Categories


Neuroimaging

In vivo and ex vivo magnetic resonance imaging data. A listing of scanners and protocols is available here.

Subcategories

In Vivo Imaging

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 data using BIANCA (Griffanti et al., Neuroimage 2016; 141:191-205) (fsl.fmrib.ox.ac.uk/fsl/fslwiki/ ). 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.
  5. Diffusion tensor imaging (DTI): Maps of fractional anisotropy (FA), trace, axial and radial diffusivity are generated using TORTOISE (Pierpaoli et al. ISMRM 2010; p.1597) (science.nichd.nih.gov/confluence/display/nihpd/TORTOISE ).
  6. Functional connectivity MRI (functional connectome): A whole brain functional connectivity matrix is generated for each participant using our resting state functional connectivity data (SPM) (Friston et al., Hum Brain Map 1995;3-165-189) (www.fil.ion.ucl.ac.uk/spm/ ) and a set of gray matter labels defined based on clustering neighboring voxels with similar signal time-courses.
  7. Microbleeds: Susceptibility-weighted images are reconstructed from 3D GRE data and microbleeds are counted. (In progress)
  8. Magnetic susceptibility: Magnetic susceptibility maps are generated using quantitative susceptibility mapping on 3D GRE data (Wei et al., NMR Biomed 2015;28:1294-1303) (email STI-Suite).
  9. Infarcts: Lacunar infarcts larger than 3mm are segmented and the total number as well as the volume of infarcts is calculated. (In progress)

Ex Vivo Imaging

Documentation in progress.