ArticlePloS one2020
A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed, 107 citations in OpenAlex.
- The multi-modal digital heart: From future perspective to challenges.Journal of translational internal medicine · 2026Article
- Cardiac remodelling in type 2 diabetes: Pathophysiological mechanisms and opportunities for multiscale computational modelling and simulation.The Journal of physiology · 2026Review
- Neural implicit heart coordinates: 3D cardiac shape reconstruction from sparse segmentations.Medical image analysis · 2026Article
- Assessing the importance of sex and disease-specific anatomy in electrophysiology and mechanical simulations with a newly developed public virtual cohort of four-chamber heart models.PLoS computational biology · 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
- A finite element computational framework coupling four-chamber heart mechanics with the systemic and pulmonary circulations.Research square · 2026Article
- Regional heterogeneity in left atrial stiffness impacts passive deformation in a cohort of patient-specific models.PLoS computational biology · 2025Article
- Developing cardiac biomechanical models beyond the clinic: modeling stressors of daily life.Biomechanics and modeling in mechanobiology · 2025Review
- Article
- Rhythm control benefits left ventricular function compared with rate control in patients with atrial fibrillation: A computational study.Heart rhythm O2 · 2025Article
- Population-based computational simulations elucidate mechanisms of focal arrhythmia following stem cell injection.Journal of molecular and cellular cardiology · 2025Article
- Digital Twin Models in Atrial Fibrillation: Charting the Future of Precision Therapy?Journal of personalized medicine · 2025Review
- Computational modelling of biological systems now and then: revisiting tools and visions from the beginning of the century.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- An in silico guide for ventriculo-ventricular delay programming for left bundle branch-optimized cardiac resynchronization therapy.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
- Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.Nature cardiovascular research · 2025Article
- 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
- Cardiac digital twins at scale from MRI: Open tools and representative models from ~ 55000 UK Biobank participants.PloS one · 2025Article
- From bits to bedside: entering the age of digital twins in cardiac electrophysiology.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 · 2024Review
- Fast interactive simulations of cardiac electrical activity in anatomically accurate heart structures by compressing sparse uniform cartesian grids.Computer methods and programs in biomedicine · 2024Article
- Credibility assessment of in silico clinical trials for medical devices.PLoS computational biology · 2024Review
Corrections and comments
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Authors and funding
16 authors at 3 institutions in 3 countries.
Funding
Abstract
Computational models of the heart are increasingly being used in the development of devices, patient diagnosis and therapy guidance. While software techniques have been developed for simulating single hearts, there remain significant challenges in simulating cohorts of virtual hearts from multiple patients. To facilitate the development of new simulation and model analysis techniques by groups without direct access to medical data, image analysis techniques and meshing tools, we have created the first publicly available virtual cohort of twenty-four four-chamber hearts. Our cohort was built from heart failure patients, age 67±14 years. We segmented four-chamber heart geometries from end-diastolic (ED) CT images and generated linear tetrahedral meshes with an average edge length of 1.1±0.2mm. Ventricular fibres were added in the ventricles with a rule-based method with an orientation of -60° and 80° at the epicardium and endocardium, respectively. We additionally refined the meshes to an average edge length of 0.39±0.10mm to show that all given meshes can be resampled to achieve an arbitrary desired resolution. We ran simulations for ventricular electrical activation and free mechanical contraction on all 1.1mm-resolution meshes to ensure that our meshes are suitable for electro-mechanical simulations. Simulations for electrical activation resulted in a total activation time of 149±16ms. Free mechanical contractions gave an average left ventricular (LV) and right ventricular (RV) ejection fraction (EF) of 35±1% and 30±2%, respectively, and a LV and RV stroke volume (SV) of 95±28mL and 65±11mL, respectively. By making the cohort publicly available, we hope to facilitate large cohort computational studies and to promote the development of cardiac computational electro-mechanics for clinical applications.
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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.