Hostname: page-component-586b7cd67f-l7hp2 Total loading time: 0 Render date: 2024-11-26T09:45:11.597Z Has data issue: false hasContentIssue false

A predictive method allowing the use of a single ionic model innumerical cardiac electrophysiology

Published online by Cambridge University Press:  07 June 2013

M. Rioux
Affiliation:
Department of Mathematics and Statistics, University of Ottawa, Canada. [email protected]
Y. Bourgault
Affiliation:
Department of Mathematics and Statistics, University of Ottawa, Canada. [email protected]
Get access

Abstract

One of the current debate about simulating the electrical activity in the heart is thefollowing: Using a realistic anatomical setting, i.e. realisticgeometries, fibres orientations, etc., is it enough to use a simplified 2-variablephenomenological model to reproduce the main characteristics of the cardiac actionpotential propagation, and in what sense is it sufficient? Using a combination ofdimensional and asymptotic analysis, together with the well-known Mitchell − Schaeffermodel, it is shown that it is possible to accurately control (at least locally) thesolution while spatial propagation is involved. In particular, we reduce the set ofparameters by writing the bidomain model in a new nondimensional form. The parameters ofthe bidomain model with Mitchell − Schaeffer ion kinetics are then set and shown to be inone-to-one relation with the main characteristics of the four phases of a propagatedaction potential. Explicit relations are derived using a combination of asymptotic methodsand ansatz. These relations are tested against numerical results. We illustrate how theserelations can be used to recover the time/space scales and speed of the action potentialin various regions of the heart.

Type
Research Article
Copyright
© EDP Sciences, SMAI, 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aliev, R.R. and Panfilov, A.V., A simple two-variable model of cardiac excitation. Chaos Soliton. Fract. 7 (1996) 293301. Google Scholar
Beck, M., Jones, C.K.R.T., Schaeffer, D. and Wechselberger, M., Electrical Waves in a One-Dimensional Model of Cardiac Tissue. SIAM J. Appl. Dynam. Syst. 7 (2008) 15581581. Google Scholar
Beeler, G. W. and Reuter, H., Reconstruction of the action potential of ventricular myocardial fibres. J. Physiol. 268 (1977) 177210. Google ScholarPubMed
M. Boulakia, M. Fernàndez, J.-F. Gerbeau and N. Zemzemi, Towards the numerical simulation of electrocardiograms, in Functional Imaging and Modeling of the Heart, vol. 4466 of Lect. Notes Comput. Sci., edited by F. Sachse and G. Seemann. Springer, Berlin/Heidelberg (2007) 240–249.
N. F. Britton, Essential Mathematical Biology. Springer Undergrad. Math. Series (2005).
Cain, J.W., Taking math to the heart: Mathematical challenges in cardiac electrophysiology. Notices of the AMS 58 (2011) 542549. Google Scholar
Clayton, R.H. and Panfilov, A.V., A guide to modelling cardiac electrical activity in anatomically detailed ventricles. Prog. Biophys. Mol. Bio. 96 (2008) 1943. Google ScholarPubMed
P. Colli Franzone, Guerri, L. and Rovida, S., Wavefront propagation in an activation model of the anisotropic cardiac tissue: asymptotic analysis and numerical simulations. J. Math. Biol. 28 (1990) 121176. DOI: 10.1007/BF00163143. Google Scholar
Deng, B., The existence of infinitely many traveling front and back waves in the Fitzhugh - Nagumo equations. SIAM J. Math. Anal. 22 (1991) 16311650. Google Scholar
K. Djabella, M. Landau and M. Sorine, A two-variable model of cardiac action potential with controlled pacemaker activity and ionic current interpretation. 46th IEEE Conf. Decis. Control (2007) 5186–5191.
Tolkacheva, E.G., Schaeffer, D.G., Gauthier, D.J. and Mitchell, C.C., Analysis of the Fenton-Karma model through an approximation by a one-dimensional map. Chaos 12 (2002) 10341042 . Google ScholarPubMed
Fenton, F. and Karma, A., Vortex dynamics in three-dimensional continuous myocardium with fiber rotation: Filament instability and fibrillation. Chaos 8 (1998) 2047. Google ScholarPubMed
FitzHugh, R.A., Impulses and physiological states in theoretical models of nerve membrane. Biophys. J. 1 (1961) 445466. Google ScholarPubMed
Hastings, S., Single and multiple pulse waves for the Fitzhugh-Nagumo equations. SIAM J. Appl. Math. 42 (1982) 247260. Google Scholar
Hodgkin, A.L. and Huxley, A.F., A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol. 117 (1952) 500544. Google ScholarPubMed
J. Keener and J. Sneyd, Mathematical Physiology. Springer (2004).
J.P. Keener, Modeling electrical activity of cardiac cells, Two variable models, Mitchell-Schaeffer revised. Available at www.math.utah.edu/˜keener/lectures/ionic_models/Two_variable_models.
Keener, J.P., An eikonal-curvature equation for action potential propagation in myocardium. J. Math. Biol. 29 (1991) 629651. DOI: 10.1007/BF00163916. Google ScholarPubMed
Ten Tusscher, K.H., Noble, D., Noble, P.J. and Panfilov, A.V., A model for human ventricular tissue. Am. J. Physiol. Heart Circ. Physiol. 286 (2004) H1973H1589. Google ScholarPubMed
Killmann, R., Wach, P. and Dienstl, F., Three-dimensional computer model of the entire human heart for simulation of reentry and tachycardia: gap phenomenon and Wolff-Parkinson-White syndrome. Basic Res. Cardiol. 86 (1991) 485501. Google Scholar
Luo, C.H. and Rudy, Y., A dynamic model of the cardiac ventricular action potential: I. simulations of ionic currents and concentration changes. Circ. Res. 74 (1994) 10711096. Google ScholarPubMed
Mitchell, C. and Schaeffer, D., A two-current model for the dynamics of cardiac membrane. Bull. Math. Bio. 65 (2003) 767793. Google ScholarPubMed
B.R. Munson, D.F. Young and T.H. Okiishi, Fundamentals of Fluid Mechanics. Wiley and Sons (2001).
Nagumo, J., Arimoto, S. and Yoshizawa, S., An active pulse transmission line simulating nerve axon. Proc. IRE. 50 (1962) 20612070. Google Scholar
Noble, D., A modification of the Hodgkin-Huxley equations applicable to purkinje fibre action and pacemaker potentials. J. Physiol. 160 (1962) 317352. Google Scholar
C. Pierre, Modélisation et simulation de l’activité électrique du coeur dans le thorax, analyse numérique et méthodes de volumes finis. PhD thesis, University of Nantes (2005).
J. Relan, M. Sermesant, H. Delingette, M. Pop, G.A. Wright and N. Ayache, Quantitative comparison of two cardiac electrophysiology models using personalisation to optical and mr data, in Proc. Sixth IEEE Int. Symp. Biomed. Imaging 2009 (ISBI’09).
J. Relan, M. Sermesant, M. Pop, H. Delingette, M. Sorine, G.A. Wright and N. Ayache, Parameter estimation of a 3d cardiac electrophysiology model including the restitution curve using optical and MR data, in World Congr. on Med. Phys. and Biomed. Eng., WC 2009, München (2009).
Schaeffer, D., Cain, J., Gauthier, D., Kalb, S., Oliver, R., Tolkacheva, E., Ying, W. and Krassowska, W., An ionically based mapping model with memory for cardiac restitution. Bull. Math. Bio. 69 (2007) 459482. DOI: 10.1007/s11538-006-9116-6. Google ScholarPubMed
Schaeffer, D., Ying, W. and Zhao, X., Asymptotic approximation of an ionic model for cardiac restitution. Nonlinear Dyn. 51 (2008) 189198. DOI: 10.1007/s11071-007-9202-9. Google ScholarPubMed
M. Sermesant, Y. Coudière, V. Moreau Villéger, K.S. Rhode, D.L.G. Hill and R. Ravazi, A fast-marching approach to cardiac electrophysiology simulation for XMR interventional imaging, in Proc. of MICCAI’05, vol. 3750 of Lect. Notes Comput. Sci., Palm Springs, California. Springer Verlag (2005) 607–615.
J. Sundnes, G.T. Lines, X. Cai, B.F. Nielsen, K.-A. Mardal and A. Tveito, Computing the Electrical Activity in the Heart. Springer, Monogr. Comput. Sci. Eng. 1 (2006).