In-vivo brain MRI data are collected through the RADC cohort studies and substudies. Participants are imaged biennially using a number of pulse sequences providing structural, functional, and chemical information about the brain. The raw data are processed locally. Raw and processed data are made available for research inside and outside of the RADC. Raw data are made available "as is", but all processed data have passed our quality checks. We use a 3-step quality control strategy testing: 1) MRI scanner performance on a phantom, 2) quality of raw MRI data collected on humans, and 3) quality of information derived from processing. Each step involves thorough tests tailored to each MRI processing output as well as visual inspection.

Raw data is collected with the following sequences:

1. T1-weighted 3D Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE)
2. Spin-Echo Echo-Planar Diffusion-Weighted Imaging (SE-EPI-DWI)
3. Multi-Echo 2D Fast Spin-Echo (FSE)
4. T2-weighted 2D Fluid-Attenuated Inversion Recovery (FLAIR)
5. Multi-Echo 3D Gradient-Recalled Echo (GRE)
6. Resting State, Gradient-Recalled Echo, Echo-Planar Imaging (GRE-EPI)

(Note: The above are sequences used on the 3T scanners. Similar sequences were run on the older 1.5T scanner. See protocols for exact description of the sequences.)

Processing of the raw MR images generates the following output (click on each type of output for more information on the methods used):

1. Freesurfer output: MPRAGE data is segmented into cortical and subcortical regions, and hippocampal subfields, using Freesurfer with manual corrections (Fischl et al. Cereb Cortex 2004;14:11-22) (surfer.nmr.mgh.harvard.edu ). Regional volumes, cortical thicknesses and surface areas are calculated.
2. Total volumes: Gray matter, white matter, and cerebrospinal fluid (CSF) probability maps, as well as masks, are generated from MPRAGE data using the Computational Anatomy Toolbox (CAT) (www.neuro.uni-jena.de/cat/ ) for SPM (Friston et al., Hum Brain Map 1995;3-165-189) (www.fil.ion.ucl.ac.uk/spm/ ). The total volumes of gray matter, white matter, CSF, as well as the intracranial volume are calculated.
3. White matter hyperintensities: White matter lesions appearing hyperintense in T2-weighted images are segmented based on FLAIR and T1-weighted data using sysu (Li H, et al. Neuroimage 2018;183:650-665) (doi.org/10.1016/j.neuroimage.2018.07.005). A mask of white matter hyperintensities is generated and the total volume of hyperintensities is calculated.
4. T2 maps: Maps of T2 relaxation times are generated by fitting the multi-echo fast spin-echo signals with a mono-exponential decay model.

Regional gray matter volumes generated by the multi-atlas segmentation pipeline (MAS_ROI_**M)

Gray matter is first segmented and then divided into regions based on multi-atlas segmentation. The volumes of homologous regions in contralateral hemispheres are averaged. The average volumes are then divided by the intracranial volume and the ratio is multiplied by 1000. To find the name of the region corresponding to each variable name use the lookup table for the gray matter nodes of the IIT white matter atlas (www.nitrc.org/projects/iit ). Note: There are 3 variables which refer to combinations of two regions. These are MAS_ROI_05_15M: entorhinal and parahippocampal; MAS_ROI_26_31M: frontal pole and rostral middle frontal; and MAS_ROI_29_32M: temporal pole and superior temporal.

Median R2 values for gray matter regions segmented by the multi-atlas segmentation pipeline (R2med_ROI_**)

R2 values (i.e. 1/T2 values) for gray matter regions segmented by the multi-atlas segmentation pipeline. For each region, the R2 values from all voxels of the region in both the left and right hemisphere are grouped together and their median value is identified. The R2 values have units ms-1. To find the name of the region corresponding to each variable name use the lookup table for the gray matter nodes of the IIT white matter atlas (www.nitrc.org/projects/iit ). Note 1: There are 3 variables which refer to combinations of two regions. These are MAS_ROI_05_15M: entorhinal and parahippocampal; MAS_ROI_26_31M: frontal pole and rostral middle frontal; and MAS_ROI_29_32M: temporal pole and superior temporal. Note 2: The mean of the medians of all cortical regions and the mean of the medians of all subcortical regions are also provided.

Regional cortical thickness generated by Freesurfer (THK_ROI_**M)

The thicknesses of homologous regions in contralateral hemispheres are averaged. To find the name of the region corresponding to each variable name use the lookup table for the gray matter nodes of the IIT white matter atlas (www.nitrc.org/projects/iit ).

Reference: Fleischman DA, Leurgans S, Arfanakis K, Arvanitakis Z, Barnes LL, Boyle PA, Han SD, Bennett DA. Gray-matter macrostructure in cognitively healthy older persons: associations with age and cognition. Brain Struct Funct. 2014 Nov;219(6):2029-49. doi: 10.1007/s00429-013-0622-7. Epub 2013 Aug 17. PMID: 23955313; PMCID: PMC3926914

Regional gray matter volumes generated by Freesurfer (VOLG_ROI_**M)

The volumes of homologous regions in contralateral hemispheres are averaged. The average volumes are then divided by the intracranial volume and the ratio is finally multiplied by 1000. To find the name of the region corresponding to each variable name use the lookup table for the gray matter nodes of the IIT white matter atlas (www.nitrc.org/projects/iit ).

Documentation in progress.