TITLE:
The effect of different number of diffusion gradients on SNR of diffusion tensor-derived measurement maps
AUTHORS:
Na Zhang, Zhen-Sheng Deng, Fang Wang, Xiao-Yi Wang
KEYWORDS:
Diffusion Tensor Imaging, Diffusion Gradient, Signal Noise Ratio, Estimating Variance
JOURNAL NAME:
Journal of Biomedical Science and Engineering,
Vol.2 No.2,
April
2,
2009
ABSTRACT: Diffusion tensor imaging (DTI) is mainly applied to white matter fiber tracking in human brain, but there is still a debate on how many diffusion gradient directions should be used to get the best results. In this paper, the performance of 7 protocols corresponding to 6, 9, 12, 15, 20, 25, and 30 noncollinear number of diffusion gradi-ent directions (NDGD) were discussed by com-paring signal-noise ratio (SNR) of tensor- de-rived measurement maps and fractional ani-sotropy (FA) values.
All DTI data (eight healthy volunteers) were downloaded from the website of Johns Hopkins Medical Institute Laboratory of Brain Anatomi-cal MRI with permission. FA, apparent diffusion constant mean (ADC-mean), the largest eigen-value (LEV), and eigenvector orientation (EVO) maps associated with LEV of all subjects were calculated derived from tensor in the 7 proto-cols via DTI Studio. A method to estimate the variance was presented to calculate SNR of these tensor-derived maps. Mean ± standard deviation of the SNR and FA values within re-gion of interest (ROI) selected in the white mat-ter were compared among the 7 protocols.
The SNR were improved significantly with NDGD increasing from 6 to 20 (P<0.05). From 20 to 30, SNR were improved significantly for LEV and EVO maps (P<0.05), but no significant dif-ferences for FA and ADC-mean maps (P>0.05). There were no significant variances in FA val-ues within ROI between any two protocols (P> 0.05).
The SNR could be improved with NDGD in-creasing, but an optimum protocol is needed because of clinical limitations.