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Artificial Intelligence-assisted System in Colonoscopy

Recruiting
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
Inclusion Criteria
  1. age > 50 years old;
  2. required diagnostic colonoscopy, screening colonoscopy, or follow-up colonoscopy;
  3. voluntarily sign informed consent;
  4. Commitment to abide by the study procedures and cooperate with the implementation of the whole process of the study.
Exclusion Criteria
  1. have participated in other clinical trials, signed informed consent and are in the follow-up period of other clinical trials;
  2. known polyposis syndrome patients;
  3. patients with known IBD;
  4. patients considered by the investigators to be unsuitable or unable to undergo complete digestive endoscopy and related examinations;
  5. 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
GroupInterventionDescription
AI-assisted groupANDOANGELGroup with AI assistance
Primary Outcome Measures
NameTimeMethod
Adenoma detection rateDuring 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
NameTimeMethod
Detection rate of serrated adenomaDuring 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 colonoscopyDuring 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 framesDuring Endoscopy procesure
Polyp detection rateDuring 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 timeDuring 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

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