Meeting Banner
Abstract #4488

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

1 Medical Physics, University of Wisconsin, Madison, Wisconsin, United States, 2 Waisman Laboratory for Brain Imaging and Behavior, Madison, Wisconsin, United States, 3 Radiology, University of Wisconsin, Madison, Wisconsin, United States

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.

This abstract and the presentation materials are available to members only; a login is required.

Join Here