Send to

Choose Destination
Wiley Interdiscip Rev Syst Biol Med. 2010 Jul-Aug;2(4):489-506. doi: 10.1002/wsbm.76.

Image-based models of cardiac structure in health and disease.

Author information

Institute for Computational Medicine and the Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Institute of Biophysics and Institute of Physiology, Medical University of Graz, Graz, Austria.
Consortium for Translational Research in Advanced Imaging and Nanomedicine, Washington University School of Medicine, St. Louis, MO, USA.
CAE Software Solutions, Eggenburg, Austria.
Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, UK.


Computational approaches to investigating the electromechanics of healthy and diseased hearts are becoming essential for the comprehensive understanding of cardiac function. In this article, we first present a brief review of existing image-based computational models of cardiac structure. We then provide a detailed explanation of a processing pipeline which we have recently developed for constructing realistic computational models of the heart from high resolution structural and diffusion tensor (DT) magnetic resonance (MR) images acquired ex vivo. The presentation of the pipeline incorporates a review of the methodologies that can be used to reconstruct models of cardiac structure. In this pipeline, the structural image is segmented to reconstruct the ventricles, normal myocardium, and infarct. A finite element mesh is generated from the segmented structural image, and fiber orientations are assigned to the elements based on DTMR data. The methods were applied to construct seven different models of healthy and diseased hearts. These models contain millions of elements, with spatial resolutions in the order of hundreds of microns, providing unprecedented detail in the representation of cardiac structure for simulation studies.

[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Wiley Icon for PubMed Central
Loading ...
Support Center