Voxel-based Morphometry of Brain Imaging Data

Brain imaging data were converted from DICOM images to Neuroimaging Informatics Technology Initiative (NIFTI) files using dcm2nii from the MRIcron package (http://people.cas.sc.edu/rorden/mricron/index.html, accessed on 20 December 2022). Images were manually reoriented with the coordinate system’s origin set to the anterior commissure. Voxel-based morphometry analysis was performed on the structural imaging data with the Computational Anatomy Toolbox (CAT12) toolbox (http://www.neuro.uni-jena.de/cat/, accessed on 20 December 2022), an extended toolbox of SPM12 [15 (link)], with default settings. The preprocessing pipeline included realignment, skull stripping, segmentation by tissue type (i.e., gray matter and white matter), and finally, the segmented gray matter images were non-linearly warped to the standard Montreal Neurological Institute (MNI) template [19 (link)], modulated to account for volume changes. Modulated and warped 3D gray matter density maps (GMDMs) were smoothed using a 2-mm full width at half maximum Gaussian kernel. The GMDMs had a dimensionality of 121 × 145 × 121 in the voxel space (a voxel size of 1.5 × 1.5 × 1.5 mm⁷). The GMDMs were further re-sampled to an isotropic voxel size of 3 × 3 × 3 mm³ to provide an image dimension of 64 × 64 × 64 for an efficient computation.