Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure an...

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Published inInterface focus Vol. 6; no. 2; p. 20150083
Main Authors Chabiniok, Radomir, Wang, Vicky Y., Hadjicharalambous, Myrianthi, Asner, Liya, Lee, Jack, Sermesant, Maxime, Kuhl, Ellen, Young, Alistair A., Moireau, Philippe, Nash, Martyn P., Chapelle, Dominique, Nordsletten, David A.
Format Journal Article
LanguageEnglish
Published England The Royal Society 06.04.2016
Royal Society publishing
Subjects
Cardiac Mechanics
Data–model Fusion
Heart Mechanics
Mathematics
Numerical Analysis
Part II: Methodology Needed for Establishing a Clinically Relevant Human Physiome
Patient-Specific Modelling
Review
Translational Cardiac Modelling
data–model fusion
heart mechanics
cardiac mechanics
translational cardiac modelling
patient-specific modelling
data-model fusion
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Abstract With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.
AbstractList With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.
With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.
Author Asner, Liya
Hadjicharalambous, Myrianthi
Nash, Martyn P.
Kuhl, Ellen
Wang, Vicky Y.
Lee, Jack
Sermesant, Maxime
Young, Alistair A.
Chabiniok, Radomir
Moireau, Philippe
Chapelle, Dominique
Nordsletten, David A.
AuthorAffiliation 2 Inria and Paris-Saclay University, Bâtiment Alan Turing , 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120 , France
5 Inria, Asclepios team , 2004 route des Lucioles BP 93, Sophia Antipolis Cedex 06902 , France
3 Auckland Bioengineering Institute , University of Auckland , 70 Symonds Street, Auckland , New Zealand
4 Department of Engineering Science , University of Auckland , 70 Symonds Street, Auckland , New Zealand
1 Division of Imaging Sciences and Biomedical Engineering , King's College London , St Thomas’ Hospital, London SE1 7EH , UK
6 Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , 496 Lomita Mall, Durand 217, Stanford, CA 94306 , USA
AuthorAffiliation_xml – name: 2 Inria and Paris-Saclay University, Bâtiment Alan Turing , 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120 , France
– name: 1 Division of Imaging Sciences and Biomedical Engineering , King's College London , St Thomas’ Hospital, London SE1 7EH , UK
– name: 3 Auckland Bioengineering Institute , University of Auckland , 70 Symonds Street, Auckland , New Zealand
– name: 4 Department of Engineering Science , University of Auckland , 70 Symonds Street, Auckland , New Zealand
– name: 5 Inria, Asclepios team , 2004 route des Lucioles BP 93, Sophia Antipolis Cedex 06902 , France
– name: 6 Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery , Stanford University , 496 Lomita Mall, Durand 217, Stanford, CA 94306 , USA
Author_xml – sequence: 1
  givenname: Radomir
  surname: Chabiniok
  fullname: Chabiniok, Radomir
  organization: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas’ Hospital, London SE1 7EH, UK; Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120, France
– sequence: 2
  givenname: Vicky Y.
  surname: Wang
  fullname: Wang, Vicky Y.
  organization: Auckland Bioengineering Institute, University of Auckland, 70 Symonds Street, Auckland, New Zealand
– sequence: 3
  givenname: Myrianthi
  surname: Hadjicharalambous
  fullname: Hadjicharalambous, Myrianthi
  organization: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas’ Hospital, London SE1 7EH, UK
– sequence: 4
  givenname: Liya
  surname: Asner
  fullname: Asner, Liya
  organization: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas’ Hospital, London SE1 7EH, UK
– sequence: 5
  givenname: Jack
  surname: Lee
  fullname: Lee, Jack
  organization: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas’ Hospital, London SE1 7EH, UK
– sequence: 6
  givenname: Maxime
  surname: Sermesant
  fullname: Sermesant, Maxime
  organization: Inria, Asclepios team, 2004 route des Lucioles BP 93, Sophia Antipolis Cedex 06902, France
– sequence: 7
  givenname: Ellen
  surname: Kuhl
  fullname: Kuhl, Ellen
  organization: Departments of Mechanical Engineering, Bioengineering, and Cardiothoracic Surgery, Stanford University, 496 Lomita Mall, Durand 217, Stanford, CA 94306, USA
– sequence: 8
  givenname: Alistair A.
  surname: Young
  fullname: Young, Alistair A.
  organization: Auckland Bioengineering Institute, University of Auckland, 70 Symonds Street, Auckland, New Zealand
– sequence: 9
  givenname: Philippe
  surname: Moireau
  fullname: Moireau, Philippe
  organization: Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120, France
– sequence: 10
  givenname: Martyn P.
  surname: Nash
  fullname: Nash, Martyn P.
  organization: Auckland Bioengineering Institute, University of Auckland, 70 Symonds Street, Auckland, New Zealand; Department of Engineering Science, University of Auckland, 70 Symonds Street, Auckland, New Zealand
– sequence: 11
  givenname: Dominique
  surname: Chapelle
  fullname: Chapelle, Dominique
  organization: Inria and Paris-Saclay University, Bâtiment Alan Turing, 1 rue Honoré d'Estienne d'Orves, Campus de l'Ecole Polytechnique, Palaiseau 91120, France
– sequence: 12
  givenname: David A.
  orcidid: 0000-0002-5363-4715
  surname: Nordsletten
  fullname: Nordsletten, David A.
  email: david.nordsletten@gmail.com
  organization: Division of Imaging Sciences and Biomedical Engineering, King's College London, St Thomas’ Hospital, London SE1 7EH, UK
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27051509$$D View this record in MEDLINE/PubMed
https://inria.hal.science/hal-01277684$$DView record in HAL
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Issue 2
Keywords data–model fusion
heart mechanics
cardiac mechanics
translational cardiac modelling
patient-specific modelling
data-model fusion
Language English
License open-access: Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Distributed under a Creative Commons Attribution 4.0 International License: http://creativecommons.org/licenses/by/4.0
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Notes Theme issue ‘The Human Physiome: a necessary key to the creative destruction of medicine’ organized by Stig W. Omholt and Peter Hunter
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Authors acknowledge equal contributions as senior authors.
One contribution of 12 to a theme issue ‘The Human Physiome: a necessary key to the creative destruction of medicine’.
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Snippet With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into...
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SubjectTerms Cardiac Mechanics
Data–model Fusion
Heart Mechanics
Mathematics
Numerical Analysis
Part II: Methodology Needed for Establishing a Clinically Relevant Human Physiome
Patient-Specific Modelling
Review
Translational Cardiac Modelling
Title Multiphysics and multiscale modelling, data–model fusion and integration of organ physiology in the clinic: ventricular cardiac mechanics
URI https://royalsocietypublishing.org/doi/full/10.1098/rsfs.2015.0083
https://www.ncbi.nlm.nih.gov/pubmed/27051509
https://www.proquest.com/docview/1779879579
https://inria.hal.science/hal-01277684
https://pubmed.ncbi.nlm.nih.gov/PMC4759748
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