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CC BY 4.0 · Endosc Int Open 2025; 13: a25215169
DOI: 10.1055/a-2521-5169
Original article

Improvement in adenoma detection rate by artificial intelligence-assisted colonoscopy: Multicenter quasi-randomized controlled trial

Authors

  • Ronja Maria Birgitta Lagström 

    1   Department of Surgery, Zealand University Hospital Koge, Køge, Denmark (Ringgold ID: RIN524788)

  • Karoline Bendix Bräuner

    2   Department of Surgery, Slagelse Hospital, Slagelse, Denmark (Ringgold ID: RIN73014)
    1   Department of Surgery, Zealand University Hospital Koge, Køge, Denmark (Ringgold ID: RIN524788)

  • Julia Bielik

    3   Department of Surgery, Holbæk Sygehus, Holbæk, Denmark (Ringgold ID: RIN53163)

  • Andreas Weinberger Rosen

    1   Department of Surgery, Zealand University Hospital Koge, Køge, Denmark (Ringgold ID: RIN524788)

  • Julie Gräs Crone

    4   Department of Surgery, Næstved Hospital, Næstved, Denmark (Ringgold ID: RIN91907)

  • Ismail Gögenur

    1   Department of Surgery, Zealand University Hospital Koge, Køge, Denmark (Ringgold ID: RIN524788)
    5   Department of Clinical Medicine, University of Copenhagen Faculty of Health and Medical Sciences, Copenhagen, Denmark (Ringgold ID: RIN53139)

  • Mustafa Bulut

    1   Department of Surgery, Zealand University Hospital Koge, Køge, Denmark (Ringgold ID: RIN524788)
    5   Department of Clinical Medicine, University of Copenhagen Faculty of Health and Medical Sciences, Copenhagen, Denmark (Ringgold ID: RIN53139)
    6   Copenhagen Academy for Medical Education and Simulation (CAMES), Copenhagen, Denmark
Clinical Trial: Registration number (trial ID): NCT05740137, Trial registry: Clinical Trials Registry (https://www.clinicaltrials.gov), Type of Study: Quasi-randomized controlled trial
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Abstract

Background and study aims

Adenoma detection rate (ADR) is a key performance measure with variability among endoscopists. Artificial intelligence (AI) in colonoscopy could reduce this variability and has shown to improve ADR. This study assessed the impact of AI on ADR among Danish endoscopists of varying experience levels.

Patients and methods

We conducted a prospective, quasi-randomized, controlled, multicenter trial involving patients aged 18 and older undergoing screening, surveillance, and diagnostic colonoscopy at four centers. Participants were assigned to AI-assisted colonoscopy (GI Genius, Medtronic) or conventional colonoscopy. Endoscopists were classified as experts (> 1000 colonoscopies) or non-experts (≤ 1000 colonoscopies). The primary outcome was ADR. We performed a subgroup analysis stratified on endoscopist experience and a subset analysis of the screening population.

Results

A total of 795 patients were analyzed: 400 in the AI group and 395 in the control group. The AI group demonstrated a significantly higher ADR than the control group (59.1% vs. 46.6%, P < 0.001). The increase was significant among experts (59.9% vs. 47.3%, P < 0.002) but not among non-experts. AI assistance significantly improved ADR (74.4% vs. 58.1%, P = 0.003) in screening colonoscopies. Polyp detection rate (PDR) was also higher in the AI group (69.8% vs. 56.2%, P < 0.001). There was no significant difference in the non-neoplastic resection rate (NNRR) (15.1% vs. 17.1%, P = 0.542).

Conclusions

AI-assisted colonoscopy significantly increased ADR by 12.5% overall, with a notable 16.3% increase in the screening population. The unchanged NNRR indicates that the higher PDR was due to increased ADR, not unnecessary resections.

Keywords

Endoscopy Lower GI Tract - Polyps / adenomas / ... - CRC screening - Endoscopic resection (polypectomy, ESD, EMRc, ...) - Colorectal cancer


Publication History

Received: 04 December 2024

Accepted: 15 January 2025

Article published online:
26 February 2025

© 2025. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/).

Georg Thieme Verlag KG
Oswald-Hesse-Straße 50, 70469 Stuttgart, Germany

Bibliographical Record
Ronja Maria Birgitta Lagström, Karoline Bendix Bräuner, Julia Bielik, Andreas Weinberger Rosen, Julie Gräs Crone, Ismail Gögenur, Mustafa Bulut. Improvement in adenoma detection rate by artificial intelligence-assisted colonoscopy: Multicenter quasi-randomized controlled trial. Endosc Int Open 2025; 13: a25215169.
DOI: 10.1055/a-2521-5169
 

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