Optimal Experimental Design for Diffusion Kurtosis Imaging

Diffusion Kurtosis Imaging (DKI) is a new magnetic resonance imaging model that describes the non-Gaussian diffusion behavior in tissues. It has recently been shown that DKI parameters, such as the radial or axial kurtosis, are more sensitive to brain physiology changes than the well known diffusion tensor imaging (DTI) parameters in several white and gray matter structures. In order to estimate either DTI or DKI parameters with maximum precision, the diffusion weighting gradient settings that are applied during the acquisition need to be optimized. Indeed, it has been shown previously that optimizing the set of diffusion weighting gradient settings can have a significant effect on the precision with which DTI parameters can be estimated. In this paper, we focus on the optimization of DKI gradients settings. Commonly, DKI data are acquired using a standard set of diffusion weighting gradients with fixed directions and with regularly spaced gradient strengths. In this work, we show tha...

• Type: Journal
• Year: 2010
• Where: TMI
• Authors: Dirk H. J. Poot, Arnold Jan den Dekker, Eric Achten, Marleen Verhoye, Jan Sijbers
• Keywords: Diffusion, Gradient, Gradient Settings, Management, TMI 2010