Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm.


Journal

Gut
ISSN: 1468-3288
Titre abrégé: Gut
Pays: England
ID NLM: 2985108R

Informations de publication

Date de publication:
12 2022
Historique:
received: 01 11 2021
accepted: 29 06 2022
pubmed: 16 9 2022
medline: 10 11 2022
entrez: 15 9 2022
Statut: ppublish

Résumé

In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, for example, bleeding and perforation. A DeepLabv3-based model was trained to delineate vessels, tissue structures and instruments on endoscopic still images from such procedures. The mean cross-validated Intersection over Union and Dice Score were 63% and 76%, respectively. Applied to standardised video clips from third-space endoscopic procedures, the algorithm showed a mean vessel detection rate of 85% with a false-positive rate of 0.75/min. These performance statistics suggest a potential clinical benefit for procedure safety, time and also training.

Identifiants

pubmed: 36109151
pii: gutjnl-2021-326470
doi: 10.1136/gutjnl-2021-326470
pmc: PMC9664130
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2388-2390

Informations de copyright

© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: NS: speaker honorarium, Boston Scientific and Pharmascience. MB: CEO and founder, Satisfai Health. HM: consulting fees, Olympus.

Références

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Auteurs

Alanna Ebigbo (A)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany alanna.ebigbo@uk-augsburg.de.

Robert Mendel (R)

Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.

Markus W Scheppach (MW)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

Andreas Probst (A)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

Neal Shahidi (N)

Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada.

Friederike Prinz (F)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

Carola Fleischmann (C)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

Christoph Römmele (C)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

Stefan Karl Goelder (SK)

Department of Gastroenterology, Ostalb-Klinikum Aalen, Aalen, Germany.

Georg Braun (G)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

David Rauber (D)

Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.

Tobias Rueckert (T)

Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.

Luis A de Souza (LA)

Department of Computing, Federal University of São Carlos, São Carlos, Brazil.

Joao Papa (J)

Department of Computing, São Paulo State University, Botucatu, Brazil.

Michael Byrne (M)

Vancouver General Hospital, The University of British Columbia, Vancouver, British Columbia, Canada.

Christoph Palm (C)

Regensburg Medical Image Computing (ReMIC), Ostbayerische Technische Hochschule Regensburg, Regensburg, Germany.

Helmut Messmann (H)

Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.

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Classifications MeSH