在心律失常期间检测正规的旋转活动,使用导向图的赫尔姆霍尔茨分解
Sebastiaan Lootens1, Robin Van den Abeele1, Vineesh Kappadan2
1Department of Physics and Astronomy, Ghent University, Ghent, Belgium.
Journal of molecular and cellular cardiology
|May 22, 2025
概括
我们开发了DGM-CURL,这是一种使用指向图表检测心脏再进入的新方法. 这种方法是定向图形映射 (DGM) 的扩展,通过分析激活时间差异来确定重新进入区域.
科学领域:
- 计算生物学 计算生物学
- 心血管电生理学 心血管电生理学
- 图形理论 图形理论
背景情况:
- 心律不整,特别是心律不整重返,在诊断和治疗方面带来了重大挑战.
- 现有的检测再进入的方法,如相位映射和定向循环搜索,都有局限性.
- 需要新的计算方法来提高重新进入检测的准确性和可靠性.
研究的目的:
- 引入DGM-CURL,这是一种基于导向图的赫尔姆霍尔茨分解检测心脏再进入的新方法.
- 评估DGM-CURL的性能与使用各种数据集的现有方法相比.
- 强调使用多个算法的重要性,以便对心脏旋转活动进行可靠的检测.
主要方法:
- DGM-CURL是指向图形映射 (DGM) 框架的扩展,在指向图形上使用赫尔姆霍尔茨分解.
- 在心脏组织的图形表示中分析节点之间的局部激活时间差异.
- 在四个不同的数据集中与相位映射 (PM) 和定向循环搜索 (DGM-CYCLE) 进行比较.
主要成果:
- 在模拟的2D和3D模型中,DGM-CURL成功地识别了再进入,临床心房高心率数据和实验性心室动数据.
- DGM-CURL中的高卷曲值与图节点平衡激活时间差异相关,表明重新进入.
- 在所有数据集中观察到DGM-CURL,PM和DGM-CYCLE之间的一般一致性.
结论:
- DGM-CURL提供了一种新且有效的方法来检测心脏再进入.
- 结合多个检测算法,包括DGM-CURL,提高了识别旋转活动的可靠性和准确性.
- 多算法方法提供了对心律失常动态的更全面的理解.
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