CC BY 4.0 · Endoscopy 2023; 55(08): 756-765
DOI: 10.1055/a-2009-3990
Original article

Computer-aided diagnosis for optical diagnosis of diminutive colorectal polyps including sessile serrated lesions: a real-time comparison with screening endoscopists

 1   Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
,
Yark Hazewinkel
 2   Department of Gastroenterology and Hepatology, Radboud University Nijmegen Medical Center, Radboud University of Nijmegen, Nijmegen, The Netherlands
,
Ioannis Giotis
 3   ZiuZ Visual Intelligence, Gorredijk, the Netherlands
,
Jasper L. A. Vleugels
 1   Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
,
Nahid S. Mostafavi
 4   Department of Gastroenterology and Hepatology, Subdivision Statistics, Amsterdam University Medical Center, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
,
Paul van Putten
 5   Department of Gastroenterology and Hepatology, Medical Center Leeuwarden, Leeuwarden, The Netherlands
,
Paul Fockens
 1   Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
,
 1   Department of Gastroenterology and Hepatology, Amsterdam University Medical Center, Amsterdam, the Netherlands
 6   Bergman Clinics Maag and Darm Amsterdam, Amsterdam, The Netherlands
,
POLAR Study Group
› Author Affiliations
Supported by: the European Regional Development Fund region Northern-Netherlands UP-18–00565
Supported by: PPP Allowance made available by Health~Holland, Top Sector Life Sciences & Health, to the Dutch Digestive Disease Foundation to stimulate public-private partnerships TKI 18–01
Supported by: The province of Friesland NA

Trial Registration: ClinicalTrials.gov Registration number (trial ID): NCT03822390 Type of study: Prospective, Multicenter study, Comparative

Abstract

Background We aimed to compare the accuracy of the optical diagnosis of diminutive colorectal polyps, including sessile serrated lesions (SSLs), between a computer-aided diagnosis (CADx) system and endoscopists during real-time colonoscopy.

Methods We developed the POLyp Artificial Recognition (POLAR) system, which was capable of performing real-time characterization of diminutive colorectal polyps. For pretraining, the Microsoft-COCO dataset with over 300 000 nonpolyp object images was used. For training, eight hospitals prospectively collected 2637 annotated images from 1339 polyps (i. e. publicly available online POLAR database). For clinical validation, POLAR was tested during colonoscopy in patients with a positive fecal immunochemical test (FIT), and compared with the performance of 20 endoscopists from eight hospitals. Endoscopists were blinded to the POLAR output. Primary outcome was the comparison of accuracy of the optical diagnosis of diminutive colorectal polyps between POLAR and endoscopists (neoplastic [adenomas and SSLs] versus non-neoplastic [hyperplastic polyps]). Histopathology served as the reference standard.

Results During clinical validation, 423 diminutive polyps detected in 194 FIT-positive individuals were included for analysis (300 adenomas, 41 SSLs, 82 hyperplastic polyps). POLAR distinguished neoplastic from non-neoplastic lesions with 79 % accuracy, 89 % sensitivity, and 38 % specificity. The endoscopists achieved 83 % accuracy, 92 % sensitivity, and 44 % specificity. The optical diagnosis accuracy between POLAR and endoscopists was not significantly different (P = 0.10). The proportion of polyps in which POLAR was able to provide an optical diagnosis was 98 % (i. e. success rate).

Conclusions We developed a CADx system that differentiated neoplastic from non-neoplastic diminutive polyps during endoscopy, with an accuracy comparable to that of screening endoscopists and near-perfect success rate.

Supplementary material



Publication History

Received: 13 July 2022

Accepted after revision: 09 January 2023

Accepted Manuscript online:
09 January 2023

Article published online:
02 March 2023

© 2023. 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
Rüdigerstraße 14, 70469 Stuttgart, Germany

 
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