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
About this trial
This is an interventional diagnostic trial for Adenoma Detection Rate
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
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
NCT ID
NCT05141773
First Posted
November 19, 2021
Last Updated
November 19, 2021
Sponsor
Hospital Universitario de Canarias
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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Artificial Intelligence Aid Systems and Endocuff in Colorectal Adenoma Detection
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