Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE
Analysis and visualization of intracardiac electrograms in diagnosis and research: Concept and application of KaPAVIE
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DOI：
10.1016/j.cmpb.2015.12.007
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发表时间：
2016-04-01
影响因子：
6.1
通讯作者：
Luik, Armin
中科院分区：
文献类型：
--
作者：
Oesterlein, Tobias Georg;Schmid, Jochen;Luik, Armin
背景和目的：生物医学工程的进展改善了可用于诊断和治疗心律失常的硬件。但是，虽然在电生理检查中可以获得大量的心内电信号，但仍然缺乏辅助诊断的软件。由于这项任务的高度跨学科性质，并阻碍了临床系统中的数据访问，因此开发用于EGM自动分析的新算法已被证明是困难的。为此，我们开发了一个软件平台，可以快速实现新算法，验证其功能，并适合在临床环境中讨论可视化。方法：利用VTK类库，用Qt5和C++开发可视化软件。信号分析算法在MatLab中实现。结果：实现了可视化软件KaPAVIE(Karlsruhe Platform For Analyst And VisualizationofInactericalExtra)，并在多个临床数据集上进行了测试。实现了常见和新颖的算法，解决了诊断不同心律失常的重要临床问题。由于其交互式和用户友好的设计，它在与临床医生的讨论中被证明是有用的。从临床地图系统导出到可视化的时间不超过5分钟。结论：KaPAVIE)是在临床环境下开发新算法的强大平台。测量的心电地形图数据和分析结果的同步和交互可视化将有助于诊断，并有助于了解房颤等复杂心律失常的潜在机制。(C)2015爱思唯尔爱尔兰有限公司。保留所有权利。
Background and objective: Progress in biomedical engineering has improved the hardware available for diagnosis and treatment of cardiac arrhythmias. But although huge amounts of intracardiac electrograms (EGMs) can be acquired during electrophysiological examinations, there is still a lack of software aiding diagnosis. The development of novel algorithms for the automated analysis of EGMs has proven difficult, due to the highly interdisciplinary nature of this task and hampered data access in clinical systems. Thus we developed a software platform, which allows rapid implementation of new algorithms, verification of their functionality and suitable visualization for discussion in the clinical environment.Methods: A software for visualization was developed in Qt5 and C++ utilizing the class library of VTK. The algorithms for signal analysis were implemented in MATLAB. Clinical data for analysis was exported from electroanatomical mapping systems.Results: The visualization software KaPAVIE (Karlsruhe Platform for Analysis and Visualization of Intracardiac Electrograms) was implemented and tested on several clinical datasets. Both common and novel algorithms were implemented which address important clinical questions in diagnosis of different arrhythmias. It proved useful in discussions with clinicians due to its interactive and user-friendly design. Time after export from the clinical mapping system to visualization is below 5 min.Conclusion: KaPAVIE) is a powerful platform for the development of novel algorithms in the clinical environment. Simultaneous and interactive visualization of measured EGM data and the results of analysis will aid diagnosis and help understanding the underlying mechanisms of complex arrhythmias like atrial fibrillation. (C) 2015 Elsevier Ireland Ltd. All rights reserved.