Image-based models of cardiac structure with applications in arrhythmia and defibrillation studies

Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, MD, USA.
Journal of electrocardiology (Impact Factor: 1.36). 02/2009; 42(2):157.e1-10. DOI: 10.1016/j.jelectrocard.2008.12.003
Source: PubMed


The objective of this article is to present a set of methods for constructing realistic computational models of cardiac structure from high-resolution structural and diffusion tensor magnetic resonance images and to demonstrate the applicability of the models in simulation studies. The structural image is segmented to identify various regions such as normal myocardium, ventricles, and infarct. A finite element mesh is generated from the processed structural data, and fiber orientations are assigned to the elements. The Purkinje system, when visible, is modeled using linear elements that interconnect a set of manually identified points. The methods were applied to construct 2 different models; and 2 simulation studies, which demonstrate the applicability of the models in the analysis of arrhythmia and defibrillation, were performed. The models represent cardiac structure with unprecedented detail for simulation studies.

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    • "Biophysically detailed atrial models (Kneller et al., 2002; Vigmond et al., 2004; Ridler et al., 2011) can simulate normal and arrhythmic conditions and also response to ablation procedures. Image based models represent the complex geometrical structure of atria and also includes functional aspects such as fiber orientation and APD heterogeneity (Vadakkumpadan et al., 2009; Ridler et al., 2011). 2D tissue models have been proposed to analyze specific arrhythmia conditions like long QT syndrome (Clayton et al., 2001) which can cause the risk of ventricular arrhythmia and SCD. "
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    ABSTRACT: Cardiac arrhythmias are defined as disturbances in normal heart rhythm which vary from inconsequential to serious life threatening conditions. Simulation studies of cardiac arrhythmias at the whole heart level with electrocardiogram (ECG) gives an understanding how the underlying cell and tissue level changes manifest as rhythm disturbances in the ECG. We present a 2D whole heart model (WHM2D) which can accommodate variations at the cellular level and can generate an ECG waveform. It is shown that, by varying cellular-level parameters like the gap junction conductance (GJC), excitability, action potential duration(APD) and frequency of oscillations of the auto-rhythmic cell in WHM2D a large variety of cardiac arrhythmias can be generated. Sinus tachycardia, sinus bradycardia, sinus arrhythmia, sinus pause, junctional rhythm, Wolf Parkinson White syndrome and AV conduction blocks are thereby simulated. WHM2D includes key components of the electrical conduction system of the heart like the SA (Sino atrial) node cells, fast conducting inter-atrial pathways, slow conducting Atrivenctricular (AV) node, bundleof His cells, Purkinje network, atrial and ventricular myocardial cells. SA nodal cells, AV nodal cells, bundleof His cells and Purkinje cells are represented by the Fitzhugh-Nagumo (FN) model which is a reduced model of the Hodgkin-Huxley neuron model. The atrial and ventricular myocardial cells are modeled by the Aliev-Panfilov (AP) two-variable model proposed for cardiac excitation. WHM2D can prove to be a valuable clinical tool for understanding cardiac arrhythmias.
    Full-text · Article · Dec 2015 · Frontiers in Physiology
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    • "Figure 1 presents the generation of the model geometry from ex vivo MRI scans, the pipeline for which we have described previously (Vadakkumpadan et al., 2010b). Dilatation and ventricular wall thinning, as well as the changes in the fiber/ sheet architecture, that are associated with HF were incorporated naturally into the electromechanical model of the HF canine ventricles, via the image-based geometry (Vadakkumpadan et al., 2009; Gurev et al., 2011). Briefly, the electromechanical model is composed of two parts: an electrical component and a mechanical component. "
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    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.
    Full-text · Article · Sep 2015 · Frontiers in Bioengineering and Biotechnology
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    • "led to the construction of population-based computational models of the distal section of the CCS in the ventricles (Behradfar et al., 2014; Deo et al., 2010; Sebastian et al., 2013; Walton et al., 2014). Among the techniques that have been used to model the geometry of the CCS there are fractal models (Abboud et al., 1991), manually delineated models (Romero et al., 2010), models guided by ex-vivo electrical recordings (Pollard and Barr, 1990), models guided by histological information (Sebastian et al., 2013), and models guided by high-resolution images in animals (Vadakkumpadan et al., 2009). The reader is referred to Sebastian et al. (2013) for a review on different techniques commonly used to build computer models of the CCS. "
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    ABSTRACT: The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, patient-specific activation times on ventricular chambers can be estimated from electro-anatomical maps, providing crucial information to clinicians for guiding cardiac radio-frequency ablation treatment. However, some relevant electrical pathways such as those of the Purkinje system are very difficult to interpret from these maps due to sparsity of data and the limited spatial resolution of the system. We present here a novel method to estimate these fast electrical pathways from the local activations maps (LATs) obtained from electro-anatomical maps. The location of Purkinje-myocardial junctions (PMJs) is estimated considering them as critical points of a distance map defined by the electro-anatomical activation maps, and then minimal cost paths are computed on the ventricular surface between the detected junctions. Experiments to validate the proposed method have been carried out in simplified and realistic simulated data, showing good performance on recovering the main characteristics of simulated Purkinje networks (e.g. PMJs). A feasibility study with real cases of fascicular VT was also performed, showing promising results.
    Full-text · Article · May 2015 · Medical Image Analysis
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