21 Introduction Figure 8. Representation of A.) diffusion as an isotropic shape of the corresponding diffusion lengths (λ1, λ2, and λ3), the eigenvalues. B.) diffusion as an anisotropic shape of the corresponding eigenvalues C.) fibre tracking by using the different voxels. The white matter metrics from DTI, voxel-by-voxel, are mathematically based on 3 mutually perpendicular eigenvectors, whose magnitude is given by 3 corresponding eigenvalues sorted in order of decreasing magnitude as ʎ1, ʎ2 and ʎ3. An ellipsoid is created by the long axis of ʎ1, and the small axes ʎ2 and ʎ3, from where the measured length of the three axes are the eigenvalues. DTI describes the magnitude, the degree and orientation of diffusion anisotropy. These eigenvalues are used to generate quantitative maps of fractional anisotropy (FA), the derivation of axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD). FA represents the amount of diffusional asymmetry in a voxel, which is presented from 0 (infinite isotropy) to 1 (infinite anisotropy). AD stands for the diffusivity along the neural tract: ʎ1. The diffusivity of the minor axes, ʎ2 and ʎ3, is called the perpendicular or radial diffusivity. The mean of these diffusivity ʎ1, ʎ2 and ʎ3 is known as MD. FA, MD, AD and RD are used as indirect markers of white matter microstructure of these young patients.93 To summarize, DTI maps the course of the neural axon bundles in the brain. With DTI we obtain a sufficient number of gradient directions to determine the tensor components per voxel. We determine eigenvalues and eigenvectors which indicate the major and minor directions of the diffusion movement down the axonal bundles. This measurement of diffusion of water in tissue could be used to investigate the microarchitecture of the white matter of the brain and produce white matter tracts. 1
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