Whole brain fibers shorter than expected

Hi to mrtrixers!
I am working on 2 human groups’ brain tractography. But the .tck files seem weird because the fiber lengths are much shorter than what I expected.

My DWI data for both subject groups underwent eddy only. As single-shell data, I ran:

  1. dwi2response tournier -shells 1000,0 -nthreads 8
    and averaged responses within groups (responsemean command).

  2. FODs were calculated via:
    dwi2fod -shells 1000 msmt_csd dwi_eddy_prepro.nii common_mean_res.txt “$fod_file” -mask dwi_eddy_prepro_mask.nii.

  3. 5ttgen T1_raw.mif 5tt_nocoreg.mif

  4. flirt T1_raw.nii mean_b0_dwi_eddy_prepro.mif -dof 6 -omat diff2struct_fsl.mat

  5. transformconvert diff2struct_fsl.mat mean_b0_dwi_eddy_prepro.mif T1_raw.mif flirt_import diff2struct_mrtrix.txt

  6. Coregistered T1_coreg.mif and 5tt_coreg.mif via:
    mrtransform -linear diff2struct_mrtrix.txt -inverse.

  7. Generated GM-WM interface mask:
    5tt2gmwmi 5tt_coreg.mif gmwmSeed_coreg.mif.

  8. Executed tractography:
    tckgen -act 5tt_coreg.mif -backtrack -seed_gmwmi gmwmSeed_coreg.mif -select 10000 wmfod_norm.mif tracks_10k.tck.

Questions:

  1. Are my parameters and steps reasonable?
  2. Are abnormally short whole-brain tracts (see fig.1) caused by inadequate preprocessing (e.g., missing bias field correction)?

Many thanks
Yaqin

Hi Yaqin.

I am not an MRtrix expert. It seems you are missing some preprocessing steps (see for some information and links: Structural connectome construction using constrained spherical deconvolution in multi-shell diffusion-weighted magnetic resonance imaging | Nature Protocols, Questions about FOD abnormalities and bias correction in single-shell FBA pipeline - #2 by WilliamFCB)

Also, when using single shell data you should use Single-Shell 3-Tissue CSD (SS3T-CSD) and not MSMT-CSD.

Cheers
William

HI William,
Thanks for your comments.
I think the MSMT-CSD can be used with single-shell data, according to Fibre density and cross-section - Single-tissue CSD — MRtrix3 3.0 documentation, specifically subsection 9 supports it. But I am not sure whether using SS3T-CSD will output better results or not.

I can only doubt that there is a problem with the preprocessing steps. Referring to the paper you mentioned, I found that my previous misunderstanding was that the denoising and Gibbs ringing processes are optional rather than necessary. It seems that eddy correction alone is still not sufficient. Next, I plan to start from the denoising step, reprocess the data, and then proceed with tractography.

Many thanks
Yaqin

Correct!

The most crucial preprocessing steps for dwi2fod are probably motion and eddy correction (as you mentioned) and bias field correction. That is if there was significant motion and bias field to begin with.

Denoising will certainly clean up the DWI images, and is highly recommended, but the effect on the output of dwi2fod is not always that noticeable because that procedure is quite resilient to noise. mrdegibbs is also highly recommended, but will also not dramatically alter your tractogram.

Regarding your original question whether your results are suboptimal or not, this is very hard to judge based on the screenshot. Your data is acquired with a very low b-value for fODF estimation and tractography. The number of diffusion econding directions is not mentioned, but if that is also very low, that can certainly be problematic. While it is technically all supported by MRtrix, reduced quality compared to e.g. multi-shell HARDI is expected. Given that you are running on what is essentially DTI data, tckgen might also benefit from custom arguments (in particular related to stopping criteria) as the defaults are probably more tuned for HARDI data sets.

My suggestion of using SS3T-CSD instead of MSMT-CSD for single shell data comes from Single-Shell 3-Tissue CSD | MRtrix3Tissue(Single-Shell 3-Tissue CSD (SS3T-CSD) | MRtrix3Tissue) and the discussion in Single shell vs. “Single tissue” - #5 by araikes)"

I especially note": [quote=“araikes, post:7, topic:5761”]
In the tutorial for the single tissue CSD (https://mrtrix.readthedocs.io/en/3.0.3/fixel_based_analysis/st_fibre_density_cross-section.html) uses dwi2response tournier and then states the following:

When performing fixel-based analysis, constrained spherical deconvolution (CSD) should be performed using the unique (average) white matter response function obtained before. Note that dwi2fod csd can be used, however here we use dwi2fod msmt_csd (even with single shell data) to benefit from the hard non-negativity constraint, which has been observed to lead to more robust outcomes
[/quote]

Were Thijs states:
Ah yes, that is true. I’d already forgotten about that. This is something I once also advocated for, but my experiences on that have become more mixed in recent years. The reasons for that are more complicated; and since the forced moderation of my posts, I don’t think I’ve shared that in any recent times here. I personally wouldn’t always use the “hard-constrained” version (i.e. the MSMT-CSD code, but within the single-tissue pipeline as you linked to above) for a single-tissue scenario anymore; it lacks an amount of flexibility that can be surprisingly relevant for certain specific applications or contexts.

However, that would indeed still be a single-tissue approach (i.e. fitting everything as if it were WM only); something which itself is arguably no longer necessary in any scenario. That said, I can now also better appreciate your possible confusion when you saw MSMT-CSD in the single-tissue FBA pipeline.

But to indeed be 100% clear: I don’t consider the above to be necessary anymore regardless. Put differently: the whole “single-tissue” FBA pipeline, I would strongly advice, should no longer be used. With the availability of both MSMT-CSD and SS3T-CSD, it’s always possible to use 3 tissues (WM/GM/CSF) with the “multi-tissue” FBA pipeline. In some exceptionally challenging or problematic scenarios (we’re talking combinations of non-human, ex-vivo and/or before birth here; or very unfavourable acquisitions), this could be limited to 2 tissues, often WM and CSF/fluid. But even in those scenarios, some manual work in getting the right response functions can overcome that (though you’ll need some technical expertise there to dig in). But to be clear also on this point: the necessity of the latter is extremely exceptional. Long story short: 3-tissue modelling, be it with MSMT-CSD or SS3T-CSD is almost always possible, and I would strongly advise to use always use the “multi-tissue” FBA pipeline, combined with the appropriate CSD technique. That’s the pipeline we also described in the review paper: regardless of single-shell (+b=0) or multi-shell data, the pipeline is always “multi-tissue”, allowing for the use of the best methods throughout. If it were up to me, I’d remove the single-tissue FBA pipeline from the online manual at this stage, or at least don’t link it directly from the main menu. It only tends to confuse people unnecessarily."

See also, https://www.sciencedirect.com/science/article/pii/S1053811921006923?via%3Dihub

@bjeurissen, is this now incorporated in MSMT-CSD, or is Thijs’s recommendation outdated?

Not 100% sure I understand the question, but if you are asking if MSMT-CSD as implemented in MRtrix3 supports decomposing the DWI signal into more compartments than unique b-values, the answer is no.

I cannot give a recommendation on the use of SS3T-CSD for an FBA study as I have not tried it myself, but there are certainly studies out there that have done it.

I believe the main reason it hasn’t been included in the MRtrix3 codebase is that it’s a heuristic method (involving “early stopping”) whose performance characteristics under varying conditions were not well understood. Only more recently, extensive simulations to test the method have been published here: https://cds.ismrm.org/protected/22MProceedings/PDFfiles/1419.html