Modelovanie elektrickej aktivity srdca v prostredí COMSOL Multiphysics

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Modelovanie elektrickej aktivity srdca v prostredí COMSOL Multiphysics (Modeling of the electrical activity of the heart in COMSOL Multiphysics environment) Elena Cocherová

PRESENTATION OUTLINE Electrical excitation - action potential (AP) in the heart Models of AP of atrial and ventricular heart cells Simplified model of heart cells (modified FitzHugh- Nagumo model) in Matlab Modeling of AP propagation monodomain model Modeling of AP propagation - in COMSOL Multiphysics 2

Electrical excitation of the heart Electrical excitation (in form of action potential) is spreading in the heart through various types of heart cells [1] [3]: SA nodal origin of excitation Atrial AV nodal Bundle of His Bundle branches Purkinje fibers Endocardial Mid-myocardial Epicardial Action potential shape [2] is different for different types of heart cells 3

Membrane potential [mv ] Action potential +30 initial phase of repolarization plateau 0 depolarization terminal phase of repolarization -80 resting potential 100 200 300 400 Time [ms] Action potential phases in typical cardiomyocyte (cardiac muscle cell) 4

Various types of cardiomyocyte action potential shapes Various types of action potential shapes in ventricular cardiomyocyte [4], [5] 5

Models of heart ventricular cells [4] [11] Luo Rudy I model (1991) [6] Luo Rudy II model (1994) [7] Winslow model (1999) [8] Shannon-Bers model (2004) [9] Hund-Rudy dynamic model (2004) [130] O'Hara-Rudy model (2011) - enables to model [4], [5]: - epicardial - endocardial - mid-myocardial cells 6

Model of heart atrial cells [12] - [15] Courtemanche-Ramirez-Nattel model (1998) [12], [13] enables to control AP morphology (three main morphological types) - 21 ordinary differential equations (ODE) Simplified model of heart cells modified FitzHugh-Nagumo model [16] [20] enables to control AP shape - 2 ordinary differential equations 7

Courtemanche-Ramirez-Nattel model of human atrial cell [12] I NaCa I NaK I pca cell membrane Troponin Calmodulin I Na Ca I to I Kr I Ks I Ca,L I tr I up I Kur I rel SR I leak Myoplasm (intracellular fluid) I K1 I Na,b I Ca,b Sarcolemma (extracellular fluid) 8

Courtemanche-Ramirez-Nattel membrane model of the human atrial cell I st V Intracellular solution I Na I K I C G Na G K C m Membrane V Na V K dv dt Extracellular solution Cm Iion I st dv dt Iion I st Cm I ion I Na ICa, L Ito IKr IKs IK1 IKur I NaK I NaCa ICa, p ICa, b I Na, b I where e. g.: Na G Na m 3 h V V Na 21 ordinary differential equations (ODE) 75 algebraic equations 9

Modified FitzHugh-Nagumo model of the cardiac cell - using modified FitzHugh-Nagumo equations [16] [20] dv dt V B V B m m k c1v m B a 1 k c2rv A A d R dt k e V m B A R m B where V m is the membrane potential, R is the recovery variable a is relating to the excitation threshold e is relating to the excitability A is the action potential amplitude B is the resting membrane potential and c 1, c 2, and k are membrane-specific parameters. 10

FitzHugh-Nagumo model simulation in Matlab Influence of membrane parameters on : - action potential duration (APD) Influence of membrane parameter "e on APD [20]. 11

FitzHugh-Nagumo model simulation in Matlab Iinfluence of membrane parameters on : - action potential amplitude (APA) Influence of membrane parameter A on AP amplitude [20]. 12

Modeling of propagation of electrical activation using monodomain model - monodomain model [21], [22] with incorporated modified FitzHugh-Nagumo equations [18] [20], [23] V t where m V m C m I ion I s 1 C m V I I m ion is the membrane potential, is the membrane surface-to-volume ratio, is the membrane capacitance per unit area, is the tissue conductivity, is the ionic transmembrane current density per unit area and is the stimulation current density per unit area. s D C m 13

Simulation parameters - of monodomain model with modified FitzHugh- Nagumo equations:. a = 0.13 - relating to the excitation threshold e = 0.0132 - relating to the excitability A = 0.120 V - the action potential amplitude B = -0.085 V - the resting membrane potential c 1 = 2.6 - membrane-specific parameter c 2 = 1 - membrane-specific parameter k = 1000 s -1 - membrane-specific parameter D = 0.0005 m 2 /s - diffusivity 14

Modeling of propagation of electrical activation in COMSOL Multiphysics - monodomain model for AP propagation in the heart is: V t m 1 C m V I I m - this PDE (partial differential equation) is numerically solved in COMSOL Multiphysics - detailed description how realize similar example for heart of ellipsoidal shape in COMSOL Multiphysics is in [23]: ion s Select Physics: u Mathematics u PDE Interfaces u General Form PDE (g) 15

Modeling in COMSOL Multiphysics General Form PDE (g) in COMSOL Multiphysics: Mathematical description of monodomain model: V m 1 Vm t C 1 m C m I ion I s where: u V m e a = 0 d a = 1 i ion I C -Γ f ion m 16

Modeling geometry of heart wall whole heart as a hollow sphere: part of heart wall: approximate part of heart wall of box ( SLAB ) shape: the SLAB model of wall that is used for the following simulation 17

Meshing of the model The SLAB model of the heart wall covered with mesh (predefined Fine mesh). The stimulated area is a cylinder with r = 1 mm radius situated in the middle of the slab model. 18

Meshing of the model More dense meshing of the SLAB near the boundary of stimulated area of r = 1 mm radius (green) is performed with two manually added boundary mesh layers from both sides. 19

Propagation of AP simulation results Distribution of membrane potential [V] in the SLAB model at 0.006 s and 0.008 s after stimulation onset (r = 1 mm, stimulation duration T s = 0.002 s, amplitude of stimulation current i s = 100 A/F). Activated area is shown in red, resting area in blue. 20

Action potential in Point Probe Distribution of membrane potential [V] (action potential) in the slab model in point x = 1.5 mm, y = 0 mm, z = 2 mm (T s = 0.002 s, i s = 100 A/F). 21

Ion current in Point Probe Distribution of I ion normalized current [A/F] in the slab model in point x = 1.5 mm, y = 0 mm, z = 2 mm (T s = 0.002 s, i s = 100 A/F). First negative current causes depolarization of membrane (AP onset), positive peak of current causes membrane repolarization (terminal phase of repolarization). 22

Conclusion Simulation of electrical activity (AP) of heart cell using FitzHugh-Nagumo equations - ordinary differential equations (ODE) - in Matlab. Simulation of AP propagation in heart tissue using monodomain model with FitzHugh-Nagumo equations - partial differential equations (PDE) - in Comsol Multiphysics. 23

THANK YOU FOR YOUR ATTENTION! 24

References [1] MACFARLANE, P. W. - OOSTEROM, A. - PAHLM, O. - KLIGFIELD, P. - JANSE, M. - CAMM, J.: Comprehensive Electrocardiology. 2nd ed. London: Springer-Verlag, 2011. [2] MALMIVUO, J. - PLONSEY, R.: Bioelectromagnetism. Principles and Applications of Bioelectric and Biomagnetic Fields. Oxford University Press, Oxford, 1995, ISBN 0-19-505823-2, < http://www.bem.fi/book/>. [3] PULLAN, A.J. - CHENG, L.K. - BUIST, L.: Mathematically Modelling the Electrical Activity of the Heart: From Cell to Body Surface and Back Again. Singapore : World Scientific, 2005. ISBN 981-256-373-3. [4] O'HARA, T. - VIRÁG, L. - VARRÓ, A. - RUDY, Y.: Simulation of the undiseased human cardiac ventricular action potential: model formulation and experimental validation. PLoS Computational Biology, 2011, Vol.7, N. 5. [5] RUDY, Y.: List of Models for Ion Channels, Myocytes and Regulatory Pathways: ORd orginal human ventricular model, 2011. Matlab code, Rudy Laboratory, < http://rudylab.wustl.edu/research/cell/code/allcodes.html >. 25

[6] LUO, CH. - RUDY, Y.: A model of the ventricular cardiac action potential. Depolarization, repolarization, and their interaction, Circulation Research, 1991, Vol. 68, pp.1501-1526. [7] LUO, CH. - RUDY, Y.: A dynamic model of the cardiac entricular action potential: I. Simulations of ionic currents and concentration changes, Circulation Research, 1994, Vol. 74, pp.1071-1096. [8] WINSLOW, R. L. RICE, J. JAFRI, S.- MARBAN, E.- O'ROURKE, B.: Mechanisms of altered excitation-contraction coupling in canine tachycardia-induced heart failure, II: model studies. Circ. Res., 1999, Vol. 84, pp. 571-586. [9] SHANNON, T. R. - WANG, F. - PUGLISI, J. - WEBER, C. - BERS. D. M.: A mathematical treatment of integrated Ca dynamics within the ventricular myocyte. Biophys.J., 2004, Vol. 87, pp.3351-3371. [10] HUND, T. J. - RUDY, Y.: Rate dependence and regulation of action potential and calcium transient in a canine cardiac ventricular cell model. Circulation, vol. 110, no. 20, pp. 3168-3174, Nov, 2004. [11] TEN TUSSCHER, K. H. - BERNUS, O. - HREN, R. - PANFILOV, A. V.: Comparison of electrophysiological models for human ventricular cells and tissues. Prog Biophys Mol Biol, vol. 90, no. 1-3, pp. 326-45, Jan-Apr, 2006. 26

[12] COURTEMANCHE, M. - RAMIREZ, R. J. - NATTEL, S.: Ionic mechanisms underlying human atrial action potential properties: insights from a mathematical model. American Journal of Physiology-Heart and Circulatory Physiology, 1998, vol. 275, no. 1, p. 301-321. [13] FENG, J.- YUE, L. - WANG, Z. - NATTEL, S.: Ionic mechanisms of regional action potential heterogeneity in the canine right atrium. Circulation Research, 1998, vol. 83, no. 5, p. 541-551. [14] NATTEL, S. - MAGUY, A. - LE BOUTER, S. - YEH, Y.-H.: Arrhythmogenic ion-channel remodeling in the heart: Heart failure, myocardial infarction, and atrial fibrillation. Physiological Reviews, 2007, vol. 87, no. 2, p. 425-456. [15] WILHELMS, M. - HETTMANN, H. - MALECKAR, M. M. - KOIVUMAKI, J. T. - DOSSEL, O. - SEEMANN, G.: Benchmarking electrophysiological models of human atrial myocytes. Front Physiol, vol. 3, pp. 487, 2012. [16] FITZHUGH, R.: Impulses and physiological states in theoretical models of nerve membrane. Biophysical J., 1: 445-466, 1961. [17] NAGUMO, J. ARIMOTO, S. YOSHIZAWA, S.: An active pulse transmission line simulating nerve axon. Proc. IRE., 50: 2061-2070, 1962. [18] SOVILJ, S. MAGJAREVIĆ. R. LOVELL, N. H. DOKOS, S.: A simplified 3D model of whole heart electrical activity and 12-lead ECG generation. Computational and Mathematical Methods in Medicine, 2013, doi:10.1155/2013/134208. 27

[19] SOVILJ, S. - MAGJAREVIC, R. - LOVELL, N. - DOKOS, S.: Realistic 3D Bidomain Model of Whole Heart Electrical Activity and ECG Generation. 2013 Computing in Cardiology Conference, Computing in Cardiology Conference, pp. 377-380, New York: IEEE, 2013. [20] COCHEROVÁ, E.: Modeling of electrophysiological properties of heart cells. In Technical Computing Bratislava 2014, 22nd Annual Conference Proceedings. Bratislava, SR, 4. 11. 2014. Prague : Institute of Chemical Technology, 2014, < http://www2.humusoft.cz/www/papers/tcb2014/014_cocherova.pdf >. [21] POTSE, M. DUBÉ, B. RICHER, J. VINET, A. GULRAJANI, R.M.A.: Comparison of Monodomain and Bidomain Reaction-Diffusion Models for Action Potential Propagation in the Human Heart. IEEE Transactions on Biomedical Engineering, 53 (12): 2425-2435, 2006. [22] CLAYTON, R. H. - BERNUS, O. - CHERRY, E. M. - DIERCKX, H. - FENTON, F. H. - MIRABELLA, L. - PANFILOV, A. V. - SACHSE, F. B. - SEEMANN, G. - ZHANG, H.: Models of cardiac tissue electrophysiology: Progress, challenges and open questions. Progress in Biophysics & Molecular Biology, vol. 104, no. 1-3, pp. 22-48, Jan, 2011 [23] FILIPPI, S. CHERUBINI, C.: Electrical Signals in a Heart. Application ID: 981, University Campus Biomedico di Roma, Italy. < https://www.comsol.com/model/electrical-signals-in-a-heart-981 > 28