Personalization of Mathematical Models of Human Atrial Action Potential

Andrey V. Pikunov, Roman A. Syunyaev*, Vanessa Steckmeister, Ingo Kutschka, Niels Voigt, Igor R. Efimov

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapter

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.

Original languageEnglish (US)
Title of host publicationSmart Innovation, Systems and Technologies
PublisherSpringer Science and Business Media Deutschland GmbH
Pages223-236
Number of pages14
DOIs
StatePublished - 2021

Publication series

NameSmart Innovation, Systems and Technologies
Volume214
ISSN (Print)2190-3018
ISSN (Electronic)2190-3026

Keywords

  • Atrial fibrillation
  • Genetic algorithms
  • Model benchmarking
  • Model personalization

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Computer Science(all)

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