Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision

NCT05863208 | Recruiting DMC

• 1 other identifier: EMRP53109N
• Study Type: interventional
• Target: 1,000
• Locations: 1 country
• Sites: 1

Brief Summary

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

Adenoma Detection Rate

Outcome Measures

Primary Outcomes (1)

• Adenoma detection rate

  The proportion of patients with at least one adenomas

  One month after colonoscopy

Secondary Outcomes (7)

• Polyp detection rate

  One month after colonoscopy

• Sessile serrated adenoma detection rate

  One month after colonoscopy

• Sessile serrated polyps detection rate

  One month after colonoscopy

• Advanced adenoma detection rate

  One month after colonoscopy

• Mean number of polyp per patient

  One month after colonoscopy

Study Arms (3)

Artificial Intelligence-assisted Colonoscopy with Endocuff Vision

ACTIVE COMPARATOR

Use artificial intelligence-assisted colonoscopy with Endocuff Vision

Device: Artificial intelligence; Device: Endocuff vision; Device: High-definition endoscope

Artificial Intelligence-assisted Colonoscopy

ACTIVE COMPARATOR

Use artificial intelligence-assisted colonoscopy alone

Device: Artificial intelligence; Device: High-definition endoscope

Standard colonoscopy

SHAM COMPARATOR

Use standard colonoscopy without artificial intelligence-assisted colonoscopy or Endocuff Vision

Device: High-definition endoscope

Interventions

Artificial intelligence DEVICE

ASUS EndoAim AI Endoscopy System (ASUS, Taiwan) is used to help the detection of colon adenoma

Artificial Intelligence-assisted Colonoscopy; Artificial Intelligence-assisted Colonoscopy with Endocuff Vision

Endocuff vision DEVICE

Endocuff vision (Olympus, UK) is used to help the detection of colon adenoma

Artificial Intelligence-assisted Colonoscopy with Endocuff Vision

High-definition endoscope DEVICE

High-definition endoscope (EVIS-EXERA 290 video system, Olympus Optical, Aizu, Japan) is used under white light for the detection of colon adenoma

Artificial Intelligence-assisted Colonoscopy; Artificial Intelligence-assisted Colonoscopy with Endocuff Vision; Standard colonoscopy

Eligibility Criteria

• Age: 40 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Patients over 20 years old are undergoing outpatient sedative colonoscopy in the E-Da Hospital, E-Da cancer Hospital and Chung Shan Medical University Hospital in Taiwan

You may not qualify if:

• A prior history of of inflammatory bowel disease, colorectal cancer, previous bowel resection, Peutz-Jeghers syndrome, familial adenomatous polyposis or other polyposis syndromes
• Bleeding tendency
• For scheduled endoscopic treatment

Sponsors & Collaborators

• E-DA Hospital: lead
• Chung Shan Medical University: collaborator

Study Sites (1)

E-DA Hospital

Kaohsiung City, 82445, Taiwan

RECRUITING

Related Publications (5)

• Gonzalez-Fernandez C, Garcia-Rangel D, Aguilar-Olivos NE, Barreto-Zuniga R, Romano-Munive AF, Grajales-Figueroa G, Zamora-Nava LE, Tellez-Avila FI. Higher adenoma detection rate with the endocuff: a randomized trial. Endoscopy. 2017 Nov;49(11):1061-1068. doi: 10.1055/s-0043-117879. Epub 2017 Sep 12.

  PMID: 28898920 BACKGROUND

• Triantafyllou K, Polymeros D, Apostolopoulos P, Lopes Brandao C, Gkolfakis P, Repici A, Papanikolaou IS, Dinis-Ribeiro M, Alexandrakis G, Hassan C. Endocuff-assisted colonoscopy is associated with a lower adenoma miss rate: a multicenter randomized tandem study. Endoscopy. 2017 Nov;49(11):1051-1060. doi: 10.1055/s-0043-114412. Epub 2017 Aug 1.

  PMID: 28763808 BACKGROUND

• Williet N, Tournier Q, Vernet C, Dumas O, Rinaldi L, Roblin X, Phelip JM, Pioche M. Effect of Endocuff-assisted colonoscopy on adenoma detection rate: meta-analysis of randomized controlled trials. Endoscopy. 2018 Sep;50(9):846-860. doi: 10.1055/a-0577-3500. Epub 2018 Apr 26.

  PMID: 29698990 BACKGROUND

• Xu H, Tang RSY, Lam TYT, Zhao G, Lau JYW, Liu Y, Wu Q, Rong L, Xu W, Li X, Wong SH, Cai S, Wang J, Liu G, Ma T, Liang X, Mak JWY, Xu H, Yuan P, Cao T, Li F, Ye Z, Shutian Z, Sung JJY. Artificial Intelligence-Assisted Colonoscopy for Colorectal Cancer Screening: A Multicenter Randomized Controlled Trial. Clin Gastroenterol Hepatol. 2023 Feb;21(2):337-346.e3. doi: 10.1016/j.cgh.2022.07.006. Epub 2022 Jul 19.

  PMID: 35863686 BACKGROUND

• Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.

  PMID: 32598963 BACKGROUND

Study Officials

• Ying Nan Tsai, MD

  Division of Gastroenterology and Hepatology, E-Da Cancer Hospital, Kaohsiung, Taiwan

  STUDY CHAIR

Central Study Contacts

Ying Nan Tsai, MD

CONTACT

+88676150022; littlepig9933@gmail.com

Wen-Lun Wang, Ph.D

CONTACT

+88676150022; warrengodr@gmail.com

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 9, 2023
• First Posted: May 17, 2023
• Study Start: May 2, 2023
• Primary Completion: December 31, 2025
• Study Completion (Estimated): December 31, 2026
• Last Updated: June 27, 2025

Record last verified: 2025-05

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)