Clinical trial NCT05089071: Effect of Two Colonoscopy AI Systems for Colon Polyp Detection
Official 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
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Adenoma
Colonoscopy
Sessile Serrated Adenoma
Keywords: endoscopist
adenoma detection rate
colonoscopy
artificial intelligence
Lead sponsor: Seoul National University Hospital
Sponsor class: OTHER
Collaborators: name: Seoul National University
First posted: 2021-10-22
Enrollment: 3046
Sex: ALL
Minimum age (years): 45
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: The primary outcome was the comparison of ADR between the control and AI groups according to the intervention system (SCAI vs ENAD system).
Primary purpose: DIAGNOSTIC

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.

Eligibility criteria: 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

Primary outcomes:
measure: Adenoma detection rate
timeFrame: 12 months
measure: Sessile serrated lesion detection rate
timeFrame: 12 months
Secondary outcomes:
measure: polyp detection rate
timeFrame: 12 months
Other outcomes:
Locations:
city: Seoul
country: Korea, Republic of
facility: Healthcare System Gangnam Center, Seoul National University Hospital
Study officials:
affiliation: Seoul National University Hospital
name: Jung Ho Bae, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Hassan C, Spadaccini M, Iannone A, Maselli R, Jovani M, Chandrasekar VT, Antonelli G, Yu H, Areia M, Dinis-Ribeiro M, Bhandari P, Sharma P, Rex DK, Rosch T, Wallace M, Repici A. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta-analysis. Gastrointest Endosc. 2021 Jan;93(1):77-85.e6. doi: 10.1016/j.gie.2020.06.059. Epub 2020 Jun 26.