Key result
The computational modeling method successfully simulated realistic magnetocardiographic signals by coupling cardiac electrical activity with a volume conduction problem in a realistic torso model.
Computational modeling of magnetocardiographic signals using realistic human anatomical models may aid in developing computer-based tools for medical diagnosis and clarifying electrophysiological questions.
May support MCG tool development for diagnosis; leaves open clinical utility pending validation.
Although the first measurement of the cardiac magnetic field was reported almost half a century ago magnetocardiography (MCG) is not yet widely used as a clinical diagnostic technique. With the development of a new generation of magnetoelectric sensors it is believed that MCG will become widely accepted in the clinical diagnosis. Our goal is to build a computer-based tool for medical diagnosis and to use it for the clarification of open electro-physiological questions. Here we present results from modelling of the cardiac electrical activity and computation of the generated magnetic field. For the simulations we use MRT-based anatomical models of the human atria and ventricles where the shape of the action potential is determined by ionic currents passing through the cardiac cell membranes. The monodomain reaction-diffusion equation is chosen for the description of the heart's electrical activity. This equation is solved for the transmembrane voltage which is in turn used to calculate current densities at discrete time instants. In subsequent simulations these current densities represent primary sources of magnetostatic fields arising from a volume conduction problem. In these simulations the heart is placed in a realistic torso model where the lungs are also considered. Both, the volume conduction problem as well as the reaction-diffusion problem are modelled using Finite-Element techniques.
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Motrescu et al. (2012) studied Healthy (n=1). Computational modeling of magnetocardiographic signals was evaluated on Computed magnetic fields of the heart (magnetocardiographic signals). The computational modeling method successfully simulated realistic magnetocardiographic signals by coupling cardiac electrical activity with a volume conduction problem in a realistic torso model.
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