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

ABSTRACT 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.

Download full-text


Available from: Gernot Plank, Aug 21, 2015
  • Source
    • "Direct characterisation of tissue structure in whole hearts is also possible to some extent by high resolution ex vivo T2* enhanced MRI (Gilbert et al., 2012). Models of cardiac electrophysiology based on tissue structure distribution obtained from ex vivo DT-MRI acquired from a single subject (Vadakkumpadan et al., 2010), or statistical atlases based on ex vivo DT-MRI of multiple datasets (Relan et al., 2011), have been used to predict the evolution of arrhythmia in the infarcted rabbit (Vadakkumpadan et al., 2009) and human heart (Relan et al., 2011). Given that high-resolution DT-MRI studies are only possible ex vivo, solutions have been proposed to build patient-specific fibre models by warping fibre atlases onto patient-specific gross cardiac geometries (McDowell et al., 2013). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.
    Progress in Biophysics and Molecular Biology 08/2014; 115(2-3). DOI:10.1016/j.pbiomolbio.2014.08.005 · 3.38 Impact Factor
  • Source
    • "the FRPS from MR data is complicated by the small size of Purkinje fibres relative to the myocardium. Full segmentations of the FRPS have previously been created by manual extraction (Vadakkumpadan et al., 2009) and using the method described here (Bordas et al., 2010). Isolated segments of the FRPS have also been segmented using a non-linear orientation filter (Cetingul et al., 2009). "
    [Show abstract] [Hide abstract]
    ABSTRACT: The function of the ventricular specialized conduction system in the heart is to ensure the coordinated electrical activation of the ventricles. It is therefore critical to the overall function of the heart, and has also been implicated as an important player in various diseases, including lethal ventricular arrhythmias such as ventricular fibrillation and drug-induced torsades de pointes. However, current ventricular models of electrophysiology usually ignore, or include highly simplified representations of the specialized conduction system. Here, we describe the development of an image-based, species-consistent, anatomically-detailed model of rabbit ventricular electrophysiology that incorporates a detailed description of the free-running part of the specialized conduction system. Techniques used for the construction of the geometrical model of the specialized conduction system from a magnetic resonance dataset and integration of the system model into a ventricular anatomical model, developed from the same dataset, are described. Computer simulations of rabbit ventricular electrophysiology are conducted using the novel anatomical model and rabbit-specific membrane kinetics to investigate the importance of the components and properties of the conduction system in determining ventricular function under physiological conditions. Simulation results are compared to panoramic optical mapping experiments for model validation and results interpretation. Full access is provided to the anatomical models developed in this study.
    Progress in Biophysics and Molecular Biology 06/2011; 107(1):90-100. DOI:10.1016/j.pbiomolbio.2011.05.002 · 3.38 Impact Factor
  • Source
    • "ate electrical models of the heart from MR and DTMR 85 imaging data (Vadakkumpadan et al. 2009b); these models 86 have been used successfully to study problems in cardiac 87 arrhythmogenesis and defibrillation (Vadakkumpadan et al. 88 2009b). "
    [Show abstract] [Hide abstract]
    ABSTRACT: Current multi-scale computational models of ventricular electromechanics describe the full process of cardiac contraction on both the micro- and macro- scales including: the depolarization of cardiac cells, the release of calcium from intracellular stores, tension generation by cardiac myofilaments, and mechanical contraction of the whole heart. Such models are used to reveal basic mechanisms of cardiac contraction as well as the mechanisms of cardiac dysfunction in disease conditions. In this paper, we present a methodology to construct finite element electromechanical models of ventricular contraction with anatomically accurate ventricular geometry based on magnetic resonance and diffusion tensor magnetic resonance imaging of the heart. The electromechanical model couples detailed representations of the cardiac cell membrane, cardiac myofilament dynamics, electrical impulse propagation, ventricular contraction, and circulation to simulate the electrical and mechanical activity of the ventricles. The utility of the model is demonstrated in an example simulation of contraction during sinus rhythm using a model of the normal canine ventricles.
    Biomechanics and Modeling in Mechanobiology 06/2011; 10(3):295-306. DOI:10.1007/s10237-010-0235-5 · 3.25 Impact Factor
Show more