Development of voxel-based optimization diffusion kurtosis imaging (DKI) and comparison with conventional DKI

The aims of this study were to implement voxel-based optimization diffusion kurtosis imaging (DKI) and evaluate the accuracy of the method for the analysis of diffusion imaging data in comparison with conventional DKI. Conventional DKI and voxel-based optimization DKI were tested on a phantom and a human in a 1.5 T whole-body scanner. The differences in the diffusion coefficient (D) and diffusion kurtosis (K) values were analyzed using the Mann-Whitney U test, and the Holm correction was applied to the statistical analyses. In the phantom study, the D value resulting from voxel-based optimization DKI was significantly lower than those from conventional DKI in water and agarose solutions at concentrations of 50 and 100 g/L (all p < 0.01). Moreover, the K value was significantly lower in the water and agarose solutions at concentrations of 50, 100, and 200 g/L (all p < 0.01). In the human study, the D value resulting from voxel-based optimization DKI was significantly lower than that of conventional DKI in both white matter (WM), and gray matter (GM) (all p < 0.01). Moreover, the K value was significantly lower in cerebrospinal fluid, WM, and GM (all p < 0.01). To correctly measure the DKI, the optimized b values for each voxel must be used. Voxel-based optimization DKI is a method that optimizes the b values for each voxel. It appears that voxel-based optimization DKI improves the accuracy of the K value for biological tissues.