title: Effects of number of diffusion gradient directions on derived diffusion tensor imaging indices in human brain.
abstract: OBJECTIVE
  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 (lambda(1), lambda(2), and lambda(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 lambda(1) and lambda(2) and lower values for lambda(3) in most ROIs (P < .05) compared with the other protocols. At the voxel level, the correlation between the protocols r(21-31) were higher than r(6-21) and r(6-31) in most ROIs. The correlation of FA among 3 protocols also increased with increasing anisotropy.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Radiology, University of Rochester Medical Center, Rochester, NY 14642, USA.
authors.forename: H
authors.initials: H
authors.lastname: Ni
authors.forename: V
authors.initials: V
authors.lastname: Kavcic
authors.forename: T
authors.initials: T
authors.lastname: Zhu
authors.forename: S
authors.initials: S
authors.lastname: Ekholm
authors.forename: J
authors.initials: J
authors.lastname: Zhong
mesh_terms: D000328:Adult; D016880:Anisotropy; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012680:Sensitivity and Specificity