A dual adaptive explicit time integration algorithm for efficiently solving the cardiac monodomain equation

Mountris, Konstantinos A.; Pueyo, Esther

doi:10.1002/cnm.3461

Cited by 16 publications

(15 citation statements)

References 31 publications

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“…Simulations were performed using ELECTRA which is an in-house cardiac electrophysiology solver implementing the Finite Element Method and Meshless methods ( Mountris and Pueyo, 2020 , 2021a ) for the solution of the cardiac monodomain model ( Mountris and Pueyo, 2020 , 2021b ). In this work, the dual-adaptive explicit integration algorithm ( Mountris and Pueyo, 2021b ) was used to efficiently solve the monodomain model.…”

Section: Methodsmentioning

confidence: 99%

Analysis of age-related left ventricular collagen remodeling in living donors: Implications in arrhythmogenesis

et al. 2022

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Section: Methodsmentioning

confidence: 99%

Analysis of age-related left ventricular collagen remodeling in living donors: Implications in arrhythmogenesis

et al. 2022

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“…In this study, the finite element implementation was used as in previous studies, where we have simulated human atrial electrophysiology (Celotto et al, 2020 ). Simulations were performed using explicit time integration with an adaptive time step ranging from 0.005 to 0.01 ms. A dual adaptive explicit time integration (DAETI) method was used (Mountris and Pueyo, 2020a ). DAETI employs adaptive explicit integration for the solution of both the reaction and diffusion terms of the cardiac monodomain model, which allows obtaining accurate solutions while reducing the computational time.…”

Section: Methodsmentioning

confidence: 99%

“…step ranging from 0.005 to 0.01 ms. A dual adaptive explicit time integration (DAETI) method was used (Mountris and Pueyo, 2020a). DAETI employs adaptive explicit integration for the solution of both the reaction and diffusion terms of the cardiac monodomain model, which allows obtaining accurate solutions while reducing the computational time.…”

Section: Simulation Protocolsmentioning

confidence: 99%

Location of Parasympathetic Innervation Regions From Electrograms to Guide Atrial Fibrillation Ablation Therapy: An in silico Modeling Study

et al. 2021

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The autonomic nervous system (ANS) plays an essential role in the generation and maintenance of cardiac arrhythmias. The cardiac ANS can be divided into its extrinsic and intrinsic components, with the latter being organized in an epicardial neural network of interconnecting axons and clusters of autonomic ganglia called ganglionated plexi (GPs). GP ablation has been associated with a decreased risk of atrial fibrillation (AF) recurrence, but the accurate location of GPs is required for ablation to be effective. Although GP stimulation triggers both sympathetic and parasympathetic ANS branches, a predominance of parasympathetic activity has been shown. This study aims was to develop a method to locate atrial parasympathetic innervation sites based on measurements from a grid of electrograms (EGMs). Electrophysiological models representative of non-AF, paroxysmal AF (PxAF), and persistent AF (PsAF) tissues were developed. Parasympathetic effects were modeled by increasing the concentration of the neurotransmitter acetylcholine (ACh) in randomly distributed circles across the tissue. Different circle sizes of ACh and fibrosis geometries were considered, accounting for both uniform diffuse and non-uniform diffuse fibrosis. Computational simulations were performed, from which unipolar EGMs were computed in a 16 × 1 6 electrode mesh. Different distances of the electrodes to the tissue (0.5, 1, and 2 mm) and noise levels with signal-to-noise ratio (SNR) values of 0, 5, 10, 15, and 20 dB were tested. The amplitude of the atrial EGM repolarization wave was found to be representative of the presence or absence of ACh release sites, with larger positive amplitudes indicating that the electrode was placed over an ACh region. Statistical analysis was performed to identify the optimal thresholds for the identification of ACh sites. In all non-AF, PxAF, and PsAF tissues, the repolarization amplitude rendered successful identification. The algorithm performed better in the absence of fibrosis or when fibrosis was uniformly diffuse, with a mean accuracy of 0.94 in contrast with a mean accuracy of 0.89 for non-uniform diffuse fibrotic cases. The algorithm was robust against noise and worked for the tested ranges of electrode-to-tissue distance. In conclusion, the results from this study support the feasibility to locate atrial parasympathetic innervation sites from the amplitude of repolarization wave.

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“…The decoupled PDE was solved by the Finite Element Method (FEM) using the ELECTRA solver [ 52 , 53 ] with a spatial resolution of 0.015 cm. Numerical time integration was performed using a dual adaptive explicit time integration algorithm [ 54 ].…”

Section: Methodsmentioning

confidence: 99%

The role of β-adrenergic stimulation in QT interval adaptation to heart rate during stress test

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Cebollada²,

Mountris³

et al. 2023

PLoS ONE

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The adaptation lag of the QT interval after heart rate (HR) has been proposed as an arrhythmic risk marker. Most studies have quantified the QT adaptation lag in response to abrupt, step-like changes in HR induced by atrial pacing, in response to tilt test or during ambulatory recordings. Recent studies have introduced novel methods to quantify the QT adaptation lag to gradual, ramp-like HR changes in stress tests by evaluating the differences between the measured QT series and an estimated, memoryless QT series obtained from the instantaneous HR. These studies have observed the QT adaptation lag to progressively reduce when approaching the stress peak, with the underlying mechanisms being still unclear. This study analyzes the contribution of β-adrenergic stimulation to QT interval rate adaptation in response to gradual, ramp-like HR changes. We first quantify the QT adaptation lag in Coronary Artery Disease (CAD) patients undergoing stress test. To uncover the involved mechanisms, we use biophysically detailed computational models coupling descriptions of human ventricular electrophysiology and β-adrenergic signaling, from which we simulate ventricular action potentials and ECG signals. We characterize the adaptation of the simulated QT interval in response to the HR time series measured from each of the analyzed CAD patients. We show that, when the simulated ventricular tissue is subjected to a time-varying β-adrenergic stimulation pattern, with higher stimulation levels close to the stress peak, the simulated QT interval presents adaptation lags during exercise that are more similar to those measured from the patients than when subjected to constant β-adrenergic stimulation. During stress test recovery, constant and time-varying β-adrenergic stimulation patterns render similar adaptation lags, which are generally shorter than during exercise, in agreement with results from the patients. In conclusion, our findings support the role of time-varying β-adrenergic stimulation in contributing to QT interval adaptation to gradually increasing HR changes as those seen during the exercise phase of a stress test.

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A dual adaptive explicit time integration algorithm for efficiently solving the cardiac monodomain equation

Cited by 16 publications

References 31 publications

Analysis of age-related left ventricular collagen remodeling in living donors: Implications in arrhythmogenesis

Analysis of age-related left ventricular collagen remodeling in living donors: Implications in arrhythmogenesis

Location of Parasympathetic Innervation Regions From Electrograms to Guide Atrial Fibrillation Ablation Therapy: An in silico Modeling Study

The role of β-adrenergic stimulation in QT interval adaptation to heart rate during stress test

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