Computer-aided Detection During Screening Colonoscopy (Experts)
Real-time Computer-aided Polyp Detection During Screening Colonoscopy Performed by Expert Endoscopists
1 other identifier
interventional
209
1 country
1
Brief Summary
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor). The endoscopy images will be seen on a 27inch, flat-panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned. The number, location, and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare. The same patient will be submitted to a second, the same session, computed aided real-time colonoscopy using the DISCOVERY, AI-assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Apr 2021
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
April 26, 2021
CompletedFirst Submitted
Initial submission to the registry
June 1, 2021
CompletedFirst Posted
Study publicly available on registry
June 7, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
April 30, 2022
CompletedStudy Completion
Last participant's last visit for all outcomes
June 28, 2022
CompletedMarch 31, 2022
March 1, 2022
1 year
June 1, 2021
March 30, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Adenoma detection rate of computer-aided after standard colonoscopy.
Number of examinations with at least one adenoma detected during colonoscopy while using the AI-based model
30 days
Polyp detection rate of computer-aided following standard colonoscopy.
Number of examination with at least one polyp detected while using the AI-based model
30 days
Secondary Outcomes (2)
Polyp miss rate of standard high-definition colonoscopy.
30 days
Adenoma miss rate of standard high-definition colonoscopy.
30 days
Study Arms (1)
Patients for CRC screening and diagnostic colonoscopy
EXPERIMENTALConsecutive patients \>45 years of age submitted for diagnostic colonoscopy
Interventions
Evaluation of the colonic mucosa with a high definition colonoscope (EPKi7010 video processor). The endoscopy images will be seen on a 27inch, flat panel, high-definition LCD monitor (Radiance™ ultraSC-WU27-G1520 model) only by one expert endoscopist, randomly assigned. The number, location and polyps' features (Paris classification) will be recorded by the operator. If a polyp is detected, the endoscopist will remove the polyp endoscopically with a cold snare and forceps biopsy.
The same patient will be submitted to a second, same session, computed aided real-time colonoscopy using the DISCOVERY, AI assisted polyp detector. Colonoscopy will be performed by a same-level-of-expertise operator in comparison to the initial procedure. Any polyp or lesion detected with the AI system will be recorded and endoscopically removed and considered as a missed lesion from standard colonoscopy.
Eligibility Criteria
You may qualify if:
- Provided informed written consent
- Age greater than 45 years of age
- Adequate Bowel preparation
You may not qualify if:
- History of inflammatory bowel disease, familial polyposis syndrome
- History of colorectal carcinoma, colorectal surgery
- History of uncontrolled coagulopathy
- History of previously failed attempt colonoscopy
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Ecuadorian Institute of Digestive Diseases
Guayaquil, Guayas, 090505, Ecuador
Related Publications (2)
Wang P, Berzin TM, Glissen Brown JR, Bharadwaj S, Becq A, Xiao X, Liu P, Li L, Song Y, Zhang D, Li Y, Xu G, Tu M, Liu X. Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut. 2019 Oct;68(10):1813-1819. doi: 10.1136/gutjnl-2018-317500. Epub 2019 Feb 27.
PMID: 30814121BACKGROUNDVinsard DG, Mori Y, Misawa M, Kudo SE, Rastogi A, Bagci U, Rex DK, Wallace MB. Quality assurance of computer-aided detection and diagnosis in colonoscopy. Gastrointest Endosc. 2019 Jul;90(1):55-63. doi: 10.1016/j.gie.2019.03.019. Epub 2019 Mar 26.
PMID: 30926431BACKGROUND
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Carlos Robles-Medranda, MD FASGE
Ecuadorian Institute of Digestive Diseases
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NA
- Masking
- NONE
- Purpose
- DIAGNOSTIC
- Intervention Model
- SINGLE GROUP
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
June 1, 2021
First Posted
June 7, 2021
Study Start
April 26, 2021
Primary Completion
April 30, 2022
Study Completion
June 28, 2022
Last Updated
March 31, 2022
Record last verified: 2022-03
Data Sharing
- IPD Sharing
- Will not share