ArticleBiophysics reviews2021
Whole-heart ventricular arrhythmia modeling moving forward: Mechanistic insights and translational applications.
Article in Biophysics reviews, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed.
- Accelerated Intrinsic Beating Rate in Heterogeneously Coupled Human Pluripotent Stem Cell-Derived Cardiomyocytes Can Underlie Focal Ventricular Tachycardia in Regenerative Therapy.Journal of precision medicine (Amsterdam, Netherlands) · 2026Article
- Self-organizing network simulation of cardiac contraction dynamics.Chaos (Woodbury, N.Y.) · 2025Article
- Current trends in virtual electrophysiology use for risk stratification and treatment of ventricular arrhythmias.Frontiers in cardiovascular medicine · 2025Review
- Connecting transcriptomics with computational modeling to reveal developmental adaptations in pediatric human atrial tissue.American journal of physiology. Heart and circulatory physiology · 2024Article
- Computational modeling of cardiac electrophysiology and arrhythmogenesis: toward clinical translation.Physiological reviews · 2024Review
- Current progress toward isogeometric modeling of the heart biophysics.Biophysics reviews · 2023Review
- Article
- Arrhythmogenic vulnerability of reentrant pathways in post-infarct ventricular tachycardia assessed by advanced computational modelling.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
- Efficient, cell-based simulations of cardiac electrophysiology; The Kirchhoff Network Model (KNM).NPJ systems biology and applications · 2023Article
- GPU accelerated digital twins of the human heart open new routes for cardiovascular research.Scientific reports · 2023Article
- Wavefront directionality and decremental stimuli synergistically improve identification of ventricular tachycardia substrate: insights from personalized computational heart models.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
- Modeling signaling pathways in biology with MaBoSS: From one single cell to a dynamic population of heterogeneous interacting cells.Computational and structural biotechnology journal · 2022Review
- Advanced imaging for risk stratification for ventricular arrhythmias and sudden cardiac death.Frontiers in cardiovascular medicine · 2022Review
- Multiscale and Multiphysics Modeling of Anisotropic Cardiac RFCA: Experimental-Based Model CalibrationFrontiers in physiology · 2022Article
- Bidomain modeling of electrical and mechanical properties of cardiac tissue.Biophysics reviews · 2021Review
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Ventricular arrhythmias are the primary cause of sudden cardiac death and one of the leading causes of mortality worldwide. Whole-heart computational modeling offers a unique approach for studying ventricular arrhythmias, offering vast potential for developing both a mechanistic understanding of ventricular arrhythmias and clinical applications for treatment. In this review, the fundamentals of whole-heart ventricular modeling and current methods of personalizing models using clinical data are presented. From this foundation, the authors summarize recent advances in whole-heart ventricular arrhythmia modeling. Efforts in gaining mechanistic insights into ventricular arrhythmias are discussed, in addition to other applications of models such as the assessment of novel therapeutics. The review emphasizes the unique benefits of computational modeling that allow for insights that are not obtainable by contemporary experimental or clinical means. Additionally, the clinical impact of modeling is explored, demonstrating how patient care is influenced by the information gained from ventricular arrhythmia models. The authors conclude with future perspectives about the direction of whole-heart ventricular arrhythmia modeling, outlining how advances in neural network methodologies hold the potential to reduce computational expense and permit for efficient whole-heart modeling.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.