve the ADR. However, the effect of combining AI and Endocuff vision on ADR remains unclear. The aim of this prospective randomized study is to compare the ADR of AI plus Endocuff vision, AI alone and standard colonoscopy examination.

CONDITIONS

Official Title

Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision

Who Can Participate

Age: 40Years +
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Patients over 20 years old undergoing outpatient sedative colonoscopy at E-Da Hospital, E-Da Cancer Hospital, or Chung Shan Medical University Hospital in Taiwan
Not Eligible

You will not qualify if you...

  • History of inflammatory bowel disease, colorectal cancer, previous bowel resection, Peutz-Jeghers syndrome, familial adenomatous polyposis, or other polyposis syndromes
  • Bleeding tendency
  • Scheduled for endoscopic treatment

AI-Screening

AI-Powered Screening

Complete this quick 3-step screening to check your eligibility

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Trial Site Locations

Total: 1 location

1

E-DA Hospital

Kaohsiung City, Taiwan, 82445

Actively Recruiting

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Research Team

Y

Ying Nan Tsai, MD

CONTACT

W

Wen-Lun Wang, Ph.D

CONTACT

How is the study designed?

Study Type

INTERVENTIONAL

Masking

SINGLE

Allocation

RANDOMIZED

Model

PARALLEL

Primary Purpose

DIAGNOSTIC

Number of Arms

3

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