A Comparative Study of Graph-Based, Eikonal, and Monodomain Simulations for the Estimation of Cardiac Activation Times

The bidomain and monodomain equations are well established as the standard set of equations for the simulation of cardiac electrophysiological behavior. However, the computational cost of detailed bidomain/monodomain simulations limits their applicability in scenarios where a large number of simulations needs to be performed (e.g., parameter estimation). In this study, we present a graph-based method, which relies on point-to-point path finding to estimate activation times for single points in cardiac tissue with minimal computational costs. To validate our approach, activation times are compared to monodomain simulation results for an anatomically based rabbit ventricular model, incorporating realistic fiber orientation and conduction heterogeneities. Differences in activation times between the graph-based method and monodomain results are less than 10% of the total activation time, and computational performance is orders of magnitude faster with the proposed method when calculating activation times at single points. These results suggest that the graph-based method is well suited for estimating activation times when the need for fast performance justifies a limited loss of accuracy.

[1]  Angelo Auricchio,et al.  Cardiac resynchronization therapy in heart failure. , 2005, Italian heart journal : official journal of the Italian Federation of Cardiology.

[2]  Thom F. Oostendorp,et al.  Application of the fastest route algorithm in the interactive simulation of the effect of local ischemia on the ECG , 2008, Medical & Biological Engineering & Computing.

[3]  Hervé Delingette,et al.  An Anisotropic Multi-front Fast Marching Method for Real-Time Simulation of Cardiac Electrophysiology , 2007, FIMH.

[4]  Mark Potse,et al.  A Comparison of Monodomain and Bidomain Reaction-Diffusion Models for Action Potential Propagation in the Human Heart , 2006, IEEE Transactions on Biomedical Engineering.

[5]  Alexander V Panfilov,et al.  Organization of Ventricular Fibrillation in the Human Heart , 2007, Circulation research.

[6]  P. C. Franzone,et al.  Spreading of excitation in 3-D models of the anisotropic cardiac tissue. I. Validation of the eikonal model. , 1993, Mathematical biosciences.

[7]  Leslie Tung,et al.  A bi-domain model for describing ischemic myocardial d-c potentials , 1978 .

[8]  Alan Garny,et al.  A numerical guide to the solution of the bi-domain equations of cardiac electrophysiology. , 2010, Progress in biophysics and molecular biology.

[9]  Xing Cai,et al.  On the Computational Complexity of the Bidomain and the Monodomain Models of Electrophysiology , 2006, Annals of Biomedical Engineering.

[10]  J A Sethian,et al.  A fast marching level set method for monotonically advancing fronts. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Sandeep Patil,et al.  Voxel-based representation, display and thickness analysis of intricate shapes , 2005, Ninth International Conference on Computer Aided Design and Computer Graphics (CAD-CG'05).

[12]  N. Trayanova Whole-heart modeling: applications to cardiac electrophysiology and electromechanics. , 2011, Circulation research.

[13]  Nils J. Nilsson,et al.  A Formal Basis for the Heuristic Determination of Minimum Cost Paths , 1968, IEEE Trans. Syst. Sci. Cybern..

[14]  Kawal S. Rhode,et al.  A Fast-Marching Approach to Cardiac Electrophysiology Simulation for XMR Interventional Imaging , 2005, MICCAI.

[15]  J. Sethian,et al.  Fast methods for the Eikonal and related Hamilton- Jacobi equations on unstructured meshes. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Kalyanam Shivkumar,et al.  Distribution of late potentials within infarct scars assessed by ultra high-density mapping. , 2010, Heart rhythm.

[17]  Nicolas Smith,et al.  Estimation of Activation Times in Cardiac Tissue Using Graph Based Methods , 2011, FIMH.

[18]  Henry R. Halperin,et al.  Magnetic Resonance–Based Anatomical Analysis of Scar-Related Ventricular Tachycardia: Implications for Catheter Ablation , 2007, Circulation research.

[19]  Natalia A Trayanova,et al.  Differences Between Left and Right Ventricular Chamber Geometry Affect Cardiac Vulnerability to Electric Shocks , 2005, Circulation research.

[20]  Hervé Delingette,et al.  Efficient probabilistic model personalization integrating uncertainty on data and parameters: Application to eikonal-diffusion models in cardiac electrophysiology. , 2011, Progress in biophysics and molecular biology.

[21]  Roy C. P. Kerckhoffs,et al.  Effects of biventricular pacing and scar size in a computational model of the failing heart with left bundle branch block , 2009, Medical Image Anal..

[22]  J. Ross,et al.  Fiber Orientation in the Canine Left Ventricle during Diastole and Systole , 1969, Circulation research.

[23]  Alejandro F Frangi,et al.  A mesh-less approach for fast estimation of electrical activation time in the ventricular wall , 2009, 2009 36th Annual Computers in Cardiology Conference (CinC).

[24]  Alexander Vladimirsky,et al.  Ordered Upwind Methods for Static Hamilton-Jacobi Equations: Theory and Algorithms , 2003, SIAM J. Numer. Anal..

[25]  J. Restrepo,et al.  A rabbit ventricular action potential model replicating cardiac dynamics at rapid heart rates. , 2007, Biophysical journal.

[26]  J. Keener An eikonal-curvature equation for action potential propagation in myocardium , 1991, Journal of mathematical biology.

[27]  P. Ursell,et al.  Structural and Electrophysiological Changes in the Epicardial Border Zone of Canine Myocardial Infarcts during Infarct Healing , 1985, Circulation research.

[28]  Alexander G. Fletcher,et al.  Chaste: A test-driven approach to software development for biological modelling , 2009, Comput. Phys. Commun..

[29]  G Plank,et al.  Solvers for the cardiac bidomain equations. , 2008, Progress in biophysics and molecular biology.

[30]  J. Hespanha,et al.  Discrete approximations to continuous shortest-path: application to minimum-risk path planning for groups of UAVs , 2003, 42nd IEEE International Conference on Decision and Control (IEEE Cat. No.03CH37475).