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Completed

NCT Number: NCT05089071

Effect of Two Colonoscopy AI Systems for Colon Polyp Detection

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

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Key information

Conditions

Adenoma Colonoscopy Neoplasms Neoplasms by Histologic Type Neoplasms, Glandular and Epithelial Sessile Serrated Adenoma

Age range

45 year–100 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Healthcare System Gangnam Center, Seoul National University Hospital

Seoul, South Korea

About this study

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.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

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

Treatment and study plan

Assist by artificial intelligence system for colon polyp detection

Device

Assist by artificial intelligence system for colon polyp detection

Primary outcomes

  1. Adenoma detection rate

    Time frame: 12 months

    proportion of colonoscopies with at least one adenoma detected overall and as detected by the physician.

  2. Sessile serrated lesion detection rate

    Time frame: 12 months

    proportion of colonoscopies with at least one sessile serrated lesion detected overall and as detected by the physician.

Secondary outcomes

  1. polyp detection rate

    Time frame: 12 months

    proportion of colonoscopies with at least one polyp detected overall and as detected by the physician.

Sponsors and collaborators

Lead sponsor

Seoul National University Hospital

Other

Collaborators

  • Seoul National University

Registry information

Official study title

Effect of Two Colonoscopy AI Systems for Colon Polyp Detection According to the False Positive Rates of the Systems: A Single-center Prospective Study

Important dates

Study start
2021
Primary completion
2022
Study completion
2022
First posted
Oct 22, 2021
Registry last updated
Jul 27, 2023

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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