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
1 other identifier
interventional
1,906
1 country
2
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.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jul 2023
Shorter than P25 for not_applicable
2 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
July 4, 2023
CompletedFirst Posted
Study publicly available on registry
July 12, 2023
CompletedStudy Start
First participant enrolled
July 25, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
September 20, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
September 30, 2023
CompletedOctober 10, 2023
July 1, 2023
2 months
July 4, 2023
October 9, 2023
Conditions
Outcome Measures
Primary Outcomes (2)
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 Outcomes (3)
polyp detection rate
up to 2 months
adenoma per colonoscopy
up to 2 months
polyp per colonoscopy
up to 2 months
Study Arms (2)
AI-assisted group
EXPERIMENTALSubjects 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.
control group
NO INTERVENTIONSubjects in this group undergo routine colonoscopy.
Interventions
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.
Eligibility Criteria
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (2)
Xiangya Hospital Central South University
Changsha, Hunan, China
Loudi Central Hospital
Loudi, Hunan, China
Study Officials
- PRINCIPAL INVESTIGATOR
Xiaowei Liu, doctor
Xiangya Hospital of Central South University
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- DOUBLE
- Who Masked
- PARTICIPANT, OUTCOMES ASSESSOR
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
July 4, 2023
First Posted
July 12, 2023
Study Start
July 25, 2023
Primary Completion
September 20, 2023
Study Completion
September 30, 2023
Last Updated
October 10, 2023
Record last verified: 2023-07