ArticleInternational journal for numerical methods in biomedical engineering2018
Efficient estimation of personalized biventricular mechanical function employing gradient-based optimization.
Article in International journal for numerical methods in biomedical engineering, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- HeartSimSage: Attention-Enhanced Graph Neural Networks for Accelerating Cardiac Mechanics Modeling.Journal of computational physics · 2026Article
- Statistical Atlas-Based Surrogate Model of Biventricular Wall Mechanics.bioRxiv : the preprint server for biology · 2026Article
- Estimation of Active Tension in Cardiac Microtissues by Solving a PDE-Constrained Optimization Problem.International journal for numerical methods in biomedical engineering · 2025Article
- Acute effects of mechanical dyssynchrony on left ventricular function and coronary perfusion.Frontiers in bioengineering and biotechnology · 2025Article
- Multiscale Finite Element Modeling of Left Ventricular Growth in Simulations of Valve Disease.Annals of biomedical engineering · 2024Article
- Comparison of Left Ventricular Function Derived from Subject-Specific Inverse Finite Element Modeling Based on 3D ECHO and Magnetic Resonance Images.Bioengineering (Basel, Switzerland) · 2024Article
- Role of tissue biomechanics in the formation and function of myocardial trabeculae in zebrafish embryos.The Journal of physiology · 2024Article
- MicroBundleCompute: Automated segmentation, tracking, and analysis of subdomain deformation in cardiac microbundles.PloS one · 2024Article
- A computational study of right ventricular mechanics in a rat model of pulmonary arterial hypertension.Frontiers in physiology · 2024Article
- The dependency of fetal left ventricular biomechanics function on myocardium helix angle configuration.Biomechanics and modeling in mechanobiology · 2023Article
- Regional Left Ventricular Fiber Stress Analysis for Cardiac Resynchronization Therapy Response.Annals of biomedical engineering · 2023Article
- Robust and efficient fixed-point algorithm for the inverse elastostatic problem to identify myocardial passive material parameters and the unloaded reference configuration.Journal of computational physics · 2022Article
- An Integrated Workflow for Building Digital Twins of Cardiac Electromechanics-A Multi-Fidelity Approach for Personalising Active Mechanics.Mathematics (Basel, Switzerland) · 2022Article
- Data-driven computational models of ventricular-arterial hemodynamics in pediatric pulmonary arterial hypertension.Frontiers in physiology · 2022Article
- A computationally efficient physiologically comprehensive 3D-0D closed-loop model of the heart and circulation.Computer methods in applied mechanics and engineering · 2021Article
- Inverse modeling framework for characterizing patient-specific microstructural changes in the pulmonary arteries.Journal of the mechanical behavior of biomedical materials · 2021Article
- Mechanical stimuli for left ventricular growth during pressure overload.Experimental mechanics · 2021Article
- Surrogate models based on machine learning methods for parameter estimation of left ventricular myocardium.Royal Society open science · 2021Article
- [A review on motion tracking methods for left myocardium based on cardiac cine magnetic resonance image].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2020Review
- An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine.Frontiers in bioengineering and biotechnology · 2020Review
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Authors and funding
8 authors.
Funding
Abstract
Individually personalized computational models of heart mechanics can be used to estimate important physiological and clinically-relevant quantities that are difficult, if not impossible, to directly measure in the beating heart. Here, we present a novel and efficient framework for creating patient-specific biventricular models using a gradient-based data assimilation method for evaluating regional myocardial contractility and estimating myofiber stress. These simulations can be performed on a regular laptop in less than 2 h and produce excellent fit between measured and simulated volume and strain data through the entire cardiac cycle. By applying the framework using data obtained from 3 healthy human biventricles, we extracted clinically important quantities as well as explored the role of fiber angles on heart function. Our results show that steep fiber angles at the endocardium and epicardium are required to produce simulated motion compatible with measured strain and volume data. We also find that the contraction and subsequent systolic stresses in the right ventricle are significantly lower than that in the left ventricle. Variability of the estimated quantities with respect to both patient data and modeling choices are also found to be low. Because of its high efficiency, this framework may be applicable to modeling of patient specific cardiac mechanics for diagnostic purposes.
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