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SUPPLEMENTARY MATERIAL: DIFFUSION TENSOR IMAGING, NEIGHBOURHOOD
TRACTOGRAPHY, AND ACQUISITION METHODS AND IMAGE PROCESSING.
1. Diffusion tensor imaging
The diffusion of water molecules in the brain depends on the characteristics of the
surrounding tissue. In both cerebrospinal fluid and grey matter, diffusion is equal in all
directions (isotropic). Because water molecules move more freely in fluids, the magnitude (or
radius) of this isotropic diffusion is greater in cerebrospinal fluid than in grey matter. In white
matter, although the overall magnitude of diffusion is equal to grey matter, diffusion is
anisotropic: greater parallel to the direction of axons than perpendicular to the fibres.
Diffusion Tensor Imaging (DTI) measures the magnitude of this anisotropy, which is typically
quantified by fractional anisotropy (FA) on a voxel-wise basis. Although it is unclear whether
FA or any other measure resulting from DTI reflects the extent of myelination, the coherence
of fibre orientation or the number of axons, it is nevertheless assumed to provide a measure
of WM integrity in general1.
FA can be used to make comparisons of white matter integrity between populations.
These comparisons can be made in a whole brain, voxel-based manner or by applying a
region-of-interest (ROI) method. Considering the long, thin shape of white matter tracts the
ROI approach has to cope with substantial partial volume effects, whereas whole-brain
voxel-wise comparisons do not take into account individual differences in tract morphology.
However, by segmenting the complete tracts in each individual brain using a method called
tractography, these anatomical differences can be taken into account; and because only the
voxels within the tracts are analysed, partial volume effects are minimised.
2. Neighbourhood tractography
In tractography, tracts are segmented by starting at a 'seed point' with streamlines fitted
through consecutive voxels. However, the topography of the tracts resulting from
tractography is highly dependent on the seed location. Therefore, a method has been
developed whereby tracts can be selected a posteriori from a set of 'candidate tracts'. This
method is referred to as 'neighbourhood tractography'2.
In this method, a data-independent reference tract is first identified, as is described in
detail by Muñoz Maniega et al.3. Briefly, the region of the tract of interest is segmented by
hand from the standard brain by referring to a white matter atlas4. This region is then
resampled to the resolution of the data, binarised, smoothed with a 2 mm Gaussian kernel
and skeletonised. Second, the seed points selected in the reference tracts are transferred
from standard MNI space to each individual's native space; and grown into a 7 x 7 x 7
neighbourhood, resulting in 343 'candidate' seed points per hemisphere. Third, the candidate
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tracts are generated from the candidate seeds and automatically compared to the reference
tract, using an algorithm designed for this purpose2. The candidate tract that best matches
the reference tract in terms of length and shape is selected. Finally, the best-match tracts
are checked by eye blind to genotype group, and those that are truncated, branched or
deviate from the expected anatomical structure are discarded. For the remaining tracts,
mean FA values can be calculated which can be compared between samples.
3. Acquisition methods, image processing and ATR segmentation
For the present study, MRI data were collected on a GE Signa 1.5 T (General Electric
Milwaukee, WI, USA) clinical scanner equipped with a self-shielding gradient set (22mT/m
maximum gradient strength) and manufacturer-supplied 'birdcage' quadrature head coil.
Whole brain DTI data were acquired for each subject using a single-shot pulsed gradient
spin-echo echo-planar imaging (EPI) sequence with diffusion gradients (b = 1000 s/mm²)
applied in 51 non-collinear directions, and 3 T2-weighted EPI baseline scans. Forty-eight 2.8
mm contiguous axial slices were acquired with a field-of-view of 220 x 220 mm (TR=17 s,
TE=93.4ms and matrix= 96 x 96, zero-filled to 128 x 128).
The imaging data were pre-processed using the FSL toolbox (FMRIB, Oxford, UK).
The imaging data were corrected for eddy current induced distortions and bulk motion
effects by registering all EPI volumes to the first T2-weighted EPI volume. The brain was
extracted and FA maps were calculated by fitting the diffusion data to a tensor model with
DTIFIT (FMRIB, Oxford, UK).
The left and right ATR were identified and segmented in each subject using
neighbourhood tractography, as described above. The MNI coordinates of the seed points
selected in the reference tract were (-19, 19,-3) mm and (17, 19, 0) mm, for left and right
ATR respectively. The candidate tracts were generated using the BEDPOST/ProbTrack
algorithm5.The means of the FA values within the selected tracts were weighted according to
the likelihood of connection between the voxel and the seed point as given by ProbTrack.
Figure 2 depicts two examples of left ATRs resulting from the tractography.
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References
1. Kubicki, M, McCarley, R, Westin, C, Park, H, Maier, S, Kikinis, R, Jolesz, FA, Shenton, ME. A
review of diffusion tensor imaging studies in schizophrenia. J Psychiatr Res 2007; 41:15-30.
2. Clayden, JD, Bastin, ME, Storkey, AJ.Improved segmentation reproducibility in group
tractography using a quantitative tract similarity measure. NeuroImage 2006; 33:482-492.
3. Muñoz Maniega S., Bastin M., McIntosh A., Lawrie S. & Clayden J. Atlasbased reference tracts
improve automatic white matter segmentation with neighbourhood tractography. In Proceedings
of the ISMRM 16th Scientific Meeting & Exhibition. International Society for Magnetic Resonance
in Medicine 2008; pp. 3318.
4. Mori, S, Wakana, S, Nagae-Poetscher, L, van Zijl, P. MRI atlas of human white matter. Elsevier:
Amsterdam, The Netherlands 2005.
5. Behrens, TEJ, Johansen-Berg, H, Woolrich, MW, Smith, SM, Wheeler-Kingshott, CAM, Boulby,
PA, Barker, GJ, Sillery, EL, Sheehan, K, Ciccarelli, O, Thompson, AJ, Brady, JM, Matthews, PM.
Non-invasive mapping of connections between human thalamus and cortex using diffusion
imaging. Nature Neurosci. 2003; 6:750-757.
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Figure Legend:
Figure 2. Examples of left ATR tracts successfully obtained with tractography in an individual
with the CC genotype (left) and a carrier of the T-allele (right) of NRG8SNP243177