Computational protocol: White matter alterations related to attention-deficit hyperactivity disorder and COMT val158met polymorphism: children with valine homozygote attention-deficit hyperactivity disorder have altered white matter connectivity in the right cingulum (cingulate gyrus)

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Protocol publication

[…] The Oxford Center for Functional Magnetic Resonance Imaging of the Brain Statistical Library (FMRIB Software Library [FSL 4.1.4], was used in the image analyses and tensor calculations. The imaging data were processed in the following manner. The diffusion images were corrected for the distortion, induced by gradient coils and simple head motion, using the eddy current correction routine within FSL. First, the FA images were created by fitting a tensor model to the raw diffusion data, and then FSL’s Brain Extraction Tool was used to remove non-brain tissue from the image. The diffusion tensor was then calculated using FSL DTIFIT for whole brain volumes, and the resulting FA maps together with the AD (λ1) and RD ([λ2 + λ3]/2) maps were used in subsequent tract-based spatial statistics (TBSS) analysis.Voxelwise statistical analyses of the FA data were performed using TBSS. Each individual FA map was projected onto the common FA skeleton to obtain the individual FA skeleton, on which a voxelwise analysis was performed to examine the population differences. All the subjects’ FA data were then aligned into a common space (ie, normalized into the 1 mm ×1 mm ×1 mm Montreal Neurological Institute MNI152 standardized space) using the FMRIB’s Non-Linear Image Registration Tool,, which uses a b-spline representation of the registration warp field. This combined transformation was applied to all the parametric maps (FA, AD, MD, and RD). Next, the mean FA image was created and thinned to create a mean FA skeleton that represents the centers of all tracts common to the group. Each subject’s aligned FA data were then projected onto this skeleton, and the resulting data were fed into voxelwise cross-subject statistics. The FA threshold was then set at 0.2 (TBSS default), in order to confine the analysis to WM. Voxelwise permutation-based nonparametric inference was performed on skeletonized FA data, using FSL Randomize Version 2.1. We performed a multiple comparison correction using threshold-free cluster enhancement, which allowed us to avoid making an arbitrary choice of the cluster-forming threshold, while preserving the sensitivity benefits of clusterwise correction. To compare trace, AD, and RD, we used FSL using the FA images to achieve nonlinear registration and skeletonization stages and also to estimate the projection vectors from each individual subject onto the mean FA skeleton. The nonlinear warps and skeleton projection can then also be applied to other images.All extracted skeletons were overlaid with the John Hopkins University DTI-based probabilistic tractography atlas. Averaged DTI indices were then calculated for each atlas region. […]

Pipeline specifications

Software tools FSL, BET
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens
Chemicals Methionine