Computational protocol: Alternations of White Matter Structural Networks in First Episode Untreated Major Depressive Disorder with Short Duration

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Protocol publication

[…] In this study, DTI data preprocessing and brain network were performed using the PANDA toolbox () which was an integration analysis toolbox comprising the Diffusion Toolkit (), FMRIB Software Library (), MRIcron (), and Pipeline System for Octave and Matlab (PSOM) (). And the whole process had been described in detail previously (). [...] Briefly, the preprocessing procedure included skull-stripping, eddy-current, and head-motion correction, FA calculation and whole-brain deterministic DTI fiber tractography (). First, the non-brain tissues of the images were deleted by employing the brain extraction tool (). Second, the head motion and eddy current distortions were corrected through registering the DW images to the b0 image with an affine transformation (). After correction, six elements of the diffusion tensor were then estimated from which FA was calculated. Then, Whole-brain fiber tractography was subsequently reconstructed by seeding at every voxel in the brain and using fiber assignment by continuous tracking algorithm (). This algorithm computes fiber trajectories starting from the deep WM regions and terminating at a voxel with a turning angle greater than 45° or reached a voxel with FA less than 0.15.As the construction of the structural network requires the following basic elements: nodes and edges, we adopted the same procedures used in previous WM network studies to define network nodes and edges. [...] In this study, we parcellated the cerebral cortex into 90 cortical and subcortical regions (45 for each hemisphere, see Table S1 in Supplementary Material), using the Automated Anatomical Labeling (AAL) template. And each region representing a node of the cortical network (). For each participant, the parcelation process must be conducted in the native DTI space. To achieve this, the individual 3D T1-weighted images were coregistered to the b0 images in the DTI native space. The transformed 3D T1-weighted images were then nonlinearly transformed to the ICBM152 T1 template in the Montreal Neurological Institute (MNI) space. Inverse transformations were used to warp the AAL atlas from the MNI space to the DTI native space (). […]

Pipeline specifications

Software tools PANDA, DTK, FSL, MRIcron, BET, AAL
Applications Magnetic resonance imaging, Diffusion magnetic resonance imaging analysis
Organisms Homo sapiens