The goal is to calculate diffusivity in specific ROIs.
My steps were to preprocess, normalize, and register the ROI mask to subject native space. I am confident in those commands as the output look good.
To get DTI values I then used :
#whole brain streamlines, probabilistic (includes random variation/noise)
tckgen -act ${dir_out_sub}/anatomical/${subject}_T1_5tt_coreg.mif -backtrack -seed_gmwmi ${dir_out_sub}/anatomical/${subject}_gmwmSeed_coreg.mif -seed_image ${dir_out_sub}/preprocessed/dwi_${subject}_mask.mif -nthreads 8 -minlength 25 -cutoff 0.06 -select 10M ${dir_out_sub}/basis_functions/wmfod_norm_${subject}.mif ${outDir}/${subject}_WholeBrain_ACT_10M.tck -info
echo "Sifting the tracks with tcksift:" #-term_number 10M <not needed?
tcksift -act ${dir_out_sub}/anatomical/${subject}_T1_5tt_coreg.mif ${outDir}/${subject}_WholeBrain_ACT_10M.tck ${dir_out_sub}/basis_functions/wmfod_norm_${subject}.mif ${outDir}/${subject}_sift_10mio.tck
echo "convert ROI into mif and then mask"
mrconvert ${dir_out_sub}/Warped_Tract/${subject}_LEFT.nii.gz ${dir_out_sub}/Warped_Tract/${subject}_LEFT.mif
#mask
mrthreshold ${dir_out_sub}/Warped_Tract/${subject}_LEFT.mif ${dir_out_sub}/Warped_Tract/${subject}_LEFT_mask.mif
echo "tckedit to get streamlines within ROI mask"
tckedit ${outDir}/${subject}_sift_10mio.tck ${outDir}/${subject}_sift_LEFT_10mio.tck -mask ${dir_out_sub}/Warped_Tract/${subject}_LEFT_mask.mif
echo "calculating mean FA in subject space / ROI"
tcksample -stat_tck mean ${outDir}/${subject}_sift_LEFT_10mio.tck ${dir_out_sub}/tensors/FA_${subject}.mif ${meanDIR}/FA/${subject}_LEFT_meanFA.txt
I then use R to calculate the average of the entire ${subject}_LEFT_meanFA.txt
output file.
Is there any issue with my approach? Or suggestions to improve? Thanks in advance.