PURPOSE: To prospectively quantify differences in age-related changes in the diffusivity parameters and fiber characteristics between association, callosal, and projection fibers. MATERIALS AND METHODS: This study was approved by the institutional review board, and informed consent was obtained. Diffusion-tensor imaging data with an isotropic voxel size of 1.9 mm(3) were acquired at 3 T in 38 healthy volunteers (age range, 18-88 years; 18 women). Quantitative fiber tracking was used to calculate fractional anisotropy (FA) and mean diffusivity values, eigenvalues (lambda(1), lambda(2), and lambda(3)), the number of fiber projections, and the number of fiber projections per voxel for three-dimensional reconstructed association, callosal, projection, and total brain fibers. Bivariate linear regression models were used to analyze correlations. Significant differences between correlations were assessed with the Hotelling-Williams test. RESULTS: For FA, the strongest degradation in association fibers and no significant changes in projection fibers were observed. The difference in correlation was significant (P = .002). The number of fiber projections and the number of fiber projections per voxel showed strong to moderate negative correlations that were dependent on age (P < .001) in the three fiber structures and total brain fibers, with the exception of the number of fiber projections per voxel in projection fibers, which showed no significant correlation. The decrease in the number of fiber projections was significantly greater (P = .043) in projection fibers than in total brain fibers, whereas the decrease in the number of fiber projections per voxel was significantly weaker (P = .005). Association fibers showed the largest changes per decade of age for FA (-1.13%) and for the number of fiber projections per voxel (-4.7%), whereas callosal fibers showed the largest changes per decade of age for the number of fiber projections (-10.4%). CONCLUSION: Quantitative fiber tracking enables identification of differences in diffusivity and fiber characteristics due to normal aging.
PURPOSE: To prospectively quantify differences in age-related changes in the diffusivity parameters and fiber characteristics between association, callosal, and projection fibers. MATERIALS AND METHODS: This study was approved by the institutional review board, and informed consent was obtained. Diffusion-tensor imaging data with an isotropic voxel size of 1.9 mm(3) were acquired at 3 T in 38 healthy volunteers (age range, 18-88 years; 18 women). Quantitative fiber tracking was used to calculate fractional anisotropy (FA) and mean diffusivity values, eigenvalues (lambda(1), lambda(2), and lambda(3)), the number of fiber projections, and the number of fiber projections per voxel for three-dimensional reconstructed association, callosal, projection, and total brain fibers. Bivariate linear regression models were used to analyze correlations. Significant differences between correlations were assessed with the Hotelling-Williams test. RESULTS: For FA, the strongest degradation in association fibers and no significant changes in projection fibers were observed. The difference in correlation was significant (P = .002). The number of fiber projections and the number of fiber projections per voxel showed strong to moderate negative correlations that were dependent on age (P < .001) in the three fiber structures and total brain fibers, with the exception of the number of fiber projections per voxel in projection fibers, which showed no significant correlation. The decrease in the number of fiber projections was significantly greater (P = .043) in projection fibers than in total brain fibers, whereas the decrease in the number of fiber projections per voxel was significantly weaker (P = .005). Association fibers showed the largest changes per decade of age for FA (-1.13%) and for the number of fiber projections per voxel (-4.7%), whereas callosal fibers showed the largest changes per decade of age for the number of fiber projections (-10.4%). CONCLUSION: Quantitative fiber tracking enables identification of differences in diffusivity and fiber characteristics due to normal aging.
Authors: Mark E Bastin; Susana Muñoz Maniega; Karen J Ferguson; Laura J Brown; Joanna M Wardlaw; Alasdair M J MacLullich; Jonathan D Clayden Journal: Neuroimage Date: 2010-02-17 Impact factor: 6.556
Authors: Ilana J Bennett; David J Madden; Chandan J Vaidya; Darlene V Howard; James H Howard Journal: Hum Brain Mapp Date: 2010-03 Impact factor: 5.038
Authors: Khader M Hasan; Arash Kamali; Amal Iftikhar; Larry A Kramer; Andrew C Papanicolaou; Jack M Fletcher; Linda Ewing-Cobbs Journal: Brain Res Date: 2008-10-28 Impact factor: 3.252