Collaborative Research: Developing a Quantitative Three-Dimensional Understanding of Cardiac Arrhythmias

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This project aims to develop a better understanding of what initiates some of the most lethal heart rhythms using mathematics and data assimilation methods used in weather forecasting. The detailed behavior of cardiac cells and tissue cannot be measured directly, especially inside of the heart muscle. This project will develop and validate new ways to estimate the behavior of the heart during abnormal rhythms. The knowledge gained will be used to identify ways that could be used to improve the effectiveness of treatments for these abnormal rhythms as delivered by electrical devices. The research efforts will also contribute to broadening participation of underrepresented groups and integration of research into both classroom teaching and informal education. The success of this project will directly contribute towards the progress of science to advance the national health. Many cardiac arrhythmias develop when the propagation of electrical waves through cardiac muscle, a process that triggers contraction, is disrupted. Despite the importance of understanding these arrhythmias and notwithstanding advances made through experimentation and computational modeling, many unanswered questions remain, especially regarding what happens in the typically unobserved thickness of cardiac tissue. This project will involve studying the role of tissue thickness on the development and progression of complicated spatiotemporal dynamics for certain types of arrhythmias such as tachycardia and fibrillation, when experiments often reveal little obvious correlation between surface observations. In particular, the detailed effects of potentially therapeutic electrical interventions will be analyzed. To accomplish these goals, data assimilation, a technique from weather forecasting, will be applied to recover high-resolution estimates of complex cardiac electrical states observed in experiments using spatiotemporally sparse observations of only one state variable. The response of the cardiac system when methods to control the dynamics are applied will be quantified. The resulting improved understanding of the heart's behavior and response to control attempts could lead to improved control methods that can restore normal behavior across the heart's thickness more reliably, more quickly, or with lower energies compared to standard methods.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.