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MRI-Based Heart and Torso Personalization for Computer Modeling and Simulation of Cardiac Electrophysiology

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Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound (BIVPCS 2017, POCUS 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10549))

Abstract

In the last decade, electrophysiological models for in-silico simulations of cardiac electrophysiology have gained much attention in the research field. However, to translate them to clinical uses, the models need personalization based on recordings from the patient. In this work, we explore methodologies for the patient-specific personalization of torso and heart geometric models based on standard clinical cardiac magnetic resonance acquisitions to enable simulations. The inclusion of the torso and its internal structures allows simulations of the human ventricular electrophysiological activity from the ionic level to the body surface potentials and to the electrocardiogram.

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Notes

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Acknowledgments

EZ acknowledges the Marie Sklodowska-Curie Individual Fellowship from the H2020 EU Framework Programme for Research and Innovation (Proposal No: 655020-DTI4micro-MSCA-IF-EF-ST). AM and BR are supported by BR’s Wellcome Trust Senior Research Fellowship in Basic Biomedical Sciences, the CompBiomed project (grant agreement No 675451) and the NC3R Infrastructure for Impact award (NC/P001076/1). BV acknowledges the support of the RCUK Digital Economy Programme grant number EP/G036861/1 (Oxford Centre for Doctoral Training in Healthcare Innovation). VC was supported by ERACoSysMed through a grant to the project SysAFib - Systems medicine for diagnosis and stratification of atrial fibrillation. RA is supported by a British Heart Foundation Clinical Research Training Fellowship. VG is supported by a BBSRC grant (BB/I012117/1), an EPSRC grant (EP/J013250/1), by BHF New Horizon Grant NH/13/30238 and by the CompBiomed project (grant agreement No 675451).

Author information

Authors and Affiliations

  1. Department of Engineering Science, Institute of Biomedical Engineering, University of Oxford, Oxford, UK

    Ernesto Zacur, Benjamin Villard & Vicente Grau

  2. Department of Computer Science, University of Oxford, Oxford, UK

    Ana Minchole & Blanca Rodriguez

  3. Division of Cardiovascular Medicine, University of Oxford Centre for Clinical Magnetic Resonance Research, Oxford, UK

    Rina Ariga

  4. Simula Research Laboratory, Bærum, Norway

    Valentina Carapella

Authors
  1. Ernesto Zacur
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  2. Ana Minchole
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  3. Benjamin Villard
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  4. Valentina Carapella
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  5. Rina Ariga
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  6. Blanca Rodriguez
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  7. Vicente Grau
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Corresponding author

Correspondence to Ernesto Zacur .

Editor information

Editors and Affiliations

  1. University College London, London, United Kingdom

    M. Jorge Cardoso

  2. McGill University, Montreal, Québec, Canada

    Tal Arbel

  3. Universidade do Porto, Porto, Portugal

    JoĂŁo Manuel R.S. Tavares

  4. Kitware Inc., Carrboro, North Carolina, USA

    Stephen Aylward

  5. University of Western Ontario, London, Ontario, Canada

    Shuo Li

  6. Johns Hopkins University, Baltimore, Maryland, USA

    Emad Boctor

  7. Queen’s University, Kingston, Ontario, Canada

    Gabor Fichtinger

  8. Children’s National Medical Center, Washington, District of Columbia, USA

    Kevin Cleary

  9. Washington University Medical Center, St. Louis, Missouri, USA

    Bradley Freeman

  10. InnerOptic Technology, Hillsborough, North Carolina, USA

    Luv Kohli

  11. Washington University Medical Center, St. Louis, Missouri, USA

    Deborah Shipley Kane

  12. Children’s National Medical Center, Washington, District of Columbia, USA

    Matt Oetgen

  13. Brigham and Women’s Hospital, Boston, Massachusetts, USA

    Sonja Pujol

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Zacur, E. et al. (2017). MRI-Based Heart and Torso Personalization for Computer Modeling and Simulation of Cardiac Electrophysiology. In: Cardoso, M., et al. Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. BIVPCS POCUS 2017 2017. Lecture Notes in Computer Science(), vol 10549. Springer, Cham. https://doi.org/10.1007/978-3-319-67552-7_8

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  • DOI: https://doi.org/10.1007/978-3-319-67552-7_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67551-0

  • Online ISBN: 978-3-319-67552-7

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