Authors:

CORREIA, M.M., Newcombe,V., Williams, G.B.

Reference:

Year of publication:

2011

CBU number:

7306

Abstract:

Over the past 15years, diffusion-weighted MRI data has been used to measure the degree of diffusion anisotropy in different regions in both the healthy and the pathological brain. In this study we compared the performance of several different anisotropy indices in terms of their ability to differentiate between tissue types, using both simulated and experimental data. Simulations were performed for one-, two- and three-fibre populations. The results obtained suggest that only indices derived from tensors of rank higher than two, and indices derived from model free approaches can differentiate between an isotropic voxel and a population of three orthogonal fibres. Indices such as geodesic anisotropy (GeoA), generalised anisotropy (GA), and scaled entropy (SE) produce greater contrast-to-noise ratios than fractional anisotropy (FA) for simulated data and large anisotropy differences between brain regions. However, the biological scatter seen within brain regions is large enough to mask the expected differences between indices when looking at small anisotropy differences in the brain. The comparison of different acquisition schemes revealed that the use of multiple b-values seems to result in improved contrast-to-noise ratios for indices derived from the traditional diffusion tensor model.