Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping
Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the h...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-09-01
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| Series: | Frontiers in Physiology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fphys.2019.01138/full |
| _version_ | 1818011368625799168 |
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| author | Nele Vandersickel Enid Van Nieuwenhuyse Nico Van Cleemput Jan Goedgebeur Jan Goedgebeur Milad El Haddad Jan De Neve Anthony Demolder Teresa Strisciuglio Mattias Duytschaever Mattias Duytschaever Alexander V. Panfilov Alexander V. Panfilov |
| author_facet | Nele Vandersickel Enid Van Nieuwenhuyse Nico Van Cleemput Jan Goedgebeur Jan Goedgebeur Milad El Haddad Jan De Neve Anthony Demolder Teresa Strisciuglio Mattias Duytschaever Mattias Duytschaever Alexander V. Panfilov Alexander V. Panfilov |
| author_sort | Nele Vandersickel |
| collection | DOAJ |
| description | Networks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proof-of-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow determination of the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve the accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood. |
| first_indexed | 2024-04-14T06:06:49Z |
| format | Article |
| id | doaj.art-a4552fcf30cf4d3f9cf98fa434111c99 |
| institution | Directory Open Access Journal |
| issn | 1664-042X |
| language | English |
| last_indexed | 2024-04-14T06:06:49Z |
| publishDate | 2019-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Physiology |
| spelling | doaj.art-a4552fcf30cf4d3f9cf98fa434111c992022-12-22T02:08:30ZengFrontiers Media S.A.Frontiers in Physiology1664-042X2019-09-011010.3389/fphys.2019.01138476310Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph MappingNele Vandersickel0Enid Van Nieuwenhuyse1Nico Van Cleemput2Jan Goedgebeur3Jan Goedgebeur4Milad El Haddad5Jan De Neve6Anthony Demolder7Teresa Strisciuglio8Mattias Duytschaever9Mattias Duytschaever10Alexander V. Panfilov11Alexander V. Panfilov12Department of Physics and Astronomy, Ghent University, Ghent, BelgiumDepartment of Physics and Astronomy, Ghent University, Ghent, BelgiumDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, BelgiumDepartment of Applied Mathematics, Computer Science and Statistics, Ghent University, Ghent, BelgiumComputer Science Department, University of Mons, Mons, BelgiumGhent University Hospital Heart Center, Ghent University, Ghent, BelgiumDepartment of Data Analysis, Ghent University, Ghent, BelgiumGhent University Hospital Heart Center, Ghent University, Ghent, BelgiumCardiology Department, AZ Sint-Jan, Bruges, BelgiumGhent University Hospital Heart Center, Ghent University, Ghent, BelgiumCardiology Department, AZ Sint-Jan, Bruges, BelgiumDepartment of Physics and Astronomy, Ghent University, Ghent, BelgiumLaboratory of Computational Biology and Medicine, Ural Federal University, Ekaterinburg, RussiaNetworks provide a powerful methodology with applications in a variety of biological, technological and social systems such as analysis of brain data, social networks, internet search engine algorithms, etc. To date, directed networks have not yet been applied to characterize the excitation of the human heart. In clinical practice, cardiac excitation is recorded by multiple discrete electrodes. During (normal) sinus rhythm or during cardiac arrhythmias, successive excitation connects neighboring electrodes, resulting in their own unique directed network. This in theory makes it a perfect fit for directed network analysis. In this study, we applied directed networks to the heart in order to describe and characterize cardiac arrhythmias. Proof-of-principle was established using in-silico and clinical data. We demonstrated that tools used in network theory analysis allow determination of the mechanism and location of certain cardiac arrhythmias. We show that the robustness of this approach can potentially exceed the existing state-of-the art methodology used in clinics. Furthermore, implementation of these techniques in daily practice can improve the accuracy and speed of cardiac arrhythmia analysis. It may also provide novel insights in arrhythmias that are still incompletely understood.https://www.frontiersin.org/article/10.3389/fphys.2019.01138/fullnetwork theorycardiac arrhythmiaatrial tachycardiarotational activityfocal activityphase mapping |
| spellingShingle | Nele Vandersickel Enid Van Nieuwenhuyse Nico Van Cleemput Jan Goedgebeur Jan Goedgebeur Milad El Haddad Jan De Neve Anthony Demolder Teresa Strisciuglio Mattias Duytschaever Mattias Duytschaever Alexander V. Panfilov Alexander V. Panfilov Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping Frontiers in Physiology network theory cardiac arrhythmia atrial tachycardia rotational activity focal activity phase mapping |
| title | Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping |
| title_full | Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping |
| title_fullStr | Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping |
| title_full_unstemmed | Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping |
| title_short | Directed Networks as a Novel Way to Describe and Analyze Cardiac Excitation: Directed Graph Mapping |
| title_sort | directed networks as a novel way to describe and analyze cardiac excitation directed graph mapping |
| topic | network theory cardiac arrhythmia atrial tachycardia rotational activity focal activity phase mapping |
| url | https://www.frontiersin.org/article/10.3389/fphys.2019.01138/full |
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