Novel Mapping Algorithms for Atrial Fibrillation

描述(申请人提供)：目前的房颤手术治疗包括在心房上创建无数的切口，以阻断曾经被认为是潜在机制的多个大折返回路。然而，最近的研究表明，房颤通常由单个或少数空间稳定的焦源维持。不幸的是，目前的心外膜标测技术是耗时的，并且不允许在MAP引导下进行外科治疗。我们建议开发一种算法来实时识别这些独特的房颤底物。使用之前的房颤记录数据库中的信息，我们将首先使用短时傅立叶变换来评估房颤，这允许快速三维表示主频。这一算法的发展将有助于更好地理解房颤的发生机制。在开发了算法之后，我们将使用心房颤动的犬模型来演示实时标测的能力。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动编辑技术进行权衡)。最后，这种实时算法的使用和对房颤的了解将允许开发一种使用MAP导向治疗的新的外科手术入路。

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.