Effect of increasing diffusion gradient direction number on diffusion tensor imaging fiber tracking in the human brain.
OBJECTIVE
To assess the effects of varying the number of diffusion gradient directions (NDGDs) on diffusion tensor fiber tracking (FT) in human brain white matter using tract characteristics.


METHODS
Twelve normal volunteers underwent diffusion tensor imaging (DTI) scanning with NDGDs of 6, 11, 15, 21, and 31 orientations. Three fiber tract groups, including the splenium of the corpus callosum (CC), the entire CC, and the full brain tract, were reconstructed by deterministic DTI-FT. Tract architecture was first qualitatively evaluated by visual observation. Six quantitative tract characteristics, including the number of fibers (NF), average length (AL), fractional anisotropy (FA), relative anisotropy (RA), mean diffusivity (MD), and volume ratio (VR) were measured for the splenium of the CC at the tract branch level, for the entire CC at tract level, and for the full brain tract at the whole brain level. Visual results and those of NF, AL, FA, RA, MD, and VR were compared among the five different NDGDs.


RESULTS
The DTI-FT with NDGD of 11, 15, 21, and 31 orientations gave better tracking results compared with NDGD of 6 after the visual evaluation. NF, FA, RA, MD, and VR values with NDGD of six were significantly greater (smallest p = 0.001 to largest p = 0.042) than those with four other NDGDs (11, 15, 21, or 31 orientations), whereas AL measured with NDGD of six was significantly smaller (smallest p = 0.001 to largest p = 0.041) than with four other NDGDs (11, 15, 21, or 31 orientations). No significant differences were observed in the results among the four NDGD groups of 11, 15, 21, and 31 directions (smallest p = 0.059 to largest p = 1.000).


CONCLUSIONS
The main fiber tracts were detected with NDGD of six orientations; however, the use of larger NDGD (≥ 11 orientations) could provide improved tract characteristics at the expense of longer scanning time.
School of Optical-Electrical and Computer Engineering, Shanghai Medical Instrument College, University of Shanghai for Science and Technology, Shanghai 200093, China.
Xufeng
X
Yao
Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China.
Tonggang
T
Yu
School of Optical-Electrical and Computer Engineering, Shanghai Medical Instrument College, University of Shanghai for Science and Technology, Shanghai 200093, China.
Beibei
B
Liang
School of Optical-Electrical and Computer Engineering, Shanghai Medical Instrument College, University of Shanghai for Science and Technology, Shanghai 200093, China.
Tian
T
Xia
School of Optical-Electrical and Computer Engineering, Shanghai Medical Instrument College, University of Shanghai for Science and Technology, Shanghai 200093, China.
Qinming
Q
Huang
School of Optical-Electrical and Computer Engineering, Shanghai Medical Instrument College, University of Shanghai for Science and Technology, Shanghai 200093, China.
Songlin
S
Zhuang
D000328:Adult; D016880:Anisotropy; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D011859:Radiography; D066127:White Matter / Q000000981:diagnostic imaging*; D055815:Young Adult
Diffusion tensor imaging; Fiber tracking; Number of diffusion gradient directions; Tract characteristics