3 April 2008 Assessing influence of conductivity in heart modelling with the aim of studying cardiovascular diseases
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Proceedings Volume 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images; 691627 (2008); doi: 10.1117/12.770258
Event: Medical Imaging, 2008, San Diego, California, United States
Abstract
The bidomain/monodomain equations have been widely used to model electrical activity in cardiac tissue. Here we present a sensitivity study of a crucial parameter in the bidomain model, the tissue conductivity. This study is necessary since there is no general agreement on the actual values that should be employed, mainly due to inconsistencies between the few sources of empirical information existent in the literature. Furthermore, estimates of this parameter from either imaging techniques or from experiments on isolated cardiac tissue have been inconsistent. For this study, a 3D biventricular model built from Multi-Detector Computer Tomography was used with the most relevant electrical structures, such as myocardial fiber orientation and the Purkinje system, were included. Specific ionic models for normal myocardium and for the Purkinje system were taken into account. Finite Element methods were used to solve the monodomain equation for a number of different conductivity settings. Comparative results using isochronal maps are shown in combination with statistical tests to measure changes in the sequence of electrical activation in the myocardium, conduction velocities (CV), and local activation times (LAT).
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Rafael Sebastian, Sebastian Ordas, Gernot Plank, Blanca Rodriguez, Edward J. Vigmond, Alejandro F. Frangi, "Assessing influence of conductivity in heart modelling with the aim of studying cardiovascular diseases", Proc. SPIE 6916, Medical Imaging 2008: Physiology, Function, and Structure from Medical Images, 691627 (3 April 2008); doi: 10.1117/12.770258; https://doi.org/10.1117/12.770258
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KEYWORDS
3D modeling

Tissues

Computer simulations

Anisotropy

Heart

Mathematical modeling

Computed tomography

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