An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility
Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been rece...
| Main Authors: | , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
MDPI
2022
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| _version_ | 1797106628845109248 |
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| author | Serra, D Romero, P Garcia-Fernandez, I Lozano, M Liberos, A Rodrigo, M Berruezo, A Sebastian, R |
| author_facet | Serra, D Romero, P Garcia-Fernandez, I Lozano, M Liberos, A Rodrigo, M Berruezo, A Sebastian, R |
| author_sort | Serra, D |
| collection | OXFORD |
| description | Personalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios. |
| first_indexed | 2024-03-07T07:05:14Z |
| format | Journal article |
| id | oxford-uuid:bfdf7769-47e6-4810-92d8-721580a94215 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T07:05:14Z |
| publishDate | 2022 |
| publisher | MDPI |
| record_format | dspace |
| spelling | oxford-uuid:bfdf7769-47e6-4810-92d8-721580a942152022-04-22T15:22:43ZAn automata-based cardiac electrophysiology simulator to assess arrhythmia inducibilityJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:bfdf7769-47e6-4810-92d8-721580a94215EnglishSymplectic ElementsMDPI2022Serra, DRomero, PGarcia-Fernandez, ILozano, MLiberos, ARodrigo, MBerruezo, ASebastian, RPersonalized cardiac electrophysiology simulations have demonstrated great potential to study cardiac arrhythmias and help in therapy planning of radio-frequency ablation. Its application to analyze vulnerability to ventricular tachycardia and sudden cardiac death in infarcted patients has been recently explored. However, the detailed multi-scale biophysical simulations used in these studies are very demanding in terms of memory and computational resources, which prevents their clinical translation. In this work, we present a fast phenomenological system based on cellular automata (CA) to simulate personalized cardiac electrophysiology. The system is trained on biophysical simulations to reproduce cellular and tissue dynamics in healthy and pathological conditions, including action potential restitution, conduction velocity restitution and cell safety factor. We show that a full ventricular simulation can be performed in the order of seconds, emulate the results of a biophysical simulation and reproduce a patient’s ventricular tachycardia in a model that includes a heterogeneous scar region. The system could be used to study the risk of arrhythmia in infarcted patients for a large number of scenarios. |
| spellingShingle | Serra, D Romero, P Garcia-Fernandez, I Lozano, M Liberos, A Rodrigo, M Berruezo, A Sebastian, R An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title | An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title_full | An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title_fullStr | An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title_full_unstemmed | An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title_short | An automata-based cardiac electrophysiology simulator to assess arrhythmia inducibility |
| title_sort | automata based cardiac electrophysiology simulator to assess arrhythmia inducibility |
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