Computational Modeling of Cardiac Biomechanics

The goal of this dissertation was to develop a realistic and patient-specific computational model of the heart that ultimately would help medical scientists to better diagnose and treat heart diseases. In order to achieve this goal, a three dimensional finite element model of the heart was created using magnetic resonance images of the beating pig heart. This model was loaded by the pressure of blood inside the left ventricle which was measured by synchronous catheterization. A recently developed structurally based constitutive model of the myocardium was incorporated in the finite element solver to model passive left ventricular myocardium. Additionally, an unloading algorithm originally designed for arteries was adapted to estimate the stress-free geometry of the heart from its partially-loaded geometry obtained from magnetic resonance imaging. Finally, a regionally varying growth module was added to the computational model to predict eccentric hypertrophy of the heart under various pathological conditions that result in volume overload of the heart. The computational model was validated using experimental data obtained from porcine heart such as in vivo strains measured from magnetic resonance imaging

lifex-fiber: an open tool for myofibers generation in cardiac computational models

Background: Modeling the whole cardiac function involves the solution of several complex multi-physics and multi-scale models that are highly computationally demanding, which call for simpler yet accurate, high-performance computational tools. Despite the efforts made by several research groups, no software for whole-heart fully coupled cardiac simulations in the scientific community has reached full maturity yet.Results: In this work we present life(x)-fiber, an innovative tool for the generation of myocardial fibers based on Laplace-Dirichlet Rule-Based Methods, which are the essential building blocks for modeling the electrophysiological, mechanical and electromechanical cardiac function, from single-chamber to whole-heart simulations. life(x)-fiber is the first publicly released module for cardiac simulations based on life(x), an open-source, high-performance Finite Element solver for multi-physics, multi-scale and multi-domain problems developed in the framework of the iHEART project, which aims at making in silico experiments easily reproducible and accessible to a wide community of users, including those with a background in medicine or bio-engineering.Conclusions: The tool presented in this document is intended to provide the scientific community with a computational tool that incorporates general state of the art models and solvers for simulating the cardiac function within a high-performance framework that exposes a user-and developer-friendly interface. This report comes with an extensive technical and mathematical documentation to welcome new users to the core structure of life(x)-fiber and to provide them with a possible approach to include the generated cardiac fibers into more sophisticated computational pipelines. In the near future, more modules will be successively published either as pre-compiled binaries for x86-64 Linux systems or as open source software

The Impact of Standard Ablation Strategies for Atrial Fibrillation on Cardiovascular Performance in a Four-chamber Heart Model

Atrial fibrillation is one of the most frequent cardiac arrhythmias in the industrialized world and ablation therapy is the method of choice for many patients. However, ablation scars alter the electrophysiological activation and the mechanical behavior of the affected atria. Different ablation strategies with the aim to terminate atrial fibrillation and prevent its recurrence exist but their impact on the hemodynamic performance of the heart has not been investigated thoroughly. In this work, we present a simulation study analyzing five commonly used ablation scar patterns and their combinations in the left atrium regarding their impact on the pumping function of the heart using an electromechanical whole-heart model. We analyzed how the altered atrial activation and increased stiffness due to the ablation scar affect atrial as well as ventricular contraction and relaxation. We found that systolic and diastolic function of the left atrium is impaired by ablation scars and that the reduction of atrial stroke volume of up to 11.43% depends linearly on the amount of inactivated tissue. Consequently, the end-diastolic volume of the left ventricle, and thus stroke volume, was reduced by up to 1.4% and 1.8%, respectively. During ventricular systole, left atrial pressure was increased by up to 20% due to changes in the atrial activation sequence and the stiffening of scar tissue. This study provides biomechanical evidence that atrial ablation has acute effects not only on atrial contraction but also on ventricular pumping function. Our results have the potential to help tailoring ablation strategies towards minimal global hemodynamic impairment

Using parametric model order reduction for inverse analysis of large nonlinear cardiac simulations

Predictive high-fidelity finite element simulations of human cardiac mechanics commonly require a large number of structural degrees of freedom. Additionally, these models are often coupled with lumped-parameter models of hemodynamics. High computational demands, however, slow down model calibration and therefore limit the use of cardiac simulations in clinical practice. As cardiac models rely on several patient-specific parameters, just one solution corresponding to one specific parameter set does not at all meet clinical demands. Moreover, while solving the nonlinear problem, 90% of the computation time is spent solving linear systems of equations. We propose to reduce the structural dimension of a monolithically coupled structure-Windkessel system by projection onto a lower-dimensional subspace. We obtain a good approximation of the displacement field as well as of key scalar cardiac outputs even with very few reduced degrees of freedom, while achieving considerable speedups. For subspace generation, we use proper orthogonal decomposition of displacement snapshots. Following a brief comparison of subspace interpolation methods, we demonstrate how projection-based model order reduction can be easily integrated into a gradient-based optimization. We demonstrate the performance of our method in a real-world multivariate inverse analysis scenario. Using the presented projection-based model order reduction approach can significantly speed up model personalization and could be used for many-query tasks in a clinical setting

The impact of standard ablation strategies for atrial fibrillation on cardiovascular performance in a four-chamber heart model

Purpose: Atrial fibrillation is one of the most frequent cardiac arrhythmias in the industrialized world and ablation therapy is the method of choice for many patients. However, ablation scars alter the electrophysiological activation and the mechanical behavior of the affected atria. Different ablation strategies with the aim to terminate atrial fibrillation and prevent its recurrence exist but their impact on the hemodynamic performance of the heart has not been investigated thoroughly. Methods: In this work, we present a simulation study analyzing five commonly used ablation scar patterns and their combinations in the left atrium regarding their impact on the pumping function of the heart using an electromechanical whole-heart model. We analyzed how the altered atrial activation and increased stiffness due to the ablation scar affect atrial as well as ventricular contraction and relaxation. Results: We found that systolic and diastolic function of the left atrium is impaired by ablation scars and that the reduction of atrial stroke volume of up to 11.43% depends linearly on the amount of inactivated tissue. Consequently, the end-diastolic volume of the left ventricle, and thus stroke volume, was reduced by up to 1.4% and 1.8%, espectively. During ventricular systole, left atrial pressure was increased by up to 20% due to changes in the atrial activation sequence and the stiffening of scar tissue. Conclusion: This study provides biomechanical evidence that atrial ablation has acute effects not only on atrial contraction but also on ventricular pumping function. Our results have the potential to help tailoring ablation strategies towards minimal global hemodynamic impairment

Electro-mechanical whole-heart digital twins: A fully coupled multi-physics approach

Mathematical models of the human heart are evolving to become a cornerstone of precision medicine and support clinical decision making by providing a powerful tool to understand the mechanisms underlying pathophysiological conditions. In this study, we present a detailed mathematical description of a fully coupled multi-scale model of the human heart, including electrophysiology, mechanics, and a closed-loop model of circulation. State-of-the-art models based on human physiology are used to describe membrane kinetics, excitation-contraction coupling and active tension generation in the atria and the ventricles. Furthermore, we highlight ways to adapt this framework to patient specific measurements to build digital twins. The validity of the model is demonstrated through simulations on a personalized whole heart geometry based on magnetic resonance imaging data of a healthy volunteer. Additionally, the fully coupled model was employed to evaluate the effects of a typical atrial ablation scar on the cardiovascular system. With this work, we provide an adaptable multi-scale model that allows a comprehensive personalization from ion channels to the organ level enabling digital twin modeling

Computational biomechanics of acute myocardial infarction and its treatment

The intramyocardial injection of biomaterials is an emerging therapy for myocardial infarction. Computational methods can help to study the mechanical effect s of biomaterial injectates on the infarcted heart s and can contribute to advance and optimise the concept of this therapy. The distribution of polyethylene glycol hydrogel injectate delivered immediately after the infarct induction was studied using rat infarct model. A micro-structural three-dimensional geometrical model of the entire injectate was reconstructed from histological micro graphs. The model provides a realistic representation of biomaterial injectates in computational models at macroscopic and microscopic level. Biaxial and compression mechanical testing was conducted for healing rat myocardial infarcted tissue at immediate (0 day), 7, 14 and 28 days after infarction onset. Infarcts were found to be mechanically anisotropic with the tissue being stiffer in circumferential direction than in longitudinal direction. The 0, 7, 14 and 28 days infarcts showed 443, 670, 857 and 1218 kPa circumferential tensile moduli. The 28 day infarct group showed a significantly higher compressive modulus compared to the other infarct groups (p= 0.0055, 0.028, and 0.018 for 0, 7 and 14 days groups). The biaxial mechanical data were utilized to establish material constitutive models of rat healing infarcts. Finite element model s and genetic algorithms were employed to identify the parameters of Fung orthotropic hyperelastic strain energy function for the healing infarcts. The provided infarct mechanical data and the identified constitutive parameters offer a platform for investigations of mechanical aspects of myocardial infarction and therapies in the rat, an experimental model extensively used in the development of infarct therapies. Micro-structurally detailed finite element model of a hydrogel injectate in an infarct was developed to provide an insight into the micromechanics of a hydrogel injectate and infarct during the diastolic filling. The injectate caused the end-diastolic fibre stresses in the infarct zone to decrease from 22.1 to 7.7 kPa in the 7 day infarct and from 35.7 to 9.7 kPa in the 28 day infarct. This stress reduction effect declined as the stiffness of the biomaterial increased. It is suggested that the gel works as a force attenuating system through micromechanical mechanisms reducing the force acting on tissue layers during the passive diastolic dilation of the left ventricle and thus reducing the stress induced in these tissue layers

A COMPUTATIONAL STUDY OF PATCH IMPLANTATION AND MITRAL VALVE MECHANICS

Myocardial infarction (i.e., a heart attack) is the most common heart disease in the United States. Mitral valve regurgitation, or the backflow of blood into the atrium from the left ventricle, is one of the complications associated with myocardial infarction. In this dissertation, a validated model of a sheep heart that has suffered myocardial infarction has been employed to study mitral valve regurgitation. The model was rebuilt with the knowledge of geometrical changes captured with MRI technique and is assigned with anisotropic, inhomogeneous, nearly incompressible and highly non-linear material properties. Patch augmentation was performed on its anterior leaflet, using a simplified approach, and its posterior leaflet, using a more realistic approach. In this finite element simulation, we virtually installed an elliptical patch within the central portion of the posterior leaflet. To the best of the author’s knowledge, this type of simulation has not been performed previously. In another simulation, the effect of patch within the anterior leaflet was simulated. The results from the two different surgical simulations show that patch implantation helps the free edges of the leaflets come close to one another, which leads to improved coaptation. Additionally, the changes in chordal force distributions are also reported. Finally, this study answers a few questions regarding mitral valve patch augmentation surgeries and emphasizes the importance of further investigations on the influence of patch positioning and material properties on key outcomes. The ultimate goal is to use the proposed techniques to assess human models that are patient-specific

Integrated Heart - Coupling multiscale and multiphysics models for the simulation of the cardiac function

Mathematical modelling of the human heart and its function can expand our understanding of various cardiac diseases, which remain the most common cause of death in the developed world. Like other physiological systems, the heart can be understood as a complex multiscale system involving interacting phenomena at the molecular, cellular, tissue, and organ levels. This article addresses the numerical modelling of many aspects of heart function, including the interaction of the cardiac electrophysiology system with contractile muscle tissue, the sub-cellular activation-contraction mechanisms, as well as the hemodynamics inside the heart chambers. Resolution of each of these sub-systems requires separate mathematical analysis and specially developed numerical algorithms, which we review in detail. By using specific sub-systems as examples, we also look at systemic stability, and explain for example how physiological concepts such as microscopic force generation in cardiac muscle cells, translate to coupled systems of differential equations, and how their stability properties influence the choice of numerical coupling algorithms. Several numerical examples illustrate three fundamental challenges of developing multiphysics and multiscale numerical models for simulating heart function, namely: (i) the correct upscaling from single-cell models to the entire cardiac muscle, (ii) the proper coupling of electrophysiology and tissue mechanics to simulate electromechanical feedback, and (iii) the stable simulation of ventricular hemodynamics during rapid valve opening and closure