OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research
| Autor: | Louisa O'Neill, Nick Linton, Mark D O'Neill, Steven Williams, Iain Sim, Steven A. Niederer, Daniel O'Hare, Matthew Wright, John Whitaker, Caroline H. Roney, Martin J. Bishop, Adam Connolly, Irum Kotadia, Cesare Corrado |
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| Rok vydání: | 2021 |
| Předmět: |
ablation electrophysiology
Source code Physiology Computer science media_common.quotation_subject 0206 medical engineering 02 engineering and technology 030204 cardiovascular system & hematology computer.software_genre lcsh:Physiology electroanatomic mapping conduction velocity 03 medical and health sciences 0302 clinical medicine Physiology (medical) Cross-platform Technology and Code atrial fibrillation MATLAB Representation (mathematics) data storage and retrieval media_common computer.programming_language lcsh:QP1-981 Data structure 020601 biomedical engineering Visualization Data mapping electroanatomic mapping atrial fibrillation data storage and retrieval conduction velocity ablation electrophysiology contact force electrophysiology – arrhythmia mapping and ablation Data mining contact force computer electrophysiology – arrhythmia mapping and ablation Volume (compression) |
| Zdroj: | Frontiers in Physiology, Vol 12 (2021) Williams, S E, Roney, C H, Connolly, A, Sim, I, Whitaker, J, O'Hare, D, Kotadia, I, O'Neill, L, Corrado, C, Bishop, M, Niederer, S A, Wright, M, O'Neill, M & Linton, N W F 2021, ' OpenEP: A Cross-Platform Electroanatomic Mapping Data Format and Analysis Platform for Electrophysiology Research ', Frontiers in physiology, vol. 12, 646023 . https://doi.org/10.3389/fphys.2021.646023 Frontiers in Physiology |
| ISSN: | 1664-042X |
| DOI: | 10.3389/fphys.2021.646023 |
| Popis: | BackgroundElectroanatomic 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.MethodsA 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.ResultsThe 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.ConclusionsWe 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. |
| Databáze: | OpenAIRE |
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