Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision

NCT ID: NCT05863208

Last Updated: 2025-06-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

1000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-05-02

Study Completion Date

2026-12-31

Brief Summary

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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.

Detailed Description

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This is a prospective single-blinded randomized controlled trial of three different types of colonoscopy examinations by 1:1:1 ratio. We use EndoAim AI (ASUS, Taiwan) and Endocuff vision (Olympus, UK) assisted colonoscopy in the first group. We use AI assisted colonoscopy in the 2nd group. We use standard colonoscopy in the 3rd group.

Eligible patients are older than 40 years old and receive colonoscopy for either symptomatic or screening/surveillance. All endoscopists should receive training on EndoAim AI systems and Endocuff vision. During the procedure, experienced endoscopists use high-definition endoscopes (EVIS-EXERA 290 video system, Olympus Optical, Aizu, Japan) under white light and insert to the cecum in the three different groups. The cecal intubation is confirmed by the identification of ileocecal valve and appendiceal orifice.

The Boston Bowel Preparation Scale is used for grading the bowel preparation quality. The size (compared with biopsy forceps), location and morphology of polyps are recorded by the independent endoscopist. All polyps ae removed by either biopsy or polypectomy. The insertion and withdrawal time are measured. The time of the polypectomy site is not included in the withdrawal time.

Conditions

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Adenoma Detection Rate

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

SINGLE

Participants

Study Groups

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Artificial Intelligence-assisted Colonoscopy with Endocuff Vision

Use artificial intelligence-assisted colonoscopy with Endocuff Vision

Group Type ACTIVE_COMPARATOR

Artificial intelligence

Intervention Type DEVICE

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

Endocuff vision

Intervention Type DEVICE

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

High-definition endoscope

Intervention Type 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

Use artificial intelligence-assisted colonoscopy alone

Group Type ACTIVE_COMPARATOR

Artificial intelligence

Intervention Type DEVICE

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

High-definition endoscope

Intervention Type DEVICE

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

Standard colonoscopy

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

Group Type SHAM_COMPARATOR

High-definition endoscope

Intervention Type DEVICE

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

Interventions

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Artificial intelligence

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

Intervention Type DEVICE

Endocuff vision

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

Intervention Type DEVICE

High-definition endoscope

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

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

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

Exclusion Criteria

* 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
Minimum Eligible Age

40 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Chung Shan Medical University

OTHER

Sponsor Role collaborator

E-DA Hospital

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Ying Nan Tsai, MD

Role: STUDY_CHAIR

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

Locations

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E-DA Hospital

Kaohsiung City, , Taiwan

Site Status RECRUITING

Countries

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Taiwan

Central Contacts

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Ying Nan Tsai, MD

Role: CONTACT

+88676150022 ext. 252294

Wen-Lun Wang, Ph.D

Role: CONTACT

+88676150022 ext. 251346

Facility Contacts

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Ying Nan Tsai, M.D

Role: primary

886-7-6150011 ext. 252294

References

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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.

Reference Type BACKGROUND
PMID: 28898920 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 28763808 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 29698990 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 35863686 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 32598963 (View on PubMed)

Other Identifiers

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EMRP53109N

Identifier Type: -

Identifier Source: org_study_id

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