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

这个项目旨在利用天气预报中使用的数学和数据同化方法，更好地理解是什么引发了一些最致命的心率节律。心肌细胞和组织的详细行为不能直接测量，特别是在心肌内。该项目将开发和验证新的方法来估计异常节律期间的心脏行为。所获得的知识将被用来确定可以用来提高对电子设备所传递的这些异常节律的治疗效果的方法。研究工作还将有助于扩大代表性不足群体的参与，并将研究纳入课堂教学和非正规教育。该项目的成功将直接促进科学进步，促进国民健康。当电波在心肌中的传播被中断时，许多心律失常就会发生，这是一个触发收缩的过程。尽管了解这些心律失常很重要，尽管通过实验和计算建模取得了进展，但仍有许多未回答的问题，特别是关于通常未观察到的心脏组织厚度发生了什么。这个项目将涉及研究组织厚度在某些类型的心律失常(如心动过速和纤颤)复杂时空动力学的发展和进展中的作用，而实验往往显示表面观察之间几乎没有明显的相关性。特别是，潜在治疗性电干预的详细影响将被分析。为了实现这些目标，天气预报中的一种技术--数据同化将被应用于恢复在实验中观察到的复杂心脏电状态的高分辨率估计，该估计只使用一个状态变量的时空稀疏观测。当应用控制动力学的方法时，心脏系统的反应将被量化。由此产生的对心脏行为和对控制尝试的响应的改进可能会导致改进的控制方法，与标准方法相比，可以更可靠、更快或以更低的能量恢复心脏厚度的正常行为。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.