An automated near-real time computational method for induction and treatment of scar-related ventricular tachycardias.


Journal

Medical image analysis
ISSN: 1361-8423
Titre abrégé: Med Image Anal
Pays: Netherlands
ID NLM: 9713490

Informations de publication

Date de publication:
08 2022
Historique:
received: 30 08 2021
revised: 22 04 2022
accepted: 20 05 2022
pubmed: 7 6 2022
medline: 27 7 2022
entrez: 6 6 2022
Statut: ppublish

Résumé

Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.

Identifiants

pubmed: 35667328
pii: S1361-8415(22)00130-X
doi: 10.1016/j.media.2022.102483
pmc: PMC10114098
pii:
doi:

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

102483

Subventions

Organisme : Wellcome Trust
ID : 213342/Z/18/Z
Pays : United Kingdom
Organisme : British Heart Foundation
ID : PG/16/81/32441
Pays : United Kingdom
Organisme : Wellcome Trust
ID : WT 203148/Z/16/Z
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/N011007/1
Pays : United Kingdom

Informations de copyright

Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None.

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Auteurs

Fernando O Campos (FO)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom. Electronic address: fernando.campos@kcl.ac.uk.

Aurel Neic (A)

NumeriCor GmbH, Graz, Austria.

Caroline Mendonca Costa (C)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

John Whitaker (J)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Guy's and St. Thomas' NHS Foundation Trust, Cardiovascular Directorate.

Mark O'Neill (M)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Guy's and St. Thomas' NHS Foundation Trust, Cardiovascular Directorate.

Reza Razavi (R)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

Christopher A Rinaldi (CA)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom; Guy's and St. Thomas' NHS Foundation Trust, Cardiovascular Directorate.
Division of Cardiology, Department of Internal Medicine, Medical University of Graz, Austria.

Steven A Niederer (SA)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

Gernot Plank (G)

Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria; BioTechMed-Graz, Graz, Austria.

Martin J Bishop (MJ)

School of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

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