Real-Time Artificial Intelligence Assissted Colonoscopy to Identify and Classify Polyps

Not Applicable

Completed

• Conditions: Artificial Intelligence; Colonoscopy; Quality Control

• Registration Number: NCT05718193
• Lead Sponsor: Xiangya Hospital of Central South University

Brief Summary

To investigate the degree of the real-time detection and classification system for increasing the adenoma detection rate during colonoscopy.

Detailed Description

Not available

Study Timeline

• Study Start: 2022-06-01
• Status Verified: 2023-01
• Study First Submitted: 2023-01-03
• Study First Submitted QC: 2023-01-29
• Study First Posted: 2023-02-08
• Primary Completion: 2023-02-28
• Study Completion: 2023-03-15
• Last Update Submitted: 2023-04-09
• Last Update Posted: 2023-04-11

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 2868

Inclusion Criteria

Aged 18 to 85 years old. Colonoscopies for primary CRC screening of the subjects are required.

Exclusion Criteria

History of CRC,inflammatory bowel disease, previous colonic resection, antithrombotic therapy precluding polyp resection.

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Primary Outcome Measures

Name	Time	Method
adenoma detection rate	up to 9 months	Percentage of patients who have 1 or more histologically confirmed adenoma resected divided by the total number of colonoscopies.
adenomas per colonoscopy	up to 9 months	Total number of histologically confirmed adenomas resected divided by the total number of colonoscopies.

Trial Locations

Locations (2)

Xiangya Hospital Central South University; 🇨🇳 Changsha, Hunan, China

Loudi Central Hospital; 🇨🇳 Loudi, Hunan, China