- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT04945044
Artificial Intelligence Aid Systems in Colorectal Adenoma Detection (INTELAID)
Usefulness of the Endo-AID Artificial Intelligence System in the Detection of Colorectal Adenomas. a Randomized Controlled Trial
The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy.
The secondary aims were:
- To evaluate the benefit of Endo-AID 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.
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
Priority guidelines have been established regarding IA 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 in endoscopists with different adenoma detection rates. In addition, there are no studies with the recent CADe Endo-AID system (Olympus Corp. Tokyo).
The main purpose of the study to evaluate the usefulness of the Endo-AID artificial intelligence system in the detection of colorectal adenomas in consecutive patients for outpatient colonoscopy. 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 four groups: CADe system and high ADR endoscopist; CADe system and low ADR endoscopist; Control and high ADR endoscopist; Control and low ADR endoscopist.
For the sample size calculation a 14.4 of difference in favor of the CADe system was considered. Taking onto account an alpha error of 0.05 in a unilateral contrast, a power of 80% and a loss of 10%, 165 patients per group would be required.
Study Type
Enrollment (Actual)
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
S/C De Tenerife
-
La Laguna, S/C De Tenerife, Spain, 38320
- Department of Gastroenterology
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Age ≥ 18 years.
- Patients referred for outpatient colonoscopy
Exclusion Criteria:
- Colonic resection
- Taking anticoagulants or antiagregants that contraindicate the performance of therapy
- Patients with a recent colonoscopy (<6 months) of good quality (e.g. cited for endoscopic therapy)
- Inflammatory bowel disease
- 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
- Refusal to participate in the study.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Computed adenoma detection system (CADe)
Tis system can detect in the screen suspicion areas of adenomatous polyps.
This is an additional help for the endoscopist for the detection of lesions
|
This is a computed system that helps the endoscopist to increase the detection of colorectal polyps
|
|
Active Comparator: Control group (absence of CADe)
This is the control group.
As in the routine colonoscopy the endoscopist is in charge of the detection of the lesions.
|
It is exclusively the endoscopist in charge of the detection of the polyps (usual practice)
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Adenoma detection rate
Time Frame: [Time frame: 1 years][Designated as safety issue: No]
|
Number of colonoscopies with colorectal adenoma/Number of total colonoscopies
|
[Time frame: 1 years][Designated as safety issue: No]
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Serrated detection rate
Time Frame: [Time Frame: 1 years][Designated as safety issue: No]
|
Number of colonoscopies with serrated adenoma/Number of total colonoscopies
|
[Time Frame: 1 years][Designated as safety issue: No]
|
|
Advanced adenoma detection rate
Time Frame: [Time Frame: 1 years][Designated as safety issue: No]
|
Number of colonoscopies with advanced adenoma/Number of total colonoscopies
|
[Time Frame: 1 years][Designated as safety issue: No]
|
Collaborators and Investigators
Investigators
- Principal Investigator: Antonio Gimeno Garcia, MD, PhD, Hospital Universitario de Canarias
Publications and helpful links
General Publications
- 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.
- Berzin TM, Parasa S, Wallace MB, Gross SA, Repici A, Sharma P. Position statement on priorities for artificial intelligence in GI endoscopy: a report by the ASGE Task Force. Gastrointest Endosc. 2020 Oct;92(4):951-959. doi: 10.1016/j.gie.2020.06.035. Epub 2020 Jun 19.
- Wang P, Liu X, Berzin TM, Glissen Brown JR, Liu P, Zhou C, Lei L, Li L, Guo Z, Lei S, Xiong F, Wang H, Song Y, Pan Y, Zhou G. Effect of a deep-learning computer-aided detection system on adenoma detection during colonoscopy (CADe-DB trial): a double-blind randomised study. Lancet Gastroenterol Hepatol. 2020 Apr;5(4):343-351. doi: 10.1016/S2468-1253(19)30411-X. Epub 2020 Jan 22. Erratum In: Lancet Gastroenterol Hepatol. 2020 Apr;5(4):e3.
- Wang P, Liu P, Glissen Brown JR, Berzin TM, Zhou G, Lei S, Liu X, Li L, Xiao X. Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study. Gastroenterology. 2020 Oct;159(4):1252-1261.e5. doi: 10.1053/j.gastro.2020.06.023. Epub 2020 Jun 17.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Actual)
Study Completion (Actual)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- Computer aid adenoma detection
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.
Clinical Trials on Adenoma Detection Rate
-
Alexandra Hospital, Athens, GreeceCompletedColonoscopy | Adenoma Detection Rate | Adenoma Miss Rate | RetroflexionGreece
-
E-DA HospitalChung Shan Medical UniversityRecruitingAdenoma Detection RateTaiwan
-
Evergreen General Hospital, TaiwanChang Gung Memorial Hospital; E-DA Hospital; E-Da Dachang Hospital; Sepulveda Ambulatory...RecruitingColonoscopy | Adenoma Detection RateUnited States, Taiwan
-
Hospital Universitario de CanariasCompletedAdenoma Detection RateSpain
-
Gastroenterologie Baden-WettingenCompleted
-
Renmin Hospital of Wuhan UniversityUnknownAdenoma Detection RateChina
-
Universitätsklinikum Hamburg-EppendorfCompletedAdenoma Detection RateGermany
-
Technical University of MunichCompleted
-
The First Affiliated Hospital of Zhejiang Chinese...Completed
Clinical Trials on Computed adenoma detection system (CADe)
-
Hospital Universitario de CanariasCompletedAdenoma Detection RateSpain
-
Jagiellonian UniversityRecruitingColonoscopy Diagnostic Techniques and Procedures | Quality Indicators, Health Care | Artificial Intelligence (AI)Poland
-
Verily Life Sciences LLCCompletedColon Adenoma | Colon Polyp | Colon LesionUnited States, Israel
-
Fundacin Biomedica Galicia SurEuropean Regional Development Fund; Ministerio de Ciencia e Innovación, Spain; Asociación Española de Gastroenterología and other collaboratorsCompleted
-
NEC CorporationMeditrial Europe Ltd.; Meditrial USA Inc.CompletedColorectal Cancer | Polyp of Colon | Adenoma ColonItaly, United Kingdom, Germany, United States
-
Chinese University of Hong KongActive, not recruiting
-
Radboud University Medical CenterPENTAX Europe GmbHCompletedAdenoma | Artificial Intelligence | Colonoscopy | Colorectal PolypNetherlands
-
Fundación para el Fomento de la Investigación Sanitaria...University of ValenciaActive, not recruitingInflammatory Bowel Diseases | DysplasiaSpain
-
Cosmo Artificial Intelligence-AI LtdCompletedArtificial IntelligenceItaly
-
National Taiwan University HospitalChanghua Christian Hospital; Fu Jen Catholic University Hospital; Shin Kong Hospital and other collaboratorsRecruitingColorectal Cancer | Colon AdenomaTaiwan