Optimal strategies for measuring diffusion in anisotropic systems by magnetic resonance imaging

The optimization of acquisition parameters for precise measurement of diffusion in anisotropic systems is described. First, an algorithm is presented that minimizes the bias inherent in making measurements with a fixed set of gradient vector directions by spreading out measurements in 3‐dimensional gradient vector space. Next, it is shown how the set of b—matrices and echo time can be optimized for estimating the diffusion tensor and its scalar invariants. The standard deviation in the estimate of the tensor trace in a water phantom was reduced by more than 40% and the artefactual anisotropy was reduced by more than 60% when using the optimized scheme compared with a more conventional scheme for the same scan time, and marked improvements are demonstrated in the human brain with the optimized sequences. Use of these optimal schemes results in reduced scan times, increased precision, or improved resolution in diffusion tensor images. Magn Reson Med 42:515–525, 1999. © 1999 Wiley‐Liss, Inc.

[1]  J. E. Tanner,et al.  Spin diffusion measurements : spin echoes in the presence of a time-dependent field gradient , 1965 .

[2]  P. R. Bevington,et al.  Data Reduction and Error Analysis for the Physical Sciences , 1969 .

[3]  Z H Cho,et al.  An improved nuclear magnetic resonance diffusion coefficient imaging method using an optimized pulse sequence. , 1986, Medical physics.

[4]  Bruce R. Rosen,et al.  MR Diffusion Imaging of the Human Brain , 1990, Journal of computer assisted tomography.

[5]  O Nalcioglu,et al.  A modified pulse sequence for in vivo diffusion imaging with reduced motion artifacts , 1991, Magnetic resonance in medicine.

[6]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[7]  N. Reo,et al.  A nuclear magnetic resonance investigation of the upper airways in ferrets. ii. contrast‐enhanced imaging to distinguish vascular from other nasal fluids , 1992, Magnetic resonance in medicine.

[8]  P. R. Bevington,et al.  Data Reduction and Error Analysis for the Physical Sciences, 2nd ed. , 1993 .

[9]  P. Basser,et al.  MR diffusion tensor spectroscopy and imaging. , 1994, Biophysical journal.

[10]  A. Song,et al.  Optimized isotropic diffusion weighting , 1995, Magnetic resonance in medicine.

[11]  M. Eis,et al.  Correction of Gradient Crosstalk and Optimization of Measurement Parameters in Diffusion MR Imaging , 1995 .

[12]  T E Conturo,et al.  Diffusion MRI: Precision, accuracy and flow effects , 1995, NMR in biomedicine.

[13]  P. V. van Zijl,et al.  Diffusion Weighting by the Trace of the Diffusion Tensor within a Single Scan , 1995, Magnetic resonance in medicine.

[14]  P. Basser,et al.  Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. , 1996, Journal of magnetic resonance. Series B.

[15]  P. Basser,et al.  Toward a quantitative assessment of diffusion anisotropy , 1996, Magnetic resonance in medicine.

[16]  E. Akbudak,et al.  Encoding of anisotropic diffusion with tetrahedral gradients: A general mathematical diffusion formalism and experimental results , 1996, Magnetic resonance in medicine.

[17]  D. Gadian,et al.  Optimisation of experimental parameters for diffusion-weighted single-shot trace measurement , 1997 .

[18]  A. Mackay,et al.  In vivo measurement of T2 distributions and water contents in normal human brain , 1997, Magnetic resonance in medicine.

[19]  T. A. Carpenter,et al.  Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. , 1997, Magnetic resonance imaging.

[20]  D L Hill,et al.  Automated three-dimensional registration of magnetic resonance and positron emission tomography brain images by multiresolution optimization of voxel similarity measures. , 1997, Medical physics.

[21]  D G Gadian,et al.  Correction for eddy current induced Bo shifts in diffusion‐weighted echo‐planar imaging , 1999, Magnetic resonance in medicine.