ArticleIMA journal of applied mathematics2014
Dynamic finite-strain modelling of the human left ventricle in health and disease using an immersed boundary-finite element method.
Article in IMA journal of applied mathematics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02072850 (Cardiac Magnetic Resonance Imaging), which is not on this map. Cited by 23 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Cardiac Magnetic Resonance Imaging: New Pathological Insights and Their Functional and Clinical Significance in ST Elevation Acute Myocardial Infarction.
Who cites it
23 citing papers in PubMed.
- Deep Learning-Based Estimation of Myocardial Material Parameters from Cardiac MRI.Bioengineering (Basel, Switzerland) · 2025Article
- A Heart Rate Matched Patch for Mechano-Chemical Treatment of Myocardial Infarction: Optimal Design and Transspecies Application.Research (Washington, D.C.) · 2024Article
- The dependency of fetal left ventricular biomechanics function on myocardium helix angle configuration.Biomechanics and modeling in mechanobiology · 2023Article
- A stabilized linear finite element method for anisotropic poroelastodynamics with application to cardiac perfusion.Computer methods in applied mechanics and engineering · 2023Article
- On the Lagrangian-Eulerian Coupling in the Immersed Finite Element/Difference Method.Journal of computational physics · 2022Article
- Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework.Scientific reports · 2021Article
- A poroelastic immersed finite element framework for modelling cardiac perfusion and fluid-structure interaction.International journal for numerical methods in biomedical engineering · 2021Article
- Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium.Royal Society open science · 2021Article
- Analysis of Cardiac Amyloidosis Progression Using Model-Based Markers.Frontiers in physiology · 2020Article
- An Immersed Interface Method for Discrete Surfaces.Journal of computational physics · 2020Article
- Fast parameter inference in a biomechanical model of the left ventricle by using statistical emulation.Journal of the Royal Statistical Society. Series C, Applied statistics · 2019Article
- Simulation of action potential propagation based on the ghost structure method.Scientific reports · 2019Article
- Gaussian process emulation to accelerate parameter estimation in a mechanical model of the left ventricle: a critical step towards clinical end-user relevance.Journal of the Royal Society, Interface · 2019Article
- Coupled agent-based and hyperelastic modelling of the left ventricle post-myocardial infarction.International journal for numerical methods in biomedical engineering · 2019Article
- In vivo estimation of elastic heterogeneity in an infarcted human heart.Biomechanics and modeling in mechanobiology · 2018Article
- Effect of Transmural Differences in Excitation-Contraction Delay and Contraction Velocity on Left Ventricle Isovolumic Contraction: A Simulation Study.BioMed research international · 2018Article
- Hybrid finite difference/finite element immersed boundary method.International journal for numerical methods in biomedical engineering · 2017Article
- Estimating prognosis in patients with acute myocardial infarction using personalized computational heart models.Scientific reports · 2017Article
- Changes and classification in myocardial contractile function in the left ventricle following acute myocardial infarction.Journal of the Royal Society, Interface · 2017Article
- A mathematical model for active contraction in healthy and failing myocytes and left ventricles.PloS one · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Detailed models of the biomechanics of the heart are important both for developing improved interventions for patients with heart disease and also for patient risk stratification and treatment planning. For instance, stress distributions in the heart affect cardiac remodelling, but such distributions are not presently accessible in patients. Biomechanical models of the heart offer detailed three-dimensional deformation, stress and strain fields that can supplement conventional clinical data. In this work, we introduce dynamic computational models of the human left ventricle (LV) that are derived from clinical imaging data obtained from a healthy subject and from a patient with a myocardial infarction (MI). Both models incorporate a detailed invariant-based orthotropic description of the passive elasticity of the ventricular myocardium along with a detailed biophysical model of active tension generation in the ventricular muscle. These constitutive models are employed within a dynamic simulation framework that accounts for the inertia of the ventricular muscle and the blood that is based on an immersed boundary (IB) method with a finite element description of the structural mechanics. The geometry of the models is based on data obtained non-invasively by cardiac magnetic resonance (CMR). CMR imaging data are also used to estimate the parameters of the passive and active constitutive models, which are determined so that the simulated end-diastolic and end-systolic volumes agree with the corresponding volumes determined from the CMR imaging studies. Using these models, we simulate LV dynamics from enddiastole to end-systole. The results of our simulations are shown to be in good agreement with subject-specific CMR-derived strain measurements and also with earlier clinical studies on human LV strain distributions.
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