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Home arrow Computer Science arrow Computational Diffusion MRI: MICCAI Workshop, Athens, Greece, October 2016

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Materials and Methods

In this section, we first detail the diffusion MRI data acquisition, preprocessing and region of interest selection of the AD rats. We then give a brief overview of the methods we use and their metrics of interest. We detail the fractional anisotropy (FA) and mean diffusivity (MD) of classical DTI, the orientation dispersion index (ODI), neurite density index (NDI) and isotropic volume fraction (IsoVF) of the multi-compartment NODDI model, and finally the formulation of several q-space indices of the MAP-MRI functional basis. We estimated the DTI and MAP-MRI metrics using the diffusion imaging in python (dipy) open source software [12] and the NODDI metrics using the NODDI toolbox [3].

Processing of Transgenic Alzheimer Rat Data Sets

We use multi-shell dMRI data of three ex-vivo transgenic Alzheimer rats (line TgF344-AD) [10], also previously analyzed by Daianu et al. [8]. The rats were euthanized at 10, 15 and 24 months, fixed brains were prepared as described in [8], and scanned using a 7 Tesla Bruker Biospin MRI scanner at California Institute of Technology. A high-resolution fast low angle magnetic shot (FLASH) anatomical image with a mix of T1 and T2 weighting (375 x 224 x 160 matrix; voxel size: 0.08 x 0.08 x 0.08 mm3) was used. The diffusion MRI data were sampled on 5 shells with b-values {1000,3000,4000, 8000,12,000} s/mm2, all with the same 60 directions and 5 b0 measurements. Other parameters were 1/Л = 11/16 ms and TE/TR = 34/500 ms. The voxel dimensions were 0.15 x 0.15 x 0.25 mm3.

During preprocessing, extra-cerebral tissue was removed using the “skullstripping” Brain Extraction Tool from BrainSuite (http://brainsuite.org/), for both the anatomical images and the DWIs. We corrected for eddy current distortions using the “eddy correct FSL” tool (www.fmrib.ox.ac.uk/fsl) for which a gradient table was calculated to account for the distortions. As an image processing step, DWIs were up-sampled to the resolution of the anatomical images (with isotropic voxels) using FSL’s flirt function with 9 degrees of freedom; the gradient direction tables were rotated accordingly after each linear registration. For our study, we draw regions of interest (ROIs) in the cingulate cortex, hippocampus and corpus callosum as shown in Fig. 1.

 
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