OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research.
OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research.
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OpenEP：一种用于电生理研究的跨平台电解剖制图数据格式和分析平台。
DOI：
10.3389/fphys.2021.646023
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发表时间：
2021
影响因子：
4
通讯作者：
Linton NWF
中科院分区：
文献类型：
--
作者：
Williams SE;Roney CH;Connolly A;Sim I;Whitaker J;O'Hare D;Kotadia I;O'Neill L;Corrado C;Bishop M;Niederer SA;Wright M;O'Neill M;Linton NWF
电解剖标测系统用于支持电生理学研究。从这些系统中导出的数据以专有格式存储，这些格式访问起来具有挑战性，并且存储空间效率低下。以前的工作没有提供一个开源平台，用于以标准化格式解析和查询这些数据。因此，我们试图开发一种标准化的开源数据结构和相关的计算机代码，以节省空间和易于访问的方式存储电解剖标测数据。定义了一种数据结构，用于捕获可用的解剖和电气数据。在MATLAB中实现的OpenEP被开发用于解析和询问这些数据。提供了分析腔室几何结构、激活标测、传导速度标测、电压标测、消融部位和电描记图的功能以及可视化和输入/输出功能。对数据导入和存储进行了性能基准测试。对腔室几何形状、激活标测、电压标测和消融表示进行了数据导入和分析确认。最后，对电生理学文献进行了系统分析，以确定OpenEP对当代电生理学研究的适用性。解析临床数据集的平均时间为每位患者400 ± 162秒。OpenEP数据比压缩的临床数据小两个数量级（OpenEP：20.5 ± 8.7 Mb，临床：1.46 ± 0.77 Gb）。OpenEP衍生的几何度量与相同的临床度量相关（面积：R2 = 0.7726，P < 0.0001;体积：R2 = 0.5179，P < 0.0001）。调查这些相关性中系统偏倚的原因显示，OpenEP在恢复准确值方面优于临床平台。使用OpenEP创建的激活和电压标测数据均与临床值相关（平均电压R2 = 0.8708，P < 0.001;局部激活时间R2 = 0.8892，P < 0.0001）。OpenEP为当代映射研究队列中92种定性评估分析技术中的87种（95%）和136种定量评估分析技术中的119种（88%）提供了必要的处理。我们提出了用于评价电解剖标测数据的OpenEP框架。OpenEP提供了进行电解剖标测研究所需的核心功能。我们证明了OpenEP既节省空间又能准确地代表原始数据。我们发现OpenEP捕获了当代基于电解剖标测的电生理学研究所需的大部分数据，并为未来的发展提出了路线图。
Electroanatomic mapping systems are used to support electrophysiology research. Data exported from these systems is stored in proprietary formats which are challenging to access and storage-space inefficient. No previous work has made available an open-source platform for parsing and interrogating this data in a standardized format. We therefore sought to develop a standardized, open-source data structure and associated computer code to store electroanatomic mapping data in a space-efficient and easily accessible manner. A data structure was defined capturing the available anatomic and electrical data. OpenEP, implemented in MATLAB, was developed to parse and interrogate this data. Functions are provided for analysis of chamber geometry, activation mapping, conduction velocity mapping, voltage mapping, ablation sites, and electrograms as well as visualization and input/output functions. Performance benchmarking for data import and storage was performed. Data import and analysis validation was performed for chamber geometry, activation mapping, voltage mapping and ablation representation. Finally, systematic analysis of electrophysiology literature was performed to determine the suitability of OpenEP for contemporary electrophysiology research. The average time to parse clinical datasets was 400 ± 162 s per patient. OpenEP data was two orders of magnitude smaller than compressed clinical data (OpenEP: 20.5 ± 8.7 Mb, vs clinical: 1.46 ± 0.77 Gb). OpenEP-derived geometry metrics were correlated with the same clinical metrics (Area: R2 = 0.7726, P < 0.0001; Volume: R2 = 0.5179, P < 0.0001). Investigating the cause of systematic bias in these correlations revealed OpenEP to outperform the clinical platform in recovering accurate values. Both activation and voltage mapping data created with OpenEP were correlated with clinical values (mean voltage R2 = 0.8708, P < 0.001; local activation time R2 = 0.8892, P < 0.0001). OpenEP provides the processing necessary for 87 of 92 qualitatively assessed analysis techniques (95%) and 119 of 136 quantitatively assessed analysis techniques (88%) in a contemporary cohort of mapping studies. We present the OpenEP framework for evaluating electroanatomic mapping data. OpenEP provides the core functionality necessary to conduct electroanatomic mapping research. We demonstrate that OpenEP is both space-efficient and accurately representative of the original data. We show that OpenEP captures the majority of data required for contemporary electroanatomic mapping-based electrophysiology research and propose a roadmap for future development.
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2.7
作者：
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