Sensitivity of left ventricular mechanics to myofiber architecture: A finite element study

Nikou, Amir; Gorman, Robert C.; Wenk, Jonathan F.

doi:10.1177/0954411916638685

Cited by 11 publications

(12 citation statements)

References 14 publications

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“…We interpolate the fiber orientation smoothly at each integration point. It is well known that the fiber orientation has a strong impact on passive and active cardiac mechanics [41,42,43,44,45,46]. In order to make a more clear statement about the pericardial boundary conditions independently of the fiber orientation and to show the interplay between boundary conditions and fiber orientations, we compare in this work three different fiber distributions: ±50 • , ±60 • , and ±70 • .…”

Section: Modeling the Pericardiummentioning

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: Modeling the Pericardiummentioning

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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“…Sensitivity of cardiac models to the myofiber orientation was also highlighted in previous studies. 18,32,33 One explanation for limited use of UQ and SA in cardiac modeling is the computational expense of the involved models. A popular statistical approach is the Monte Carlo (MC) method, but this method typically requires a large number of model evaluations for converged results.…”

Section: Introductionmentioning

confidence: 99%

Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response

Rodríguez‐Cantano

Sundnes

Rognes

2019

Numer Methods Biomed Eng

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Computational cardiac modelling is a mature area of biomedical computing and is currently evolving from a pure research tool to aiding in clinical decision making. Assessing the reliability of computational model predictions is a key factor for clinical use, and uncertainty quantification (UQ) and sensitivity analysis are important parts of such an assessment. In this study, we apply UQ in computational heart mechanics to study uncertainty both in material parameters characterizing global myocardial stiffness and in the local muscle fiber orientation that governs tissue anisotropy. The uncertainty analysis is performed using the polynomial chaos expansion (PCE) method, which is a nonintrusive meta‐modeling technique that surrogates the original computational model with a series of orthonormal polynomials over the random input parameter space. In addition, in order to study variability in the muscle fiber architecture, we model the uncertainty in orientation of the fiber field as an approximated random field using a truncated Karhunen‐Loéve expansion. The results from the UQ and sensitivity analysis identify clear differences in the impact of various material parameters on global output quantities. Furthermore, our analysis of random field variations in the fiber architecture demonstrate a substantial impact of fiber angle variations on the selected outputs, highlighting the need for accurate assignment of fiber orientation in computational heart mechanics models.

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“…Image-based computational models of PAH, including both biventricular cardiac models as well as hemodynamic models of the pulmonary vasculature, hold promise to advance our understanding of cardiac and vascular remodeling under PAH, and there has been growing interest in developing such models [13][14][15][16]. As computational cardiac models have elucidated the marked effect of myofiber orientation in the load distribution in the myocardial wall [17][18][19][20], remodeling in fiber structure alone is expected to influence the overall contractile function of the ventricle. Indeed, different transmural distributions of myofibers with the same contractile force could lead to distinct contractile patterns, and in turn different pumping efficiencies, at the organ level.…”

Section: Introductionmentioning

confidence: 99%

Interactions Between Structural Remodeling and Hypertrophy in the Right Ventricle in Response to Pulmonary Arterial Hypertension

Avazmohammadi¹,

Mendiola²,

Li³

et al. 2019

Journal of Biomechanical Engineering

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Pulmonary arterial hypertension (PAH) exerts substantial pressure overload on the right ventricle (RV), inducing RV remodeling and myocardial tissue adaptation often leading to right heart failure. The associated RV free wall (RVFW) adaptation involves myocardial hypertrophy, augmented intrinsic contractility, collagen fibrosis, and structural remodeling in an attempt to cope with pressure overload. If RVFW adaptation cannot maintain the RV stroke volume (SV), RV dilation will prevail as an exit mechanism, which usually decompensates RV function, leading to RV failure. Our knowledge of the factors determining the transition from the upper limit of RVFW adaptation to RV decompensation and the role of fiber remodeling events such as extracellular fibrosis and fiber reorientation in this transition remains very limited. Computational heart models that connect the growth and remodeling (G&R) events at the fiber and tissue levels with alterations in the organ-level function are essential to predict the temporal order and the compensatory level of the underlying mechanisms. In this work, building upon our recently developed rodent heart models (RHM) of PAH, we integrated mathematical models that describe volumetric growth of the RV and structural remodeling of the RVFW. The time-evolution of RV remodeling from control and post-PAH time points was simulated. The results suggest that the augmentation of the intrinsic contractility of myofibers, accompanied by an increase in passive stiffness of RVFW, is among the first remodeling events through which the RV strives to maintain the cardiac output. Interestingly, we found that the observed reorientation of the myofibers toward the longitudinal (apex-to-base) direction was a maladaptive mechanism that impaired the RVFW contractile pattern and advanced along with RV dilation at later stages of PAH. In fact, although individual fibers were more contractile post-PAH, the disruption in the optimal transmural fiber architecture compromised the effective contractile function of the RVFW, contributing to the depressed ejection fraction (EF) of the RV. Our findings clearly demonstrate the critical need for developing multiscale approaches that can model and delineate relationships between pathological alterations in cardiac function and underlying remodeling events across fiber, cellular, and molecular levels.

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Sensitivity of left ventricular mechanics to myofiber architecture: A finite element study

Cited by 11 publications

References 14 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

Uncertainty in cardiac myofiber orientation and stiffnesses dominate the variability of left ventricle deformation response

Interactions Between Structural Remodeling and Hypertrophy in the Right Ventricle in Response to Pulmonary Arterial Hypertension

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