Construction and validation of anisotropic and orthotropic ventricular geometries for quantitative predictive cardiac electrophysiology (original) (raw)

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Review article| 03 Dec 2010

Alan P. Benson;

1

Institute of Membrane and Systems Biology

,

University of Leeds

,

Leeds LS2 9JT, UK

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

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Olivier Bernus;

1

Institute of Membrane and Systems Biology

,

University of Leeds

,

Leeds LS2 9JT, UK

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

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Hans Dierckx;

8

Department of Physics and Astronomy

,

Gent University

,

9000 Gent, Belgium

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Stephen H. Gilbert;

1

Institute of Membrane and Systems Biology

,

University of Leeds

,

Leeds LS2 9JT, UK

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

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John P. Greenwood;

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

3

Division of Cardiovascular and Neuronal Remodelling

,

University of Leeds

,

Leeds LS2 9JT, UK

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Arun V. Holden;

1

Institute of Membrane and Systems Biology

,

University of Leeds

,

Leeds LS2 9JT, UK

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

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Kevin Mohee;

4

School of Medicine

,

University of Leeds

,

Leeds LS2 9JT, UK

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Sven Plein;

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

3

Division of Cardiovascular and Neuronal Remodelling

,

University of Leeds

,

Leeds LS2 9JT, UK

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Aleksandra Radjenovic;

5

Section of Musculoskeletal Disease

,

University of Leeds

,

Leeds LS2 9JT, UK

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Michael E. Ries;

6

School of Physics and Astronomy

,

University of Leeds

,

Leeds LS2 9JT, UK

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Godfrey L. Smith;

9

Faculty of Biomedical and Life Sciences, Integrative and Systems Biology

,

University of Glasgow

,

Glasgow G12 8QQ, UK

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Steven Sourbron;

7

Division of Medical Physics

,

University of Leeds

,

Leeds LS2 9JT, UK

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Richard D. Walton

1

Institute of Membrane and Systems Biology

,

University of Leeds

,

Leeds LS2 9JT, UK

2

Multidisciplinary Cardiovascular Research Centre

,

University of Leeds

,

Leeds LS2 9JT, UK

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Publisher: The Royal Society

Received: 10 Sep 2010

Accepted: 08 Nov 2010

Published online: 03 Dec 2010

Online ISSN: 2042-8901

Print ISSN: 2042-8898

Interface Focus (2011) 1 (1): 101–116 .

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Citation

Alan P. Benson, Olivier Bernus, Hans Dierckx, Stephen H. Gilbert, John P. Greenwood, Arun V. Holden, Kevin Mohee, Sven Plein, Aleksandra Radjenovic, Michael E. Ries, Godfrey L. Smith, Steven Sourbron, Richard D. Walton; Construction and validation of anisotropic and orthotropic ventricular geometries for quantitative predictive cardiac electrophysiology. _Interface Focus 6 February 2011; 1 (1): 101–116. https://doi.org/10.1098/rsfs.2010.0005

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Abstract

Reaction–diffusion computational models of cardiac electrophysiology require both dynamic excitation models that reconstruct the action potentials of myocytes as well as datasets of cardiac geometry and architecture that provide the electrical diffusion tensor D, which determines how excitation spreads through the tissue. We illustrate an experimental pipeline we have developed in our laboratories for constructing and validating such datasets. The tensor D changes with location in the myocardium, and is determined by tissue architecture. Diffusion tensor magnetic resonance imaging (DT-MRI) provides three eigenvectors ei and eigenvalues λ i at each voxel throughout the tissue that can be used to reconstruct this architecture. The primary eigenvector e1 is a histologically validated measure of myocyte orientation (responsible for anisotropic propagation). The secondary and tertiary eigenvectors (e2 and e3) specify the directions of any orthotropic structure if _λ_2 is significantly greater than _λ_3—this orthotropy has been identified with sheets or cleavage planes. For simulations, the components of D are scaled in the fibre and cross-fibre directions for anisotropic simulations (or fibre, sheet and sheet normal directions for orthotropic tissues) so that simulated conduction velocities match values from optical imaging or plunge electrode experiments. The simulated pattern of propagation of action potentials in the models is partially validated by optical recordings of spatio-temporal activity on the surfaces of hearts. We also describe several techniques that enhance components of the pipeline, or that allow the pipeline to be applied to different areas of research: Q ball imaging provides evidence for multi-modal orientation distributions within a fraction of voxels, infarcts can be identified by changes in the anisotropic structure—irregularity in myocyte orientation and a decrease in fractional anisotropy, clinical imaging provides human ventricular geometry and can identify ischaemic and infarcted regions, and simulations in human geometries examine the roles of anisotropic and orthotropic architecture in the initiation of arrhythmias.

This Journal is © 2010 The Royal Society

2010

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