Influence of atrial contraction dynamics on cardiac function

Land, Sander; Niederer, Steven

doi:10.1002/cnm.2931

Cited by 39 publications

(42 citation statements)

References 42 publications

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“…Fewer references exist for four chamber geometries. A common combination of boundary conditions for four chamber geometries are homogeneous Dirichlet conditions on vessel cut-offs and a soft material connected to the apex [25,31], or springs on the outside of great vessels [32]. In those cases, however, homogeneous Neumann conditions are applied on the remaining epicar-dial surface, neglecting any influence of the pericardium as in the biventricular case.…”

Section: Current Pericardial Boundary Conditionsmentioning

confidence: 99%

The importance of the pericardium for cardiac biomechanics: from physiology to computational modeling

Pfaller

Hörmann

Weigl

et al. 2018

Biomech Model Mechanobiol

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The human heart is enclosed in the pericardial cavity. The pericardium consists of a layered thin sac and is separated from the myocardium by a thin film of fluid. It provides a fixture in space and frictionless sliding of the myocardium. The influence of the pericardium is essential for predictive mechanical simulations of the heart. However, there is no consensus on physiologically correct and computationally tractable pericardial boundary conditions. Here we propose to model the pericardial influence as a parallel spring and dashpot acting in normal direction to the epicardium. Using a four-chamber geometry, we compare a model with pericardial boundary conditions to a model with fixated apex. The influence of pericardial stiffness is demonstrated in a parametric study. Comparing simulation results to measurements from cine magnetic resonance imaging reveals that adding pericardial boundary conditions yields a better approximation with respect to atrioventricular plane displacement, atrial filling, and overall spatial approximation error. We demonstrate that this simple model of pericardial-myocardial inter-M. R. Pfaller * joint last authors action can correctly predict the pumping mechanisms of the heart as previously assessed in clinical studies. Utilizing a pericardial model can not only provide much more realistic cardiac mechanics simulations but also allows new insights into pericardial-myocardial interaction which cannot be assessed in clinical measurements yet.

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Section: Current Pericardial Boundary Conditionsmentioning

confidence: 99%

The importance of the pericardium for cardiac biomechanics: from physiology to computational modeling

Pfaller

Hörmann

Weigl

et al. 2018

Biomech Model Mechanobiol

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“…Recently, computational electro-mechanics started moving towards four-chamber models [11][12][13][14]. Simulations including the atria as well as the major vessels allow for a more realistic predicted motion, therefore offering an increased predictive power of the model.…”

Section: Introductionmentioning

confidence: 99%

“…Simulations including the atria as well as the major vessels allow for a more realistic predicted motion, therefore offering an increased predictive power of the model. Furthermore, the interest in the role of atrial dynamics on ventricular function has been growing in the clinical community [14][15][16]. Four-chamber heart models are, however, still in their infancy, as existing studies focus on one single heart rather than a cohort of individuals [12-14, 17, 18].…”

Section: Introductionmentioning

confidence: 99%

A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

et al. 2020

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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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“…The model was used to simulate the effect of changes in the LV shape on the ventricle performance. A more complicated 3D anatomically detailed multiscale model that included all four heart chambers was used for the estimation of the influence of atrial activation and contraction on the heart function …”

Section: Introductionmentioning

confidence: 99%

“…A more complicated 3D anatomically detailed multiscale model that included all four heart chambers was used for the estimation of the influence of atrial activation and contraction on the heart function. 16 Because of the left ventricle is the major blood pump in the heart, one can use a complex multiscale model to simulate only the LV contraction, while other heart chambers can be treated as reservoirs with time-dependent elasticity within a lumped parameter model. Previously, we developed a new simple model of myocardium based on a kinetic model of muscle contraction and its activation.…”

Section: Introductionmentioning

confidence: 99%

Multiscale simulation of the effects of atrioventricular block and valve diseases on heart performance

Syomin

Zberia

Tsaturyan

2019

Numer Methods Biomed Eng

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A new mathematical model of the cardiovascular system is proposed. The left ventricle is described by an axisymmetric multiscale model where myocardium is treated as an incompressible transversely isotropic medium with a realistic distribution of fibre orientation. Active tension and its regulation by Ca2+ ions are described by our recent kinetic model. A lumped parameter model is used for the simulation of blood circulation, in which the left and right atria and the right ventricle are described by a system of ordinary differential equations for active pressure‐volume relationships. The stress and strain of the left ventricle myocardium were calculated by the finite element method implemented by the authors. The changes in the haemodynamics upon changes in preload of a healthy heart, upon physical exercise, and in case of atrioventricular block with different types of arrhythmias were simulated. To simulate the effect of stenosis or regurgitation of the aortic or mitral valves, the hydraulic and inertial flow resistances of the heart valves were set as functions of their orifice areas. The model reproduced a number of phenomena observed in clinical practice, including the classification of the severity of valve disease.

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Influence of atrial contraction dynamics on cardiac function

Cited by 39 publications

References 42 publications

The importance of the pericardium for cardiac biomechanics: from physiology to computational modeling

The importance of the pericardium for cardiac biomechanics: from physiology to computational modeling

A publicly available virtual cohort of four-chamber heart meshes for cardiac electro-mechanics simulations

Multiscale simulation of the effects of atrioventricular block and valve diseases on heart performance

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