Abstract
This work investigates the possibilities of applying high-angular-resolution-diffusion-imaging- (HARDI-) based methods in a clinical setting by investigating the performance of non-Gaussian diffusion probability density function (PDF) estimation for a range of b-values and diffusion gradient direction tables. It does so at realistic SNR levels achievable in limited time on a high-performance 3T system for the whole human brain in vivo. We use both computational simulations and in vivo brain scans to quantify the angular resolution of two selected reconstruction methods: Q-ball imaging and the diffusion orientation transform. We propose a new analytical solution to the ODF derived from the DOT. Both techniques are analytical decomposition approaches that require identical acquisition and modest postprocessing times and, given the proposed modifications of the DOT, can be analyzed in a similar fashion. We find that an optimal HARDI protocol given a stringent time constraint (<10 min) combines a moderate b-value (around 2000 s/mm2) with a relatively low number of acquired directions (>48). Our findings generalize to other methods and additional improvements in MR acquisition techniques.
Highlights
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a clinical medical imaging technique that provides a unique view on the structure of brain white matter in vivo
To get an indication on the optimal parameters for each simulated angle, we run a series of tests, where we determine the minimal angular error that can be obtained with the minimal combination of b-value b-value 1000 1500 2000 3000
The noise corrupts the reconstructed profiles, and modeling with high orders of spherical harmonics (SH) will result in capturing the noise, which is dominant in these cases
Summary
Diffusion-weighted magnetic resonance imaging (DW-MRI) is a clinical medical imaging technique that provides a unique view on the structure of brain white matter in vivo. Numerous advents in diffusion imaging technology have greatly augmented image quality unraveling new clinical applications. The debut of diffusion tensor imaging (DTI) and fiber tractography enabled a completely new, noninvasive view on white matter fibre bundles connecting gray matter neural populations, of increasing importance for cognitive neuroimaging applications. In DW-MRI, white matter fiber bundles are probed indirectly by measuring the directional specificity (anisotropy) of local water diffusion. Postprocessing of diffusion-weighted images is fundamentally aimed at calculating the probability density function (PDF) p(r), for this displacement of water molecules in each imaging voxel, where r is the 3D displacement vector.
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