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Costa, CM; Plank, G; Rinaldi, CA; Niederer, SA; Bishop, MJ.
Modeling the Electrophysiological Properties of the Infarct Border Zone
FRONT PHYSIOL. 2018; 9: 356
Doi: 10.3389/fphys.2018.00356
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- Führende Autor*innen der Med Uni Graz
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Mendonca Costa Caroline
- Co-Autor*innen der Med Uni Graz
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Plank Gernot
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- Abstract:
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Ventricular arrhythmias (VA) in patients with myocardial infarction (MI) are thought to be associated with structural and electrophysiological remodeling within the infarct border zone (BZ). Personalized computational models have been used to investigate the potential role of the infarct BZ in arrhythmogenesis, which still remains incompletely understood. Most recent models have relied on experimental data to assign BZ properties. However, experimental measurements vary significantly resulting in different computational representations of this region. Here, we review experimental data available in the literature to determine the most prominent properties of the infarct BZ. Computational models are then used to investigate the effect of different representations of the BZ on activation and repolarization properties, which may be associated with VA. Experimental data obtained from several animal species and patients with infarct show that BZ properties vary significantly depending on disease's stage, with the early disease stage dominated by ionic remodeling and the chronic stage by structural remodeling. In addition, our simulations show that ionic remodeling in the BZ leads to large repolarization gradients in the vicinity of the scar, which may have a significant impact on arrhythmia simulations, while structural remodeling plays a secondary role. We conclude that it is imperative to faithfully represent the properties of regions of infarction within computational models specific to the disease stage under investigation in order to conduct in silico mechanistic investigations.
- Find related publications in this database (Keywords)
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cardiac electrophysiology
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myocardial infarct
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infarct border zone
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gray zone
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computational modeling