ArticleScientific reports2023
Enhanced optimization-based method for the generation of patient-specific models of Purkinje networks.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- In silico optimization of regenerative cell therapy in the infarcted human ventricles to mitigate arrhythmic burden.Stem cell reports · 2026Article
- Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.The Journal of physiology · 2026Review
- T-World Virtual Human Cardiomyocyte. II. Organ-Scale Simulations and Applications.Circulation research · 2026Article
- Effects of Purkinje Fiber Conduction Block on Cardiac Pump Function: Computational Modeling Study.Bioengineering (Basel, Switzerland) · 2026Article
- Toward cardiac electrophysiology digital twins with an efficient open source scalable solver on GPU clusters.Scientific reports · 2026Article
- Harnessing 12-lead ECG and MRI data to personalise repolarisation profiles in cardiac digital twin models for enhanced virtual drug testing.Medical image analysis · 2025Article
- Cardiac conduction system regeneration prevents arrhythmias after myocardial infarction.Nature cardiovascular research · 2025Article
- In silico evaluation of cell therapy in acute versus chronic infarction: role of automaticity, heterogeneity and Purkinje in human.Scientific reports · 2024Article
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Authors and funding
8 authors.
Funding
Abstract
Cardiac Purkinje networks are a fundamental part of the conduction system and are known to initiate a variety of cardiac arrhythmias. However, patient-specific modeling of Purkinje networks remains a challenge due to their high morphological complexity. This work presents a novel method based on optimization principles for the generation of Purkinje networks that combines geometric and activation accuracy in branch size, bifurcation angles, and Purkinje-ventricular-junction activation times. Three biventricular meshes with increasing levels of complexity are used to evaluate the performance of our approach. Purkinje-tissue coupled monodomain simulations are executed to evaluate the generated networks in a realistic scenario using the most recent Purkinje/ventricular human cellular models and physiological values for the Purkinje-ventricular-junction characteristic delay. The results demonstrate that the new method can generate patient-specific Purkinje networks with controlled morphological metrics and specified local activation times at the Purkinje-ventricular junctions.
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