Williams Steven E, Roney Caroline H, Connolly Adam, Sim Iain, Whitaker John, O'Hare Daniel, Kotadia Irum, O'Neill Louisa, Corrado Cesare, Bishop Martin, Niederer Steven A, Wright Matt, O'Neill Mark, Linton Nick W F
King's College London, London, United Kingdom.
Centre for Cardiovascular Science, The University of Edinburgh, Edinburgh, United Kingdom.
Front Physiol. 2021 Feb 26;12:646023. doi: 10.3389/fphys.2021.646023. eCollection 2021.
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: = 0.7726, < 0.0001; Volume: = 0.5179, < 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 = 0.8708, < 0.001; local activation time = 0.8892, < 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.
电解剖标测系统用于支持电生理学研究。从这些系统导出的数据以专有格式存储，难以访问且存储空间效率低下。以前没有工作提供过一个开源平台，用于以标准化格式解析和查询此数据。因此，我们试图开发一种标准化的开源数据结构和相关计算机代码，以高效利用空间且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来捕获可用的解剖学和电学数据。开发了在MATLAB中实现的OpenEP来解析和查询此数据。提供了用于分析腔室几何形状、激活标测、传导速度标测、电压标测、消融部位和心电图的功能，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验证。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数据比压缩后的临床数据小两个数量级（OpenEP：20.5±8.7 Mb，临床数据：1.46±0.77 Gb）。OpenEP得出的几何测量值与相同的临床测量值相关（面积：r = 0.7726，P < 0.0001；体积：r = 0.5179，P < 0.0001）。研究这些相关性中系统偏差的原因发现，OpenEP在恢复准确值方面优于临床平台。用OpenEP创建的激活标测和电压标测数据均与临床值相关（平均电压r = 0.8708，P < 0.001；局部激活时间r = 0.8892，P < 0.0001）。在当代一组标测研究中，OpenEP为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。
我们提出了用于评估电解剖标测数据的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既高效利用空间，又能准确代表原始数据。我们表明OpenEP捕获了当代基于电解剖标测的电生理学研究所需要的大部分数据，并提出了未来发展的路线图。
