Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial intelligence, Endocuff vision, High-definition endoscope.
- Who it may be relevant to
- Registry conditions: Adenoma Detection Rate. Basic parameters: from 40 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Taiwan
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Comparison of The Adenoma Detection Rate Between Artificial Intelligence-assisted Colonoscopy With or Without Endocuff Vision and Standard Colonscopy: A Randomized Controlled Study
Overview
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
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.
Interventions
- Device Artificial intelligence
ASUS EndoAim AI Endoscopy System (ASUS, Taiwan) is used to help the detection of colon adenoma - Device Endocuff vision
Endocuff vision (Olympus, UK) is used to help the detection of colon adenoma - 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
Primary outcome measures
- Adenoma detection rate [Time frame: One month after colonoscopy]
Secondary outcome measures (7)
- Polyp detection rate [Time frame: One month after colonoscopy]
- Sessile serrated adenoma detection rate [Time frame: One month after colonoscopy]
- Sessile serrated polyps detection rate [Time frame: One month after colonoscopy]
- Advanced adenoma detection rate [Time frame: One month after colonoscopy]
- Mean number of polyp per patient [Time frame: One month after colonoscopy]
- Mean number of adenoma per patient [Time frame: One month after colonoscopy]
- Total number of polyp or adenoma per patient [Time frame: One month after colonoscopy]
Eligibility criteria
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
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- Randomized
- Model
- Parallel assignment
- Masking
- Single blind
- Primary purpose
- Diagnostic
Study locations
Taiwan · 1 center
- E-DA Hospital — Kaohsiung City
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. PMID 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. PMID 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. PMID 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 202 PMID 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. PMID 32598963
Identifiers
NCT: NCT05863208 · EMRP53109N