Real-Time Artificial Intelligence Assissted Colonoscopy to Identify and Classify Polyps
1 other identifier
interventional
2,868
1 country
2
Brief Summary
To investigate the degree of the real-time detection and classification system for increasing the adenoma detection rate during colonoscopy.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for not_applicable
Started Jun 2022
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
Study Start
First participant enrolled
June 1, 2022
CompletedFirst Submitted
Initial submission to the registry
January 3, 2023
CompletedFirst Posted
Study publicly available on registry
February 8, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
February 28, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
March 15, 2023
CompletedApril 11, 2023
January 1, 2023
9 months
January 3, 2023
April 9, 2023
Conditions
Outcome Measures
Primary Outcomes (2)
adenoma detection rate
Percentage of patients who have 1 or more histologically confirmed adenoma resected divided by the total number of colonoscopies.
up to 9 months
adenomas per colonoscopy
Total number of histologically confirmed adenomas resected divided by the total number of colonoscopies.
up to 9 months
Study Arms (3)
The DeFrame Group
EXPERIMENTALSubjects in the DeFrame group were treated with a real-time computer-aided polyp detection system named DeFrame during colonoscopy.
The Classified DeFrame Group
EXPERIMENTALSubjects in the Classified DeFrame group were treated with a real-time computer-aided polyp detection and classification system named Classified DeFrame during colonoscopy.
The Control Group
EXPERIMENTALSubjects in the control group underwent standard colonoscopy.
Interventions
The DeFrame system is applicated during colonoscopy. The DeFrame system superimposes a rectangular box on the polyp lesion area in the colonoscopy field of view, notifying the endoscopists of the presence of the lesion.
The Classified DeFrame system is applicated during colonoscopy. The Classified DeFrame system superimposes a rectangular box on the polyp lesion area in the colonoscopy field of view, the color of the rectangle box will turn blue when the polyp is considered as an adenoma, notifying the endoscopists of the presence of the lesion.
Eligibility Criteria
You may qualify if:
- Aged 18 to 85 years old. Colonoscopies for primary CRC screening of the subjects are required.
You may not qualify if:
- History of CRC,inflammatory bowel disease, previous colonic resection, antithrombotic therapy precluding polyp resection.
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
- STUDY DIRECTOR
xiaowei liu, doctor
Xiangya Hospital of Central South University
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- RANDOMIZED
- Masking
- SINGLE
- Who Masked
- PARTICIPANT
- Purpose
- DIAGNOSTIC
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
January 3, 2023
First Posted
February 8, 2023
Study Start
June 1, 2022
Primary Completion
February 28, 2023
Study Completion
March 15, 2023
Last Updated
April 11, 2023
Record last verified: 2023-01
Data Sharing
- IPD Sharing
- Will not share