Towards a robust and compact deep learning system for primary detection of early Barrett's neoplasia: Initial image-based results of training on a multi-center retrospectively collected data set.

Barrett's esophagus Barrett's neoplasia artificial intelligence computer aided detection endoscopy machine learning

Journal

United European gastroenterology journal
ISSN: 2050-6414
Titre abrégé: United European Gastroenterol J
Pays: England
ID NLM: 101606807

Informations de publication

Date de publication:
05 2023
Historique:
received: 23 09 2022
accepted: 09 01 2023
medline: 9 5 2023
pubmed: 25 4 2023
entrez: 25 04 2023
Statut: ppublish

Résumé

Endoscopic detection of early neoplasia in Barrett's esophagus is difficult. Computer Aided Detection (CADe) systems may assist in neoplasia detection. The aim of this study was to report the first steps in the development of a CADe system for Barrett's neoplasia and to evaluate its performance when compared with endoscopists. This CADe system was developed by a consortium, consisting of the Amsterdam University Medical Center, Eindhoven University of Technology, and 15 international hospitals. After pretraining, the system was trained and validated using 1.713 neoplastic (564 patients) and 2.707 non-dysplastic Barrett's esophagus (NDBE; 665 patients) images. Neoplastic lesions were delineated by 14 experts. The performance of the CADe system was tested on three independent test sets. Test set 1 (50 neoplastic and 150 NDBE images) contained subtle neoplastic lesions representing challenging cases and was benchmarked by 52 general endoscopists. Test set 2 (50 neoplastic and 50 NDBE images) contained a heterogeneous case-mix of neoplastic lesions, representing distribution in clinical practice. Test set 3 (50 neoplastic and 150 NDBE images) contained prospectively collected imagery. The main outcome was correct classification of the images in terms of sensitivity. The sensitivity of the CADe system on test set 1 was 84%. For general endoscopists, sensitivity was 63%, corresponding to a neoplasia miss-rate of one-third of neoplastic lesions and a potential relative increase in neoplasia detection of 33% for CADe-assisted detection. The sensitivity of the CADe system on test sets 2 and 3 was 100% and 88%, respectively. The specificity of the CADe system varied for the three test sets between 64% and 66%. This study describes the first steps towards the establishment of an unprecedented data infrastructure for using machine learning to improve the endoscopic detection of Barrett's neoplasia. The CADe system detected neoplasia reliably and outperformed a large group of endoscopists in terms of sensitivity.

Identifiants

pubmed: 37095718
doi: 10.1002/ueg2.12363
pmc: PMC10165317
doi:

Types de publication

Multicenter Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

324-336

Informations de copyright

© 2023 The Authors. United European Gastroenterology Journal published by Wiley Periodicals LLC on behalf of United European Gastroenterology.

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Auteurs

Kiki N Fockens (KN)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

Jelmer B Jukema (JB)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

Tim Boers (T)

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

Martijn R Jong (MR)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

Joost A van der Putten (JA)

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

Roos E Pouw (RE)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

Bas L A M Weusten (BLAM)

Department of Gastroenterology and Hepatology, UMC Utrecht, University of Utrecht, Utrecht, the Netherlands.
Department of Gastroenterology and Hepatology, Sint Antonius Hospital, Nieuwegein, the Netherlands.

Lorenza Alvarez Herrero (L)

Department of Gastroenterology and Hepatology, Sint Antonius Hospital, Nieuwegein, the Netherlands.

Martin H M G Houben (MHMG)

Department of Gastroenterology and Hepatology, Haga Teaching Hospital, Den Haag, the Netherlands.

Wouter B Nagengast (WB)

Department of Gastroenterology and Hepatology, University of Groningen, Groningen, the Netherlands.

Jessie Westerhof (J)

Department of Gastroenterology and Hepatology, University of Groningen, Groningen, the Netherlands.

Alaa Alkhalaf (A)

Department of Gastroenterology and Hepatology, Isala Hospital Zwolle, Zwolle, the Netherlands.

Rosalie Mallant (R)

Department of Gastroenterology and Hepatology, Flevoziekenhuis Almere, Almere, the Netherlands.

Krish Ragunath (K)

Department of Gastroenterology and Hepatology, Royal Perth Hospital, Perth, Australia.

Stefan Seewald (S)

Department of Gastroenterology and Hepatology, Hirslanden Klinik, Zurich, Switzerland.

Peter Elbe (P)

Department of Digestive Diseasess, Karolinska University Hospital, Stockholm, Sweden.
Division of Surgery, Department of Clinical Science, Intervention and Technology, CLINTEC, Karolinska Institutet, Stockholm, Sweden.

Maximilien Barret (M)

Department of Gastroenterology and Hepatology, Cochin Hospital Paris, Paris, France.

Jacobo Ortiz Fernández-Sordo (J)

Department of Gastroenterology and Hepatology, Nottingham University Hospital, Nottingham, UK.

Oliver Pech (O)

Department of Gastroenterology and Hepatology, Krankenhaus Barmherzige Brüder Regensburg, Regensburg, Germany.

Torsten Beyna (T)

Department of Gastroenterology and Hepatology, Evangalische Klinik Düsseldorf, Düsseldorf, Germany.

Fons van der Sommen (F)

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

Peter H de With (PH)

Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands.

A Jeroen de Groof (AJ)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

Jacques J Bergman (JJ)

Department of Gastroenterology and Hepatology, Amsterdam Gastroenterology, Endocrinology and Metabolism, University of Amsterdam, Amsterdam, the Netherlands.

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