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Artificial Intelligence Aid Systems and Endocuff in Colorectal Adenoma Detection (CUFFAID)

Primary Purpose

Adenoma Detection Rate

Status
Not yet recruiting
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Computed adenoma detection system (CADe) plus endocuff
Endocuff
Sponsored by
Hospital Universitario de Canarias
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Adenoma Detection Rate

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  • Age ≥ 18 years.
  • Patients referred for outpatient colonoscopy

Exclusion Criteria:

  • Colonic resection
  • Taking anticoagulants or antiaggregants that contraindicate the performance of therapy
  • Patients with a recent colonoscopy (<6 months) of good quality (e.g. cited for endoscopic therapy)
  • IBD
  • Patients with incomplete colonoscopy
  • Patients with inadequate preparation using the Boston Colonic Preparation Scale (BBPS). A cleaning quality of less than 2 points in any of the 3 colonic sections will be considered inadequate.
  • Patients with polyposis syndromes

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Experimental

    Active Comparator

    Arm Label

    Computed adenoma detection system (CADe) and Endocuff

    Control group (Endocuff)

    Arm Description

    CADe system can detect in the screen suspicion areas of adenomatous polyps. This is an additional help for the endoscopist for the detection of lesions. Endocuff increases the colonic surface examinated

    Endocuff increases the colonic surface examinated

    Outcomes

    Primary Outcome Measures

    Adenoma detection rate
    (number of colonoscopies with adenoma/number of colonoscopies)

    Secondary Outcome Measures

    Serrated detection rate
    (number of colonoscopies with serrated adenoma/number of colonoscopies)
    Advanced adenoma detection rate
    (number of colonoscopies with advanced adenomas/number of colonoscopies)

    Full Information

    First Posted
    November 19, 2021
    Last Updated
    November 19, 2021
    Sponsor
    Hospital Universitario de Canarias
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    1. Study Identification

    Unique Protocol Identification Number
    NCT05141773
    Brief Title
    Artificial Intelligence Aid Systems and Endocuff in Colorectal Adenoma Detection
    Acronym
    CUFFAID
    Official Title
    Computer-assisted Adenoma Detection Coloscopy With Endo-AID Artificial Intelligence System and Endocuff Versus Endocuff Assisted Colonoscopy: a Randomized Controlled Trial
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    November 2021
    Overall Recruitment Status
    Not yet recruiting
    Study Start Date
    November 22, 2021 (Anticipated)
    Primary Completion Date
    February 28, 2022 (Anticipated)
    Study Completion Date
    February 28, 2022 (Anticipated)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor
    Name of the Sponsor
    Hospital Universitario de Canarias

    4. Oversight

    Studies a U.S. FDA-regulated Drug Product
    No
    Studies a U.S. FDA-regulated Device Product
    No
    Data Monitoring Committee
    No

    5. Study Description

    Brief Summary
    The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system combined with endocuff compared with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy. The secondary aims were: To evaluate the benefit of Endo-AID and endocuff in adenoma detection rate by comparing endoscopists with high and low adenoma detection rate. To evaluate serrated detection rate, advanced adenoma detection rate, adenoma detection rate according to the size (<= 5mm, 6-9mm,> = 10mm) and number of adenomas by colonoscopy. Stratification by location and morphology.
    Detailed Description
    Guidelines have been established regarding artificial intelligence (AI) applied to gastrointestinal endoscopy. Regarding the priority uses for their development, there are applications that improve vision, placing computer-assisted lesion detection (CADe) as one of the most necessary priorities, given the importance of colorectal cancer screening (CRC) and post-polypectomy surveillance. The evaluation of these systems in different clinical practices and patient groups has been recommend. In this regard, studies in the western population are limited and have been carried out by expert endoscopists. It has not been evaluated comparing with other strategies such as add-on devices. In addition, there are no studies with the recent CADe Endo-AID system (Olympus Corp. Tokyo). The main purpose of the study is to evaluate the usefulness of the Endo-AID artificial intelligence system with endocuff in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy compared with standard colonoscopy with endocuff. In addition, the benefit of the CADe system will be assessed according to the endoscopist ADR. A randomized controlled trial will be carried out in consecutive outpatients meeting the inclusion criteria and none of the exclusion criteria. Patients with be randomized to one of the two groups: CADe system with endocuff and standard colonoscopy with endocuff.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Adenoma Detection Rate

    7. Study Design

    Primary Purpose
    Diagnostic
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Masking
    None (Open Label)
    Allocation
    Randomized
    Enrollment
    696 (Anticipated)

    8. Arms, Groups, and Interventions

    Arm Title
    Computed adenoma detection system (CADe) and Endocuff
    Arm Type
    Experimental
    Arm Description
    CADe system can detect in the screen suspicion areas of adenomatous polyps. This is an additional help for the endoscopist for the detection of lesions. Endocuff increases the colonic surface examinated
    Arm Title
    Control group (Endocuff)
    Arm Type
    Active Comparator
    Arm Description
    Endocuff increases the colonic surface examinated
    Intervention Type
    Device
    Intervention Name(s)
    Computed adenoma detection system (CADe) plus endocuff
    Intervention Description
    This is a computed system that helps the endoscopist to increase the detection of colorectal polyps. An add-on device (Endocuff) is also incorporated to the tip of the colonoscope
    Intervention Type
    Device
    Intervention Name(s)
    Endocuff
    Intervention Description
    An add-on device (Endocuff) is also incorporated to the tip of the colonoscope
    Primary Outcome Measure Information:
    Title
    Adenoma detection rate
    Description
    (number of colonoscopies with adenoma/number of colonoscopies)
    Time Frame
    1 year
    Secondary Outcome Measure Information:
    Title
    Serrated detection rate
    Description
    (number of colonoscopies with serrated adenoma/number of colonoscopies)
    Time Frame
    1 year
    Title
    Advanced adenoma detection rate
    Description
    (number of colonoscopies with advanced adenomas/number of colonoscopies)
    Time Frame
    1 year

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: Age ≥ 18 years. Patients referred for outpatient colonoscopy Exclusion Criteria: Colonic resection Taking anticoagulants or antiaggregants that contraindicate the performance of therapy Patients with a recent colonoscopy (<6 months) of good quality (e.g. cited for endoscopic therapy) IBD Patients with incomplete colonoscopy Patients with inadequate preparation using the Boston Colonic Preparation Scale (BBPS). A cleaning quality of less than 2 points in any of the 3 colonic sections will be considered inadequate. Patients with polyposis syndromes
    Central Contact Person:
    First Name & Middle Initial & Last Name or Official Title & Degree
    Antonio Z Gimeno García, MD, PhD
    Phone
    34-922678039
    Email
    antozeben@gmail.com
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Antonio Z García, MD, PhD
    Organizational Affiliation
    Hospital Universitario de Canarias
    Official's Role
    Principal Investigator

    12. IPD Sharing Statement

    Plan to Share IPD
    No
    Citations:
    PubMed Identifier
    29363535
    Citation
    Ngu WS, Bevan R, Tsiamoulos ZP, Bassett P, Hoare Z, Rutter MD, Clifford G, Totton N, Lee TJ, Ramadas A, Silcock JG, Painter J, Neilson LJ, Saunders BP, Rees CJ. Improved adenoma detection with Endocuff Vision: the ADENOMA randomised controlled trial. Gut. 2019 Feb;68(2):280-288. doi: 10.1136/gutjnl-2017-314889. Epub 2018 Jan 23.
    Results Reference
    background
    PubMed Identifier
    32371116
    Citation
    Repici A, Badalamenti M, Maselli R, Correale L, Radaelli F, Rondonotti E, Ferrara E, Spadaccini M, Alkandari A, Fugazza A, Anderloni A, Galtieri PA, Pellegatta G, Carrara S, Di Leo M, Craviotto V, Lamonaca L, Lorenzetti R, Andrealli A, Antonelli G, Wallace M, Sharma P, Rosch T, Hassan C. Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology. 2020 Aug;159(2):512-520.e7. doi: 10.1053/j.gastro.2020.04.062. Epub 2020 May 1.
    Results Reference
    background
    PubMed Identifier
    33403235
    Citation
    Aziz M, Haghbin H, Gangwani MK, Sharma S, Nawras Y, Khan Z, Chandan S, Mohan BP, Lee-Smith W, Nawras A. Efficacy of Endocuff Vision compared to first-generation Endocuff in adenoma detection rate and polyp detection rate in high-definition colonoscopy: a systematic review and network meta-analysis. Endosc Int Open. 2021 Jan;9(1):E41-E50. doi: 10.1055/a-1293-7327. Epub 2021 Jan 1.
    Results Reference
    background
    PubMed Identifier
    33816771
    Citation
    Ashat M, Klair JS, Singh D, Murali AR, Krishnamoorthi R. Impact of real-time use of artificial intelligence in improving adenoma detection during colonoscopy: A systematic review and meta-analysis. Endosc Int Open. 2021 Apr;9(4):E513-E521. doi: 10.1055/a-1341-0457. Epub 2021 Mar 17.
    Results Reference
    background
    PubMed Identifier
    32557490
    Citation
    Barua I, Vinsard DG, Jodal HC, Loberg M, Kalager M, Holme O, Misawa M, Bretthauer M, Mori Y. Artificial intelligence for polyp detection during colonoscopy: a systematic review and meta-analysis. Endoscopy. 2021 Mar;53(3):277-284. doi: 10.1055/a-1201-7165. Epub 2020 Sep 29.
    Results Reference
    background
    PubMed Identifier
    32598963
    Citation
    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.
    Results Reference
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