Competing mechanisms of stress-assisted diffusivity and stretch-activated currents in cardiac electromechanics

We numerically investigate the role of mechanical stress in modifying the conductivity properties of the cardiac tissue and its impact in computational models for cardiac electromechanics. We follow a theoretical framework recently proposed in [Cherubini, Filippi, Gizzi, Ruiz-Baier, JTB 2017], in the context of general reaction-diffusion-mechanics systems using multiphysics continuum mechanics and finite elasticity. In the present study, the adapted models are compared against preliminary experimental data of pig right ventricle fluorescence optical mapping. These data contribute to the characterization of the observed inhomogeneity and anisotropy properties that result from mechanical deformation. Our novel approach simultaneously incorporates two mechanisms for mechano-electric feedback (MEF): stretch-activated currents (SAC) and stress-assisted diffusion (SAD); and we also identify their influence into the nonlinear spatiotemporal dynamics. It is found that i) only specific combinations of the two MEF effects allow proper conduction velocity measurement; ii) expected heterogeneities and anisotropies are obtained via the novel stress-assisted diffusion mechanisms; iii) spiral wave meandering and drifting is highly mediated by the applied mechanical loading. We provide an analysis of the intrinsic structure of the nonlinear coupling using computational tests, conducted using a finite element method. In particular, we compare static and dynamic deformation regimes in the onset of cardiac arrhythmias and address other potential biomedical applications

Patient-Specific Quantification of the Relationship Between the Left Atrium Pressure and the Ostial Diameter of the Left Atrial Appendage

The left atrial appendage has been a historically understudied region of the heart until fairly recently with the new understanding of its role in the stroke pathway of patients with atrial fibrillation. The goal of this study is to take a look at the biomechanical behavior of the left atrium and left atrial appendage under normal physiological loading conditions using material properties taken from biaxial stretch tests. Several different options for material properties models were tested and biaxial stretch test data of cadaveric human tissue samples for the left atrium and appendage were fit to a Fung-type strain-energy function for input into simulation. Simulations were performed on geometry of the left atrium and appendage extracted from computed tomographical images of a single patient spanning from the pulmonary veins to the mitral valve annulus. Physiological pressure loading conditions were simulated at 5 mmHg, 7.5 mmHg, 10 mmHg, 15 mmHg, and 20 mmHg over two cardiac cycles. Results showed that peak stresses and strains were concentrated at branches in the atrium as well as the ostial entrance to the appendage. Ostial diameter of the appendage was measured across to axes and showed increases from a baseline of 1.347 cm x 2.927 cm in the unloaded configuration up to a size of 1.749 cm x 3.219 cm in the loaded configuration. Finite element simulations may be a useful tool for improving patient treatment options, especially when it comes to mechanical left atrial appendage occlusion devices

Dynamic finite-strain modelling of the human left ventricle in health and disease using an immersed boundary-finite element method

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 end-diastole 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

Modeling cardiac muscle fibers in ventricular and atrial electrophysiology simulations

Since myocardial fibers drive the electric signal propagation throughout the myocardium, accurately modeling their arrangement is essential for simulating heart electrophysiology (EP). Rule-Based-Methods (RBMs) represent a commonly used strategy to include cardiac fibers in computational models. A particular class of such methods is known as Laplace-Dirichlet-Rule-Based-Methods (LDRBMs) since they rely on the solution of Laplace problems. In this work we provide a unified framework, based on LDRBMs, for generating full heart muscle fibers. First, we review existing ventricular LDRBMs providing a communal mathematical description and introducing also some modeling improvements with respect to the existing literature. We then carry out a systematic comparison of LDRBMs based on meaningful biomarkers produced by numerical EP simulations. Next we propose, for the first time, a LDRBM to be used for generating atrial fibers. The new method, tested both on idealized and realistic atrial models, can be applied to any arbitrary geometries. Finally, we present numerical results obtained in a realistic whole heart where fibers are included for all the four chambers using the discussed LDRBMs

Training for muscular power adaptations : the role of contraction type and velocity

Muscular power, an integral component in most sport, is the product of force and velocity. Power is often viewed as synonymous, yet incorrectly, with strength. Where power has an inherent speed component, strength is independent of movement velocity, and is a measure of a muscle’s ability to produce a maximal force. In a majority of athletic events power is requisite to success, and is often more decisive in performance outcomes than strength alone. Currently, results from existing research examining the effectiveness of differing velocities of contraction in improving maximal power are mixed. Common methodologies used in research settings to study muscular power changes are isotonic training, isokinetic training, isometric training, and plyometric training. However, little research has been done examining the potential efficacy of training using inertial loading. This report examines existing research on movement velocities and loads, compares the effects of training velocities for increasing maximal power, identifies shortfalls and information gaps, and recommends future research in training for muscular power adaptations and improved athletic performance. This report also provides a detailed description of inertial load training and establishes a theoretical study design, hypothesis, and reasoning outlining why and how inertial load training may elicit muscular power increases and improved athletic performance.Kinesiology and Health Educatio

Biomechanical behavior of bioprosthetic heart valve heterograft tissues: characterization, simulation, and performance

The use of replacement heart valves continues to grow due to the increased prevalence of valvular heart disease resulting from an ageing population. Since bioprosthetic heart valves (BHVs) continue to be the preferred replacement valve, there continues to be a strong need to develop better and more reliable BHVs through and improved the general understanding of BHV failure mechanisms. The major technological hurdle for the lifespan of the BHV implant continues to be the durability of the constituent leaflet biomaterials, which if improved can lead to substantial clinical impact. In order to develop improved solutions for BHV biomaterials, it is critical to have a better understanding of the inherent biomechanical behaviors of the leaflet biomaterials, including chemical treatment technologies, the impact of repetitive mechanical loading, and the inherent failure modes. This review seeks to provide a comprehensive overview of these issues, with a focus on developing insight on the mechanisms of BHV function and failure. Additionally, this review provides a detailed summary of the computational biomechanical simulations that have been used to inform and develop a higher level of understanding of BHV tissues and their failure modes. Collectively, this information should serve as a tool not only to infer reliable and dependable prosthesis function, but also to instigate and facilitate the design of future bioprosthetic valves and clinically impact cardiology

Estimating cardiac active tension from wall motion—An inverse problem of cardiac biomechanics

The contraction of the human heart is a complex process as a consequence of the interaction of internal and external forces. In current clinical routine, the resulting deformation can be imaged during an entire heart beat. However, the active tension development cannot be measured in vivo but may provide valuable diagnostic information. In this work, we present a novel numerical method for solving an inverse problem of cardiac biomechanics—estimating the dynamic active tension field, provided the motion of the myocardial wall is known. This ill‐posed non‐linear problem is solved using second order Tikhonov regularization in space and time. We conducted a sensitivity analysis by varying the fiber orientation in the range of measurement accuracy. To achieve RMSE 0.95). The results obtained with non‐matching input data are promising and indicate directions for further improvement of the method. In future, this method will be extended to estimate the active tension field based on motion data from clinical images, which could provide important insights in terms of a new diagnostic tool for the identification and treatment of diseased heart tissue

Impact of uncertainties in cardiac mechanics simulations

Modeling the mechanics of the heart have led to considerable insights, but it still representes a complex and demanding computational problem, especially in a strongly coupled electromechanical setting. Passive cardiac tissue is commonly modeled as a hyperelastic, near-incompressible and orthotropic material, which are properties very challenging for the numerical solution of the model. In particular, near-incompressibility is known to cause numerical issues. In this work, some improvements were done in a cardiac mechanics simulator in order to be more efficient in the treatment of these numerical issues. With the improved solver for cardiac mechanics, it was possible to run problems with higher computational cost, such as sensitivity and uncertainty quantification analyses. This type of analysis has been a topic of scientific interest to assess the possibility of translating patient-specific simulations to clinical applications. However, personalized simulations are still challenging problems, because of the wide biological variability among patients, the uncertainties in experimental measurements and in the geometric representation of the heart. Due to these uncertainties in model inputs, it is difficult to define a reliable model that can be translated to clinical applications. Recent studies have focused on quantifying uncertainties for cardiac models in order to investigate how they can influence simulation results and, consequently, how we can make the models more reliable. Then, the present work also quantifies how uncertainties in the geometry can impact in quantities of interest from cardiac mechanics. The polynomial chaos approach was used to quantify uncertainties in geometries of the left ventricle during cardiac mechanics simulations. Initially, we performed some studies using simplified geometries during ventricular filling phase simulations and, after, we quantify uncertainties in more realistic geometries during the full cardiac cycle.A modelagem da mecânica cardíaca tem levado a descobertas interessantes, porém este continua sendo um problema complexo e de alta demanda computacional, especialmente em modelos eletromecânicos fortemente acoplados. O tecido cardíaco é geralmente considerado como um material hiperelástico, quase incompressível e ortotrópico, fatores que dificultam a solução numérica do modelo. Neste trabalho, melhorias foram realizadas em um simulador da mecânica cardíaca para tratar tais problemas numéricos de forma mais eficiente. Com este simulador mais eficiente foi possível tratar problemas que demandam de um maior esfoço computacional, como as análises de sensibilidade e quantificação de incertezas, onde várias simulações precisam ser realizadas. Este tipo de análise tem sido tópico de interesse científico para avaliar a possibilidade de usar simulações personalizadas por paciente em aplicações clínicas. Porém, estas simulações ainda são problemas desafiadores, por causa da grande variabilidade biológica entre pacientes e das incertezas em medidas experimentais e em representações geométricas do coração. Devido a estas incertezas em entradas do modelo, é difícil definir um modelo confiável que possa ser usado em aplicações clínicas. Estudos recentes têm se voltado à investigação de como estas incertezas podem influenciar no resultado de simulações e, consequentemente, descobrir como tornar os modelos mais confiáveis. Então, o presente trabalho quantifica incertezas nas geometrias usadas nas simulações para investigar como quantidades de interesse da mecânica cardíaca podem ser afetadas. A abordagem do polinômio caos é utilizada para a quantificação de incertezas em geometrias do ventrículo esquerdo submetidas a simulações da mecânica cardíaca. Inicialmente, as análises foram realizadas usando geometrias simplificadas em simulações da fase de preenchimento ventricular e, posteriormente, análises de quantificação de incertezas em geometrias mais realísticas submetidas a simulações do ciclo cardíaco completo são realizadas.CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superio