ClinicalTrials.gg
RecruitingNCT05863208Updated Jun 27, 2025

Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision

An interventional study of Artificial intelligence and Endocuff vision in Adenoma Detection Rate, sponsored by E-DA Hospital. Recruiting at 1 site in Taiwan. Open to participants aged 40 Years and older. Per ClinicalTrials.gov, last updated 2025-06-27.

Sponsored by E-DA Hospital · Not applicable, Interventional, and Diagnostic

From the registry’s dates

  • Primary completion was expected by Dec 2025, 10 months ago, but the record still lists the study as recruiting.
  • Started May 2023; still recruiting 3 years 6 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
1,000
Allocation
Randomized
Ages
40 Years and older
Sex
All
01

Study 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.

Read the detailed description

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.

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Conditions studied

  • Adenoma Detection Rate
03

In context

Lead sponsor

E-DA Hospital is the lead sponsor of 35 studies on the registry; 8 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
40 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

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

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
05

Study design

Phase
Not applicable
Primary purpose
Diagnostic
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Single (Participant)
Enrollment
1,000 participants (estimated)

Study arms

  • Active comparator
    Artificial Intelligence-assisted Colonoscopy with Endocuff Vision

    Use artificial intelligence-assisted colonoscopy with Endocuff Vision

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

  • Active comparator
    Artificial Intelligence-assisted Colonoscopy

    Use artificial intelligence-assisted colonoscopy alone

    Device: Artificial intelligence · Device: High-definition endoscope

  • Sham comparator
    Standard colonoscopy

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

    Device: High-definition endoscope

Interventions

  • DeviceArtificial intelligence

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

  • DeviceEndocuff vision

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

  • DeviceHigh-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

06

What researchers measure

Primary outcomes

  1. Adenoma detection rate

    The proportion of patients with at least one adenomas

    Time frame: One month after colonoscopy

Secondary outcomes

  1. Polyp detection rate

    The proportion of patients with at least one polyp

    Time frame: One month after colonoscopy

  2. Sessile serrated adenoma detection rate

    The proportion of patients with at least one sessile serrated adenoma

    Time frame: One month after colonoscopy

  3. Sessile serrated polyps detection rate

    The proportion of patients with at least one sessile serrated polyp

    Time frame: One month after colonoscopy

  4. Advanced adenoma detection rate

    The proportion of patients with at least one advanced adenoma

    Time frame: One month after colonoscopy

  5. Mean number of polyp per patient

    The mean number of polyp per patient

    Time frame: One month after colonoscopy

  6. Mean number of adenoma per patient

    The mean number of adenoma per patient

    Time frame: One month after colonoscopy

  7. Total number of polyp or adenoma per patient

    The total number of polyp or adenoma per patient

    Time frame: One month after colonoscopy

07

Study locations

1 of 1 sites recruiting
08

References and documents

Publications

  • 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. PubMed 28898920 ↗
  • 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. PubMed 28763808 ↗
  • 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. PubMed 29698990 ↗
  • 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. PubMed 35863686 ↗
  • 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. PubMed 32598963 ↗

Individual participant data

Plan to share: No

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reached

Started May 2023 (actual). Primary completion is estimated for Dec 2025, 31 months after the start.

How these figures are worked out, and which studies are left out of them.

Registered
May 9, 2023
First posted
May 17, 2023
StartActual
May 2, 2023
Primary completionEst.
Dec 31, 2025
CompletionEst.
Dec 31, 2026
Last update
Jun 27, 2025
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Jun 27, 2025, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT05863208
Lead sponsor
E-DA Hospital
Responsible party
Sponsor
First posted
May 17, 2023
Start date
May 2, 2023
Primary completion
Dec 31, 2025 (estimated)
Completion
Dec 31, 2026 (estimated)
Last update
Jun 27, 2025

Study contacts

Ying Nan Tsai, MD
Contact
littlepig9933@gmail.com
+88676150022 ext. 252294
Wen-Lun Wang, Ph.D
Contact
warrengodr@gmail.com
+88676150022 ext. 251346
Ying Nan Tsai, MD
study chair · Division of Gastroenterology and Hepatology, E-Da Cancer Hospital, Kaohsiung, Taiwan

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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