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Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System

Primary Purpose

Adenoma Colon

Status
Completed
Phase
Not Applicable
Locations
China
Study Type
Interventional
Intervention
AI-assisted colonoscopy
Sponsored by
Xiangya Hospital of Central South University
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional diagnostic trial for Adenoma Colon

Eligibility Criteria

18 Years - 85 Years (Adult, Older Adult)All SexesAccepts Healthy Volunteers

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. -

Sites / Locations

  • Xiangya Hospital Central South University
  • Loudi Central Hospital

Arms of the Study

Arm 1

Arm 2

Arm Type

Experimental

No Intervention

Arm Label

AI-assisted group

control group

Arm Description

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.

Subjects in this group undergo routine colonoscopy.

Outcomes

Primary Outcome Measures

adenoma detection rate
The proportion of patients with at least one histologically proven adenoma or carcinoma
withdrawal time compliance rate
The proportion of patients with clean withdrawal time >6min.

Secondary Outcome Measures

polyp detection rate
The proportion of patients with at least one polyp.
adenoma per colonoscopy
The number of adenomas detected per colonoscopy
polyp per colonoscopy
The number of polys detected per colonoscopy

Full Information

First Posted
July 4, 2023
Last Updated
October 9, 2023
Sponsor
Xiangya Hospital of Central South University
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1. Study Identification

Unique Protocol Identification Number
NCT05941689
Brief Title
Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System
Official Title
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
Study Type
Interventional

2. Study Status

Record Verification Date
July 2023
Overall Recruitment Status
Completed
Study Start Date
July 25, 2023 (Actual)
Primary Completion Date
September 20, 2023 (Actual)
Study Completion Date
September 30, 2023 (Actual)

3. Sponsor/Collaborators

Responsible Party, by Official Title
Sponsor
Name of the Sponsor
Xiangya Hospital of Central South University

4. Oversight

Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No

5. Study Description

Brief Summary
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.

6. Conditions and Keywords

Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Adenoma Colon

7. Study Design

Primary Purpose
Diagnostic
Study Phase
Not Applicable
Interventional Study Model
Parallel Assignment
Masking
ParticipantOutcomes Assessor
Allocation
Randomized
Enrollment
1906 (Actual)

8. Arms, Groups, and Interventions

Arm Title
AI-assisted group
Arm Type
Experimental
Arm Description
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.
Arm Title
control group
Arm Type
No Intervention
Arm Description
Subjects in this group undergo routine colonoscopy.
Intervention Type
Device
Intervention Name(s)
AI-assisted colonoscopy
Intervention Description
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.
Primary Outcome Measure Information:
Title
adenoma detection rate
Description
The proportion of patients with at least one histologically proven adenoma or carcinoma
Time Frame
up to 2months
Title
withdrawal time compliance rate
Description
The proportion of patients with clean withdrawal time >6min.
Time Frame
up to 2months
Secondary Outcome Measure Information:
Title
polyp detection rate
Description
The proportion of patients with at least one polyp.
Time Frame
up to 2 months
Title
adenoma per colonoscopy
Description
The number of adenomas detected per colonoscopy
Time Frame
up to 2 months
Title
polyp per colonoscopy
Description
The number of polys detected per colonoscopy
Time Frame
up to 2 months

10. Eligibility

Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
85 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
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. -
Overall Study Officials:
First Name & Middle Initial & Last Name & Degree
Xiaowei Liu, doctor
Organizational Affiliation
Xiangya Hospital of Central South University
Official's Role
Principal Investigator
Facility Information:
Facility Name
Xiangya Hospital Central South University
City
Changsha
State/Province
Hunan
Country
China
Facility Name
Loudi Central Hospital
City
Loudi
State/Province
Hunan
Country
China

12. IPD Sharing Statement

Learn more about this trial

Efficacy of Artificial Intelligence-assisted Colonic Polyp Detection System

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