10 Supplementary Material

10.1 NKI-RS Voxel-based morphometry processing and quality control

Prior to processing, 695 T1 images were visually inspected for quality. Voxel-based morphometry (VBM) completed in 693 scans using the Computational Anatomy Toolbox 12 (CAT12: Version 12.5) in Statistical Parametric Mapping 12 (SPM12: Version 7487) Ashburner (2009). T1-weighted structural images were corrected for bias-field inhomogeneities, registered using linear (12 parameter affine) and non-linear transformations, then spatially normalized using the DARTEL algorithm, and segmented into gray matter, white matter and cerebrospinal fluid (Ashburner 2007). Further quality control was conducted using the CAT12’s quality assurance framework. This is a retrospective, quantitative measure that evaluates image parameters such as noise, inhomogeneities and image resolution, placing images on a rating scale and assigning a letter grade to each image. Any scan rated B- or above is considered good quality, and any scans rated C- to C+ are considered satisfactory. In our data, all CAT12 output rated C+ or below were further visually inspected for gray matter segmentation quality. Any scan with gray matter segmentation that did not capture the gray matter, or included non-gray matter voxels, were excluded from further analysis. A total of 682 participants passed this quality inspection criteria and had complete demographic data.

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References

Ashburner, John. 2007. “A Fast Diffeomorphic Image Registration Algorithm.” Neuroimage 38 (1): 95–113.
———. 2009. “Computational Anatomy with the SPM Software.” Magnetic Resonance Imaging 27 (8): 1163–74.