Atrial fibrillation (AF) is the most common heart rhythm disorder, affecting over 5 million Americans in whom it may cause skipped heart beats, dizziness, stroke and even death. Recent advances in mapping techniques have revealed that spiral waves, similar to electrical spinning tops, are present in the vast majority of AF patients.It was found that these spiral waves do not migrate throughout the atrial chambers but remain in a confined and stable spatial location. What is not clear, and limiting our ability to improve therap for AF, is how these stable spiral waves disorganize and cause AF. This project will test the novel hypothesis that structural components of the atrial tissue are responsible for the spatial stability of the spiral waves and that the disorganization is caused by 'functional' properties of the heart that occur at the level of cells. We will address this hypothesis using a combined theoretical/clinical approach that employs advanced multiscale computational techniques and state-of-the-art clinical mapping. We will 1) determine using computational simulations how structural properties of heart tissue can prevent spiral waves from migrating throughout the atria; 2) determine how drugs affect the migration and disorganization of spiral waves; 3) create patient-specific digital computer models to test possible causes of AF. The patient-specific digital computer models that we will create in this project will be among the most detailed and clinically-relevant in the field, and can be used by others to understand the disease and help design better therapy. This project is significant because it will establish new mechanisms for human atrial fibrillation, potentially resulting in novel therapies to eliminate AF. Understanding AF at this level may also allow a more rational approach to drug development and gene therapy. This project will be performed in patients during electrophysiologic study, so that its results can be translated directly to practice.
Atrial fibrillation (AF) is a serious public health issue that affects over 5 million Americans in whom it may cause skipped heart beats, dizziness, stroke and even death. In this project, we will use a combination of research in patients and computational modeling with as aim to increase our fundamental understanding of the causes of AF and to design new and more effective therapy.
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