Key result
Including the endocardium in inverse electrocardiography yields similar activation time correlations to the epicardium alone.
Why the study?
It was unknown whether solving the inverse problem of electrocardiography with the endocardium improves the reconstruction of activation and repolarization times.
Does including the endocardium in the parameter optimization mesh improve the reconstruction of activation and repolarization times in electrocardiographic imaging?
Does including the endocardium in the parameter optimization mesh improve the reconstruction of activation and repolarization times in electrocardiographic imaging?
Including the endocardium in electrocardiographic imaging inverse problem solutions may be useful when endo-epicardial gradients in activation or repolarization times play an important role.
Electrocardiographic imaging aims at reconstructing cardiac electrical events from electrical signals measured on the body surface. The most common approach relies on the inverse solution of the Laplace equation in the torso to reconstruct epicardial potential maps from body surface potential maps. Here we apply a method based on a parameter identification problem to reconstruct both activation and repolarization times. From an ansatz of action potential, based on the Mitchell-Schaeffer ionic model, we compute body surface potential signals. The inverse problem is reduced to the identification of the parameters of the Mitchell-Schaeffer model. We investigate whether solving the inverse problem with the endocardium improves the results or not. We solved the parameter identification problem on two different meshes: one with only the epicardium, and one with both the epicardium and the endocardium. We compared the results on both the heart (activation and repolarization times) and the torso. The comparison was done on validation data of sinus rhythm and ventricular pacing. We found similar results with both meshes in 6 cases out of 7: the presence of the endocardium slightly improved the activation times. This was the most visible on a sinus beat, leading to the conclusion that inclusion of the endocardium would be useful in situations where endo-epicardial gradients in activation or repolarization times play an important role.
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Ravon et al. (2019) studied Electrocardiographic imaging (ECGI). Parameter optimization method including both epicardium and endocardium (Mesh2) vs. Parameter optimization method including epicardium only (Mesh1) was evaluated on Correlation coefficient for activation times (ATs) (p=0.5). Including the endocardium in a parameter optimization method to solve the inverse problem of electrocardiography yielded similar results to using the epicardium alone, with no significant differences in correlation coefficients for activation times (p=0.5).
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