[Mrtrix-discussion] Streamtrack and connectivity values

[Simon Baker]

Hi Donald et al.,

It appears that our connectivity output depends on the voxel dimensions of
the seed, include, and mask images that are used when performing
"streamtrack".

We have used two approaches to get our seed (binarised and dilated
FreeSurfer white matter segmentation), include (parcellation based on
FreeSurfer aparca2009s and FSL FIRST), and mask (combination of seed and
include) images into FA space.

Prior to implementing Approach 1 or Approach 2, which are described below,
we put our structural (FreeSurfer brain.mgz), seed, include, and mask
images into standard space using "fslreorient2std", then we coregistered
the FA image (generated by MRtrix) to the structural image (in standard
space) and generated what we will call the fa2std transform matrix using
FSL's "flirt". The target images refer to the seed, include, and mask
images (all in standard space).

Approach 1. FSL. We inverted the fa2std transform matrix using "convert_xfm
-inverse". Then, using the inverted fa2std transform matrix in "flirt
-applyxfm", we applied spatial transformations to the target images,
creating outputs that were in FA space and that had the same voxel
dimensions as the FA image (2.3x2.3x2.3).

Approach 2. MRtrix. Using "mrtransform -inverse", we inverted the fa2std
transform matrix and applied spatial transformations to the target images,
creating outputs that were in FA space, but which retained their native
voxel dimensions (1x1x1).

These outputs were used in subsequent steps as described below.

We eroded the 2.3x2.3x2.3 white matter segmentation to create the single
fibre mask. Note that we encountered an error when attempting to erode the
1x1x1 white matter segmentation, probably because the "erode" step includes
specification of the FA image (which is 2.3x2.3x2.3) for "mrmult" and
therefore the voxel dimensions are not compatible.

We used the single fibre mask to estimate the response function coefficient.

We performed "csdeconv" with the mask specified as our 2.3x2.3x2.3 hybrid
brain mask (a combination of the 2.3x2.3x2.3 seed and include images). Note
that we encountered an error when attempting to specify our 1x1x1 hybrid
brain mask as the mask, again probably due to incompatible voxel dimensions.

Then we performed "streamtrack" twice: firstly at the 2.3x2.3x2.3
resolution (i.e., we used the 2.3x2.3x2.3 seed, include, and mask images);
and secondly at the 1x1x1 resolution (i.e., we used the 1x1x1 seed,
include, and mask images). We also discovered that "streamtrack" will allow
any combination of seed, include, and mask images; i.e., the voxel
dimensions of these images do not need to be identical - why is this?
Anyhow, we generated one million streamlines using either all 2.3x2.3x2.3
images or all 1x1x1 images.

>From each of the track files we extracted streamlines connecting two or
more regions (where regions were specified by the include image). Then we
generated two connectivity matrices (one that was based on the 2.3x2.3x2.3
images/streamlines and another that was based on the 1x1x1
images/streamlines) by counting the number of streamlines interconnecting
each pair of regions. Interestingly, these connectivity matrices were
noticeably different, suggesting that the connectivity values depended on
the voxel dimensions of the seed, include, and mask images that were used
when performing "streamtrack".

We were wondering whether the resolution of the masks affects the
tractography in anyway? Is there any reason for preferring one over the
other? We presume that the native 1 x 1 x 1 resolution is preferable, but
wanted to make sure we are not missing anything here.

Thanks in advance,

-- 

Simon Baker
PhD Candidate
Faculty of Medicine, Nursing and Health Sciences
Monash University
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