Abstract
We present a pipeline for the personalization of model-based Purkinje fast conduction system using fast electrophysiological models and optical mapping data acquired from ex-vivo porcine hearts. The regional density of the Purkinje terminals as well as the latest endocardial activation time were the parameters personalized in an iterative procedure maximizing the similarity between the outcome of the electrophysiological simulations and measurements obtained from optical mapping data. We used a fast wave-front Eikonal-based electrophysiological model that generated the depolarization time maps that were subsequently compared with measurements at each iteration of the optimization stage. The pacing site given by the experimental data and the optimized Purkinje system were introduced into the electrophysiological model. We obtained a regional distribution of Purkinje end-terminals in agreement with findings in the literature. Nevertheless, remaining differences between simulations and measurements after personalization suggest that epicardial data obtained from optical mapping data might not be sufficient to optimize the Purkinje system, which is basically located at the endocardium. On the other hand, the developed pipeline could also be used with endocardial data on electrical activation provided by non-contact or contact mapping system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ecabert, O., Smith, N.: euheart: integrated cardiac care using patient-specific cardiovascular modeling. In: SPIE Newsroom, Biomedical Optics and Medical Imaging (2008)
Sermesant, M., Moireau, P., Camara, O., Sainte-Marie, J., Andriantsimiavona, R., Cimrman, R., Hill, D., Chapelle, D., Razavi, R.: Cardiac function estimation from mri using a heart model and data assimilation: advances and difficulties. Medical Image Analysis 10(4), 642–656 (2006)
Kerckhoffs, R., Healy, S., Usyk, T., McCulloch, A.: Computational methods for cardiac electromechanics. Proceedings of the IEEE 94(6), 769–783 (2006)
Streeter, D.: Gross morphology and fibrous structure of the heart. In: Handbook of Physiology: The Cardiovascular System, vol. 1, pp. 61–112. Oxford University Press, Oxford (1979)
Peyrat, J.M., Sermesant, M., Pennec, X., Delingette, H., Xu, C., McVeigh, E.R., Ayache, N.: A computational framework for the statistical analysis of cardiac diffusion tensors: application to a small database of canine hearts. IEEE Trans. Med Imaging 26(11), 1500–1514 (2007)
Kroon, W., Delhaas, T., Bovendeerd, P., Arts, T.: Adaptive reorientation of cardiac myofibers: Comparison of left ventricular shear in model and experiment. In: Ayache, N., Delingette, H., Sermesant, M. (eds.) FIMH 2009. LNCS, vol. 5528, pp. 58–67. Springer, Heidelberg (2009)
Muñoz-Moreno, E., Frangi, A.: Spatial normalization of cardiac diffusion tensor imaging for modeling the muscular structure of the myocardium. In: Proceedings of the IEEE International Conference on Image Processing (ICIP 2010) (2010) (in Press)
Romero, D., Sebastian, R., Bijnens, B.H., Zimmerman, V., Boyle, P.M., Vigmond, E.J., Frangi, A.F.: Effects of the purkinje system and cardiac geometry on biventricular pacing: a model study. Ann. Biomed. Eng. 38(4), 1388–1398 (2010)
Zimmerman, V., Sebastian, R., Bijnens, B., Frangi, A.: Modeling the purkinje conduction system with a non deterministic rule based iterative method. Computer in Cardiology 36, 461–464 (2009)
Durrer, D., van Dam, R.T., Freud, G.E., Janse, M.J., Meijler, F.L., Arzbaecher, R.C.: Total excitation of the isolated human heart. Circulation 41, 899–912 (1970)
Pop, M., Sermesant, M., Lepiller, D., Truong, M., McVeigh, E., Crystal, E., Dick, A., Delingette, H., Ayache, N., Wright, G.: Fusion of optical imaging and mri for the evaluation and adjustment of macroscopic models of cardiac electrophysiology: a feasibility study. Medical Image Analysis 13(2), 370–380 (2009)
Relan, J., Sermesant, M., Delingette, H., Pop, M., Wright, G., Ayache, N.: Quantitative comparison of two cardiac electrophysiology models using personalisation to optical and mr data. In: Proc. IEEE International Symposium on Biomedical Imaging: From Nano to Macro (ISBI 2009), pp. 1027–1030 (2009)
Kerckhoffs, R.C.P., Faris, O.P., Bovendeerd, P.H.M., Prinzen, F.W., Smits, K., McVeigh, E.R., Arts, T.: Timing of depolarization and contraction in the paced canine left ventricle: model and experiment. J. Cardiovasc. Electrophysiol. 14(10 suppl.), 188–195 (2003)
Caldwell, B., Trew, M., Sands, G., Hooks, D., LeGrice, I., Smaill, B.: Three distinct directions of intramural activation reveal nonuniform side-to-side electrical coupling of ventricular myocytes. Circulation: Arrhythmia and Electrophysiology 2(4), 433–440 (2009)
Rawling, D.A., Joyner, R.W., Overholt, E.D.: Variations in the functional electrical coupling between the subendocardial purkinje and ventricular layers of the canine left ventricle. Circ. Res. 57(2), 252–261 (1985)
Franzone, P., Guerri, L., Pennacchio, M.M., Taccardi, B.: Spread of excitation in 3-d models of the anisotropic cardiac tissue. ii. effects of fiber architecture and ventricular geometry. Math Biosci. 147(2), 131–171 (1998)
Tomlinson, K.A., Hunter, P.J., Pullan, A.J.: A finite element method for an eikonal equation model of myocardial excitation wavefront propagation. SIAM Journal on Applied Mathematics 63, 324–350 (2002)
Chinchapatnam, P., Rhode, K.S., Ginks, M., Rinaldi, C.A., Lambiase, P., Razavi, R., Arridge, S., Sermesant, M.: Model-based imaging of cardiac apparent conductivity and local conduction velocity for diagnosis and planning of therapy. IEEE Trans. Med. Imaging 27(11), 1631–1642 (2008)
Sethian, J.A.: A fast marching level set method for monotonically advancing fronts, vol. 93, pp. 891–906 (1991)
Sermesant, M., Coudière, Y., Moreau-Villéger, V., Rhode, K., Hill, D., Razavi, R.: A fast-marching approach to cardiac electrophysiology simulation for XMR interventional imaging, vol. 8, pp. 607–615 (2005)
Mauch, S.: Efficient algorithms for solving static hamilton-jacobi equations, PhD thesis California Institute of Technology (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Camara, O., Pashaei, A., Sebastian, R., Frangi, A.F. (2010). Personalization of Fast Conduction Purkinje System in Eikonal-Based Electrophysiological Models with Optical Mapping Data. In: Camara, O., Pop, M., Rhode, K., Sermesant, M., Smith, N., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. STACOM 2010. Lecture Notes in Computer Science, vol 6364. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15835-3_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-15835-3_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15834-6
Online ISBN: 978-3-642-15835-3
eBook Packages: Computer ScienceComputer Science (R0)