Collaborative Research: Intramural Forecasting of Cardiac Electrical Dynamics

这项研究将促进预防和治疗心律失常的具体方法的设计，也是证明状态估计技术用于研究心脏电动力学和其他深度信息很少或没有的3D动力系统的有效性的重要第一步。 心律失常是由于心脏中的正常电波传播被预先存在的异质区域或动态诱导的异质性破坏而导致的，所述动态诱导的异质性是由于快速起搏沿着系统的非线性动力学而发展的，这两者都可能导致波分裂。现有的方法用于观察电波在三维实验心脏准备稀疏的数据集的结果，无论是详细的表面观察或数据从少量的点在内部。另一方面，数值模型是研究三维波传播的重要方法，但只是真实动力学的近似。预测方法-以前未使用的心脏电模型-将被调整，以产生改进的估计三维传播的心脏电波。具体而言，数据同化技术-在数值天气预报领域的发展-将被应用到结合联合收割机的心脏组织表面上的电压与数值模型结果的时空观测，以获得一个更准确和现实的三维量化的心脏电波在心律失常的开始和进展。使用这种方法，将创建一个更准确的三维时间序列，可用于确定心律失常诱导和维持的机制。心血管疾病，包括心律失常，如纤维性颤动，是工业化国家最常见的死亡原因，并对健康和经济产生严重影响。治疗心律失常的进展受到阻碍，部分原因是缺乏对其动力学的了解，这源于难以获得心脏组织厚度内的观察结果。从天气预报的成功技术将被应用到推断心脏组织的三维电动力学定量使用数据获得的内部和外部的心脏表面。这项研究有可能阐明潜在的心律失常的机制，并可能导致新的治疗方法。此外，作为这一项目的一部分所做的工作可能有助于在难以获得三维观测的各种领域，包括了解脑癌的扩散和深海的动态，在预报技术方面取得进展。

This research will promote the design of specific methods for preventing and treating arrhythmias and also is an important first step in demonstrating the effectiveness of state estimation techniques for studying cardiac electrical dynamics and other 3D dynamical systems where little or no depth information is available. Cardiac arrhythmias result from the disruption of normal electrical wave propagation in the heart by pre-existing heterogeneous regions or by dynamically induced heterogeneities that develop as a consequence of rapid pacing along with the nonlinear dynamics of the system, both of which can lead to wave breakup. Existing methods for observing electrical waves in three-dimensional experimental heart preparations result in sparse data sets, with either detailed surface observations or data from a small number of points in the interior. Numerical models, on the other hand, are an important method for studying three-dimensional wave propagation, but are only an approximation of the true dynamics. Forecasting methods - previously unused for cardiac electrical models - will be adapted to generate improved estimates of the three-dimensional propagation of cardiac electrical waves. Specifically, data assimilation techniques - developed in the field of numerical weather forecasting - will be applied to combine spatiotemporal observations of voltage on cardiac tissue surfaces with numerical model results to derive a more accurate and realistic three-dimensional quantification of cardiac electrical waves during the initiation and progression of arrhythmias. Using this approach, a more accurate three-dimensional time series that could be used to determine the mechanisms involved in arrhythmia induction and maintenance will be created. Cardiovascular diseases, including cardiac arrhythmias like fibrillation, are the most common cause of death in the industrialized world and have serious health and economic impacts. Advances in treating arrhythmias are hindered in part because of the lack of understanding of their dynamics, which stems from the difficulty of obtaining observations within the thickness of heart tissue. Successful techniques from weather forecasting will be applied to infer the three-dimensional electrical dynamics of cardiac tissue quantitatively using data obtained at the interior and exterior surfaces of the heart.This research has the potential to elucidate mechanisms underlying cardiac arrhythmias and may lead to new treatment approaches. In addition, the work done as part of this project may contribute to advances in forecasting techniques in a variety of fields where three-dimensional observations are difficult to obtain, including understanding the spread of brain cancer and the dynamics of the deep ocean.