Patient specific simulation of body surface ECG using the finite element method.

Pacing Clin Electrophysiol

Department of Human and Engineered Environmental Studies, Graduate School of Frontier Sciences, The University of Tokyo, Kashiwanoha, Japan.

Published: March 2013

AI Article Synopsis

  • Recent advances in computer science have enabled the simulation of heart excitation and repolarization processes using detailed cell models, which now extend to patient-specific electrocardiograms (ECGs).
  • The study involved creating personalized models for four patients with differing heart diseases and using the multi-grid method to accurately simulate their ECGs based on clinical data.
  • The results showed good agreement between simulated and actual ECGs, even under bi-ventricular pacing, suggesting that these personalized models can enhance our understanding of heart function and have potential clinical applications.

Article Abstract

Background: Recent studies, supported by advances in computer science, have successfully simulated the excitation and repolarization processes of the heart, based on detailed cell models of electrophysiology and implemented with realistic morphology.

Methods: In this study, we extend these approaches to simulate the body surface electrocardiogram (ECG) of specific individuals. Patient-specific finite element models of the heart and torso are created for four patients with various heart diseases, based on clinical data including computer tomography, while the parallel multi-grid method is used to solve the dynamic bi-domain problem. Personalization procedures include demarcation of nonexcitable tissue, allocation of the failing myocyte model of electrophysiology, and modification of the excitation sequence. In particular, the adjustment of QRS morphology requires iterative computations, facilitated by the simultaneous visualization of the propagation of excitation in the heart, average QRS vector in the torso, and 12-lead ECG.

Results: In all four cases we obtained reasonable agreement between the simulated and actual ECGs. Furthermore, we also simulated the ECGs of three of the patients under bi-ventricular pacing, and once again successfully reproduced the actual ECG morphologies. Since no further adjustments were made to the heart models in the pacing simulations, the good agreement provides strong support for the validity of the models.

Conclusions: These results not only help us understand the cellular basis of the body surface ECG, but also open the possibility of heart simulation for clinical applications.

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Source
http://dx.doi.org/10.1111/pace.12057DOI Listing

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