Mechanical deformation affects the electrical activity of the heart through multiple feedback loops. The purpose of this work is to study the effect of deformation on transmural dispersion of repolarization and on surface electrograms using an in silico human ventricular wedge. To achieve this purpose, we developed a strongly coupled electromechanical cell model by coupling a human left ventricle electrophysiology model and an active contraction model reparameterized for human cells. This model was then embedded in tissue simulations on the basis of bidomain equations and nonlinear solid mechanics. The coupled model was used to evaluate effects of mechanical deformation on important features of repolarization and electrograms. Our results indicate an increase in the T-wave amplitude of the surface electrograms in simulations that account for the effects of cardiac deformation. This increased T-wave amplitude can be explained by changes to the coupling between neighboring myocytes, also known as electrotonic effect. The thickening of the ventricular wall during repolarization contributes to the decoupling of cells in the transmural direction, enhancing action potential heterogeneity and increasing both transmural repolarization dispersion and T-wave amplitude of surface electrograms. The simulations suggest that a considerable percentage of the T-wave amplitude (15%) may be related to cardiac deformation.

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Abstract. An important parameter to analyze the efficiency of the heart as a pump is Cardiac Ejection Fraction (EF), which is clinically highly correlated to the functional status of the heart. Diverse non invasive methods can be applied to measure EF, like Computer Tomography, Magnetic Resonance, Echocardiography, and others. Nevertheless, none of these techniques can be used to continuous monitoring of such parameter. On the other hand, electrical impedance tomography (EIT) may be applied to accomplish this goal. In addition, low cost and high portability are also EIT's features that justify the research for solutions involving such technique to monitor EF. EIT consists in reconstruct images of the conductivity distribution of the interior of a conductor domain by applying electric currents and measuring electrical potential on the boundary of the body. Mathematically, EIT can be classified as a non-linear inverse problem. This work proposes a method for the continuous estimation of cardiac ejection fraction, addressing it as an optimization problem. The models used in our approach assume that recent two-dimensional magnetic resonance images of the patient are available, and use them to reduce the search space. Another important feature is the parametrization of the geometry of internal inclusions inside the domain, which also reduces the cost of the method. This work proposes a Hybrid Iterated Local Search (ILS) heuristic for EIT inverse problem using Levenberg-Marquardt Method as local search. Experiments are performed on two-dimensional images with synthetically generated data for electric potentials. Two different protocols for current injection are tested in such experiments and preliminary results are presented.

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