I am relatively new to diffusion analysis and have a few questions related to processing options for the goal of building structural connectomes. I am working with DWI data from individuals with multiple sclerosis with a single b=0 and remaining b=2000 for 64 directions. All images were collected in AP. Please see my processing script below punctuated with questions.
#Denoise, eddy + motion correction, estimate response function
dwidenoise dwi.mif dwi_den.mif -noise noise.mif -force
dwifslpreproc *dwi_den.mif *dwi_den_preproc.mif -nocleanup -rpe_none -pe_dir AP
dwi2response dhollander dwi_den_preproc.mif wm.txt gm.txt csf.txt -voxels voxels.mif -force
#Create mask (used this instead of the built-in ants/fsl options with dwi2mask as they were retaining substantial areas of the neck)
bet2 …/*dwi.nii.gz dwi_bet -m
mrconvert dwi_bet_mask.nii.gz dwi_bet_mask.mif
Ideally, I’d like to do single-shell 3-tissue CSD (ss3t_csd) and this:
#Estimate fiber orientation distribution.
Ideally: dwi2fod msmt_csd dwi_den_preproc.mif -mask dwi_bet_mask.mif wm.txt wmfod.mif gm.txt gmfod.mif csf.txt csffod.mif -force
But as indicated with only 2 b-vals, I’m unable to estimate all 3 tissue types. So does that only leave below as an option?
dwi2response tournier dwi_den_preproc.mif response.txt
dwi2fod csd dwi_den_preproc.mif response.txt fod.mif
mrview vf.mif -odf.load_sh wmfod.mif
This is the fod output. Is it too sparse?
Q: For the next steps, would it be better to use a freesurfer parcellation that was fed a binary lesion mask to improve segmentation (especially since I can’t perform distortion correction)?
Thank you for your help! It’s much appreciated.