AB061. SOH26AB_0189. Audit of polypectomy rates in a single centre before and after the introduction of computer-aided detection (AI) in colonoscopy
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AB061. SOH26AB_0189. Audit of polypectomy rates in a single centre before and after the introduction of computer-aided detection (AI) in colonoscopy

John Corbett1, Alison Martin2, Ally O’Brien Davis2, Ian Nyamangodo1, Deirdre O’Hanlon1, Noel O’Brien1

1Department of Surgery, South Infirmary Victoria University Hospital, Cork, Ireland; 2College of Medicine, University College Cork, Cork, Ireland

Background: Colorectal cancer is a major cause of morbidity and mortality, and early polyp detection is central to prevention. Computer-assisted detection (CAD) systems aim to improve real-time polyp recognition during colonoscopy. This study aimed to evaluate whether CAD implementation influenced polyp detection rates (PDRs) and adenoma detection patterns.

Methods: A retrospective observational cohort study was conducted in the South Infirmary Victoria University Hospital, comparing colonoscopy and pathology data before and after CAD implementation. Two audit cycles were analysed: pre-CAD and post-CAD. The primary outcome was the PDR. Secondary outcomes included mean polyps per patient and histological subtype distribution, focusing on tubular adenomas. Statistical analysis was performed using Chi-squared and Mann-Whitney U tests, with significance set at P<0.05.

Results: A total of 315 colonoscopies were reviewed, with 177 pre-CAD and 138 post-CAD. PDRs were similar between groups (39% pre-CAD vs. 48.6% post-CAD, P=0.1). There was no significant difference in mean polyps per patient (0.76 vs. 1.01, P=0.09). A significant increase in tubular adenoma detection was observed following CAD introduction (56.3% vs. 70%, P=0.03).

Conclusions: CAD implementation did not significantly change overall PDRs or mean polyps per patient. However, it was associated with a higher proportion of tubular adenomas identified. This may reflect normal variation between audit cycles or improved detection supported by CAD. Larger studies are needed to further define CAD’s impact on adenoma detection and its potential role in colorectal cancer prevention.

Keywords: Colonoscopy; artificial intelligence (AI); computer-assisted detection (CAD); adenoma; surveillance

Acknowledgments

None.

Footnote

Funding: None.

Conflicts of Interest: The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

doi: 10.21037/map-26-ab061
Cite this abstract as: Corbett J, Martin A, Davis AO, Nyamangodo I, O’Hanlon D, O’Brien N. AB061. SOH26AB_0189. Audit of polypectomy rates in a single centre before and after the introduction of computer-aided detection (AI) in colonoscopy. Mesentery Peritoneum 2026;10:AB061.

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