Fixel-based analysis - assign significant fixels to tracks

[rmito]

Hi @Antonin_Skoch,

I can give you some more specific details on what we did in the paper, but as @ThijsDhollander says, there are a number of approaches you can take!

Here are the specific steps that were taken in our case:

Firstly, as per Dave’s recommendation:

1. Threshold significant fixels using mrthreshold
2. Create signficant voxel mask using fixel2voxel

The next step required quite some manual curating:

3. Manually create inclusion and exclusion ROIs to define regions where tracts will pass

Here, we referred to existing WM atlases. The referenced atlases were used to ‘guide’ categorisation of fixels into tracts in this way, rather than registering atlases to FOD template space.

4. Create tracts-of-interest using tckedit on the FOD-based tractogram, with inclusion/exclusion ROIs, and using the significant voxel mask
5. Generate fixel TDI of streamlines using tck2fixel
6. Threshold TDI to generate fixel mask using mrthreshold

Following these steps, mean fixel-based metrics could be computed within each tract using mrstats

To address some other comments:

@Antonin_Skoch

How the figure 6 was produced?

Fig. 6 in the paper shows the tracts-of-interest created in step 4. The tracts correspond only to the significant fixels, and fixels were grouped into tracts through categorization that involved manual ROI labelling.

@Antonin_Skoch

Better way I see to perform anatomically-informed tracking on WM-FOD template or ROI-based streamline identification on the WM-FOD-based tractogram, and using this info to segment fixels to major tracts. But I do not know how to do this in automated way. Maybe some adaptation of AutoPtx scripts could do the trick?

The ROI-based streamline identification is essentially what was done here. I don’t think there are currently good automated options available, but if you find a solution, I’d love to know too!

Hope that helps!

Remika