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

Article (PDF Available)inJournal of electrocardiology 42(2):157.e1-10 · February 2009with42 Reads
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.


    • "The comparison between the two models suggests that simplified models might be more advantageous to use in simulations of spatially extended phenomena than detailed models. Clearly, simulating detailed models is computationally expensive, as it requires solving a large set of stiff differential equations and to date, only a limited number of computational studies have been carried out using detailed models in 2 [37] and 3D [38][39][40] . The FK model, and similar simple models, on the other hand, are computationally much more efficient than detailed models [29, 41], and have been extensively used to model cardiac dynamics of single cells and in 2D [42] and 3D geometries [14, 43] . "
    [Show abstract] [Hide abstract] ABSTRACT: Computer studies are often used to study mechanisms of cardiac arrhythmias, including atrial fibrillation (AF). A crucial component in these studies is the electrophysiological model that describes the membrane potential of myocytes. The models vary from detailed, describing numerous ion channels, to simplified, grouping ionic channels into a minimal set of variables. The parameters of these models, however, are determined across different experiments in varied species. Furthermore, a single set of parameters may not describe variations across patients, and models have rarely been shown to recapitulate critical features of AF in a given patient. In this study we develop physiologically accurate computational human atrial models by fitting parameters of a detailed and of a simplified model to clinical data for five patients undergoing ablation therapy. Parameters were simultaneously fitted to action potential (AP) morphology, action potential duration (APD) restitution and conduction velocity (CV) restitution curves in these patients. For both models, our fitting procedure generated parameter sets that accurately reproduced clinical data, but differed markedly from published sets and between patients, emphasizing the need for patient-specific adjustment. Both models produced two-dimensional spiral wave dynamics for that were similar for each patient. These results show that simplified, computationally efficient models are an attractive choice for simulations of human atrial electrophysiology in spatially extended domains. This study motivates the development and validation of patient-specific model-based mechanistic studies to target therapy.
    Full-text · Article · Aug 2016
    • "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. "
    [Show abstract] [Hide abstract] 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
    • "The ventricular geometries and the fiber/sheet architectures were generated from MR and diffusion tensor MR images, respectively.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. "
    [Show abstract] [Hide abstract] 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
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