Journal of Electrocardiology
Volume 42, Issue 2 , Pages 157.e1-157.e10, March 2009

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

  • Fijoy Vadakkumpadan, PhD

      Affiliations

    • Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, MD, USA
    • ,
  • Lukas J. Rantner, MS

      Affiliations

    • Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, MD, USA
    • ,
  • Brock Tice, BS

      Affiliations

    • Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, MD, USA
    • ,
  • Patrick Boyle, BS

      Affiliations

    • Department of Electrical and Computer Engineering, University of Calgary, AB, Canada
    • ,
  • Anton J. Prassl, PhD

      Affiliations

    • Institute of Biophysics, Medical University of Graz, Graz, Austria
    • ,
  • Edward Vigmond, PhD

      Affiliations

    • Department of Electrical and Computer Engineering, University of Calgary, AB, Canada
    • ,
  • Gernot Plank, PhD

      Affiliations

    • Institute of Biophysics and Institute of Physiology, Medical University of Graz, Graz, Austria
    • Corresponding Author InformationCorresponding author. Tel.: +43 316 380 7745; fax: +43 316 380 9660.
    • ,
  • Natalia Trayanova, PhD

      Affiliations

    • Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, MD, USA

Received 22 November 2008 published online 02 February 2009.

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.

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☆ This work was supported by NIH grants R01-HL063195, R01-HL082729, and R01-HL067322, and the NSF grant CBET-0601935 to NT, by the Mathematics of Information Systems and Complex Systems network and the Natural Sciences and Engineering Research Council of Canada to EV, and by a Marie Curie Fellowship MC-OIF 040190 and the Austrian Science Fund grant SFB F3210-N18 to GP. Furthermore, the authors thank the teams of Drs Kohl, Gavaghan, and Schneider at the University of Oxford for access to data from their 3D Heart Project, BBSRC grant E003443.

PII: S0022-0736(08)00491-3

doi:10.1016/j.jelectrocard.2008.12.003

Journal of Electrocardiology
Volume 42, Issue 2 , Pages 157.e1-157.e10, March 2009

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