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Computational Analysis of Coronary Blood Flow: The Role of Asynchronous Pacing and Arrhythmias

Author

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  • Timur Gamilov

    (Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
    Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia)

  • Philipp Kopylov

    (Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia)

  • Maria Serova

    (Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia)

  • Roman Syunyaev

    (Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
    Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia)

  • Andrey Pikunov

    (Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia)

  • Sofya Belova

    (Institute of Psychology of Russian Academy of Sciences, 129366 Moscow, Russia)

  • Fuyou Liang

    (Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia
    School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

  • Jordi Alastruey

    (Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia
    King’s College London, London SE1 7EH, UK)

  • Sergey Simakov

    (Moscow Institute of Physics and Technology, 141701 Dolgoprudny, Russia
    Institute of Personalized Medicine, Sechenov University, 119992 Moscow, Russia)

Abstract

In this work we present a one-dimensional (1D) mathematical model of the coronary circulation and use it to study the effects of arrhythmias on coronary blood flow (CBF). Hydrodynamical models are rarely used to study arrhythmias’ effects on CBF. Our model accounts for action potential duration, which updates the length of systole depending on the heart rate. It also includes dependency of stroke volume on heart rate, which is based on clinical data. We apply the new methodology to the computational evaluation of CBF during interventricular asynchrony due to cardiac pacing and some types of arrhythmias including tachycardia, bradycardia, long QT syndrome and premature ventricular contraction (bigeminy, trigeminy, quadrigeminy). We find that CBF can be significantly affected by arrhythmias. CBF at rest (60 bpm) is 26% lower in LCA and 22% lower in RCA for long QT syndrome. During bigeminy, trigeminy and quadrigeminy, respectively, CBF decreases by 28%, 19% and 14% with respect to a healthy case.

Suggested Citation

  • Timur Gamilov & Philipp Kopylov & Maria Serova & Roman Syunyaev & Andrey Pikunov & Sofya Belova & Fuyou Liang & Jordi Alastruey & Sergey Simakov, 2020. "Computational Analysis of Coronary Blood Flow: The Role of Asynchronous Pacing and Arrhythmias," Mathematics, MDPI, vol. 8(8), pages 1-16, July.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1205-:d:387864
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    References listed on IDEAS

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    1. Dmitrii Smirnov & Andrey Pikunov & Roman Syunyaev & Ruslan Deviatiiarov & Oleg Gusev & Kedar Aras & Anna Gams & Aaron Koppel & Igor R Efimov, 2020. "Genetic algorithm-based personalized models of human cardiac action potential," PLOS ONE, Public Library of Science, vol. 15(5), pages 1-31, May.
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    Cited by:

    1. Timur Gamilov & Fuyou Liang & Philipp Kopylov & Natalia Kuznetsova & Artem Rogov & Sergey Simakov, 2023. "Computational Analysis of Hemodynamic Indices Based on Personalized Identification of Aortic Pulse Wave Velocity by a Neural Network," Mathematics, MDPI, vol. 11(6), pages 1-18, March.

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