Abstract
Modelling the cardiac electrophysiology (EP) can help understand pathologies and predict the response to therapies such as cardiac resynchronization. To this end, estimating patient-specific model parameters is crucial. In the case of patients with bundle branch blocks (BBB), part of the Purkinje system is often affected. The aim of this work is to estimate the activation of the right and left Purkinje systems from standard non-invasive techniques: magnetic resonance imaging (MRI) and 12-lead electrocardiogram (ECG). As it is difficult to differentiate the contribution of the Purkinje system, this work relies on a particular intermittent left BBB (LBBB) case where both LBBB and absence of LBBB (ALBBB) were recorded on different 12-lead ECGs. First, an efficient forward EP model is proposed by coupling a Mitchell-Schaeffer cardiac model with a current dipole formulation that simulates the ECG. We used the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm to optimize the 3 parameters by minimizing the error with the real ECG. The estimation of conduction velocity (CV) parameters for LBBB and ALBBB shows a good agreement on the myocardial CV (0.39 m/s for ABBB, 0.40 m/s for LBBB), while the estimation of the left Purkinje CV seems to identify the pathology (1.32 m/s for ALBBB, 0.49 m/s for LBBB). Finally, the plots of the simulated 12-lead ECGs together with the ground truth ECGs indicate similar shapes.
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Notes
- 1.
VP2HF is a European Seventh Framework Program, http://www.vp2hf.eu/. The VP2HF meshing pipeline is based on CGAL, VTK, ITK and VMTK opensources libraries.
- 2.
SOFA is an Open Source medical simulation software available at http://www.sofa-framework.org.
References
Durrer, D., et al.: Total excitation of the isolated human heart. Circulation 41, 899–912 (1970). Am Heart Assoc
Lorange, M., et al.: A computer heart model incorporating anisotropic propagation. J. Electrocardiol. 26, 263–277 (1993). Elsevier
Potse, M., et al.: Similarities and differences between electrocardiogram signs of left bundle-branch block and left-ventricular uncoupling. In: Europace, vol. 14, pp. v33–v39. Eur Heart Rhythm Assoc (2012)
Zettinig, O., et al.: Data-driven estimation of cardiac electrical diffusivity from 12-lead ECG signals. Med. Image Anal. 18, 1361–1376 (2014). Elsevier
Chávez, C.E., Zemzemi, N., Coudière, Y., Alonso-Atienza, F., Álvarez, D.: Inverse problem of electrocardiography: estimating the location of cardiac ischemia in a 3D realistic geometry. In: van Assen, H., Bovendeerd, P., Delhaas, T. (eds.) FIMH 2015. LNCS, vol. 9126, pp. 393–401. Springer, Heidelberg (2015). doi:10.1007/978-3-319-20309-6_45
Groth, A., Weese, J., Lehmann, H.: Robust left ventricular myocardium segmentation for multi-protocol MR. In: SPIE Medical Imaging, p. 83142S. International Society for Optics and Photonics (2012)
Mitchell, C., Schaeffer, D.: A two-current model for the dynamics of cardiac membrane. Bull. Math. Biol. 65, 767–793 (2003). Springer, Heidelberg
Delingette, H., Ayache, N.: Soft tissue modeling for surgery simulation. In: Handbook of Numerical Analysis, vol. 12, pp. 453–550 (2004). Elsevier
Hansen, N.: The CMA evolution strategy: a comparing review. In: Lozano, J.A., Larrañaga, P., Inza, I., Bengoetxea, E. (eds.) Towards a New Evolutionary Computation. Studies in Fuzziness and Soft Computing, vol. 192, pp. 75–102. Springer, Heidelberg (2006)
Acknowledgments
The research leading to these results has received funding from the Seventh Framework Programme (FP7/2007-2013) under grant agreement VP2HF n\(^{\circ }\)611823.
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Giffard-Roisin, S. et al. (2017). Estimation of Purkinje Activation from ECG: An Intermittent Left Bundle Branch Block Study. In: Mansi, T., McLeod, K., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2016. Lecture Notes in Computer Science(), vol 10124. Springer, Cham. https://doi.org/10.1007/978-3-319-52718-5_15
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