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Outcomes of Artificial Intelligence-Enhanced Colonoscopy in a Tertiary Clinical Setting
Kapil D Nayar1, Abdelrahman Yakout2, Nader Bakheet2
1Department of Gastroenterology and Hepatology, Mayo Clinic Florida, Jacksonville, Florida, USA.
The American Journal of Gastroenterology
|February 12, 2026
Summary
Computer-aided detection (CADe) systems significantly improved adenoma and polyp detection rates during colonoscopies. However, the clinical significance of detecting smaller polyps with CADe requires further investigation to confirm its impact on reducing colorectal cancer.
Area of Science:
- Gastroenterology
- Medical technology
- Artificial intelligence in medicine
Background:
- Colonoscopies are crucial for colorectal cancer (CRC) screening, but detecting all precancerous lesions remains a challenge.
- Operator fatigue and subtle lesions can lead to missed adenomas, necessitating tools to standardize detection quality.
- Computer-aided detection (CADe) systems offer a potential solution by leveraging AI to enhance lesion identification during colonoscopies.
Purpose of the Study:
- To evaluate the impact of a CADe system on key quality and efficiency metrics in a clinical colonoscopy setting.
- To compare adenoma detection rate (ADR) and polyp detection rate (PDR) between colonoscopies with and without CADe assistance.
- To assess secondary outcomes including adenomas per colonoscopy (APC) and polyps per colonoscopy (PPC).
Main Methods:
- A retrospective, single-center study analyzed 4,028 colonoscopies performed between October 2022 and December 2023.
- Colonoscopies were divided into a CADe group (utilizing the system in 4 suites) and a control group.
- Propensity matching was used to control for patient demographics (age, gender), indication, and physician variability.
Main Results:
- The CADe group showed a significantly higher ADR (38.6% vs. 34.2%) and PDR (67.2% vs. 59.4%) compared to the control group.
- Adenomas per colonoscopy (APC) and polyps per colonoscopy (PPC) were also significantly higher in the CADe group.
- The increase in polyp detection was primarily driven by smaller lesions (≤5 mm), with less pronounced differences for larger polyps.
Conclusions:
- Clinical implementation of CADe systems demonstrably improved key colonoscopy quality metrics, including ADR, PDR, APC, and PPC.
- The enhanced ADR observed with CADe appears largely attributed to the detection of diminutive polyps (≤5 mm).
- The definitive clinical impact of these smaller detected polyps on reducing colorectal cancer incidence requires further study.
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