Bias in Diffusion Tensor-Derived Quantities Depend on the Number of DWIs Composing the DT-MRI Dataset

Firouzeh Tannazi¹, Lindsay Walker¹, Michael Curry¹, Carlo Pierpaoli¹

In this study we investigate the effects of the number of images comprising the DTI data set on the statistical properties of diffusion tensor eigenvalues and anisotropy indices derived from them. The results of Monte Carlo simulations along with the analysis of phantom DTI data indicate an overall underestimation of Eig3 and an overestimation of FA and Eig1 as the number of images in DTI estimation is reduced.