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纤维颤动动力学的定量分析标准化框架。

Standardised Framework for Quantitative Analysis of Fibrillation Dynamics.

机构信息

National Heart and Lung Institute, Hammersmith Campus, Imperial College London, 72 Du Cane Rd, London, W120UQ, UK.

School of Biomedical Engineering & Imaging Sciences, King's College London, St. Thomas' Hospital, Westminster Bridge Road, London, UK.

出版信息

Sci Rep. 2019 Nov 13;9(1):16671. doi: 10.1038/s41598-019-52976-y.

Abstract

The analysis of complex mechanisms underlying ventricular fibrillation (VF) and atrial fibrillation (AF) requires sophisticated tools for studying spatio-temporal action potential (AP) propagation dynamics. However, fibrillation analysis tools are often custom-made or proprietary, and vary between research groups. With no optimal standardised framework for analysis, results from different studies have led to disparate findings. Given the technical gap, here we present a comprehensive framework and set of principles for quantifying properties of wavefront dynamics in phase-processed data recorded during myocardial fibrillation with potentiometric dyes. Phase transformation of the fibrillatory data is particularly useful for identifying self-perpetuating spiral waves or rotational drivers (RDs) rotating around a phase singularity (PS). RDs have been implicated in sustaining fibrillation, and thus accurate localisation and quantification of RDs is crucial for understanding specific fibrillatory mechanisms. In this work, we assess how variation of analysis parameters and thresholds in the tracking of PSs and quantification of RDs could result in different interpretations of the underlying fibrillation mechanism. These techniques have been described and applied to experimental AF and VF data, and AF simulations, and examples are provided from each of these data sets to demonstrate the range of fibrillatory behaviours and adaptability of these tools. The presented methodologies are available as an open source software and offer an off-the-shelf research toolkit for quantifying and analysing fibrillatory mechanisms.

摘要

分析心室颤动 (VF) 和心房颤动 (AF) 的复杂机制需要复杂的工具来研究时空动作电位 (AP) 传播动力学。然而,颤动分析工具通常是定制的或专有的,并且在研究小组之间存在差异。由于缺乏最佳的标准化分析框架,来自不同研究的结果导致了不同的发现。鉴于存在技术差距,我们在此提出了一个全面的框架和一套原则,用于量化在用电势染料记录的心肌颤动期间相处理数据中波前动力学的特性。相变换的纤维颤动数据特别有助于识别自我维持的螺旋波或旋转驱动器 (RD) 围绕相位奇点 (PS) 旋转。RD 与维持颤动有关,因此准确定位和量化 RD 对于理解特定的颤动机制至关重要。在这项工作中,我们评估了在跟踪 PS 和量化 RD 时分析参数和阈值的变化如何导致对潜在颤动机制的不同解释。这些技术已经被描述并应用于实验性 AF 和 VF 数据以及 AF 模拟中,并且从每个数据集提供了示例,以展示这些工具的广泛的纤维颤动行为和适应性。所提出的方法学是作为开源软件提供的,为量化和分析纤维颤动机制提供了现成的研究工具包。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cf4a/6853901/8c74129388da/41598_2019_52976_Fig1_HTML.jpg

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