Estimation of Conductivity Tensors from Human Ventricular Optical Mapping Recordings

  • John Walmsley
  • Gary R. Mirams
  • Igor R. Efimov
  • Kevin Burrage
  • Blanca Rodriguez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7945)


Experimental recordings of transmural activation in the human left ventricle show variability in recorded activation times. In this paper we demonstrate a framework for fitting the conductivity tensor of a monodomain model to reproduce activation times for an individual experiment whilst taking into account uncertainty in the fibre orientation. By directly registering anatomical features onto the difference between simulated and experimental results, we are then able to identify structural heterogeneities which impact on conduction in the left ventricle.


Wedge Angle Optical Mapping Helix Angle Conductivity Tensor Endocardial Surface 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bueno-Orovio, A., Hanson, B., Gill, J., Taggart, P., Rodríguez, B.: Left-to-right ventricular differences in rate adaptation transiently increase pro-arrhythmic risk following rate acceleration. PLoS ONE 7(12), e52234 (2012)Google Scholar
  2. 2.
    Lou, Q., Fedorov, V., Glukhov, A., Moazami, N., Fast, V., Efimov, I.: Transmural heterogeneity and remodeling of ventricular excitation-contraction coupling in human heart failure. Circulation 123, 1881–1890 (2011)CrossRefGoogle Scholar
  3. 3.
    Glukhov, A., Fedorov, V., Lou, Q., Janks, D., Ravikumar, V., Kalish, P., Scheussler, R., Moazami, N., Efimov, I.: Conduction remodeling in human end-stage nonischemic left ventricular cardiomyopathy. Circulation 125, 1835–1847 (2012)CrossRefGoogle Scholar
  4. 4.
    Eggen, M., Swingen, C., Iaizzo, P.: Analysis of fiber orientation in normal and failing human hearts using diffusion tensor MRI. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009, pp. 642–645 (2009)Google Scholar
  5. 5.
    Laughner, J., Ng, F., Sulkin, M., Arthur, M., Efimov, I.: Processing and Analysis of Cardiac Optical Mapping Data Obtained with Potentiometric Dyes. Am. J. Physiol. Heart Circ. Physiol. 303(7), H753–H765 (2012)Google Scholar
  6. 6.
    Pitt-Francis, J., et al.: Chaste: A test-driven approach to software development for biological modelling. Comp. Phys. Commun. 180, 2452–2471 (2009)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Bernabeu, M., Bishop, M., Pitt-Francis, J., Gavaghan, D., Grau, V., Rodríguez, B.: High performance computer simulations for the study of biological function in 3D heart models incorporating fibre orientation and realistic geometry at para-cellular resolution. In: Computers in Cardiology, pp. 721–724 (September 2008)Google Scholar
  8. 8.
    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. Circ. Arrhythmia Electrophysiol. 2, 433–440 (2009)CrossRefGoogle Scholar
  9. 9.
    Relan, J., Pop, M., Delingette, H., Wright, G., Ayache, N., Sermesant, M.: Personalization of a cardiac electrophysiology model using optical mapping and MRI for prediction of changes with pacing. IEEE Trans. Biomed. Eng. 58(12), 3339–3349 (2011)CrossRefGoogle Scholar
  10. 10.
    Walmsley, J., Rodríguez, J., Mirams, G., Burrage, K., Efimov, I., Rodríguez, B.: mRNA expression levels predict cellular electrophysiological remodelling in failing human hearts: A population based simulation study. PLoS ONE 8, e56359 (2013)Google Scholar
  11. 11.
    Wallman, M., Smith, N., Rodríguez, B.: A comparative study of graph-based, eikonal and monodomain simulations for the estimation of cardiac activation times. IEEE Trans. Biomed. Eng. 59(6), 1739–1748 (2012)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • John Walmsley
    • 1
  • Gary R. Mirams
    • 1
  • Igor R. Efimov
    • 2
  • Kevin Burrage
    • 1
    • 3
  • Blanca Rodriguez
    • 1
  1. 1.Department of Computer ScienceUniversity of OxfordOxfordUnited Kingdom
  2. 2.Department of Biomedical EngineeringWashington University in St. LouisSt. LouisUnited States of America
  3. 3.School of Mathematical SciencesQueensland University of TechnologyBrisbaneAustralia

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