Image-Based Biophysical Simulation of Intracardiac Abnormal Ventricular Electrograms

Goal: In this paper, we used in silico patient-specific models constructed from three-dimensional delayed-enhanced magnetic resonance imaging (DE-MRI) to simulate intracardiac electrograms (EGM). These included electrically abnormal EGM 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 (EP). Then, we simulated intracardiac EGM by modeling 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 EGM, 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 preoperative and noninvasive identification of ablation targets to guide RFA therapy.