I am in the processing of transitioning from data analyses with SPM to
analyses with FSL and was hoping for some guidance on tools to use for a
task at hand. I am in the process of evaluating a set of military service
members exposed to repetitive low-level explosive blast to determine if
their fractional anisotropy values change either before or after training,
or are different between several groups entering this study with a previous
history of differing levels of exposure. Here are the steps I have taken so far:
1. Acquire diffusion data (in 30 directions and 2.5 mm slices)
2. Convert dicom to nifti files
3. Peform eddy correction
4. Fit diffusion tensors using DTIFIT
5. Run the tbss_1_preproc, tbss_2_reg -T, tbss_3_postreg, tbss_4_prestats,
and suggested randomise steps in the TBSS documentation instructions. I then
ran the tbss_fill step to fill out the local tracts for display purposes.
So I now have a dataset which nicely demonstrates where areas of statistical
significance exist when comparing study groups. What I really need at this
point to complete the dataset is to be able to go into the specific clusters
which are significantly different determine corresponding mean FA values
within clusters for each subject in the study.
I see the documentation on "Transforming TBSS results back to native space",
and can certainly follow these instructions, but I am not entirely sure how
to get to mean FA values within a given cluster of statistically
significantly different voxels. What I am shooting for is data similar to
the Giorgio et al. Neuroimage article (NeuroImage 39 (2008) 52–61). Thanks in
advance for any help you might be able to provide with this.
|