Effect of Two Colonoscopy AI Systems for Colon Polyp Detection

Not Applicable

Completed

• Conditions: Colonoscopy; Sessile Serrated Adenoma; Adenoma
• Interventions: Device: Assist by artificial intelligence system for colon polyp detection

• Registration Number: NCT05089071
• Lead Sponsor: Seoul National University Hospital

Brief Summary

Computer-aided detection (CADe) systems have been actively researched for polyp detection in colonoscopy. The investigators aim to identify the effect of two CADe systems according to the system performance on false positive rate

Detailed Description

Artificial intelligence technology based on deep learning is being applied in various medical fields, and research is being actively conducted to develop computer-aided detection (CADe) systems for colonoscopies to overcome the limitation of the variance of human skills. These well-trained CADe systems demonstrated high performance for neoplastic polyp detection and reported a 44% increase in adenoma detection rate (ADR) for endoscopists. However, the level of performance in the CADe system is not clear for expert endoscopists to be useful for ADR increase.

Furthermore, false positives(FPs) of the CADe system may negatively influence ADR during a screening colonoscopy. Accordingly, the investigators sought to identify the effect of the colonoscopy CADe system according to FP performance in endoscopists with various levels. The investigators hypothesized that the CADe system with low FPs would be useful to prevent the decrease in ADR in case of a high endoscopy workload according to the performance of CADe systems.

Study Timeline

• Study First Submitted: 2021-10-11
• Study First Submitted QC: 2021-10-11
• Study First Posted: 2021-10-22
• Study Start: 2021-11-01
• Status Verified: 2022-03
• Primary Completion: 2022-10-31
• Study Completion: 2022-12-31
• Last Update Submitted: 2023-07-25
• Last Update Posted: 2023-07-27

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 3046

Inclusion Criteria

patient for screening or surveillance colonoscopy patients agreed with participating in the study

Exclusion Criteria

patients who do not agree with participating in the study patients with a history of colon resection patients with a history of inflammatory bowel resection patients with poor bowel preparation

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
CADe group	Assist by artificial intelligence system for colon polyp detection	Endoscopists perform colonoscopy with CADe system

Primary Outcome Measures

Name	Time	Method
Sessile serrated lesion detection rate	12 months	proportion of colonoscopies with at least one sessile serrated lesion detected overall and as detected by the physician.
Adenoma detection rate	12 months	proportion of colonoscopies with at least one adenoma detected overall and as detected by the physician.

Secondary Outcome Measures

Name	Time	Method
polyp detection rate	12 months	proportion of colonoscopies with at least one polyp detected overall and as detected by the physician.

Trial Locations

Locations (1)

Healthcare System Gangnam Center, Seoul National University Hospital; 🇰🇷 Seoul, Korea, Republic of