Strain-controlled electrophysiological wave propagation alters in silico scar-based substrate for ventricular tachycardia

E. Willems (Corresponding author), K.L.P.M. Janssens, L.R. Dekker, Frans N. van de Vosse, Matthijs J.M. Cluitmans, Peter H.M. Bovendeerd

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Samenvatting

Introduction: Assessing a patient’s risk of scar-based ventricular tachycardia (VT) after myocardial infarction is a challenging task. It can take months to years after infarction for VT to occur. Also, if selected for ablation therapy, success rates are low.
Methods: Computational ventricular models have been presented previously to support VT risk assessment and to provide ablation guidance. In this study, an extension to such virtual-heart models is proposed to phenomenologically incorporate tissue remodeling driven by mechanical load. Strain amplitudes in the heart muscle are obtained from simulations of mechanics and are used to adjust the electrical conductivity.
Results: The mechanics-driven adaptation of electrophysiology resulted in a more heterogeneous distribution of propagation velocities than that of standard models, which adapt electrophysiology in the structural substrate from medical images only. Moreover, conduction slowing was not only present in such a structural substrate, but extended in the adjacent functional border zone with impaired mechanics. This enlarged the volumes with high repolarization time gradients (≥ 10 ms/mm). However, maximum gradient values were not significantly affected. The enlarged volumes were localized along the structural substrate border, which lengthened the line of conduction block. The prolonged reentry pathways together with conduction slowing in functional regions increased VT cycle time, such that VT was easier to induce, and the number of recommended ablation sites increased from 3 to 5 locations.
Discussion: Sensitivity testing showed an accurate model of strain-dependency to be critical for low ranges of conductivity. The model extension with mechanics-driven tissue remodeling is a potential approach to capture the evolution of the functional substrate and may offer insight into the progression of VT risk over time.
Originele taal-2Engels
Artikelnummer1330157
Aantal pagina's13
TijdschriftFrontiers in Physiology
Volume15
DOI's
StatusGepubliceerd - 9 apr. 2024

Financiering

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This publication is part of the computational-model-based decision support for patients at risk for sustained ventricular tachycardias project (project no. 17983) of the research program High Tech Systems and Materials which is financed by the Dutch Research Council (NWO).

FinanciersFinanciernummer
Nederlandse Organisatie voor Wetenschappelijk Onderzoek

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