How to Choose Myofiber Orientation in a Biventricular Finite Element Model?

  • Marieke PluijmertEmail author
  • Frits Prinzen
  • Adrián Flores de la Parra
  • Wilco Kroon
  • Tammo Delhaas
  • Peter H. M. Bovendeerd
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)


Biventricular (BiV) finite element (FE) models of cardiac electromechanics are evolving to a state where they can assist in clinical decision making. Carefully designed patient-specific geometries are combined with generic myofiber orientation data, because of lack of accurate techniques to measure myofiber orientation. However, it remains unclear to what extent the assumption of a generic myofiber orientation influences predictions on cardiac function from BiV FE models. As an alternative approach, it was suggested to let the myofiber orientation adapt in response to fiber cross-fiber shear. The aim of this study was to investigate to what extent variations in myofiber orientation as induced by adaptive myofiber reorientation caused variations in global stroke work in a BiV FE model and whether the adaptation model could be used as an alternative approach to prescribe the myofiber orientation in these models. An average change in myofiber orientation over an angle of about 8\(^\circ \), predominantly in transmural direction, resulted in a 91 % increase of LV and 20 % increase of RV stroke work. These findings indicate the importance for a more thorough effort to address a realistic myofiber orientation. The currently used model for adaptive myofiber reorientation seems a useful approach to prescribe the myofiber orientations in BiV FE models.


  1. 1.
    Aguado-Sierra, J., Krishnamurthy, A., Villongco, C., Chuang, J., Howard, E., Gonzales, M.J., Omens, J., Krummen, D.E., Narayan, S., Kerckhoffs, R.C.P., McCulloch, A.D.: Patient-specific modeling of dyssynchronous heart failure: a case study. Prog. Biophys. Mol. Biol. 107(1), 147–155 (2011)CrossRefGoogle Scholar
  2. 2.
    Constantino, J., Hu, Y., Trayanova, N.A.: A computational approach to understanding the cardiac electromechanical activation sequence in the normal and failing heart, with translation to the clinical practice of crt. Prog. Biophys. Mol. Biol. 110(2–3), 372–379 (2012)CrossRefGoogle Scholar
  3. 3.
    Kerckhoffs, R.C.P., Healy, S.N., Usyk, T.P., McCulloch, A.H.: Computational methods for cardiac electromechanics. Proc. IEEE 94(4), 769–783 (2006)CrossRefGoogle Scholar
  4. 4.
    Niederer, S.A., Plank, G., Chinchapatnam, P., Ginks, M., Lamata, P., Rhode, K.S., Rinaldi, C.A., Razavi, R., Smith, N.P.: Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. Cardiovasc. Res. 89(2), 336–343 (2011)CrossRefGoogle Scholar
  5. 5.
    Saint-Marie, J., Chapelle, D., Cimrman, R., Sorine, M.: Modeling and estimation of the cardiac electromechanical activity. Comp. Struc. 84, 1743–1759 (2006)CrossRefGoogle Scholar
  6. 6.
    Xia, L., Huo, M., Wei, Q., Liu, F., Crozier, S.: Analysis of cardiac ventricular wall motion based on a three-dimensional electromechanical biventricular model. Phys. Med. Biol. 50(8), 1901–1917 (2005)CrossRefGoogle Scholar
  7. 7.
    Lamata, P., Sinclair, M., Kerfoot, E., Lee, A., Crozier, A., Blazevic, B., Land, S., Lewandowski, A.J., Barber, D., Niederer, S., Smith, N.: An automatic service for the personalization of ventricular cardiac meshes. J. R. Soc. Interface. 11(91), 20131023 (2014)CrossRefGoogle Scholar
  8. 8.
    Nielsen, P.M., LeGrice, I.J., Smaill, B.H., Hunter, P.J.: Mathematical model of geometry and fibrous structure of the heart. Am. J. Physiol. Heart Circ. Physiol. 260, H1365–H1378 (1991)Google Scholar
  9. 9.
    Sermesant, M., et al.: Personalised electromechanical model of the heart for the prediction of the acute effects of cardiac resynchronisation therapy. In: Ayache, N., Delingette, H., Sermesant, M. (eds.) FIMH 2009. LNCS, vol. 5528, pp. 239–248. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  10. 10.
    Reese, T.G., Weisskoff, R.M., Smith, R.N., Rosen, B.R., Dinsmore, R.E., Wedeen, V.J.: Imaging myocardial fiber architecture in vivo with magnetic resonance. Magn. Reson. Med. 34(6), 786–791 (1995)CrossRefGoogle Scholar
  11. 11.
    Hsu, E.W., Muzikant, A.L., Matulevicius, S.A., Penland, R.C., Henriquez, C.S.: Magnetic resonance myocardial fiber-orientation mapping with direct histological correlation. Am. J. Physiol. 274(5), H1627–H1634 (1998)Google Scholar
  12. 12.
    Lombaert, H., Peyrat, J.M., Croisille, P., Rapacchi, S., Fanton, L., Cheriet, F., Clarysse, P., Magnin, I., Delingette, H., Ayache, N.: Human atlas of the cardiac fiber architecture: study on a healthy population. IEEE Trans. Med. Imaging 31(7), 1436–1447 (2012)CrossRefGoogle Scholar
  13. 13.
    Geerts-Ossevoort, L., Kerckhoffs, R., Bovendeerd, P., Arts, T.: Towards patient specific models of cardiac mechanics: a sensitivity study. In: Magnin, I.E., Montagnat, J., Clarysse, P., Nenonen, J., Katila, T. (eds.) FIMH 2003. LNCS, vol. 2674, pp. 81–90. Springer, Heidelberg (2003) CrossRefGoogle Scholar
  14. 14.
    Bovendeerd, P.H.M., Kroon, W., Delhaas, T.: Determinants of left ventricular shear strain. Am. J. Physiol. Heart Circ. Physiol. 297(3), H1058–H1068 (2009)CrossRefGoogle Scholar
  15. 15.
    Kroon, W., Delhaas, T., Arts, T., Bovendeerd, P.: Computational analysis of the myocardial structure: adaptation of myofiber orientations through deformation in three dimensions. Med. Imag. Anal. 13, 346–353 (2009)CrossRefGoogle Scholar
  16. 16.
    Pluijmert, M., Bovendeerd, P., Kroon, W., Delhaas, T.: The effect of active cross-fiber stress on shear-induced myofiber reorientation. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 35–45. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  17. 17.
    Kerckhoffs, R.C.P., Bovendeerd, P.H.M., Kotte, J.C.S., Prinzen, F.W., Smits, K., Arts, T.: Homogeneity of cardiac contraction despite physiological asynchrony of depolarization: a model study. Ann. Biomed. Eng. 31(5), 536–547 (2003)CrossRefGoogle Scholar
  18. 18.
    Bayer, J.D., Blake, R.C., Plank, G., Trayanova, N.A.: A novel rule-based algorithm for assigning myocardial fiber orientation to computational heart models. Ann. Biomed. Eng. 40(10), 2243–2254 (2012)CrossRefGoogle Scholar
  19. 19.
    Shoukas, A.A., Sagawa, K.: Control of total systemic vascular capacity by the carotid sinus baroreceptor reflex. Circ. Res. 33(1), 22–33 (1973)CrossRefGoogle Scholar
  20. 20.
    Shoukas, A.A.: Pressure-flow and pressure-volume relations in the entire pulmonary vascular bed of the dog determined by two-port analysis. Circ. Res. 37(6), 809–818 (1975)CrossRefGoogle Scholar
  21. 21.
    Geerts-Ossevoort, L., Bovendeerd, P., Nicolay, K., Arts, T.: Characterization of the normal cardiac myofiber field in goat measured with mr-diffusion tensor imaging. Am. J. Physiol. Heart Circ. Physiol. 283(1), H139–H145 (2002)CrossRefGoogle Scholar
  22. 22.
    Guyton, A.C., Hall, J.E.: Textbook of Medical Physiology. Elsevier Saunders, Philadelphia (2006)Google Scholar
  23. 23.
    Scollan, D.F., Holmes, A., Winslow, R., Forder, J.: Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. Am. J. Physiol. 275(6), H2308–H2318 (1998)Google Scholar
  24. 24.
    Stender, B., Schlaefer, A.: Detecting rat heart myocardial fiber directions in x-ray microtomography using coherence-enhancing diffusion filtering. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 63–70. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  25. 25.
    Stephenson, R.S., Boyett, M.R., Hart, G., Nikolaidou, T., Cai, X., Corno, A.F., Alphonso, N., Jeffery, N., Jarvis, J.C.: Contrast enhanced micro-computed tomography resolves the 3-dimensional morphology of the cardiac conduction system in mammalian hearts. PLoS One 7(4), e35299 (2012)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Marieke Pluijmert
    • 1
    • 2
    Email author
  • Frits Prinzen
    • 1
  • Adrián Flores de la Parra
    • 2
  • Wilco Kroon
    • 3
  • Tammo Delhaas
    • 1
  • Peter H. M. Bovendeerd
    • 2
  1. 1.Cardiovascular Research Institute Maastricht, Departments of Biomedical Engineering/PhysiologyMaastricht UniversityMaastrichtThe Netherlands
  2. 2.Department of Biomedical EngineeringEindhoven University of TechnologyEindhovenThe Netherlands
  3. 3.Institute of Computational ScienceUniversity of LuganoLuganoSwitzerland

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