Duke Neurogenetics Study MRI Protocol
FreeSurfer
Regional measures extracted with FreeSurfer
To generate regional measures of brain morphometry, anatomical images for each subject were first skull-stripped using ANTs (Klein et al., 2009), then submitted to Freesurfer's (Version 5.3) recon-all with the 'noskullstrip' option (Dale et al., 1999; Fischl et al., 1999), using an x86_64 linux cluster running Scientific Linux. Cortical thickness and surface area for 31 regions in each hemisphere, as defined by the Desikan-Killiany-Tourville atlas (Klein and Tourville, 2012), a modified version of the Desikan-Killiany atlas (Desikan et al., 2006) meant to make region definitions as unambiguous as possible and define boundaries best suited to FreeSurfer's classifier algorithm, were extracted using Freesurfer. Additionally, gray matter volumes from eight subcortical regions (Cerebellum Cortex, Thalamus, Caudate, Putamen, Pallidum, Hippocampus, Amygdala, and Accumbens area) were extracted with Freesurfer's subcortical segmentation (“aseg”) pipeline (Fischl et al., 2002). Estimated Total Intracranial Volume (ICV), total gray matter volume, cerebral white matter volume, and left and right hemisphere mean CT were also extracted from the “aseg” pipeline, and average whole-brain CT was calculated based on the estimates for the left and right hemispheres. 1321 participants completed the high-resolution T1-weighted imaging protocol; 9 datasets were excluded for the presence of motion-related or external artifacts, 6 were excluded for incidental findings, and 1 was unable to be processed with FreeSurfer, leaving 1305 for analysis. The gray and white matter boundaries determined by recon-all were visually inspected using FreeSurfer QA Tools (https://surfer.nmr.mgh.harvard.edu/fswiki/QATools) and determined to be sufficiently accurate for all subjects.
Also see Global covariate rationale.
References
Dale, A.M., Fischl, B., Sereno, M.I., 1999. Cortical surface-based analysis. I. Segmentation and surface reconstruction. Neuroimage 9, 179-194.
Desikan, R.S., Ségonne, F., Fischl, B., Quinn, B.T., Dickerson, B.C., Blacker, D., Buckner, R.L., Dale, A.M., Maguire, R.P., Hyman, B.T., 2006. An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 31, 968-980.
Fischl, B., Salat, D.H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., Van Der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., 2002. Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33, 341-355.
Fischl, B., Sereno, M.I., Dale, A.M., 1999a. Cortical surface-based analysis. II: Inflation, flattening, and a surface-based coordinate system. Neuroimage 9, 195-207.
Arno Klein, Jesper Andersson, Babak A. Ardekani, John Ashburner, Brian Avants, Ming-Chang Chiang, Gary E. Christensen, D. Louis Collins, James Gee, Pierre Hellier, Joo Hyun Song, Mark Jenkinson, Claude Lepage, Daniel Rueckert, Paul Thompson, Tom Vercauteren, Roger P. Woods, J. John Mann, Ramin V. Parsey, Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration, NeuroImage, Volume 46, Issue 3, 1 July 2009, Pages 786-802, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2008.12.037. (http://www.sciencedirect.com/science/article/pii/S1053811908012974)
Klein, A., Tourville, J., 2012. 101 labeled brain images and a consistent human cortical labeling protocol. Frontiers in Neuroscience 6, 171.