Cargando…
Understanding AF Mechanisms Through Computational Modelling and Simulations
AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The a...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Radcliffe Cardiology
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702471/ https://www.ncbi.nlm.nih.gov/pubmed/31463059 http://dx.doi.org/10.15420/aer.2019.28.2 |
_version_ | 1783445235522600960 |
---|---|
author | Aronis, Konstantinos N Ali, Rheeda L Liang, Jialiu A Zhou, Shijie Trayanova, Natalia A |
author_facet | Aronis, Konstantinos N Ali, Rheeda L Liang, Jialiu A Zhou, Shijie Trayanova, Natalia A |
author_sort | Aronis, Konstantinos N |
collection | PubMed |
description | AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF. |
format | Online Article Text |
id | pubmed-6702471 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Radcliffe Cardiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-67024712019-08-28 Understanding AF Mechanisms Through Computational Modelling and Simulations Aronis, Konstantinos N Ali, Rheeda L Liang, Jialiu A Zhou, Shijie Trayanova, Natalia A Arrhythm Electrophysiol Rev Electrophysiology and Ablation AF is a progressive disease of the atria, involving complex mechanisms related to its initiation, maintenance and progression. Computational modelling provides a framework for integration of experimental and clinical findings, and has emerged as an essential part of mechanistic research in AF. The authors summarise recent advancements in development of multi-scale AF models and focus on the mechanistic links between alternations in atrial structure and electrophysiology with AF. Key AF mechanisms that have been explored using atrial modelling are pulmonary vein ectopy; atrial fibrosis and fibrosis distribution; atrial wall thickness heterogeneity; atrial adipose tissue infiltration; development of repolarisation alternans; cardiac ion channel mutations; and atrial stretch with mechano-electrical feedback. They review modelling approaches that capture variability at the cohort level and provide cohort-specific mechanistic insights. The authors conclude with a summary of future perspectives, as envisioned for the contributions of atrial modelling in the mechanistic understanding of AF. Radcliffe Cardiology 2019-07 /pmc/articles/PMC6702471/ /pubmed/31463059 http://dx.doi.org/10.15420/aer.2019.28.2 Text en Copyright © 2019, Radcliffe Cardiology https://creativecommons.org/licenses/by-nc/4.0/legalcode This work is open access under the CC-BY-NC 4.0 License which allows users to copy, redistribute and make derivative works for non-commercial purposes, provided the original work is cited correctly. |
spellingShingle | Electrophysiology and Ablation Aronis, Konstantinos N Ali, Rheeda L Liang, Jialiu A Zhou, Shijie Trayanova, Natalia A Understanding AF Mechanisms Through Computational Modelling and Simulations |
title | Understanding AF Mechanisms Through Computational Modelling and Simulations |
title_full | Understanding AF Mechanisms Through Computational Modelling and Simulations |
title_fullStr | Understanding AF Mechanisms Through Computational Modelling and Simulations |
title_full_unstemmed | Understanding AF Mechanisms Through Computational Modelling and Simulations |
title_short | Understanding AF Mechanisms Through Computational Modelling and Simulations |
title_sort | understanding af mechanisms through computational modelling and simulations |
topic | Electrophysiology and Ablation |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702471/ https://www.ncbi.nlm.nih.gov/pubmed/31463059 http://dx.doi.org/10.15420/aer.2019.28.2 |
work_keys_str_mv | AT aroniskonstantinosn understandingafmechanismsthroughcomputationalmodellingandsimulations AT alirheedal understandingafmechanismsthroughcomputationalmodellingandsimulations AT liangjialiua understandingafmechanismsthroughcomputationalmodellingandsimulations AT zhoushijie understandingafmechanismsthroughcomputationalmodellingandsimulations AT trayanovanataliaa understandingafmechanismsthroughcomputationalmodellingandsimulations |