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Computational cardiology: the bidomain based modified Hill model incorporating viscous effects for cardiac defibrillation

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Abstract

Working mechanisms of the cardiac defibrillation are still in debate due to the limited experimental facilities and one-third of patients even do not respond to cardiac resynchronization therapy. With an aim to develop a milestone towards reaching the unrevealed mechanisms of the defibrillation phenomenon, we propose a bidomain based finite element formulation of cardiac electromechanics by taking into account the viscous effects that are disregarded by many researchers. To do so, the material is deemed as an electro-visco-active material and described by the modified Hill model (Cansız et al. in Comput Methods Appl Mech Eng 315:434–466, 2017). On the numerical side, we utilize a staggered solution method, where the elliptic and parabolic part of the bidomain equations and the mechanical field are solved sequentially. The comparative simulations designate that the viscoelastic and elastic formulations lead to remarkably different outcomes upon an externally applied electric field to the myocardial tissue. Besides, the achieved framework requires significantly less computational time and memory compared to monolithic schemes without loss of stability for the presented examples.

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References

  1. Abraham WT, Fisher WG, Smith AL, Delurgio DB, Leon AR, Loh E, Kocovic DZ, Packer M, Clavell AL, Hayes DL, Ellestad M, Trupp RJ, Underwood J, Pickering F, Truex C, McAtee P, Messenger J (2002) Cardiac resynchronization in chronic heart failure. N Engl J Med 346:1845–1853

    Article  Google Scholar 

  2. Abraham WT, Hayes DL (2003) Cardiac resynchronization therapy for heart failure. Circulation 108:2596–2603

    Article  Google Scholar 

  3. Aliev RR, Panfilov AV (1996) A simple two-variable model of cardiac excitation. Chaos Solitons Fractals 7:293–301

    Article  Google Scholar 

  4. Augustin CM, Neic A, Liebmann M, Prassl AJ, Niederer SA, Haase G, Plank G (2016) Anatomically accurate high resolution modeling of human whole heart electromechanics: a strongly scalable algebraic multigrid solver method for nonlinear deformation. J Comput Phys 305:622–646

    Article  MathSciNet  MATH  Google Scholar 

  5. Bleeker GB, Bax JJ, Steendijk P, Schalij MJ, van del Wall EE (2006) Left ventricular dyssynchrony in patients with heart failure: pathophysiology, diagnosis and treatment. Nat Clin Pract Cardiovasc Med 3:213–219

    Article  Google Scholar 

  6. Bragard J, Elorza J, Cherry EM, Fenton FH (2013) Validation of a computational model of cardiac defibrillation. Comput Cardiol 2013:851–854

    Google Scholar 

  7. Cansız B, Dal H, Kaliske M (2015) Fully coupled cardiac electromechanics with orthotropic viscoelastic effects. Proc IUTAM 12:124–133

    Article  Google Scholar 

  8. Cansız B, Dal H, Kaliske M (2017) Computational cardiology: A modified Hill model to describe the electro-visco-elasticity of the myocardium. Comput Methods Appl Mech Eng 315:434–466

    Article  MathSciNet  Google Scholar 

  9. Cansız FBC, Dal H, Kaliske M (2015) An orthotropic viscoelastic material model for passive myocardium: theory and algorithmic treatment. Comput Methods Biomech Biomed Eng 18:1160–1172

    Article  Google Scholar 

  10. Cherubini C, Filippi S, Nardinocchi P, Teresi L (2008) An electromechanical model of cardiac tissue: constitutive issues and electrophysiological effects. Prog Biophys Mol Biol 97:562–573

    Article  Google Scholar 

  11. Colli Franzone P, Pavarino L, Savaré G (2006) Computational electrocardiology: mathematical and numerical modeling. In: Quarteroni A, Formaggia L, Veneziani A (eds) Complex systems in biomedicine. Springer, Milan, pp 187–241

    Chapter  Google Scholar 

  12. Dal H, Göktepe S, Kuhl E, Kaliske M (2012) A fully implicit finite element method for bidomain models of cardiac electrophysiology. Comput Methods Biomech Biomed Eng 15:645–656

    Article  MATH  Google Scholar 

  13. Dal H, Göktepe S, Kuhl E, Kaliske M (2013) A fully implicit finite element method for bidomain models of cardiac electromechanics. Comput Methods Appl Mech Eng 253:323–336

    Article  MathSciNet  MATH  Google Scholar 

  14. dos Santos R, Plank G, Bauer S, Vigmond E (2004) Parallel multigrid preconditioner for the cardiac bidomain model. IEEE Trans Biomed Eng 51:1960–1968

    Article  Google Scholar 

  15. Franzone PC, Pavarino L, Scacchi S (2015) Parallel multilevel solvers for the cardiac electro-mechanical coupling. Appl Numer Math 95:140–153

    Article  MathSciNet  MATH  Google Scholar 

  16. Gerardo-Giorda L, Mirabella L, Nobile F, Perego M, Veneziani A (2009) A model-based block-triangular preconditioner for the bidomain system in electrocardiology. J Comput Phys 228:3625–3639

    Article  MathSciNet  MATH  Google Scholar 

  17. Göktepe S, Kuhl E (2009) Computational modeling of cardiac electrophysiology: a novel finite element approach. Int J Numer Methods Eng 79:156–178

    Article  MathSciNet  MATH  Google Scholar 

  18. Göktepe S, Menzel A, Kuhl E (2014) The generalized hill model: a kinematic approach towards active muscle contraction. J Mech Phys Solids 72:20–39

    Article  MathSciNet  MATH  Google Scholar 

  19. Graber ML (2013) The incidence of diagnostic error in medicine. BMJ Qual Saf 22:21–27

    Article  Google Scholar 

  20. Hill AV (1938) The heat of shortening and the dynamic constants of muscle. Proc R Soc B Biol Sci 126:136–195

    Article  Google Scholar 

  21. Holzapfel GA, Ogden RW (2009) Constitutive modelling of passive myocardium: a structurally based framework for material characterization. Philos Trans R Soc A Math Phys Eng Sci 367:3445–3475

    Article  MathSciNet  MATH  Google Scholar 

  22. Hooks DA, Tomlinson KA, Marsden SG, LeGrice IJ, Smaill BH, Pullan AJ, Hunter PJ (2002) Cardiac microstructure: implications for electrical propagation and defibrillation in the heart. Circ Res 91:331–338

    Article  Google Scholar 

  23. Johnston PR (2010) A finite volume method solution for the bidomain equations and their application to modelling cardiac ischaemia. Comput Methods Biomech Biomed Eng 13:157–170

    Article  Google Scholar 

  24. Keener JP, Bogar K (1998) A numerical method for the solution of the bidomain equations in cardiac tissue. Chaos Interdiscip J Nonlinear Sci 8:234–241

    Article  MATH  Google Scholar 

  25. Kotikanyadanam M, Göktepe S, Kuhl E (2010) Computational modeling of electrocardiograms: a finite element approach toward cardiac excitation. Int J Numer Methods Biomed Eng 26:524–533

    MathSciNet  MATH  Google Scholar 

  26. Lecarpentier Y, Chemla D (1990) Mehcanical analysis of sarcomere by laser diffraction: energy excahnge and cardiac insuffiency. In: Swynghedauw B (ed) Research in cardiac hypertrophy and failure. INSERM/John Linney Eurotext, Paris, pp 137–160

    Google Scholar 

  27. Lecarpentier Y, Martin JL, Claes V, Chambaret JP, Migus A, Antonetti A, Hatt PY (1985) Real-time kinetics of sarcomere relaxation by laser diffraction. Circ Res 56:331–9

    Article  Google Scholar 

  28. Miller WT, Geselowitz DB (1978) Simulation studies of the electrocardiogram i: the normal heart. Circ Res 43:301–315

    Article  Google Scholar 

  29. Nash MP, Panfilov AV (2004) Electromechanical model of excitable tissue to study reentrant cardiac arrhythmias. Prog Biophys Mol Biol 85:501–522

    Article  Google Scholar 

  30. Nickerson D, Nash M, Nielsen P, Smith N, Hunter P (2006) Computational multiscale modeling in the IUPS physiome project: modeling cardiac electromechanics. Syst Biol 50:617–630

    Google Scholar 

  31. Niederer SA, Plank G, Chinchapatnam P, Ginks M, Lamata P, Rhode KS, Rinaldi CA, Razavi R, Smith NP (2011) Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. Cardiovasc Res 89:336

    Article  Google Scholar 

  32. Niederer SA, Shetty A, Plank G, Bostock J, Razavi R, Smith N, Rinaldi C (2012) Biophysical modeling to simulate the response to multisite left ventricular stimulation using a quadripolar pacing lead. Pacing Clin Electrophysiol 35:204–214

    Article  Google Scholar 

  33. Panfilov AV, Keldermann RH, Nash MP (2005) Self-organized pacemakers in a coupled reaction–diffusion–mechanics system. Phys Rev Lett 95:258,104-1–258,104-4

    Article  Google Scholar 

  34. Pathmanathan P, Bernabeu MO, Bordas R, Cooper J, Garny A, Pitt-Francis JM, Whiteley JP, Gavaghan DJ (2010) A numerical guide to the solution of the bidomain equations of cardiac electrophysiology. Prog Biophys Mol Biol 102:136–155

    Article  Google Scholar 

  35. Pollard AE, Hooke N, Henriquez CS (1992) Cardiac propagation simultion. Crit Rev Biomed Eng 20:171–210

    Google Scholar 

  36. Potse M, Dube B, Richer J, Vinet A, Gulrajani RM (2006) A comparison of monodomain and bidomain reaction–diffusion models for action potential propagation in the human heart. IEEE Trans Biomed Eng 53:2425–2435

    Article  Google Scholar 

  37. Roth BJ, Beaudoin DL (2003) Approximate analytical solutions of the bidomain equations for electrical stimulation of cardiac tissue with curving fibers. Phys Rev E 67:051,925–1–051,925–8

    Article  Google Scholar 

  38. Southern JA, Plank G, Vigmond EJ, Whiteley JP (2009) Solving the coupled system improves computational efficiency of the bidomain equations. IEEE Trans Biomed Eng 56:2404–2412

    Article  Google Scholar 

  39. Sundnes J, Lines GT, Tveito A (2005) An operator splitting method for solving the bidomain equations coupled to a volume conductor model for the torso. Math Biosci 194:233–248

    Article  MathSciNet  MATH  Google Scholar 

  40. Trayanova N (2006) Defibrillation of heart: insights into mechanisms from modelling studies. Exp Physiol 91:323–337

    Article  Google Scholar 

  41. Tung L (1978) A bidomain model for describing ischaemic myocardial dc potentials. Ph.D. thesis, MIT

  42. Usyk TP, LeGrice IJ, McCulloch AD (2002) Computational model of three-dimensional cardiac electromechanics. Comput Vis Sci 4:249–257

    Article  MATH  Google Scholar 

  43. Vernooy K, van Deursen CJM, Strik M, Prinzen FW (2014) Strategies to improve cardiac resynchronization therapy. Nat Rev Cardiol 11:481–493

    Article  Google Scholar 

  44. Vigmond E, Aguel F, Trayanova N (2002) Computational techniques for solving the bidomain equations in three dimensions. IEEE Trans Biomed Eng 49:1260–1269

    Article  Google Scholar 

  45. Vigmond E, dos Santos RW, Prassl A, Deo M, Plank G (2008) Solvers for the cardiac bidomain equations. Prog Biophys Mol Biol 96:3–18

    Article  Google Scholar 

  46. Vigmond E, Vadakkumpadan F, Gurev V, Arevalo H, Deo M, Plank G, Trayanova N (2009) Towards predictive modelling of the electrophysiology of the heart. Exp Physiol 94:563–577

    Article  Google Scholar 

  47. Vigmond EJ, Hughes M, Plank G, Leon LJ (2003) Computational tools for modeling electrical activity in cardiac tissue. J Electrocardiol 36:69–74

    Article  Google Scholar 

Download references

Acknowledgements

We gratefully acknowledge the contribution of Dr. med. Krunoslav Michael Sveric from Department of Cardiology, Heart Center, Technische Universität Dresden and the financial support of the German Research Foundation (DFG) under Grant KA 1163/18.

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Correspondence to Michael Kaliske.

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Cansız, B., Dal, H. & Kaliske, M. Computational cardiology: the bidomain based modified Hill model incorporating viscous effects for cardiac defibrillation. Comput Mech 62, 253–271 (2018). https://doi.org/10.1007/s00466-017-1495-z

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  • DOI: https://doi.org/10.1007/s00466-017-1495-z

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