| Description |
Atrial fibrillation (AF) is the most common cardiac arrhythmia and a major cause of stroke. Catheter ablation is the most effective treatment for paroxysmal AF, yet often fails to treat persistent AF. This low success for persistent AF is rooted in two major weaknesses. First, there is an incomplete understanding of underlying mechanisms, of what initiates and sustains persistent AF. Secondly, the current ablation techniques frequently fail to create long-term lesions. We used AF animal models to develop a more mechanistic understanding of AF. With validating our models and series of detailed electrophysiology studies, imaging, and histology, we will test the hypothesis that there are drivers sustaining AF. Finally, we performed ablation to better characterize ablation lesions. Previous studies have been able to induce AF in control animals. In some of our studies, we have induced atrial flutter that appears to be atrial fibrillation on the surface electrocardiogram (ECG). In aim 1, I explored the induced arrhythmias in control animals and verified if mechanistically they are flutter or fibrillation. I hypothesized that spectral analysis on ECG signals can help us accurately diagnose the rhythm. Past studies have analyzed atrial electrograms to find the mechanism underlying AF. Most of these methods investigated features of the signal in the temporal domain. Most of these methods suffer from a lack of reliability and reproducibility because of the random nature of AF. In aim 2, I investigated the mechanistic behavior of AF by doing iv spectral analysis of atrial electrograms of chronic AF models. I hypothesized that high dominant frequency sites are more stable, which makes them likely sites of AF drivers and potential targets for ablation. Radiofrequency ablation is associated with reversible edema that blocks electrical conduction. With the recovery of edema the conduction block can recover, resulting in recurrence of the arrhythmia. In aim 3, I characterized properties of acute ablation lesions, using late gadolinium enhanced (LGE) MRI, pathology, and histology. Based on the findings, we proposed a method where we can predict chronic lesion from LGE-MRI done immediately post-ablation of acute lesions. |
