Using cardiac ionic cell models to interpret clinical data

For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measure...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Wiley interdisciplinary reviews. Mechanisms of disease 2021-05, Vol.13 (3), p.e1508-n/a
Hauptverfasser: Corrado, Cesare, Avezzù, Adelisa, Lee, Angela W. C., Mendoca Costa, Caroline, Roney, Caroline H., Strocchi, Marina, Bishop, Martin, Niederer, Steven A.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page n/a
container_issue 3
container_start_page e1508
container_title Wiley interdisciplinary reviews. Mechanisms of disease
container_volume 13
creator Corrado, Cesare
Avezzù, Adelisa
Lee, Angela W. C.
Mendoca Costa, Caroline
Roney, Caroline H.
Strocchi, Marina
Bishop, Martin
Niederer, Steven A.
description For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi‐scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi‐scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Biomedical Engineering Cardiovascular Diseases > Molecular and Cellular Physiology We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, cardiac resynchronisation therapy, or suffering from atrial fibrillation and ventricular tachycardia.
doi_str_mv 10.1002/wsbm.1508
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2449261890</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2449261890</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4548-be22ce1ae15ef943f27cdcde7c23f05f8aaa69e017876fca15d4d4d2d0813c983</originalsourceid><addsrcrecordid>eNp10MtKAzEUBuAgii21C19ABtzoYtpc5pK40-INKi60uAxpckZS5lKTGUrf3oytIoKcRQ7k4-fwI3RK8IRgTKcbv6wmJMX8AA1pJmgsWMYPf-0DNPZ-hYNNGOacHqMBY5jmacqG6Grhbf0eaeWMVTqyTW11pKEso6oxUPqobSJbt-DWDtpIlzb8qzIyqlUn6KhQpYfx_h2hxd3t6-whnj_fP86u57FO0oTHS6BUA1FAUihEwgqaa6MN5JqyAqcFV0plAjDJeZ4VWpHUJGGowZwwLTgboYtd7to1Hx34VlbW9yeqGprOS5okgmaECxzo-R-6ajpXh-skFRgTyphgQV3ulHaN9w4KuXa2Um4rCZZ9p7LvVPadBnu2T-yWFZgf-d1gANMd2NgStv8nybeXm6evyE-CW3-i</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2900123393</pqid></control><display><type>article</type><title>Using cardiac ionic cell models to interpret clinical data</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Corrado, Cesare ; Avezzù, Adelisa ; Lee, Angela W. C. ; Mendoca Costa, Caroline ; Roney, Caroline H. ; Strocchi, Marina ; Bishop, Martin ; Niederer, Steven A.</creator><creatorcontrib>Corrado, Cesare ; Avezzù, Adelisa ; Lee, Angela W. C. ; Mendoca Costa, Caroline ; Roney, Caroline H. ; Strocchi, Marina ; Bishop, Martin ; Niederer, Steven A.</creatorcontrib><description>For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi‐scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi‐scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases &gt; Computational Models Cardiovascular Diseases &gt; Biomedical Engineering Cardiovascular Diseases &gt; Molecular and Cellular Physiology We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, cardiac resynchronisation therapy, or suffering from atrial fibrillation and ventricular tachycardia.</description><identifier>ISSN: 2692-9368</identifier><identifier>EISSN: 2692-9368</identifier><identifier>DOI: 10.1002/wsbm.1508</identifier><identifier>PMID: 33027553</identifier><language>eng</language><publisher>Hoboken, USA: John Wiley &amp; Sons, Inc</publisher><subject>Atria ; Atrial Fibrillation ; Biomedical engineering ; cardiac ; Cardiovascular diseases ; Cell culture ; Computer applications ; EKG ; Electrophysiological Phenomena ; Electrophysiology ; Heart Atria ; Heart Ventricles ; Humans ; Mathematical models ; multi‐scale ; Myocytes ; Myocytes, Cardiac ; Patients ; Tachycardia ; Ventricle</subject><ispartof>Wiley interdisciplinary reviews. Mechanisms of disease, 2021-05, Vol.13 (3), p.e1508-n/a</ispartof><rights>2020 The Authors. published by Wiley Periodicals LLC.</rights><rights>2020 The Authors. WIREs Systems Biology and Medicine published by Wiley Periodicals LLC.</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4548-be22ce1ae15ef943f27cdcde7c23f05f8aaa69e017876fca15d4d4d2d0813c983</citedby><cites>FETCH-LOGICAL-c4548-be22ce1ae15ef943f27cdcde7c23f05f8aaa69e017876fca15d4d4d2d0813c983</cites><orcidid>0000-0002-8914-8735 ; 0000-0002-4612-6982</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fwsbm.1508$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fwsbm.1508$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,1412,27905,27906,45555,45556</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33027553$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Corrado, Cesare</creatorcontrib><creatorcontrib>Avezzù, Adelisa</creatorcontrib><creatorcontrib>Lee, Angela W. C.</creatorcontrib><creatorcontrib>Mendoca Costa, Caroline</creatorcontrib><creatorcontrib>Roney, Caroline H.</creatorcontrib><creatorcontrib>Strocchi, Marina</creatorcontrib><creatorcontrib>Bishop, Martin</creatorcontrib><creatorcontrib>Niederer, Steven A.</creatorcontrib><title>Using cardiac ionic cell models to interpret clinical data</title><title>Wiley interdisciplinary reviews. Mechanisms of disease</title><addtitle>WIREs Mech Dis</addtitle><description>For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi‐scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi‐scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases &gt; Computational Models Cardiovascular Diseases &gt; Biomedical Engineering Cardiovascular Diseases &gt; Molecular and Cellular Physiology We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, cardiac resynchronisation therapy, or suffering from atrial fibrillation and ventricular tachycardia.</description><subject>Atria</subject><subject>Atrial Fibrillation</subject><subject>Biomedical engineering</subject><subject>cardiac</subject><subject>Cardiovascular diseases</subject><subject>Cell culture</subject><subject>Computer applications</subject><subject>EKG</subject><subject>Electrophysiological Phenomena</subject><subject>Electrophysiology</subject><subject>Heart Atria</subject><subject>Heart Ventricles</subject><subject>Humans</subject><subject>Mathematical models</subject><subject>multi‐scale</subject><subject>Myocytes</subject><subject>Myocytes, Cardiac</subject><subject>Patients</subject><subject>Tachycardia</subject><subject>Ventricle</subject><issn>2692-9368</issn><issn>2692-9368</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>WIN</sourceid><sourceid>EIF</sourceid><recordid>eNp10MtKAzEUBuAgii21C19ABtzoYtpc5pK40-INKi60uAxpckZS5lKTGUrf3oytIoKcRQ7k4-fwI3RK8IRgTKcbv6wmJMX8AA1pJmgsWMYPf-0DNPZ-hYNNGOacHqMBY5jmacqG6Grhbf0eaeWMVTqyTW11pKEso6oxUPqobSJbt-DWDtpIlzb8qzIyqlUn6KhQpYfx_h2hxd3t6-whnj_fP86u57FO0oTHS6BUA1FAUihEwgqaa6MN5JqyAqcFV0plAjDJeZ4VWpHUJGGowZwwLTgboYtd7to1Hx34VlbW9yeqGprOS5okgmaECxzo-R-6ajpXh-skFRgTyphgQV3ulHaN9w4KuXa2Um4rCZZ9p7LvVPadBnu2T-yWFZgf-d1gANMd2NgStv8nybeXm6evyE-CW3-i</recordid><startdate>202105</startdate><enddate>202105</enddate><creator>Corrado, Cesare</creator><creator>Avezzù, Adelisa</creator><creator>Lee, Angela W. C.</creator><creator>Mendoca Costa, Caroline</creator><creator>Roney, Caroline H.</creator><creator>Strocchi, Marina</creator><creator>Bishop, Martin</creator><creator>Niederer, Steven A.</creator><general>John Wiley &amp; Sons, Inc</general><general>Wiley Subscription Services, Inc</general><scope>24P</scope><scope>WIN</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7QP</scope><scope>7QR</scope><scope>7SS</scope><scope>7T5</scope><scope>7TK</scope><scope>8FD</scope><scope>FR3</scope><scope>H94</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8914-8735</orcidid><orcidid>https://orcid.org/0000-0002-4612-6982</orcidid></search><sort><creationdate>202105</creationdate><title>Using cardiac ionic cell models to interpret clinical data</title><author>Corrado, Cesare ; Avezzù, Adelisa ; Lee, Angela W. C. ; Mendoca Costa, Caroline ; Roney, Caroline H. ; Strocchi, Marina ; Bishop, Martin ; Niederer, Steven A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4548-be22ce1ae15ef943f27cdcde7c23f05f8aaa69e017876fca15d4d4d2d0813c983</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Atria</topic><topic>Atrial Fibrillation</topic><topic>Biomedical engineering</topic><topic>cardiac</topic><topic>Cardiovascular diseases</topic><topic>Cell culture</topic><topic>Computer applications</topic><topic>EKG</topic><topic>Electrophysiological Phenomena</topic><topic>Electrophysiology</topic><topic>Heart Atria</topic><topic>Heart Ventricles</topic><topic>Humans</topic><topic>Mathematical models</topic><topic>multi‐scale</topic><topic>Myocytes</topic><topic>Myocytes, Cardiac</topic><topic>Patients</topic><topic>Tachycardia</topic><topic>Ventricle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Corrado, Cesare</creatorcontrib><creatorcontrib>Avezzù, Adelisa</creatorcontrib><creatorcontrib>Lee, Angela W. C.</creatorcontrib><creatorcontrib>Mendoca Costa, Caroline</creatorcontrib><creatorcontrib>Roney, Caroline H.</creatorcontrib><creatorcontrib>Strocchi, Marina</creatorcontrib><creatorcontrib>Bishop, Martin</creatorcontrib><creatorcontrib>Niederer, Steven A.</creatorcontrib><collection>Wiley-Blackwell Open Access Collection</collection><collection>Wiley Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium &amp; Calcified Tissue Abstracts</collection><collection>Chemoreception Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Wiley interdisciplinary reviews. Mechanisms of disease</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Corrado, Cesare</au><au>Avezzù, Adelisa</au><au>Lee, Angela W. C.</au><au>Mendoca Costa, Caroline</au><au>Roney, Caroline H.</au><au>Strocchi, Marina</au><au>Bishop, Martin</au><au>Niederer, Steven A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using cardiac ionic cell models to interpret clinical data</atitle><jtitle>Wiley interdisciplinary reviews. Mechanisms of disease</jtitle><addtitle>WIREs Mech Dis</addtitle><date>2021-05</date><risdate>2021</risdate><volume>13</volume><issue>3</issue><spage>e1508</spage><epage>n/a</epage><pages>e1508-n/a</pages><issn>2692-9368</issn><eissn>2692-9368</eissn><abstract>For over 100 years cardiac electrophysiology has been measured in the clinic. The electrical signals that can be measured span from noninvasive ECG and body surface potentials measurements through to detailed invasive measurements of local tissue electrophysiology. These electrophysiological measurements form a crucial component of patient diagnosis and monitoring; however, it remains challenging to quantitatively link changes in clinical electrophysiology measurements to biophysical cellular function. Multi‐scale biophysical computational models represent one solution to this problem. These models provide a formal framework for linking cellular function through to emergent whole organ function and routine clinical diagnostic signals. In this review, we describe recent work on the use of computational models to interpret clinical electrophysiology signals. We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, \cardiac resynchronisation therapy or suffering from atrial fibrillation and ventricular tachycardia. There is a growing use of multi‐scale biophysical models to interpret clinical data. This allows cardiologists to link clinical observations with cellular mechanisms to better understand cardiopathophysiology and identify novel treatment strategies. This article is categorized under: Cardiovascular Diseases &gt; Computational Models Cardiovascular Diseases &gt; Biomedical Engineering Cardiovascular Diseases &gt; Molecular and Cellular Physiology We review the simulation of human cardiac myocyte electrophysiology in the atria and the ventricles and how these models are being used to link organ scale function to patient disease mechanisms and therapy response in patients receiving implanted defibrillators, cardiac resynchronisation therapy, or suffering from atrial fibrillation and ventricular tachycardia.</abstract><cop>Hoboken, USA</cop><pub>John Wiley &amp; Sons, Inc</pub><pmid>33027553</pmid><doi>10.1002/wsbm.1508</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0002-8914-8735</orcidid><orcidid>https://orcid.org/0000-0002-4612-6982</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2692-9368
ispartof Wiley interdisciplinary reviews. Mechanisms of disease, 2021-05, Vol.13 (3), p.e1508-n/a
issn 2692-9368
2692-9368
language eng
recordid cdi_proquest_miscellaneous_2449261890
source MEDLINE; Wiley Online Library Journals Frontfile Complete
subjects Atria
Atrial Fibrillation
Biomedical engineering
cardiac
Cardiovascular diseases
Cell culture
Computer applications
EKG
Electrophysiological Phenomena
Electrophysiology
Heart Atria
Heart Ventricles
Humans
Mathematical models
multi‐scale
Myocytes
Myocytes, Cardiac
Patients
Tachycardia
Ventricle
title Using cardiac ionic cell models to interpret clinical data
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-17T17%3A33%3A41IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Using%20cardiac%20ionic%20cell%20models%20to%20interpret%20clinical%20data&rft.jtitle=Wiley%20interdisciplinary%20reviews.%20Mechanisms%20of%20disease&rft.au=Corrado,%20Cesare&rft.date=2021-05&rft.volume=13&rft.issue=3&rft.spage=e1508&rft.epage=n/a&rft.pages=e1508-n/a&rft.issn=2692-9368&rft.eissn=2692-9368&rft_id=info:doi/10.1002/wsbm.1508&rft_dat=%3Cproquest_cross%3E2449261890%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2900123393&rft_id=info:pmid/33027553&rfr_iscdi=true