Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System

Research on the Auxiliary Diagnosis and Treatment System of Digestive Endoscopy Based on Artificial Intelligence: An Efficacy Study of Artificial Intelligence-assisted Colonic Polyp Detection System

This is a randomized controlled multicenter clinical trial of computer-aided detection (CADe) system for the adjuvant diagnosis of intestinal polyps/adenomas ever conducted in a Chinese population. In addition, this study will evaluate the effect of CADe system on adenoma detection of endoscopists under fatigue.

Study Overview

• Status: Completed
• Conditions: Adenoma Colon
• Intervention / Treatment: Device: AI-assisted colonoscopy

• Study Type: Interventional
• Enrollment (Actual): 1906
• Phase: Not Applicable

Contacts and Locations

Study Locations

• China
  • Hunan
    • Changsha, Hunan, China
      • Xiangya Hospital Central South University
    • Loudi, Hunan, China
      • Loudi Central Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

Description

Inclusion Criteria:Patients who need to undergo colonoscopy. -

Exclusion Criteria:Patients with CRC, inflammatory bowel disease, previous colonic resection, and antithrombotic therapy precluding polyp resection were excluded.

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Study Plan

How is the study designed?

Design Details

• Primary Purpose: Diagnostic
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: AI-assisted group; Subjects in this group undergo AI-assisted colonoscopy. The AI-assisted system not only has the function of automatic polyp detection, but also has the function of colonoscopy quality control.	Device: AI-assisted colonoscopy; AI can not only detect suspicious lesions timely, and label them in the field of view of the colonoscopy, but also monitor withdrawal speed and calculate the clean withdrawal time automatically.
No Intervention: control group; Subjects in this group undergo routine colonoscopy.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
adenoma detection rate	The proportion of patients with at least one histologically proven adenoma or carcinoma	up to 2months
withdrawal time compliance rate	The proportion of patients with clean withdrawal time >6min.	up to 2months

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
polyp detection rate	The proportion of patients with at least one polyp.	up to 2 months
adenoma per colonoscopy	The number of adenomas detected per colonoscopy	up to 2 months
polyp per colonoscopy	The number of polys detected per colonoscopy	up to 2 months

Collaborators and Investigators

• Sponsor: Xiangya Hospital of Central South University
• Investigators: Principal Investigator: Xiaowei Liu, doctor, Xiangya Hospital of Central South University

Study record dates

Study Major Dates

• Study Start (Actual): July 25, 2023
• Primary Completion (Actual): September 20, 2023
• Study Completion (Actual): September 30, 2023

Study Registration Dates

• First Submitted: July 4, 2023
• First Submitted That Met QC Criteria: July 4, 2023
• First Posted (Actual): July 12, 2023

Study Record Updates

• Last Update Posted (Estimated): October 10, 2023
• Last Update Submitted That Met QC Criteria: October 9, 2023
• Last Verified: July 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms by Histologic Type; Neoplasms; Neoplasms, Glandular and Epithelial; Pathological Conditions, Anatomical; Polyps; Intestinal Polyps; Adenoma; Colonic Polyps
• Other Study ID Numbers: 202306499

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No