Novel Mapping Algorithms for Atrial Fiberillation

描述（由申请人提供）：目前房颤的手术治疗涉及在心房中创建无数切口，以阻断曾经被认为是潜在机制的多个大再入回路。然而，最近有研究表明，自动对焦通常由单个或少量空间稳定的焦点源维持。不幸的是，目前的心外膜测图技术非常耗时，并且不允许在手术治疗中采用测图引导的方法。我们建议开发一种算法来实时识别AF的这些独特底物。利用先前自动对焦记录数据库中的信息，我们将首先使用短时傅里叶变换评估自动对焦，该变换允许主频率的快速三维表示。该算法的发展将有助于更好地理解房颤的机制。在算法开发后，我们将展示使用犬类房颤模型实时映射的能力。接下来，我们将记录人类患者的数据，并将实时分析与离线分析进行比较，以确保准确性（波形分析将与更耗时的传统手工编辑技术进行权衡）。最后，使用这种实时算法和对房颤的理解将允许开发一种新的手术方法，使用地图定向治疗。

DESCRIPTION (provided by applicant): The present surgical treatment for AF involves creating a myriad of incisions in the atrium to block the multiple macroreentrant circuits that were once thought to be the underlying mechanism. However, recently it has been shown that AF is often maintained by a single or small number of spatially stable focal sources. Unfortunately, present technologies of epicardial mapping are time-consuming and do not allow for a map-guided approach for surgical treatment. We propose to develop an algorithm to identify these unique substrates of AF in real time. Using information in a database of prior AF recordings, we will first evaluate AF using the Short Time Fourier transform, which allows rapid three-dimensional representation of a dominant frequency. The development of this algorithm will allow for a better understanding of the mechanisms of AF. After development of the algorithm, we will demonstrate the ability to map in real-time using a canine model of atrial fibrillation. We will next record data from human patients, and compare real-time analysis with off-line analysis to ensure accuracy (wave analysis will be weighed against the more time-consuming traditional manual editing technique). Finally, use of this real-time algorithm and the understanding gained of AF will allow for the development of a novel surgical approach using map-directed treatment.