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Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach

Author

Listed:
  • Tobias Gerach

    (Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Steffen Schuler

    (Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Jonathan Fröhlich

    (Institute of Applied and Numerical Mathematics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Laura Lindner

    (Institute of Applied and Numerical Mathematics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Ekaterina Kovacheva

    (Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Robin Moss

    (Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg · Bad Krozingen and Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany)

  • Eike Moritz Wülfers

    (Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg · Bad Krozingen and Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany)

  • Gunnar Seemann

    (Institute for Experimental Cardiovascular Medicine, University Heart Center Freiburg · Bad Krozingen and Faculty of Medicine, University of Freiburg, 79110 Freiburg, Germany)

  • Christian Wieners

    (Institute of Applied and Numerical Mathematics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

  • Axel Loewe

    (Institute of Biomedical Engineering, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany)

Abstract

Mathematical models of the human heart are evolving to become a cornerstone of precision medicine and support clinical decision making by providing a powerful tool to understand the mechanisms underlying pathophysiological conditions. In this study, we present a detailed mathematical description of a fully coupled multi-scale model of the human heart, including electrophysiology, mechanics, and a closed-loop model of circulation. State-of-the-art models based on human physiology are used to describe membrane kinetics, excitation-contraction coupling and active tension generation in the atria and the ventricles. Furthermore, we highlight ways to adapt this framework to patient specific measurements to build digital twins. The validity of the model is demonstrated through simulations on a personalized whole heart geometry based on magnetic resonance imaging data of a healthy volunteer. Additionally, the fully coupled model was employed to evaluate the effects of a typical atrial ablation scar on the cardiovascular system. With this work, we provide an adaptable multi-scale model that allows a comprehensive personalization from ion channels to the organ level enabling digital twin modeling.

Suggested Citation

  • Tobias Gerach & Steffen Schuler & Jonathan Fröhlich & Laura Lindner & Ekaterina Kovacheva & Robin Moss & Eike Moritz Wülfers & Gunnar Seemann & Christian Wieners & Axel Loewe, 2021. "Electro-Mechanical Whole-Heart Digital Twins: A Fully Coupled Multi-Physics Approach," Mathematics, MDPI, vol. 9(11), pages 1-33, May.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:11:p:1247-:d:564989
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    References listed on IDEAS

    as
    1. Jonathan Wong & Ellen Kuhl, 2014. "Generating fibre orientation maps in human heart models using Poisson interpolation," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 17(11), pages 1217-1226, August.
    2. S. Kallhovd & J. Sundnes & S. T. Wall, 2019. "Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 22(6), pages 664-675, April.
    3. Hermenegild J. Arevalo & Fijoy Vadakkumpadan & Eliseo Guallar & Alexander Jebb & Peter Malamas & Katherine C. Wu & Natalia A. Trayanova, 2016. "Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models," Nature Communications, Nature, vol. 7(1), pages 1-8, September.
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