부산대학교 도서관

Objective: Ablation treatment of ventricular arrhythmias can be facilitated by pre-procedure planning aided by electrocardiographic inverse solution, which can help to localize the origin of arrhythmia. Our aim was to improve localization accuracy of the inverse solution by using a novel Bayesian approach. Methods: The inverse problem of electrocardiography was solved by reconstructing epicardial potentials from 120 body-surface electrocardiograms and from patient-specific geometry of the heart and torso for four patients suffering from scar-related ventricular tachycardia who underwent epicardial catheter mapping, which included pace-mapping. Simulations using dipole sources in patient-specific geometry were also performed. The proposed method, using dynamic spatio-temporal a priori constraints of the solution, was compared with classical Tikhonov methods based on fixed constraints. Results: The mean localization error of the proposed method for all available pacing sites $(n=78)$ was significantly smaller than that achieved by Tikhonov methods; specifically, the localization accuracy for pacing in the normal tissue $(n=17)$ was $\text{8} \pm \text{6}$ mm (mean $\pm$ SD) versus $\text{13} \pm \text{9}$ mm $(P < 0.00001)$ reported in the previous study using the same clinical data and Tikhonov regularization. Simulation experiments further supported these clinical findings. Conclusion: The promising results of in vivo and in silico experiments presented in this study provide a strong incentive to pursuing further investigation of data-driven Bayesian methods in solving the electrocardiographic inverse problem. Significance: The proposed approach to localizing origin of ventricular activation sequence may have important applications in pre-procedure assessment of arrhythmias and in guiding their ablation treatment.