ArticleJournal of biomechanics2016
Generating Purkinje networks in the human heart.
Article in Journal of biomechanics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.The Journal of physiology · 2026Review
- Electrophysiological characterization of pre-adolescents born with intrauterine growth restriction: insights from clinical and computational data.The Journal of physiology · 2026Article
- Computational analysis of intracardiac collision risk and optimal site for right ventricular leadless left bundle branch area pacing: A simulation study.Heart rhythm O2 · 2026Article
- Effects of Purkinje Fiber Conduction Block on Cardiac Pump Function: Computational Modeling Study.Bioengineering (Basel, Switzerland) · 2026Article
- In silico assessment of arrhythmic risk following the implantation of engineered heart tissues in porcine hearts with varying infarct locations.PLoS computational biology · 2026Article
- Integrated multi-modal data analysis for computational modeling of healthy and location-dependent myocardial infarction conditions in porcine hearts.PLoS computational biology · 2026Article
- Full-field surrogate modeling of cardiac electrophysiology encoding geometric variability.Computer methods in applied mechanics and engineering · 2026Article
- Reconstructing ventricular activation sequences from epicardial data: Insights from Geodesic Back-Propagation optimization in porcine models.Computers in biology and medicine · 2025Article
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- A computational study on the influence of antegrade accessory pathway location on the 12-lead electrocardiogram in Wolff-Parkinson-White syndrome.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
- Assessing post-TAVR cardiac conduction abnormalities risk using an electromechanically coupled beating heart.Biomechanics and modeling in mechanobiology · 2025Article
- To reconnect or not reconnect distal Purkinje fibers, that is the question when modeling the Purkinje fiber network.Frontiers in physiology · 2025Article
- Effects of cardiac growth on electrical dyssynchrony in the single ventricle patient.Computer methods in biomechanics and biomedical engineering · 2024Article
- Digital twinning of cardiac electrophysiology for congenital heart disease.Journal of the Royal Society, Interface · 2024Article
- Computational Modelling Enabling In Silico Trials for Cardiac Physiologic Pacing.Journal of cardiovascular translational research · 2024Review
- Branched Latent Neural Maps.Computer methods in applied mechanics and engineering · 2024Article
- Digital twinning of cardiac electrophysiology for congenital heart disease.bioRxiv : the preprint server for biology · 2023Article
- Enhanced optimization-based method for the generation of patient-specific models of Purkinje networks.Scientific reports · 2023Article
- Comparison of novel ventricular pacing strategies using an electro-mechanical simulation platform.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023Article
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3 authors.
Funding
Abstract
The Purkinje network is an integral part of the excitation system in the human heart. Yet, to date, there is no in vivo imaging technique to accurately reconstruct its geometry and structure. Computational modeling of the Purkinje network is increasingly recognized as an alternative strategy to visualize, simulate, and understand the role of the Purkinje system. However, most computational models either have to be generated manually, or fail to smoothly cover the irregular surfaces inside the left and right ventricles. Here we present a new algorithm to reliably create robust Purkinje networks within the human heart. We made the source code of this algorithm freely available online. Using Monte Carlo simulations, we demonstrate that the fractal tree algorithm with our new projection method generates denser and more compact Purkinje networks than previous approaches on irregular surfaces. Under similar conditions, our algorithm generates a network with 1219±61 branches, three times more than a conventional algorithm with 419±107 branches. With a coverage of 11±3mm, the surface density of our new Purkije network is twice as dense as the conventional network with 22±7mm. To demonstrate the importance of a dense Purkinje network in cardiac electrophysiology, we simulated three cases of excitation: with our new Purkinje network, with left-sided Purkinje network, and without Purkinje network. Simulations with our new Purkinje network predicted more realistic activation sequences and activation times than simulations without. Six-lead electrocardiograms of the three case studies agreed with the clinical electrocardiograms under physiological conditions, under pathological conditions of right bundle branch block, and under pathological conditions of trifascicular block. Taken together, our results underpin the importance of the Purkinje network in realistic human heart simulations. Human heart modeling has the potential to support the design of personalized strategies for single- or bi-ventricular pacing, radiofrequency ablation, and cardiac defibrillation with the common goal to restore a normal heart rhythm.
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