Image-based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms

Abstract : Goal: In this work, we used in silico patient-specific models constructed from 3D delayed-enhanced magnetic resonance imaging (DE-MRI) to simulate intracardiac electrograms (EGM). These included electrically abnormal electrograms as these are potential radiofrequency ablation (RFA) targets. Methods: We generated signals with distinguishable macroscopic normal and abnormal characteristics by constructing MRI-based patient-specific structural heart models and by solving the simplified biophysical Mitchell-Schaeffer model of cardiac electrophysiology. Then, we simulated intracardiac electrograms by modelling a recording catheter using a dipole approach. Results: Qualitative results show that simulated EGM resemble clinical signals. Additionally, the quantitative assessment of signal features extracted from the simulated EGM showed statistically significant differences (p<0.0001) between the distributions of normal and abnormal electrograms, similarly to what is observed on clinical data. Conclusion: We demonstrate the feasibility of coupling simplified cardiac EP models with imaging data to generate intracardiac EMG. Significance: These results are a step forward in the direction of the pre-operative and non-invasive identification of ablation targets to guide RFA therapy.
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Contributor : Rocio Cabrera Lozoya <>
Submitted on : Wednesday, May 11, 2016 - 9:22:53 AM
Last modification on : Thursday, February 7, 2019 - 2:25:08 PM
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Rocío Cabrera-Lozoya, Benjamin Berte, Hubert Cochet, Pierre Jaïs, Nicholas Ayache, et al.. Image-based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2016, PP (99), ⟨10.1109/TBME.2016.2562918⟩. ⟨hal-01313615⟩



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