Logo PTI
Polish Information Processing Society
Logo FedCSIS

Annals of Computer Science and Information Systems, Volume 8

Proceedings of the 2016 Federated Conference on Computer Science and Information Systems

Improving precision and accuracy of DTI experiments with the simplified BSD calibration – computer simulations

,

DOI: http://dx.doi.org/10.15439/2016F403

Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 935–938 ()

Full text

Abstract. The b-matrix spatial distribution (BSD) is an effective method of improving accuracy of diffusion tensor imaging (DTI) measurements. It is based on a calibration with an anisotropic phantom measured in six positions inside an MRI scanner. However, if the contribution of non-diffusion gradients to the b-matrix can be neglected, simplified form of calibration with only 3 positions of the phantom could be sufficient. We called this approach simplified BSD-DTI (sBSDDTI). In this paper we introduce the above-mentioned technique and present the results of the computer simulations of BSD-DTI experiments and compare them with standard DTI. The complete BSD method, sBSD as well as BSD with assumption of phantom uniformity (uBSD) were simulated. The simulations revealed that both simplified methods are less accurate than the complete BSD-DTI. Nevertheless, the calibration procedures and the algorithms are streamlined.

References

  1. A. Lerner, M. Mogensen, P. Kim, M. Shiroishi, D. Hwang and M. Law, "Clinical Applications of Diffusion Tensor Imaging", World Neurosurgery, vol. 82, no. 1-2, pp. 96-109, 2014, http://dx.doi.org/10.4103/0971-3026.38505
  2. A. Krzyżak and Z. Olejniczak, "Improving the accuracy of PGSE DTI experiments using the spatial distribution of b matrix", Magnetic Resonance Imaging, vol. 33, no. 3, pp. 286-295, 2015, http://dx.doi.org/10.1016/j.mri.2014.10.007
  3. D. Güllmar, J. Haueisen, and J. R. Reichenbach, “Analysis of b-value calculations in diffusion weighted and diffusion tensor imaging,” Concepts Magn. Reson., vol. 25A, no. 1, pp. 53–66, Mar. 2005, http://dx.doi.org/10.1002/cmr.a.20031
  4. J. Mattiello, P. Basser and D. Lebihan, "Analytical Expressions for the b Matrix in NMR Diffusion Imaging and Spectroscopy", Journal of Magnetic Resonance, Series A, vol. 108, no. 2, pp. 131-141, 1994, http://dx.doi.org/10.1006/jmra.1994.1103
  5. J. Mattiello, P. Basser and D. Le Bihan, "The b matrix in diffusion tensor echo-planar imaging", Magnetic Resonance in Medicine, vol. 37, no. 2, pp. 292-300, 1997, http://dx.doi.org/10.1002/mrm.1910370226
  6. Hsu EW, Mori S. Analytical expressions for the NMR apparent diffusion coefficients in an anisotropic system and a simplified method for determining fiber orientation. Magn Reson Med 1995;34:194–200, http://dx.doi.org/10.1002/mrm.1910370226
  7. Neeman M, Freyer JP, Sillerud LO. A simple method for obtaining cross-term-free images for diffusion anisotropy studies in NMR microimaging. Magn Reson Med 1991;21:138–43, http://dx.doi.org/10.1002/mrm.1910210117
  8. Güllmar D, Haueisen J, Reichenbach JR. Analysis of b-value calculations in diffusion weighted and diffusion tensor imaging. Concepts Magn Reson Part A 2005;25A:53–66. http://dx.doi.org/10.1002/cmr.a.20031
  9. S. Boujraf, R. Luypaert, H. Eisendrath and M. Osteaux, "Effect of accurately calculated b matrix on the evaluation of the diffusion tensor using echoplanar diffusion tensor imaging", ITBM-RBM, vol. 23, no. 6, pp. 340-344, 2002, http://dx.doi.org/10.1016/S1297-9562(02)90003-3
  10. Ozcan A. Minimization of Imaging Gradient Effects in Diffusion Tensor Imaging. IEEE Trans Med Imaging 2011;30:642–54. http://dx.doi.org/10.1109/TMI.2010.2090539.
  11. G. Nair and X. P. Hu, “Manifestation and Post-hoc Correction of Gradient Cross-term Artifacts in DTI,” Magn Reson Imaging, vol. 30, no. 6, pp. 764–773, Jul. 2012, http://dx.doi.org/10.1016/j.mri.2012.02.021
  12. K. Borkowski and A. Krzyżak, “Simulations of rotation of the anisotropic phantom in BSD-DTI” in Magnetic Resonance Materials in Physics, Biology and Medicine, 2015 vol. 28 suppl. 1, s. 467–468. ESMRMB 2015 : 32nd annual scientific meeting : Edinburgh, UK, http://dx.doi.org/10.1007/s10334-015-0490-7
  13. P. Basher, J. Mattiello and D. Lebihan, "Estimation of the Effective Self-Diffusion Tensor from the NMR Spin Echo", Journal of Magnetic Resonance, Series B, vol. 103, no. 3, pp. 247-254, 1994, http://dx.doi.org/10.1006/jmrb.1994.1037
  14. P. Kingsley, "Introduction to diffusion tensor imaging mathematics: Part II. Anisotropy, diffusion-weighting factors, and gradient encoding schemes", Concepts in Magnetic Resonance Part A, vol. 28, no. 2, pp. 123-154, 2006, http://dx.doi.org/10.1002/cmr.a.20049
  15. A. Krzyżak and K. Borkowski, "Theoretical analysis of phantom rotations in BSD-DTI" in Engineering in Medicine and Biology Society (EMBC), 2015 37th Annual International Conference of the IEEE, vol., no., pp.410-413, 25-29 Aug. 2015, http://dx.doi.org/10.1109/EMBC.2015.7318386
  16. K. Kłodowski and A. Krzyżak, "Innovative anisotropic phantoms for calibration of diffusion tensor imaging sequences", Magnetic Resonance Imaging, vol. 34, no. 4, pp. 404-409, 2016, http://dx.doi.org/10.1016/j.mri.2015.12.010