Diffusion Tensor Imaging

Xiaohong Joe Zhou1, Keith R. Thulborn2

1 M.D. Anderson Cancer Center, Houston, Texas, 2 University of Illinois at Chicago, Chicago, Illinois
Publication Name:  Current Protocols in Magnetic Resonance Imaging
Unit Number:  Unit A6.4
DOI:  10.1002/0471142719.mia0604s11
Online Posting Date:  February, 2004
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Abstract

This unit provides step-by-step instructions on how to perform diffusion tensor imaging (DTI) in a clinical setting. A brief introduction on DTI techniques and current clinical applications is also presented. Additional technical details, practical considerations, and anticipated results are discussed in a commentary section.

     
 
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Table of Contents

  • Basic Protocol
  • Commentary
  • Literature Cited
  • Figures
  • Tables
     
 
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Materials

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Figures

  •  FigureFigure A6.4.1 Interleaved slice acquisition scheme to produce a pseudo 3-D data set. At least two sets of transverse slices are required. The second set of slices (solid gray areas) are centered at the gaps (hatched areas) between the first set of slices (solid gray areas).
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  •  FigureFigure A6.4.2 Diffusion ellipsoid in a laboratory reference frame. The lengths of the diffusion ellipsoid axes (D1, D2, and D3) correspond to the eigenvalues given by Equation A6.4.2. The directions of the axes correspond to eigenvectors (1, 2, and 3). The largest eigenvalue, D1, is known as the principal diffusion coefficient, and its eigenvector, 1, points to the principal diffusion direction.
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  •  FigureFigure A6.4.3 When eddy current compensation or correction is sub-optimal, bright rims can be observed at the edge of the diffusion anisotropy map (A). With improved eddy current compensation or correction, this artifact can be effectively reduced (B).
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  •  FigureFigure A6.4.4 Two transverse diffusion tensor images based on fractional anisotropy from a patient with infiltrating glioblastoma multiforme (hollow arrows in both A and B). Both images were acquired on a GE 1.5 T scanner with a single-shot EPI pulse sequence using the protocol given by Table A6.4.4. The solid arrows in A and B show the external capsule and splenium, respectively.
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  •  FigureFigure A6.4.5 (A) A fractional anisotropy map from a patient with multiple sclerosis. (B) A color-coded fractional anisotropy map with red, green, and blue color representing fibers along the right/left, anterior/posterior, and superior/inferior directions, respectively. Regions with white-matter loss are indicated by the arrows. The images were acquired on a GE 3.0 T scanner with a single-shot EPI pulse sequence.
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Literature Cited

Literature Cited
    Arfken, G. 1970. Mathematical Methods for Physicists. Academic Press, New York.
    Basser, P.J. 1995. Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed. 8:333-344.
    Basser, P.J. and Pierpaoli, C. 1998. A simplified method to measure the diffusion tensor from seven MR images. Magn. Reson. Med. 39:928-934.
    Basser, P.J., Mattiello, J., and LeBihan, D. 1994. Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. B 103:247-254.
    Basser, P.J., Pajevic, S., Pierpaoli, C., Duda, J., and Aldroubi, A. 2000. In vivo fiber tractography using DT-MRI data. Magn. Reson. Med. 44:625-632.
    Buhl, E.H. and Lubke, L. 1989. Intracellular lucifer injection in fixed brain slices combined with retrograde tracing, light and electron microscopy. Neuroscience 28:3-16.
    Butts, K., Pauly, K.J., deCrespigny, A., and Moseley, M. 1996. Diffusion-weighted interleaved echo-planar imaging with a pair of orthogonal navigator echoes. Magn. Reson. Med. 35:763-770.
    Jezzard, P., Barnett, A.S., and Pierpaoli, C. 1998. Characterization of and correction for eddy current artifacts in echo planar diffusion imaging. Magn. Reson. Med. 39:801-812.
    Jones, D.K., Horsfield, M.A., and Simmons, A. 1999. Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging. Magn. Reson. Med. 42:515-525.
    Melhem, E.R., Mori, S., Mukundan, G., Kraut, M.A., Pomper, M.G., and van Zijl, P.C.M. 2002. Diffusion tensor MR imaging of the brain and white matter tractography. Am. J. Roentgenol. 178:3-16.
    Mori, S., Itoh, R., Zhang, J., Kaufmann, W.E., van Zijl, P.C., Solaiyappan, M., and Yarowsky, P. 2001. Diffusion tensor imaging of the developing mouse brain. Magn. Reson. Med. 46:18-23.
    Nauta, W.J.H. and Feirtag, M. 1996. Fundamental Neuroanatomy. W.H. Freeman Co., New York.
    Pajevic, S. and Pierpaoli, C. 1999. Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: Application to white matter fiber tract mapping in the human brain. Magn. Reson. Med. 42:526-540.
    Papadakis, N.G., Xing, D., Huang, C.L., Hall, L.D., and Carpenter, T.A. 1999. A comparative study of acquisition schemes for diffusion tensor imaging using MRI. J. Magn. Reson. 137:67-82.
    Pierpaoli, C. and Basser, P.J. 1996. Toward a quantitative assessment of diffusion anisotropy. Magn. Reson. Med. 36:893-906.
    Pierpaoli, C., Jezzard, P., Basser, P.J., Barnett, A., and Di Chiro, G. 1996. Diffusion tensor MR imaging of the human brain. Radiology 201:637-648.
    Poonawalla, A., Karmonik, C., and Zhou, X.J. 2000. Optimization of b-value and gradient orientation for diffusion tensor MRI. Proc. Intl. Soc. Magn. Reson. Med. 8th Meeting 2:801.
    Shellock, F.G. 1996. Pocket Guide to MR Procedures and Metallic Objects. Lippincott-Raven, Philadelphia.
    Skare, S., Hedehus, M., Moseley, M.E., and Li, T.Q. 2000. Condition number as a measure of noise performance of diffusion tensor data acquisition schemes with MRI. J. Magn. Reson. 147:340-352.
    Sorensen, A.G., Buonanno, F.S., Gonzalez, R.G., Schwamm, L.H., Lev, M.H., Huang-Hellinger, F.R., Reese, T.G., Weisskoff, R.M., Davis, T.L., Suwanwela, N., Can, U., Moreira, J.A., Copen, W.A., Look, R.B., Finklestein, S.P., Rosen, B.R., and Koroshetz, W.J. 1996. Hyperacute stroke: Evaluation with combined multisection diffusion-weighted and hemodynamically weighted echo-planar MR imaging. Radiology 199:391-401.
    Thulborn, K.R. 1999. Clinical rationale for very-high-field (3.0 Tesla) functional magnetic resonance imaging. Top. Mag. Reson. Imaging 10:37-50.
    Ulug, A.M. and van Zijl, P.C. 1999. Orientation-independent diffusion imaging without tensor diagonalization: Anisotropy definitions based on physical attributes of the diffusion ellipsoid. J. Magn. Reson. Imaging 9:804-813.
    Weisskoff, R.M., Cohen, M.S., and Rzedzian, R.R. 1993. Nonaxial whole-body instant imaging. Magn. Reson. Med. 29:796-803.
    Woods, R.P., Mazziotta, J.C., and Cherry, S.R. 1993. MRI-PET registration with automated algorithm. J. Comput. Assist. Tomogr. 17:536-546.
    Xue, R., van Zijl, P.C., Crain, B.J., Solaiyappan, M., and Mori, S. 1999. In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn. Reson. Med. 42:1123-1127.
    Zhou, X. and Reynolds, H.G. 1997. Quantitative analysis of eddy current effects on diffusion-weighted EPI. Proc. Intl. Soc. Magn. Reson. Med. 5th Meeting 3:1722.
    Zhou, X.J., Leeds, N.E., Karmonik, C., and Mock, B.J. 2000. Magnetic resonance tractography for pre-surgical planning and post-surgical evaluation. Proc. Intl. Soc. Magn. Reson. Med. 8th Meeting 1:480.
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