Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution

Hustad, Kristian Gregorius; Ivanovic, Ena; Recha, Adrian Llop; Sakthivel, Abinaya Abbi

doi:10.1007/978-3-031-05164-7_4

Cited by 5 publications

(1 citation statement)

References 7 publications

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“…Consequently, these models are now often referred to as EMI models, but they were earlier referred to as microscopic models, see, e.g., [9]. The development of EMI models is presented in [10,11,12,13,14,15,16], and their applications are explored in [17,18,19,20,21,22]. Numerical methods for solving the EMI equations have been analyzed in [23,24,25,26,27].…”

Section: Introductionmentioning

confidence: 99%

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Jæger,

Trotter,

Cai

et al. 2024

Preprint

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Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity. Our findings reveal that cell-based models introduced in recent literature offer both efficiency and precision for simulating small tissue samples (comprising thousands of cardiomyocytes). Conversely, the traditional bidomain model and its simplified counterpart, the monodomain model, are more appropriate for larger tissue masses (encompassing millions to billions of cardiomyocytes). For simulations requiring detailed parameter variations along individual cell membranes, the EMI model emerges as the only viable choice. This model distinctively accounts for the extracellular (E), membrane (M), and intracellular (I) spaces, providing a comprehensive framework for detailed studies. Nonetheless, the EMI model's applicability to large-scale tissues is limited by its substantial computational demands for subcellular resolution.

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Section: Introductionmentioning

confidence: 99%

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Jæger,

Trotter,

Cai

et al. 2024

Preprint

View full text Add to dashboard Cite

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Efficient, cell-based simulations of cardiac electrophysiology; The Kirchhoff Network Model (KNM)

Jæger

Tveito

2023

npj Syst Biol Appl

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Mathematical models based on homogenized representation of cardiac tissue have greatly improved our understanding of cardiac electrophysiology. However, these models are too coarse to investigate the dynamics at the level of the myocytes since the cells are not present in homogenized models. Recently, fine scale models have been proposed to allow for cell-level resolution of the dynamics, but these models are too computationally expensive to be used in applications like whole heart simulations of large animals. To address this issue, we propose a model that balances computational demands and physiological accuracy. The model is founded on Kirchhoff’s current law, and represents every myocyte in the tissue. This allows specific properties to be assigned to individual cardiomyocytes, and other cell types like fibroblasts can be added to the model in an accurate manner while keeping the computing efforts reasonable.

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A possible path to persistent re-entry waves at the outlet of the left pulmonary vein

Jæger,

Tveito

2024

npj Syst Biol Appl

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Atrial fibrillation (AF) is the most common form of cardiac arrhythmia, often evolving from paroxysmal episodes to persistent stages over an extended timeframe. While various factors contribute to this progression, the precise biophysical mechanisms driving it remain unclear. Here we explore how rapid firing of cardiomyocytes at the outlet of the pulmonary vein of the left atria can create a substrate for a persistent re-entry wave. This is grounded in a recently formulated mathematical model of the regulation of calcium ion channel density by intracellular calcium concentration. According to the model, the number of calcium channels is controlled by the intracellular calcium concentration. In particular, if the concentration increases above a certain target level, the calcium current is weakened to restore the target level of calcium. During rapid pacing, the intracellular calcium concentration of the cardiomyocytes increases leading to a substantial reduction of the calcium current across the membrane of the myocytes, which again reduces the action potential duration. In a spatially resolved cell-based model of the outlet of the pulmonary vein of the left atria, we show that the reduced action potential duration can lead to re-entry. Initiated by rapid pacing, often stemming from paroxysmal AF episodes lasting several days, the reduction in calcium current is a critical factor. Our findings illustrate how such episodes can foster a conducive environment for persistent AF through electrical remodeling, characterized by diminished calcium currents. This underscores the importance of promptly addressing early AF episodes to prevent their progression to chronic stages.

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Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution

Cited by 5 publications

References 7 publications

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Efficient, cell-based simulations of cardiac electrophysiology; The Kirchhoff Network Model (KNM)

A possible path to persistent re-entry waves at the outlet of the left pulmonary vein

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