Advertisement

Cardiac Fibers Estimation from Arbitrarily Spaced Diffusion Weighted MRI

  • Andreas Nagler
  • Cristóbal BertoglioEmail author
  • Christian T. Stoeck
  • Sebastian Kozerke
  • Wolfgang A. Wall
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9126)

Abstract

We propose a framework for estimating fiber fields in the heart from arbitrarily spaced diffusion weighted MRI. The approach is based on a parametric and space-dependent mathematical representation of the helix angles across the heart, leading to a semi-analytical formula of the diffusion tensor, without any particular assumption on the ventricular shape. Then, by solving an nonlinear inverse problem, the degrees of freedom of the model can be estimated from measured diffusion weighted data. We illustrate the methodology using synthetic data and compare it with previously reported fiber reconstruction techniques.

Keywords

Fiber Orientation Helix Angle Prolate Spheroid Diffusion Tensor Magnetic Resonance Image Fiber Family 
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.

Notes

Acknowledgements

The results presented in this article are part of the Advanced Cardiac Mechanics Emulator, an initiative supported by the Institute for Advanced Study (TU München). This support is gratefully acknowledged. We also thank Radomír Chabiniok and Jack Harmer (King’s College London) for the valuable discussions.

References

  1. 1.
    Basser, P., Mattiello, J., Lebihan, D.: Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. Ser. B 103(3), 247–254 (1994)CrossRefGoogle Scholar
  2. 2.
    Gamper, U., Boesiger, P., Kozerke, S.: Diffusion imaging of the in vivo heart using spin echoesconsiderations on bulk motion sensitivity. Magn. Reson. Med. 57(2), 331–337 (2007)CrossRefGoogle Scholar
  3. 3.
    Gudbjartsson, H., Patz, S.: The Rician distribution of noisy MRI data. Magn. Reson. Med. 34(6), 910–914 (1995)CrossRefGoogle Scholar
  4. 4.
    Koay, C.G., Chang, L.C., Carew, J.D., Pierpaoli, C., Basser, P.J.: A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging. J. Magn. Reson. 182(1), 115–125 (2006)CrossRefGoogle Scholar
  5. 5.
    Lombaert, H., Peyrat, J., Croisille, P., Rapacchi, S., Fanton, L., Cheriet, F., Clarysse, P., Magnin, I., Delingette, H., Ayache, N.: Human atlas of the cardiac fiber architecture: study on a healthy population. IEEE Trans. Med. Imaging 31(7), 1436–1447 (2012)CrossRefGoogle Scholar
  6. 6.
    Nagler, A., Bertoglio, C., Gee, M., Wall, W.: Personalization of cardiac fiber orientations from image data using the unscented kalman filter. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 132–140. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  7. 7.
    Nguyen, C., Fan, Z., Sharif, B., He, Y., Dharmakumar, R., Berman, D.S., Li, D.: In vivo three-dimensional high resolution cardiac diffusion-weighted MRI: a motion compensated diffusion-prepared balanced steady-state free precession approach. Magn. Res. Med. 72(5), 1257–1267 (2013)CrossRefGoogle Scholar
  8. 8.
    Nielles-Vallespin, S., Mekkaoui, C., Gatehouse, P., Reese, T.G., Keegan, J., Ferreira, P.F., Collins, S., Speier, P., Feiweier, T., Silva, R., Jackowski, M.P., Pennell, D.J., Sosnovik, D.E., Firmin, D.: In vivo diffusion tensor MRI of the human heart: reproducibility of breath-hold and navigator-based approaches. Magn. Reson. Med. 70(2), 454–465 (2013)CrossRefGoogle Scholar
  9. 9.
    Scollan, D.F., Holmes, A., Winslow, R., Forder, J.: Histological validation of myocardial microstructure obtained from diffusion tensor magnetic resonance imaging. Am. J. Physiol. Hear. Circ. Physiol. 275(6), H2308–H2318 (1998)Google Scholar
  10. 10.
    Stejskal, E., Tanner, J.: Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 42(1), 288–292 (1965)CrossRefGoogle Scholar
  11. 11.
    Toussaint, N., Stoeck, C.T., Schaeffter, T., Kozerke, S., Sermesant, M., Batchelor, P.G.: In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing. Med. Image Anal. 17(8), 1243–1255 (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Andreas Nagler
    • 1
  • Cristóbal Bertoglio
    • 1
    • 2
    Email author
  • Christian T. Stoeck
    • 3
    • 4
  • Sebastian Kozerke
    • 3
    • 4
  • Wolfgang A. Wall
    • 1
  1. 1.Institute for Computational MechanicsTechnische Universität MünchenMunichGermany
  2. 2.Center for Mathematical ModelingUniversidad de ChileSantiagoChile
  3. 3.Institute for Biomedical EngineeringUniversity and ETH ZurichZurichSwitzerland
  4. 4.Division of Imaging Sciences and Biomedical EngineeringKing’s College of LondonLondonUK

Personalised recommendations