Optimization of a Fast Diffusion Estimation Two-Compartment Model for Diffusion Tensor Imaging
Andrew R. Hoy 1,2 , Chen Guan Koay 1 , Steven R. Kecskemeti 2,3 , and Andrew L. Alexander 1,2
Medical Physics, University of Wisconsin,
Madison, Wisconsin, United States,
Laboratory for Brain Imaging and Behavior, Madison,
Wisconsin, United States,
University of Wisconsin, Madison, Wisconsin, United
Diffusion tensor imaging yields information about tissue
microstructure. However, when a single voxel contains
tissue and free water, DTI is not appropriate. A
two-tensor fast diffusion estimation model has been
proposed to correct this shortcoming. This model was
implemented in a novel manner, and the acquisition
parameters optimized through Monte Carlo simulations.
The optimal acquisition with 68 diffusion-weighted
encoded images had three diffusion-weighted shells
(b-value in s/mm2 x number of directions) of 200x12,
650x40, 1500x12. This was confirmed in vivo. The model
is useful for tissues adjacent to CSF and removing
artifacts from CSF blurring and ghosting.
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