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From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology

Computational modeling has contributed significantly to present understanding of cardiac electrophysiology including cardiac conduction, excitation-contraction coupling, and the effects and side-effects of drugs. However, the accuracy of in silico analysis of electrochemical wave dynamics in cardiac...

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Autores principales: Jæger, Karoline Horgmo, Edwards, Andrew G., Giles, Wayne R., Tveito, Aslak
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8578869/
https://www.ncbi.nlm.nih.gov/pubmed/34777021
http://dx.doi.org/10.3389/fphys.2021.763584
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author Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
author_facet Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
author_sort Jæger, Karoline Horgmo
collection PubMed
description Computational modeling has contributed significantly to present understanding of cardiac electrophysiology including cardiac conduction, excitation-contraction coupling, and the effects and side-effects of drugs. However, the accuracy of in silico analysis of electrochemical wave dynamics in cardiac tissue is limited by the homogenization procedure (spatial averaging) intrinsic to standard continuum models of conduction. Averaged models cannot resolve the intricate dynamics in the vicinity of individual cardiomyocytes simply because the myocytes are not present in these models. Here we demonstrate how recently developed mathematical models based on representing every myocyte can significantly increase the accuracy, and thus the utility of modeling electrophysiological function and dysfunction in collections of coupled cardiomyocytes. The present gold standard of numerical simulation for cardiac electrophysiology is based on the bidomain model. In the bidomain model, the extracellular (E) space, the cell membrane (M) and the intracellular (I) space are all assumed to be present everywhere in the tissue. Consequently, it is impossible to study biophysical processes taking place close to individual myocytes. The bidomain model represents the tissue by averaging over several hundred myocytes and this inherently limits the accuracy of the model. In our alternative approach both E, M, and I are represented in the model which is therefore referred to as the EMI model. The EMI model approach allows for detailed analysis of the biophysical processes going on in functionally important spaces very close to individual myocytes, although at the cost of significantly increased CPU-requirements.
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spelling pubmed-85788692021-11-11 From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology Jæger, Karoline Horgmo Edwards, Andrew G. Giles, Wayne R. Tveito, Aslak Front Physiol Physiology Computational modeling has contributed significantly to present understanding of cardiac electrophysiology including cardiac conduction, excitation-contraction coupling, and the effects and side-effects of drugs. However, the accuracy of in silico analysis of electrochemical wave dynamics in cardiac tissue is limited by the homogenization procedure (spatial averaging) intrinsic to standard continuum models of conduction. Averaged models cannot resolve the intricate dynamics in the vicinity of individual cardiomyocytes simply because the myocytes are not present in these models. Here we demonstrate how recently developed mathematical models based on representing every myocyte can significantly increase the accuracy, and thus the utility of modeling electrophysiological function and dysfunction in collections of coupled cardiomyocytes. The present gold standard of numerical simulation for cardiac electrophysiology is based on the bidomain model. In the bidomain model, the extracellular (E) space, the cell membrane (M) and the intracellular (I) space are all assumed to be present everywhere in the tissue. Consequently, it is impossible to study biophysical processes taking place close to individual myocytes. The bidomain model represents the tissue by averaging over several hundred myocytes and this inherently limits the accuracy of the model. In our alternative approach both E, M, and I are represented in the model which is therefore referred to as the EMI model. The EMI model approach allows for detailed analysis of the biophysical processes going on in functionally important spaces very close to individual myocytes, although at the cost of significantly increased CPU-requirements. Frontiers Media S.A. 2021-10-27 /pmc/articles/PMC8578869/ /pubmed/34777021 http://dx.doi.org/10.3389/fphys.2021.763584 Text en Copyright © 2021 Jæger, Edwards, Giles and Tveito. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Jæger, Karoline Horgmo
Edwards, Andrew G.
Giles, Wayne R.
Tveito, Aslak
From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title_full From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title_fullStr From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title_full_unstemmed From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title_short From Millimeters to Micrometers; Re-introducing Myocytes in Models of Cardiac Electrophysiology
title_sort from millimeters to micrometers; re-introducing myocytes in models of cardiac electrophysiology
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8578869/
https://www.ncbi.nlm.nih.gov/pubmed/34777021
http://dx.doi.org/10.3389/fphys.2021.763584
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