In silico patient-specific models from 3D DE-MRI successfully simulated intracardiac electrograms, showing significant differences between normal and abnormal EGM distributions (p=0.0001).
Can in silico patient-specific models based on DE-MRI accurately simulate intracardiac electrograms to identify ablation targets?
Coupling simplified cardiac electrophysiology models with imaging data to generate intracardiac EGM is feasible and may help noninvasively identify radiofrequency ablation targets.
p-value: p=0.0001
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.
Lozoya et al. (Wed,) conducted a other in Abnormal ventricular electrograms. In silico patient-specific models from 3D DE-MRI was evaluated on Quantitative assessment of signal features between normal and abnormal EGM (p=0.0001). In silico patient-specific models from 3D DE-MRI successfully simulated intracardiac electrograms, showing significant differences between normal and abnormal EGM distributions (p=0.0001).