Image-based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms
Résumé
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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