Dopper, et al. 1
Appendix e-1
Structural and functional brain connectivity in presymptomatic familial frontotemporal dementia
Elise G.P. Dopper,Serge A.R.B. Rombouts, PhD, Lize C. Jiskoot, MSc, Tom den Heijer, MD PhD,J. Roos A. de Graaf, Inge de Koning, PhD, Anke R. Hammerschlag, MSc, Harro Seelaar, PhD, William W. Seeley, MD PhD, Ilya M. Veer, MSc, Mark A. van Buchem, MD PhD, Patrizia Rizzu, PhD, John C. van Swieten, MD PhD
Methods
Image acquisition
T1-weighted images were acquired using the following scanning parameters: repetition time (TR)=9.8ms, echo time (TE)=4.6ms, flip angle=8°, 140 slices, voxel size=0.88x0.88x1.20mm. DTI was performed by means of single-shot echo planar images with gradients applied along 60 non-collinear directions (TR=8250ms, TE=80ms, flip angle=90°, 70 axial slices, voxel size=2x2x2mm, total scan time=9 minutes). For resting-state fMRI T2*-weighted images were acquired using whole brain multislice gradient echo planar imaging: 200 volumes, TR=2200ms, TE=30ms, flip angle=80°, 38 axial slices, voxel size=2.75x2.75x2.72mm + 10% interslice gap, total scan time=8 minutes. Participants were instructed to lie still with their eyes closed and not to fall asleep. Finally, for registration purposes a high-resolution echo planar imaging scan (TR=2200ms, TE=30ms, flip angle=80°, 84 slices, voxel size=1.96x1.96x2.00mm) was acquired.
Imaging analysis
For VBM analyses T1-weighted images were brain-extracted,e22 tissue-type segmented,e23aligned to MNI-152 (T1 standard brain averaged over 152 subjects; Montreal Neurological Institute, Montreal, QC, Canada) standard space,e24-25 and nonlinearly registered to each other.e26-27 A study-specific template was created and native grey matter images were non-linearly re-registered to this template. The registered partial volume images were modulated to correct for local expansion or contraction by dividing by the Jacobian of the warp field. These images were smoothed with an isotropic Gaussian kernel with a sigma of 3 mm.e28-29
DTI scans were corrected for movement and eddy currents correction by aligning images to the b0 volume using FMRIB Diffusion Toolbox. The diffusion tensor model was fitted at each voxel using DTIFIT to create fractional anisotropy (FA) images. These image were subsequently brain-extracted.e22 Voxelwise statistical analysis of the FA data was carried out using tract-based spatial statistics.e30 All FA images were nonlinearly aligned to MNI-152 standard space, using the most representative “target” image.e26-27 The mean FA image was created from these individual FA images, which was thinned to create a mean FA skeleton, representing the centres of all white matter tracts common to the group. Individual FA data were then projected onto this skeleton, resulting in skeletonised FA data for each subject, which were fed into voxelwise statistics. Applying spatial transformation parameters that were estimated in the FA analysis similar analyses were run on mean (MD), axial (DA) and radial (DR) diffusivity images.
The following pre-processing steps were applied to resting-state fMRI scans: motion correction using MCFLIRT,e24 removal of non-brain structures,e22 spatial smoothing using a Gaussian kernel of 6 mm full-width at half-maximum, grand-mean intensity normalization of the entire 4D dataset by a single multiplicative factor, and high pass temporal filtering (0.01Hz cut-off). The fMRI volumes were registered to the individual’s high resolution echo planar images, which were registered to the corresponding T1-weighted images, which in turn were registered to MNI-152 standard space images and subsequently registration matrices were combined to transfer fMRI results to MNI space.e24-25