Objective To observe the characteristics of magnetic resonance diffusion tensor imaging（MR-DTI）for optic nerves and optic radiation in blind patients.Methods The optic nerves and optic radiation of 20 blind patients（blind group）and 20 controls（control group） were scanned by MR-DTI. Fractional anisotropy (FA) and directional encoded color (DEC) maps were acquired through postprocessing with the aid of volumeone 1.72 software. The signal intensity of optic nerves and optic radiation were then observed. The FA, mean diffusivity (MD), lambda;∥ and lambda;perp; value of bilateral optic nerves and optic radiation in two groups were measured in the DEC maps.Results While the high signal intensity was found in bilateral optic nerves in FA and DEC maps in control group，the signal decreased markedly in the blind group. The FA and lambda;∥ value of optic nerves in the blind group were declined obviously compared to that in the control group. The difference was statistically significant (t=16.294, 14.660;P=0.000). The MD and lambda;perp; value of optic nerves in the blind group were increased obviously compared to that in the control group, the difference was also statistically significant (t=8.096, 8.538; P=0.000). The high signal intensity was found in bilateral optic radiation in FA and DEC maps in both the blind and control groups. There were no statistic differences in FA and MD value in bilateral optic radiation between the blind and control groups (Left：t=1.456，1.811；P=0.152，0.076. Right：t=0.779，0.073；P=0.440，0.942). Conclusion A low signal intensity of bilateral optic nerves and a high signal intensity of bilateral optic radiation were found in blind patients.
Constrained spherical deconvolution can quantify white matter fiber orientation distribution information from diffusion magnetic resonance imaging data. But this method is only applicable to single shell diffusion magnetic resonance imaging data and will provide wrong fiber orientation information in white matter tissue which contains isotropic diffusion signals. To solve these problems, this paper proposes a constrained spherical deconvolution method based on multi-model response function. Multi-shell data can improve the stability of fiber orientation, and multi-model response function can attenuate isotropic diffusion signals in white matter, providing more accurate fiber orientation information. Synthetic data and real brain data from public database were used to verify the effectiveness of this algorithm. The results demonstrate that the proposed algorithm can attenuate isotropic diffusion signals in white matter and overcome the influence of partial volume effect on fiber direction estimation, thus estimate fiber direction more accurately. The reconstructed fiber direction distribution is stable, the false peaks are less, and the recognition ability of cross fiber is stronger, which lays a foundation for the further research of fiber bundle tracking technology.