Skip to main content

Systematic Study of Joint Influence of Angular Resolution and Noise in Cardiac Diffusion Tensor Imaging

  • Conference paper
  • First Online:
Functional Imaging and Modeling of the Heart (FIMH 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12738))

  • 2402 Accesses

Abstract

Diffusion tensor imaging (DTI) is a promising imaging technique to non-invasively study diffusion properties and fiber structures of myocardial tissues. Previous studies have investigated the influence of noise or angular resolution independently on the estimation of diffusion tensors in DTI. However, the joint influence of these two factors in DTI remains unclear. In this paper, we propose to systematically study the joint influence of angular resolutions and noise levels on the estimation of diffusion tensors and tensor-derived fractional anisotropy (FA) and mean diffusivity (MD). The results showed that, as expected, given a certain noise level and sufficient acquisition time, the accuracy of diffusion tensor, FA and MD all increase as the angular resolution. Moreover, when the angular resolution reached a certain value, further increasing the number of angular resolutions has little effect on the estimation of diffusion tensor, FA and MD. Also, both the mean and variance of FA or MD decrease as the angular resolution increases. For an imposed acquisition time, increasing the angular resolution reduces SNR of DW images. When fixing SNR, higher angular resolution can be obtained at the expense of longer acquisition time. These findings suggest the necessity of an optimized trade-off when designing DTI protocols.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tuch, D.S., Reese, T.G., Wiegell, M.R., Wedeen, V.J.: Diffusion MRI of complex neural architecture. Neuron 40(5), 885–895 (2003)

    Article  Google Scholar 

  2. Mekkaoui, C., et al.: Myocardial infarct delineation in vivo using diffusion tensor MRI and the tractographic propagation angle. J. Cardiovasc. Magn. Reson. 15(1), 1–3 (2013)

    MathSciNet  Google Scholar 

  3. Wu, M.-T., et al.: Diffusion tensor magnetic resonance imaging mapping the fiber architecture remodeling in human myocardium after infarction: correlation with viability and wall motion. Circulation 114(10), 1036–1045 (2006)

    Article  Google Scholar 

  4. Stejskal, E.O., Tanner, J.E.: Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 42(1), 288–292 (1965)

    Article  Google Scholar 

  5. Le Bihan, D.: IVIM method measures diffusion and perfusion (1990)

    Google Scholar 

  6. Taylor, W.D., Hsu, E., Krishnan, K.R.R., MacFall, J.R.: Diffusion tensor imaging: background, potential, and utility in psychiatric research. Biol. Psychiatry 55(3), 201–207 (2004)

    Article  Google Scholar 

  7. Hurwitz, R., Lane, S.R., Bell, R.A., Brant-Zawadzki, M.N.: Acoustic analysis of gradient-coil noise in MR imaging. Radiology 173(2), 545–548 (1989)

    Article  Google Scholar 

  8. Vovk, U., Pernus, F., Likar, B.: A review of methods for correction of intensity inhomogeneity in MRI. IEEE Trans. Med. Imaging 26(3), 405–421 (2007)

    Article  Google Scholar 

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

    Article  Google Scholar 

  10. Anderson, A.W.: Theoretical analysis of the effects of noise on diffusion tensor imaging. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 46(6), 1174–1188 (2001)

    Article  Google Scholar 

  11. Papadakis, N.G., Murrills, C.D., Hall, L.D., Huang, C.L.-H., Carpenter, T.A.: Minimal gradient encoding for robust estimation of diffusion anisotropy. Magn. Reson. Imaging 18(6), 671–679 (2000)

    Article  Google Scholar 

  12. Jones, D.K.: The effect of gradient sampling schemes on measures derived from diffusion tensor MRI: a Monte Carlo study. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 51(4), 807–815 (2004)

    Article  Google Scholar 

  13. Frindel, C., Robini, M., Croisille, P., Zhu, Y.-M.: Comparison of regularization methods for human cardiac diffusion tensor MRI. Med. Image Anal. 13(3), 405–418 (2009)

    Article  Google Scholar 

  14. Zhang, Y.-L., Liu, W.-Y., Magnin, I.E., Zhu, Y.-M.: Feature-preserving smoothing of diffusion weighted images using nonstationarity adaptive filtering. IEEE Trans. Biomed. Eng. 60(6), 1693–1701 (2013)

    Article  Google Scholar 

  15. Gudbjartsson, H., Patz, S.: The Rician distribution of noisy MRI data. Magn. Reson. Med. 34(6), 910–914 (1995)

    Article  Google Scholar 

  16. Teanby, N.A.: An icosahedron-based method for even binning of globally distributed remote sensing data. Comput. Geosci. 32(9), 1442–1450 (2006)

    Article  Google Scholar 

  17. Jones, D.K., Horsfield, M.A., Simmons, A.: Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. Off. J. Int. Soc. Magn. Reson. Med. 42(3), 515–525 (1999)

    Article  Google Scholar 

  18. Cheng, J., Shen, D., Yap, P.-T., Basser, P.J.: Single-and multiple-shell uniform sampling schemes for diffusion MRI using spherical codes. IEEE Trans. Med. Imaging 37(1), 185–199 (2017)

    Article  Google Scholar 

Download references

Acknowledgements

This work was partly supported by the Program PHC-Cai Yuanpei 2018 (N\(^{\circ }\) 41400TC), the LabEx PRIMES (Physics, Radiobiology, Imaging and Simulation), and the CNRS International Research Project METISLAB.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Yuemin Zhu .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

He, Y., Wang, L., Yang, F., Xia, Y., Clarysse, P., Zhu, Y. (2021). Systematic Study of Joint Influence of Angular Resolution and Noise in Cardiac Diffusion Tensor Imaging. In: Ennis, D.B., Perotti, L.E., Wang, V.Y. (eds) Functional Imaging and Modeling of the Heart. FIMH 2021. Lecture Notes in Computer Science(), vol 12738. Springer, Cham. https://doi.org/10.1007/978-3-030-78710-3_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78710-3_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78709-7

  • Online ISBN: 978-3-030-78710-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics