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CC BY-NC-ND 4.0 · Endosc Int Open 2023; 11(09): E818-E828
DOI: 10.1055/a-2096-2960
Original article

Accuracy of polyp characterization by artificial intelligence and endoscopists: a prospective, non-randomized study in a tertiary endoscopy center

Sebastian Baumer‡
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Kilian Streicher‡
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Saleh A. Alqahtani
2   Department of Gastroenterology and Hepatology, Johns Hopkins Hospital, Baltimore, United States (Ringgold ID: RIN1501)
3   Liver Transplant Center, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia (Ringgold ID: RIN37852)
,
Dominic Brookman-Amissah
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Monika Brunner
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Christoph Federle
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Klaus Muehlenberg
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Lukas Pfeifer
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Andrea Salzberger
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Wolfgang Schorr
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
,
Jozef Zustin
4   Private Practice, Histopathology Service Private Practice, Regensburg, Germany
5   Gerhard-Domagk-Institute of Pathology, Universitätsklinikum Münster, Munster, Germany (Ringgold ID: RIN39069)
,
Oliver Pech
1   Department of Gastroenterology and Interventional Endoscopy, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany (Ringgold ID: RIN155897)
› Author Affiliations TRIAL REGISTRATION: Registration number (trial ID): DRKS00028894, Trial registry: German Clinical Trials Register (https://drks-neu.uniklinik-freiburg.de/), Type of Study: prospective, non-randomized study
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Abstract

Background and study aims Artificial intelligence (AI) in gastrointestinal endoscopy is developing very fast. Computer-aided detection of polyps and computer-aided diagnosis (CADx) for polyp characterization are available now. This study was performed to evaluate the diagnostic performance of a new commercially available CADx system in clinical practice.

Patients and methods This prospective, non-randomized study was performed at a tertiary academic endoscopy center from March to August 2022. We included patients receiving a colonoscopy. Polypectomy had to be performed in all polyps. Every patient was examined concurrently by an endoscopist and AI using two opposing screens. The AI system, overseen by a second observer, was not visible to the endoscopist. The primary outcome was accuracy of the AI classifying the polyps into “neoplastic” and “non-neoplastic.” The secondary outcome was accuracy of the classification by the endoscopists. Sessile serrated lesions were classified as neoplastic.

Results We included 156 patients (mean age 65; 57 women) with 262 polyps ≤10 mm. Eighty-four were hyperplastic polyps (32.1%), 158 adenomas (60.3%), seven sessile serrated lesions (2.7%) and 13 other entities (normal/inflammatory colonmucosa, lymphoidic polyp) (4.9%) on histological diagnosis. Sensitivity, specificity and accuracy of AI were 89.70% (95% confidence interval [CI]: 84.02%-93.88%), 75.26% (95% CI: 65.46%-83.46%) and 84.35% (95% CI:79.38%-88.53%), respectively. Sensitivity, specificity and accuracy for less experienced endoscopists (2–5 years of endoscopy) were 95.56% (95% CI: 84.85%-99.46%), 61.54% (95% CI: 40.57%-79.77%) and 83.10% (95% CI: 72.34%-90.95%) and for experienced endoscopists 90.83% (95% CI: 84.19%-95.33%), 71.83% (95% CI: 59.90%-81.87%) and 83.77% (95% CI: 77.76%-88.70%), respectively.

Conclusion Accuracy for polyp characterization by a new commercially available AI system is high, but does not fulfill the criteria for a “resect-and-discard” strategy.



Publication History

Received: 17 February 2023

Accepted after revision: 08 May 2023

Article published online:
18 September 2023

© 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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Comment to this article:

Endoscopy International Open – recently publishedEndoscopy 2023; 55(11): 1058-1058
DOI: 10.1055/a-2155-5868

 

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