Automated Framework for the Inclusion of a His-Purkinje System in Cardiac Digital Twins of Ventricular Electrophysiology.


Journal

Annals of biomedical engineering
ISSN: 1573-9686
Titre abrégé: Ann Biomed Eng
Pays: United States
ID NLM: 0361512

Informations de publication

Date de publication:
Dec 2021
Historique:
received: 31 01 2021
accepted: 26 06 2021
pubmed: 26 8 2021
medline: 22 3 2022
entrez: 25 8 2021
Statut: ppublish

Résumé

Personalized models of cardiac electrophysiology (EP) that match clinical observation with high fidelity, referred to as cardiac digital twins (CDTs), show promise as a tool for tailoring cardiac precision therapies. Building CDTs of cardiac EP relies on the ability of models to replicate the ventricular activation sequence under a broad range of conditions. Of pivotal importance is the His-Purkinje system (HPS) within the ventricles. Workflows for the generation and incorporation of HPS models are needed for use in cardiac digital twinning pipelines that aim to minimize the misfit between model predictions and clinical data such as the 12 lead electrocardiogram (ECG). We thus develop an automated two stage approach for HPS personalization. A fascicular-based model is first introduced that modulates the endocardial Purkinje network. Only emergent features of sites of earliest activation within the ventricular myocardium and a fast-conducting sub-endocardial layer are accounted for. It is then replaced by a topologically realistic Purkinje-based representation of the HPS. Feasibility of the approach is demonstrated. Equivalence between both HPS model representations is investigated by comparing activation patterns and 12 lead ECGs under both sinus rhythm and right-ventricular apical pacing. Predominant ECG morphology is preserved by both HPS models under sinus conditions, but elucidates differences during pacing.

Identifiants

pubmed: 34431016
doi: 10.1007/s10439-021-02825-9
pii: 10.1007/s10439-021-02825-9
pmc: PMC8671274
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

3143-3153

Subventions

Organisme : Austrian Science Fund
ID : I2760-B30
Organisme : H2020 European Research Council
ID : 18HLT07
Organisme : BioTechMed-Graz
ID : ILearnHeart Project

Informations de copyright

© 2021. The Author(s).

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Auteurs

Karli Gillette (K)

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

Matthias A F Gsell (MAF)

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

Julien Bouyssier (J)

IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.

Anton J Prassl (AJ)

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

Aurel Neic (A)

NumeriCor GmbH, Graz, Austria.

Edward J Vigmond (EJ)

IHU Liryc, Electrophysiology and Heart Modeling Institute, Fondation Bordeaux Université, Pessac-Bordeaux, France.

Gernot Plank (G)

Gottfried Schatz Research Center Biophysics, Medical University of Graz, Graz, Austria. gernot.plank@medunigraz.at.
BioTechMed-Graz, Graz, Austria. gernot.plank@medunigraz.at.

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