American Journal of Neuroradiology 27:1776-1781, September 2006
© 2006 American Society of Neuroradiology
BRAIN
Effects of Number of Diffusion Gradient Directions on Derived Diffusion Tensor Imaging Indices in Human Brain
a Department of Radiology, University of Rochester Medical Center, Rochester, NY
b Department of Neurology, University of Rochester Medical Center, Rochester, NY
c Department of Biomedical Engineering, University of Rochester Medical Center, Rochester, NY
Address correspondence to Jianhui Zhong, PhD, 601 Elmwood Ave, Box 648, University of Rochester Medical Center, Rochester, NY 14642-8648; e-mail: jianhui.zhong{at}rochester.edu
BACKGROUND AND PURPOSE: The effects of a number of diffusion-encoding gradient directions (NDGD) on diffusion tensor imaging (DTI) indices have been studied previously with theoretic analysis and numeric simulations. In this study, we made in vivo measurements in the human brain to compare different clinical scan protocols and to evaluate their effects on the calculated DTI indices.
METHODS: Fifteen healthy volunteers were scanned with a 1.5T MR scanner. Single-shot DTI images were acquired using 3 protocols different in NDGD and number of excitations (NEX) for each direction (NDGD/NEX = 6/10, 21/3, 31/2). Means and standard error of mean (SEM) were calculated and compared in 6 regions of interest (ROIs) for mean diffusivity (
D
), fractional anisotropy (FA), diffusion tensor eigenvalues (
1, 2, and 3), and correlation coefficients (r) of these indices among the 3 DTI protocols.
RESULTS: At the ROI level, no significant differences were found for the mean and SEM of D and FA among protocols (P > .05). The 6-NDGD protocol, however, yielded higher values for 1 and 2 and lower values for 3 in most ROIs (P < .05) compared with the other protocols. At the voxel level, the correlation between the protocols r21–31 were higher than r6–21 and r6–31 in most ROIs. The correlation of FA among 3 protocols also increased with increasing anisotropy.
CONCLUSION: For ROI analyses, different NDGDs lead to similar values of FA and D but different eigenvalues. However, different NDGDs at the voxel level provide varying values. The selection of the NDGD, therefore, should depend on the focus of different DTI applications.
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