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Personalization of Mathematical Models of Human Atrial Action Potential

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Smart Modelling For Engineering Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 214))

Abstract

Atrial cardiomyocytes demonstrate a wide spectrum of patient-specific, tissue-specific, and pathology-specific Action potential (AP) phenotypes due to differences in protein expression and posttranslational modifications. Accurate simulation of the AP excitation and propagation in healthy or diseased atria requires a mathematical model capable of reproducing all the differences by parameter rescaling. In the present study, we have benchmarked two widely used electrophysiological models of the human atrium: the Maleckar and the Grandi models. In particular, patch-clamp AP recordings from human atrial myocytes were fitted by the genetic algorithm (GA) to test the models’ versatility. We have shown that the Maleckar model results in a more accurate fitting of heart rate dependence of action potential duration (APD) and resting potential (RP). On the other hand, both models demonstrate the poor fitting of the plateau phase and spike-and-dome morphologies. We propose that modifications to L-type calcium current–voltage relationships are required to improve atrial models’ fidelity.

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Acknowledgements

The authors thank Ines Müller and Stefanie Kestel for excellent technical assistance and the cardiac surgeons of the Department of Thoracic and Cardiovascular Surgery, University Medical Center Göttingen for kindly providing human atrial tissue samples.

This work was supported by grants from the German Center for Cardiovascular Research (DZHK), the Deutsche Forschungsgemeinschaft to Niels Voigt (DFG, German Research Foundation, VO 1568/3-1, IRTG1816 RP12, SFB1002 TPA13 and under Germany’s Excellence Strateg—EXC 2067/1-390729940), from the from the Else-Kröner-Fresenius Foundation to Niels Voigt (EKFS 2016_A20), from NIH/NHLBI (U01 HL141074) and Leducq Foundation (RHYTHM) to Igor R. Efimov, computer model optimization was supported by Russian Scientific Foundation grant 18-71-10058 to Roman A. Syunyaev.

Author information

Authors and Affiliations

  1. Moscow Institute of Physics and Technology, National Research University, 9, Institutsky per., Dolgoprudny, Moscow Region, 141701, Russian Federation

    Andrey V. Pikunov & Roman A. Syunyaev

  2. Sechenov First Moscow State Medical University, 8/2, Trubetskaya ul., Moscow, 119991, Russian Federation

    Roman A. Syunyaev

  3. The George Washington University, 800 22nd, NW, Washington, DC, USA

    Roman A. Syunyaev & Igor R. Efimov

  4. Institute of Pharmacology and Toxicology, University Medical Center Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Germany

    Vanessa Steckmeister & Niels Voigt

  5. DZHK (German Center for Cardiovascular Research), Partner Site Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Germany

    Vanessa Steckmeister, Ingo Kutschka & Niels Voigt

  6. Department of Thoracic and Cardiovascular Surgery, University Medical Center, Robert-Koch-Str. 40, 37075, Göttingen, Germany

    Ingo Kutschka

  7. Cluster of Excellence “Multiscale Bioimaging: From Molecular Machines to Networks of Excitable Cells” (MBExC), University of Goettingen, Robert-Koch-Str. 40, 37075, Göttingen, Germany

    Niels Voigt

Authors
  1. Andrey V. Pikunov
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  2. Roman A. Syunyaev
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  3. Vanessa Steckmeister
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  4. Ingo Kutschka
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  5. Niels Voigt
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  6. Igor R. Efimov
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Corresponding author

Correspondence to Roman A. Syunyaev .

Editor information

Editors and Affiliations

  1. Institute of Informatics and Telecommunications, Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russia

    Margarita N. Favorskaya

  2. Informatics and Numerical Modeling, Moscow Institute of Physics and Technology (National Research University), Dolgoprudny, Russia

    Alena V. Favorskaya

  3. Moscow Institute of Physics and Technology (National Research University), Moscow, Russia

    Igor B. Petrov

  4. Centre for Artificial Intelligence, University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Pikunov, A.V., Syunyaev, R.A., Steckmeister, V., Kutschka, I., Voigt, N., Efimov, I.R. (2021). Personalization of Mathematical Models of Human Atrial Action Potential. In: Favorskaya, M.N., Favorskaya, A.V., Petrov, I.B., Jain, L.C. (eds) Smart Modelling For Engineering Systems. Smart Innovation, Systems and Technologies, vol 214. Springer, Singapore. https://doi.org/10.1007/978-981-33-4709-0_19

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