Evaluation of ArTificial Intelligence System (Gi-Genius) for adenoMa dEtection in Lynch Syndrome.
Timely
1 other identifier
interventional
404
1 country
2
Brief Summary
The purpose of this study is to assess if artificial intelligence aid colonoscopy colonoscopy is superior to conventional colonoscopy for the detection of adenomas during surveillance colonoscopy in patients with Lynch syndrome.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Sep 2021
Typical duration for not_applicable
2 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
May 21, 2021
CompletedFirst Posted
Study publicly available on registry
June 2, 2021
CompletedStudy Start
First participant enrolled
September 13, 2021
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 1, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 1, 2023
CompletedMarch 17, 2022
March 1, 2022
2.2 years
May 21, 2021
March 16, 2022
Conditions
Outcome Measures
Primary Outcomes (1)
Mean number of adenomas per colonoscopy
Compare mean number of adenomas in both arms calculated by dividing the total number of adenomas detected by the total number of colonoscopies in each arm
18 months
Secondary Outcomes (7)
Withdrawal time
18 months
Mean number of polyps per colonoscopy
18 months
Adenoma detection rate
18 months
Polyp detection rate
18 months
False positives in CAD arm
18 months
- +2 more secondary outcomes
Study Arms (2)
CAD arm
ACTIVE COMPARATORPatients allocated to CAD arm will receive during colonoscopy withdrawal high definition white light endoscopy aided with artificial intelligence device (Gi Genius, Medtronic)
WLE arm
PLACEBO COMPARATORPatients allocated to WLE arm will receive during colonoscopy withdrawal high definition white light endoscopy as standart of care.
Interventions
GI geniusTM (Medtronic) is an artificial intelligence device designed and validated on a dataset of white-light endoscopy videos from high-quality randomized controlled trials for the detection of colorectal lesions during colonoscopy. Based on a deep learning system using convolutional neural networks, GI genius works in real-time side-to-side with the gastroenterologist during colonoscopy highlighting the presence of precancerous lesions with a visual marker (green box) in real time and designed to be integrated with the majority of colonoscopies.
High definition white light endoscopy will be used during the scope withdrawal
Eligibility Criteria
You may qualify if:
- Age ≥18 years with a proven pathogenic germline variant in one of the MMR genes (MLH1, MSH2, MSH6) or Epcam deletion who are under surveillance colonoscopy.
You may not qualify if:
- Previous history of total colectomy,
- Concomitant inflammatory bowel disease,
- Inability or refuse to sign the informed consent,
- Previous colonoscopy \< 12 months.
- Inadequate bowel preparation.
- Incomplete procedure.
- PMS2 mutation carriers
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (2)
MarĂa PellisĂ©. MD. PhD.
Barcelona, 08036, Spain
Oswaldo ortiz
Barcelona, 08036, Spain
Related Publications (23)
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PMID: 39033774DERIVED
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- DOUBLE
- Who Masked
- PARTICIPANT, OUTCOMES ASSESSOR
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal Investigator. Attending physician Gastroenterology department.
Study Record Dates
First Submitted
May 21, 2021
First Posted
June 2, 2021
Study Start
September 13, 2021
Primary Completion
December 1, 2023
Study Completion
December 1, 2023
Last Updated
March 17, 2022
Record last verified: 2022-03
Data Sharing
- IPD Sharing
- Will not share