优化12导电心电图子集的自动早期左心室激活定位方法基于节奏测绘技术的优化
Shijie Zhou1, Amir AbdelWahab2, Raymond Wang3
1Department of Chemical, Paper, and Biomedical Engineering, College of Engineering and Computing, Miami University, Oxford, Ohio, USA; Department of Electrical and Computer Engineering, College of Engineering and Computing, Miami University, Oxford, Ohio, USA.
The Canadian journal of cardiology
|June 3, 2023
概括
这项研究确定了一个最佳的3导电心电图 (ECG) 集,用于通过自动化节奏映射定位左心室 (LV) 激活源. 这种最小的领先集提高了准确性,并减少了精确的LV激活映射所需的节奏点的数量.
科学领域:
- 心脏病学 心脏病学
- 电子生理学 电子生理学
- 医疗成像医学成像
背景情况:
- 自动步伐映射可以定位早期左心室 (LV) 激活来源.
- 目前的方法需要多个节奏点,需要更少的心电图 (ECG) 线索以提高效率.
- 确定一个最佳的最小的ECG导向集对于完善这种自动化方法至关重要.
研究的目的:
- 为了确定一个最优的最低一组的心电图带给一个自动化的LV激活源定位系统.
- 为了比较不同的集在准确识别LV激活源方面的性能.
主要方法:
- 利用了1715个LV内心节奏点位用于导出和测试数据集.
- 采用随机森林回归 (RFR) 和详尽的搜索来确定最佳的三导心电图集.
- 通过703个节奏站点的测试数据集,比较了已识别的领先集的性能,并计算了弗兰克的领先.
主要成果:
- 随机森林回归确定了线索III,V1和V4;详尽的搜索确定了线索II,V2和V6.
- 在使用5个或更多的节奏点时,两组被识别的组件都显示出与弗兰克线索相似的性能.
- 准确性提高了最多9个步调位置,当聚焦在可疑区域时,准确性达到<5毫米.
结论:
- 通过RFR识别的准直角的集有效地定位了LV激活源与最小的节奏站点.
- 使用已识别的线索的定位准确度很高,可与详尽的搜索或实证的弗兰克线索使用相比较.
- 这种优化的方法最大限度地减少了准确的LV激活映射所需的训练数据.
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