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A New MRI-Based Model of Heart Function with Coupled Hemodynamics and Application to Normal and Diseased Canine Left Ventricles.

Choi YJ, Constantino J, Vedula V, Trayanova N, Mittal R - Front Bioeng Biotechnol (2015)

Bottom Line: The time-dependent endocardial surfaces are registered using a diffeomorphic mapping algorithm, while the intraventricular blood flow patterns are simulated using a sharp-interface immersed boundary method-based flow solver.The utility of the combined heart-function model is demonstrated by comparing the hemodynamic characteristics of a normal canine heart beating in sinus rhythm against that of the dyssynchronously beating failing heart.We also discuss the potential of coupled CE and hemodynamics models for various clinical applications.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, Johns Hopkins University , Baltimore, MD , USA ; Institute for Computational Medicine, Johns Hopkins University , Baltimore, MD , USA.

ABSTRACT
A methodology for the simulation of heart function that combines an MRI-based model of cardiac electromechanics (CE) with a Navier-Stokes-based hemodynamics model is presented. The CE model consists of two coupled components that simulate the electrical and the mechanical functions of the heart. Accurate representations of ventricular geometry and fiber orientations are constructed from the structural magnetic resonance and the diffusion tensor MR images, respectively. The deformation of the ventricle obtained from the electromechanical model serves as input to the hemodynamics model in this one-way coupled approach via imposed kinematic wall velocity boundary conditions and at the same time, governs the blood flow into and out of the ventricular volume. The time-dependent endocardial surfaces are registered using a diffeomorphic mapping algorithm, while the intraventricular blood flow patterns are simulated using a sharp-interface immersed boundary method-based flow solver. The utility of the combined heart-function model is demonstrated by comparing the hemodynamic characteristics of a normal canine heart beating in sinus rhythm against that of the dyssynchronously beating failing heart. We also discuss the potential of coupled CE and hemodynamics models for various clinical applications.

No MeSH data available.


Electrical activation times (left) and mechanical activation times (right) in the dyssynchronous non-failing (top) and dyssynchronous failing (bottom) canine ventricular models.
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Figure 3: Electrical activation times (left) and mechanical activation times (right) in the dyssynchronous non-failing (top) and dyssynchronous failing (bottom) canine ventricular models.

Mentions: To represent electrical activity in sinus rhythm (SR), the normal and failing ventricles were activated at discrete locations on the right ventricular (RV) and LV endocardium as if the activation originated from the Purkinje fibers, as demonstrated previously (Gurev et al., 2010, 2011; Constantino et al., 2012, 2013). The timing and locations of the stimuli were based on experimental 3D electrical propagation patterns (Durrer et al., 1970; Usyk et al., 2000; Ramanathan et al., 2006). Furthermore, two additional electromechanical models were generated, one normal and one failing, with a different SR activation sequence, i.e., left bundle branch block (LBBB), known to lead to dyssynchrony in contraction (Constantino et al., 2012, 2013). LBBB was modeled by stimulating the ventricles only at RV endocardial locations used in the normal SR simulations. An exhaustive description of all the electromechanics methodology used here, including image-based model development, mesh generation, fiber orientation assignment, representation of the electrical and mechanical properties of the myocardium, and numerical methods can be found in the detailed modeling methods paper by Gurev et al. (2011). Electrical and mechanical activation in the two LBBB models is presented in Figure 3, as an illustration of an output from the normal and failing electromechanical models. The characteristics of the four electromechanical models, two in SR, and two in LBBB activation used in this study, are presented in Table 1. Validation of the electromechanical models with experimental data can be found in a recent publication (Constantino et al., 2013).


A New MRI-Based Model of Heart Function with Coupled Hemodynamics and Application to Normal and Diseased Canine Left Ventricles.

Choi YJ, Constantino J, Vedula V, Trayanova N, Mittal R - Front Bioeng Biotechnol (2015)

Electrical activation times (left) and mechanical activation times (right) in the dyssynchronous non-failing (top) and dyssynchronous failing (bottom) canine ventricular models.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4585083&req=5

Figure 3: Electrical activation times (left) and mechanical activation times (right) in the dyssynchronous non-failing (top) and dyssynchronous failing (bottom) canine ventricular models.
Mentions: To represent electrical activity in sinus rhythm (SR), the normal and failing ventricles were activated at discrete locations on the right ventricular (RV) and LV endocardium as if the activation originated from the Purkinje fibers, as demonstrated previously (Gurev et al., 2010, 2011; Constantino et al., 2012, 2013). The timing and locations of the stimuli were based on experimental 3D electrical propagation patterns (Durrer et al., 1970; Usyk et al., 2000; Ramanathan et al., 2006). Furthermore, two additional electromechanical models were generated, one normal and one failing, with a different SR activation sequence, i.e., left bundle branch block (LBBB), known to lead to dyssynchrony in contraction (Constantino et al., 2012, 2013). LBBB was modeled by stimulating the ventricles only at RV endocardial locations used in the normal SR simulations. An exhaustive description of all the electromechanics methodology used here, including image-based model development, mesh generation, fiber orientation assignment, representation of the electrical and mechanical properties of the myocardium, and numerical methods can be found in the detailed modeling methods paper by Gurev et al. (2011). Electrical and mechanical activation in the two LBBB models is presented in Figure 3, as an illustration of an output from the normal and failing electromechanical models. The characteristics of the four electromechanical models, two in SR, and two in LBBB activation used in this study, are presented in Table 1. Validation of the electromechanical models with experimental data can be found in a recent publication (Constantino et al., 2013).

Bottom Line: The time-dependent endocardial surfaces are registered using a diffeomorphic mapping algorithm, while the intraventricular blood flow patterns are simulated using a sharp-interface immersed boundary method-based flow solver.The utility of the combined heart-function model is demonstrated by comparing the hemodynamic characteristics of a normal canine heart beating in sinus rhythm against that of the dyssynchronously beating failing heart.We also discuss the potential of coupled CE and hemodynamics models for various clinical applications.

View Article: PubMed Central - PubMed

Affiliation: Department of Mechanical Engineering, Johns Hopkins University , Baltimore, MD , USA ; Institute for Computational Medicine, Johns Hopkins University , Baltimore, MD , USA.

ABSTRACT
A methodology for the simulation of heart function that combines an MRI-based model of cardiac electromechanics (CE) with a Navier-Stokes-based hemodynamics model is presented. The CE model consists of two coupled components that simulate the electrical and the mechanical functions of the heart. Accurate representations of ventricular geometry and fiber orientations are constructed from the structural magnetic resonance and the diffusion tensor MR images, respectively. The deformation of the ventricle obtained from the electromechanical model serves as input to the hemodynamics model in this one-way coupled approach via imposed kinematic wall velocity boundary conditions and at the same time, governs the blood flow into and out of the ventricular volume. The time-dependent endocardial surfaces are registered using a diffeomorphic mapping algorithm, while the intraventricular blood flow patterns are simulated using a sharp-interface immersed boundary method-based flow solver. The utility of the combined heart-function model is demonstrated by comparing the hemodynamic characteristics of a normal canine heart beating in sinus rhythm against that of the dyssynchronously beating failing heart. We also discuss the potential of coupled CE and hemodynamics models for various clinical applications.

No MeSH data available.