MCIC Multisite sMRI Dataset Preprocessed with VBM

This is a multisite structural MRI dataset preprocessed with voxel-based morphometry (VBM). This data can be used to demonstrate how federated voxelwise regression works on the Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC).

As described in Gazula et al, 2018, this data comes from the Mind Clinical Imaging Consortium (MCIC) collection, a publicly accessible, online data repository containing curated anatomical and functional MRI, in addition to other data, collected from individuals with and without a schizophrenia spectrum disorder (Gollub et al., 2013) and available via the COINS data exchange https://coins.mrn.org (Scott et al., 2011).

The final cohort for whom data are available includes 146 patients and 160 controls with site distribution as follows: Site B (IA) 40 patients/67 controls; Site D (MGH) 32/23; Site C (UMN) 32/26; Site A (UNM) 42/44, respectively.

These T1-weighted structural MRI (sMRI) images were acquired with the following scan parameters: TR = 2, 530ms for 3 T, TR = 12ms for 1.5 T; TE = 3.79ms for 3 T, TE = 4.76ms for 1.5 T; FA = 7° for 3 T, FA = 20° for 1.5 T; TI = 1100msfor 3 T; Bandwidth = 181 for 3 T, Bandwidth = 110 for 1.5 T; voxelsize = 0.625 × 0.625mm; slice thickness 1.5 mm; FOV= 16−18cm.

The T1-weighted sMRI data were preprocessed using the Statistical Parametric Mapping software using unified segmentation (Ashburner and Friston, 2005), in which image registration, bias correction and tissue classification were performed using a single integrated algorithm resulting in individual brains segmented into gray matter, white matter and cerebrospinal fluid and nonlinearly warped to the Montreal Neurological Institute (MNI) standard space. The resulting gray matter concentration (GMC) images were re-sliced to 2 × 2 × 2mm, resulting in 91 × 109 × 91 voxels.