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A Novel Rule-Based Algorithm for Assigning Myocardial Fiber Orientation to Computational Heart Models

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Abstract

Electrical waves traveling throughout the myocardium elicit muscle contractions responsible for pumping blood throughout the body. The shape and direction of these waves depend on the spatial arrangement of ventricular myocytes, termed fiber orientation. In computational studies simulating electrical wave propagation or mechanical contraction in the heart, accurately representing fiber orientation is critical so that model predictions corroborate with experimental data. Typically, fiber orientation is assigned to heart models based on Diffusion Tensor Imaging (DTI) data, yet few alternative methodologies exist if DTI data is noisy or absent. Here we present a novel Laplace–Dirichlet Rule-Based (LDRB) algorithm to perform this task with speed, precision, and high usability. We demonstrate the application of the LDRB algorithm in an image-based computational model of the canine ventricles. Simulations of electrical activation in this model are compared to those in the same geometrical model but with DTI-derived fiber orientation. The results demonstrate that activation patterns from simulations with LDRB and DTI-derived fiber orientations are nearly indistinguishable, with relative differences ≤6%, absolute mean differences in activation times ≤3.15 ms, and positive correlations ≥0.99. These results convincingly show that the LDRB algorithm is a robust alternative to DTI for assigning fiber orientation to computational heart models.

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References

  1. Alexander, A. L., K. M. Hasan, M. Lazar, J. S. Tsuruda, and D. L. Parker. Analysis of partial volume effects in diffusion-tensor MRI. Magn. Reson. Med. 45(5):770–780, 2001.

    Article  PubMed  CAS  Google Scholar 

  2. Ashikaga, H., J. C. Criscione, J. H. Omens, J. W. Covell, and N. B. Ingels. Transmural left ventricular mechanics underlying torsional recoil during relaxation. Am. J. Physiol. Heart Circ. Physiol. 286(2):H640–H647, 2004.

    Article  PubMed  CAS  Google Scholar 

  3. Bayer, J. D., J. Beaumont, and A. Krol. Laplace–Dirichlet energy field specification for deformable models. An FEM approach to active contour fitting. Ann. Biomed. Eng. 33(9):1175–1186, 2005.

    Article  PubMed  Google Scholar 

  4. Beyar, R., and S. Sideman. A computer study of the left ventricular performance based on fiber structure, sarcomere dynamics, and transmural electrical propagation velocity. Circ. Res. 55(3):358–375, 1984.

    Article  PubMed  CAS  Google Scholar 

  5. Bishop, M. J., P. M. Boyle, G. Plank, D. G. Welsh, and E. J. Vigmond. Modeling the role of the coronary vasculature during external field stimulation. IEEE Trans. Biomed. Eng. 57(10):2335–2345, 2010.

    Article  PubMed  Google Scholar 

  6. Bishop, M. J., G. Plank, R. A. Burton, J. E. Schneider, D. J. Gavaghan, V. Grau, and P. Kohl. Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function. Am. J. Physiol. Heart. Circ. Physiol. 298(2):H699–H718, 2010.

    Article  PubMed  CAS  Google Scholar 

  7. Bovendeerd, P. H., T. Arts, J. M. Huyghe, D. H. van Campen, amd R. S. Reneman. Dependence of local left ventricular wall mechanics on myocardial fiber orientation: a model study. J. Biomech. 25(10):1129–1140, 1992.

    Article  PubMed  CAS  Google Scholar 

  8. Caldwell, B. J., M. L. Trew, G. B. Sands, D. A. Hooks, I. J. LeGrice, and B. H. Smaill. Three distinct directions of intramural activation reveal nonuniform side-to-side electrical coupling of ventricular myocytes. Circ. Arrhythm. Electrophysiol. 2(4):433–440, 2009.

    Article  PubMed  Google Scholar 

  9. Cherry, E. M., H. S. Greenside, and C. S. Henriquez. Efficient simulation of three-dimensional anisotropic cardiac tissue using an adaptive mesh refinement method. Choas 13(3):853–865, 2003.

    Article  Google Scholar 

  10. Costa, K. D., Y. Takayama, A. D. McCulloch, and J. W. Laminar fiber architecture and three-dimensional systolic mechanics in canine ventricular myocardium. Am. J. Physiol. 276(2 Pt 2):H595–H607, 1999.

    PubMed  CAS  Google Scholar 

  11. Fernandez-Teran, M. A., and J. M. Hurle. Myocardial fiber architecture of the human heart ventricles. Anat. Rec. 204(2):137–147, 1982.

    Article  PubMed  CAS  Google Scholar 

  12. Greenstein, J. L., and R. L. Winslow. An integrative model of the cardiac ventricular myocyte incorporating local control of Ca2+ release. Biophys. J. 83(6):2918–2945, 2002.

    Article  PubMed  CAS  Google Scholar 

  13. Han, C., S. M. Pogwizd, C. R. Killingsworth, and B. He. Noninvasive reconstruction of the three-dimensional ventricular activation sequence during pacing and ventricular tachycardia in the canine heart. Am. J. Physiol. Heart Circ. Physiol. 302(1):H244–H252, 2012.

    Article  PubMed  CAS  Google Scholar 

  14. Harrington, K. B., F. Rodriguez, A. Cheng, F. Langer, H. Ashikaga, G. T. Daughters, J. C. Criscione, N. B. Ingels, and D. C. Miller. Direct measurement of transmural laminar architecture in the anterolateral wall of the ovine left ventricle: new implications for wall thickening mechanics. Am. J. Physiol. Heart Circ. Physiol. 288(3):H1324–H1330, 2005.

    Article  PubMed  CAS  Google Scholar 

  15. Helm, P., M. F. Beg, M. I. Miller, and R. L. Winslow. Measuring and mapping cardiac fiber and laminar architecture using diffusion tensor MR imaging. Ann. N. Y. Acad. Sci. 1047:296–307, 2005.

    Article  PubMed  Google Scholar 

  16. Helm, P. A., L. Younes, M. F. Beg, D. B. Ennis, C. Leclercq, O. P. Faris, E. McVeigh, D. Kass, M. I. Miller, and R. L. Winslow. Evidence of structural remodeling in the dyssynchronous failing heart. Circ. Res. 98(1):125–132, 2006.

    Article  PubMed  CAS  Google Scholar 

  17. Hristov, N., O. J. Liakopoulos, G. D. Buckberg, and G. Trummer. Septal structure and function relationships parallel the left ventricular free wall ascending and descending segments of the helical heart. Eur. J. Cardiothorac. Surg. 29S:S115–S125, 2006.

    Article  Google Scholar 

  18. Hooks, D. A., M. L. Trew, B. J. Caldwell, G. B. Sands, I. J. LeGrice, and B. H. Smaill. Laminar arrangement of ventricular myocytes influences electrical behavior of the heart. Circ. Res. 101(10):e103–e112, 2007.

    Article  PubMed  CAS  Google Scholar 

  19. Hsu, E. W., A. L. Muzikant, S. A. Matulevicius, R. C. Penland, and C. S. Henriquez. Magnetic resonance myocardial fiber-orientation mapping with direct histological correlation. Am. J. Physiol. 274(5 Pt 2):H1627–H1634, 1998.

    PubMed  CAS  Google Scholar 

  20. Keller, D. U. J., D. L. Weiss, O. Dossel, and G. Seemann. Influence of I Ks heterogeneities on the genesis of the T-wave: a computational evaluation. IEEE Trans. Biomed. Eng. 59(2):311–322, 2012.

    Article  PubMed  Google Scholar 

  21. Kim, Y. H., F. Xie, M. Yashima, T. J. Wu, M. Valderrbano, M. H. Lee, T. Ohara, O. Voroshilovsky, R. N. Doshi, M. C. Fishbein, Z. Qu, A. Garfinkel, J. N. Weiss, H. S. Karagueuzian, and P. S. Chen. Role of papillary muscle in the generation and maintenance of reentry during ventricular tachycardia and fibrillation in isolated swine right ventricle. Circulation 100(13):1450–1459, 1999.

    Article  PubMed  CAS  Google Scholar 

  22. LeGrice, I. J., B. H. Smaill, L. Z. Chai, S. G. Edgar, J. B. Gavin, and P. J. Hunter. Laminar structure of the heart: Ventricular myocyte arrangement and connective tissue architecture in the dog. Am. J. Physiol. 269(2 Pt 2):H571–H582, 1995.

    PubMed  CAS  Google Scholar 

  23. Lombaert, H., J.-M. Peyrat, P. Croisille, S. Rapacchi, L. Fanton, P. Clarysse, H. Delingette, and N. Ayache. Statistical analysis of the human cardiac fiber architecture from DT-MRI. In Proceedings of the 6th International Conference on Functional Imaging and Modeling of the Heart (FIMH’11), pp. 171–179, 2011.

  24. Pierpaoli, C., and P. J. Basser. Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36(6):893–906, 1996.

    Article  PubMed  CAS  Google Scholar 

  25. Potse, M., B. Dub, J. Richer, A. Vinet, and R. M. Gulrajani. A comparison of monodomain and bidomain reaction-diffusion models for action potential propagation in the human heart. IEEE Trans. Biomed. Eng. 53(12 Pt 1):2425–2435, 2006.

    Article  PubMed  Google Scholar 

  26. Reddy, J. N. An Introduction to the Finite Element Method, 3rd ed. New York: McGraw-Hill, 766 pp., 2006.

  27. Rijcken, J., P. H. Bovendeerd, A. J. Schoofs, D. H. van Campen, and T. Arts. Optimization of cardiac fiber orientation for homogeneous fiber strain during ejection. Ann. Biomed. Eng. 27(3):289–297, 1999.

    Article  PubMed  CAS  Google Scholar 

  28. Roberts, D. E., L. T. Hersh, and A. M. Scher. Influence of cardiac fiber orientation on wavefront voltage, conduction velocity, and tissue resistivity in the dog. Circ. Res. 44(5):701–712, 1979.

    Article  PubMed  CAS  Google Scholar 

  29. Rohmer, D., A. Sitek, and G. T. Gullberg. Reconstruction and visualization of fiber and laminar structure in the normal human heart from ex vivo diffusion tensor magnetic resonance imaging (DTMRI) data. Invest. Radiol. 42(11):777–789, 2007.

    Article  PubMed  Google Scholar 

  30. Scollan, D. F., A. Holmes, R. Winslow, and J. Forder. Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. Am. J. Physiol. 275(6 Pt 2):H2308–H2318, 1998.

    PubMed  CAS  Google Scholar 

  31. Scollan, D. F., A. Holmes, J. Zhang, and R. L. Winslow. Reconstruction of cardiac ventricular geometry and fiber orientation using magnetic resonance imaging. Ann. Biomed. Eng. 28(8):934–944, 2000.

    Article  PubMed  CAS  Google Scholar 

  32. Streeter, D. D., H. M. Spotnitz, D. P. Patel, J. Ross, and E. H. Sonnenblick. Fiber orientation in the canine left ventricle during diastole and systole. Circ. Res. 24(3):339–347, 1969.

    Article  PubMed  Google Scholar 

  33. Trayanova, N. A. Whole-heart modeling: applications to cardiac electrophysiology and electromechanics. Circ. Res. 108(1):113–128, 2011.

    Article  PubMed  CAS  Google Scholar 

  34. Vadakkumpadan, F., H. Arevalo, A. J. Prassl, J. Chen, F. Kickinger, P. Kohl, G. Plank, and N. Trayanova. Image-based models of cardiac structure in health and disease. Wiley Interdiscip. Rev. Syst. Biol. Med. 2(4):489–506, 2010.

    Article  PubMed  Google Scholar 

  35. Vendelin, M., P. H. Bovendeerd, J. Engelbrecht, and T. Arts. Optimizing ventricular fibers: uniform strain or stress, but not ATP consumption, leads to high efficiency. Am. J. Physiol. Heart Circ. Physiol. 283(3):H1072–H1081, 2002.

    PubMed  CAS  Google Scholar 

  36. Vetter, F. J., S. B. Simons, S. Mironov, C. J. Hyatt, and A. M. Pertsov. Epicardial fiber organization in swine right ventricle and its impact on propagation. Circ. Res. 96(2):244–251, 2005.

    Article  PubMed  CAS  Google Scholar 

  37. Vigmond, E. J., R. Weber dos Santos, A. J. Prassl, M. Deo, and G. Plank. Solvers for the cardiac bidomain equations. Prog. Biophys. Mol. Biol. 96(1–3):3–18, 2008.

    Article  PubMed  CAS  Google Scholar 

  38. Weiss, D. L., G. Seemann, D. U. J. Keller, D. Farina, F. B. Sachse, and O. Dossel. Modeling of heterogeneous electrophysiology in the human heart with respect to ECG genesis. In Proceedings of Computers in Cardiology, pp. 49–52, 2007.

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Acknowledgments

The authors would like to thank Dr. Edward Vigmond at the University of Bordeaux for his software Meshalyzer. This work was supported by grants AHA 10PRE3650037 to Jason Bayer, NIH R01 HL082729 and HL103428, and NSF CBET-0933029 to Natalia Trayanova, and FWF F3210-N18 and NIH R01 HL10119601 to Gernot Plank.

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Authors and Affiliations

  1. Department of Biomedical Engineering and Institute for Computational Medicine, The Johns Hopkins University, Baltimore, MD, USA

    J. D. Bayer, R. C. Blake & N. A. Trayanova

  2. Institute of Biophysics and Center for Physiological Medicine, Medical University of Graz, Graz, Austria

    G. Plank

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  1. J. D. Bayer
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  2. R. C. Blake
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Correspondence to J. D. Bayer.

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Associate Editor Nathalie Virag oversaw the review of this article.

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Bayer, J.D., Blake, R.C., Plank, G. et al. A Novel Rule-Based Algorithm for Assigning Myocardial Fiber Orientation to Computational Heart Models. Ann Biomed Eng 40, 2243–2254 (2012). https://doi.org/10.1007/s10439-012-0593-5

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