NCT05963724
Completed
Not Applicable
Efficacy of Real-Time Computer Aided-Detected of Colonic Neoplasia in an Underserved Population, A Randomized Controlled Trial
Riverside University Health System Medical Center1 site in 1 country1,100 target enrollmentSeptember 1, 2022
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Colorectal Cancer
- Sponsor
- Riverside University Health System Medical Center
- Enrollment
- 1100
- Locations
- 1
- Primary Endpoint
- Adenoma Detection Rate
- Status
- Completed
- Last Updated
- 2 years ago
Overview
Brief Summary
This study assesses the sensitivity and added benefits of computer-aided detection compared to standard care (white-light) in detecting colon polyps in patients undergoing colonoscopy.
Detailed Description
Failure in polyp detection leads to colon cancer after colonoscopy. Artificial intelligence systems allow real-time computer-aided detection of polyps with high-accuracy. This study will compare GI-Genius, a real-time CAD system to standard colonoscopy in terms of how many colonoscopies detect an adenoma.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Undergoing colonoscopy at RUHS
- •Age \> 45 years
- •No contraindications to colonoscopy
Exclusion Criteria
- •Prior history of subtotal colectomy
Outcomes
Primary Outcomes
Adenoma Detection Rate
Time Frame: 1 year
Secondary Outcomes
- False Neoplasia Rate(1 year)
- Sessile Serrated Lesions Per Colon(1 year)
- Sessile Serrated Lesion Detection Rate(1 year)
- Withdrawal Time(1 year)
- Adenomas Per Colon(1 year)
Study Sites (1)
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