Artificial Intelligence-assisted System in Colonoscopy
- Conditions
- Adenoma Colon Polyp
- Interventions
- Device: ANDOANGEL
- Registration Number
- NCT06406062
- Lead Sponsor
- Renmin Hospital of Wuhan University
- Brief Summary
In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. In recent years, computer-aided diagnosis system based on artificial intelligence (AI) has been used in colorectal polyp detection. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.
This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study. However, whether AI-assisted can improve the adenoma-detection rate (ADR) is inconclusive. This study aims to evaluate the real-world performance of an AI system that combines polyp detection with colonoscopy quality control.
This study aims to explore the clinical application value of AI-based polyp detection and quality control function by comparing the data of polyp detection rate and adenoma detection rate in multiple centers with and without AI-assisted colonoscopy in a multicenter, prospective real world study.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- RECRUITING
- Sex
- All
- Target Recruitment
- 7500
- age > 50 years old;
- required diagnostic colonoscopy, screening colonoscopy, or follow-up colonoscopy;
- voluntarily sign informed consent;
- Commitment to abide by the study procedures and cooperate with the implementation of the whole process of the study.
- have participated in other clinical trials, signed informed consent and are in the follow-up period of other clinical trials;
- known polyposis syndrome patients;
- patients with known IBD;
- patients considered by the investigators to be unsuitable or unable to undergo complete digestive endoscopy and related examinations;
- high-risk diseases or other special conditions considered by the investigator to be unsuitable for clinical trial participation.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Arm && Interventions
Group Intervention Description AI-assisted group ANDOANGEL Group with AI assistance
- Primary Outcome Measures
Name Time Method Adenoma detection rate During Endoscopy procesure The numerator is the number of patients who had at least one adenoma on colonoscopy, and the denominator is the total number of patients who underwent colonoscopy
- Secondary Outcome Measures
Name Time Method Detection rate of serrated adenoma During Endoscopy procesure The numerator is the number of patients who had at least one serrated adenoma on colonoscopy, and the denominator is the total number of patients who underwent colonoscopy
Average number of polyps per colonoscopy During Endoscopy procesure The numerator is the total number of polyps detected by colonoscopy, and the denominator is the total number of colonoscopies
Proportion of over-speed frames During Endoscopy procesure Polyp detection rate During Endoscopy procesure The numerator is the number of patients who had at least one polyp on colonoscopy, and the denominator is the total number of patients who underwent colonoscopy
Colonoscopy time During Endoscopy procesure The pure negative time of the whole examination did not include the time of endoscopy entry and the time of biopsy
Trial Locations
- Locations (1)
Renmin Hospital of Wuhan Univercity
🇨🇳Wuhan, Hubei, China