Maria Eugenia Caligiuri1, Aldo Quattrone1,2, and Andrea Cherubini1
1Institute of Bioimaging and Molecular Physiology (IBFM), National Research Council, Catanzaro, Italy, 2Institute of Neurology, University Magna Graecia, Catanzaro, Italy
Diffusion-weighted MRI of the brain allows the
assessment of tissue integrity at the microscale. The most commonly used
technique to analyze diffusion-weighted data is diffusion tensor imaging (DTI),
which relies on the reconstruction of the diffusion tensor at each MRI voxel by
calculating its eigenvalues and eigenvectors. These quantities allow the
estimation of scalar DTI maps measuring mean diffusivity (MD) and fractional
anisotropy (FA), which are considered markers of structural tissue integrity. To
date, DTI has been extensively used in the field of neuroimaging to study brain
microstructural integrity in healthy subjects and patients with several
different neurological conditions. However, despite the three-dimensional
nature of the tensor, existing studies have focused on changes in DTI-derived
scalar indexes, such as MD and FA, not considering the orientation of the
principal eigenvector of the tensor, which could provide invaluable insight on
the nature of tissue changes, but is still only used for color-coding FA maps
for qualitative, visual purposes.
