TRACULA

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TRACULA is a tool for automatic reconstruction of a set of major white-matter pathways from diffusion-weighted MR images. It uses global probabilistic tractography with anatomical priors. Prior distributions on the neighboring anatomical structures of each pathway are derived from an atlas and combined with the FreeSurfer cortical parcellation and subcortical segmentation of the subject that is being analyzed to constrain the tractography solutions. This obviates the need for user interaction, e.g., to draw ROIs manually or to set thresholds on path angle and length, and thus automates the application of tractography to large datasets.

Contents

[edit] Steps for running TRACULA on a data set

[edit] Step 1: Setup the Computer

You will need Freesurfer and FSL.

If you are a member of VISTA lab, you should have access to all the programs you need by editing your .bashrc file.

For instructions, go to the Freesurfer Wiki to get Freesurfer and FSL Wiki to get FSL on your local computer.

[edit] Step 2: Prepare the data directories

In order to process a subject in TRACULA, you need these files:

  1. T1 weighted image
  2. diffusion image
  3. bvecs file (The gradient table must be saved in a simple text file in three-column format, one row for each volume in the DWI series)
  4. bvals file (The b-value table must be saved in a simple table file in single-column format, one row for each volume in the DWI series)
  5. brain mask
  6. configuration file (see step 4)

[edit] Step 3: Do a Freesurfer segmentation for each subject

In order to run Freesurfer, follow the instructions on the Freesurfer Wiki

[edit] Step 4: create a configuration file

For full instructions, see the [TRACULA Wiki]

[edit] Step 5: pre-processing

Includes:

  1. Eddy-current compensation
  2. Intra-subject registration (individual DWI to individual T1)
  3. Inter-subject registration (individual T1 to a common template space)
  4. Creation of cortical and white-matter masks from FreeSurfer reconstructions
  5. Tensor fitting for extract of tensor-based measures (FA, MD, etc)
  6. Computing anatomical priors for white-matter pathways from the TRACULA atlas

[edit] How to run:

In order to run all of the pre-processing steps, type into the terminal:

export SUBJECTS_DIR=/path/to/folder/with/subject's/freesurfer/segmentation

trac-all -prep -c /path/to/subject's/congiguration/file

[edit] How to check the output:

Depending on how the data is imported from the MRI, the diffusion gradient directions may be reversed. After pre-processing, check to make sure the diffusion gradients are visually in line with the white matter pathways.

This can be visualized in fslview. In the "dmri" file from the pre-processing output, overlay the "dtifit_FA.nii.gz" and "dtifit_V1.nii.gz" images.

Check to make sure the gradient directions are not flipped in the X Y or Z directions. If they are incorrect, alter the bvecs file so that the values in the relevant dimention are flipped (negative numbers become positive and positive numbers become negative).

This is what it will look like if it is misaligned:

Not Aligned 1.png Not Aligned 2.png Not Aligned 3.png

This is what it will look like if it is correct:

Aligned 1.png Aligned 2.png Aligned 3.png

[edit] Step 6: Ball-and-stick model fit

[edit] Step 7: Reconstruct white-matter pathways

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