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SCAIFIELD MRSI analysis

This tool performs the SCAIFIELD MRSI analysis

Prerequisite

  • Data must already be in BIDSlike format
  • Some third party software
    • LCModel
    • FSL

Usage

just call

python mrsi_analysis.py [-h] [--path PATH] [--site SITE] [--sub SUB] [--ses SES]
  --path PATH  path #BIDS folder (default: None)
  --site SITE  site (default: None)
  --sub SUB    subject name (default: None)
  --ses SES    session name (default: None)

Output

You can find the output in

path/derivatives/site/sub/ses/mrsi/lcm

path/derivatives/site/sub/ses/mrsi/maps

  • lcm
    • LCModel input and output of each voxel within brain mask
  • maps
    • Metabolites' maps (in .nii format)
    • FWHM/SNR maps

Working principle

  1. Read in all .dcm / .IMA files
    • Sort for z-Position (code borrowed from suspect)
  2. Appy Hamming filter
  3. Create dummy nii file (in MRSI image space)
  4. Use MPRAGE to create brain mask
    • register to MRSI image space (only quaternions)
  5. Perform LCModel quantification for all voxels in brain mask
  6. Read in LCModel files and create maps

TODO:

  • Pseudo single-voxel