Beginner: Connectome pipeline (Updated)

5

Thanks for the tips. I have made some changes to the workflow to get from the DWI and Freesurfer-T1 to an ACT-informed connectome matrix.

I have pasted the steps and outputs for a single subject with a neurodegenerative disease. Will appreciate any comments especially with regards to the tckgen step. The next thing I will like to do is to weight these matrices by (a) mean FA and to (b) normalise the streamline counts by the average volumes between 2 regions :slight_smile:

A. Registration of T1 and aparc+aseg.mgz to processed DTI

  1. recon-all the T1 data with Freesurfer

  2. bbregister b0 images to orig.mgz / brainmask.mgz

  3. tkregister to check/edit registration. This matrix will be used to perform inverse registration of the T1 to DTI space without losing resolution.

  4. Refer to another MRtrix thread for structural-diffusion registration

    Screen Shot 2016-08-11 at 18.09.56.png799×618 267 KB

    Blue = DWI, Greyscale = Aligned T1

B. DWI processing

  1. Denoise DWI
    dwidenoise i.mif i_denoised.mif;

  2. Process diffusion data and perform bias-correction
    dwipreproc -0 i_denoised.nii i_preproc.mif -rpe_none
    dwibiascorrect i_preproc.mif i_biascorrected.mif -fsl

    Screen Shot 2016-08-11 at 18.19.11.png993×784 136 KB

  3. Estimate response function
    dwi2response tournier i_biascorrected.mif i_response.txt

  4. FOD
    dwi2fod csd i_biascorrected.mif i_response.txt i_fod.mif

    Screen Shot 2016-08-11 at 18.23.48.png1030×718 505 KB

C. T1 Processing (after Freesurfer and Registration to DWI)

  1. Derive tissue-segmented image
    5ttgen freesurfer i_aparc+aseg_mrtransformed.mgz i_freesurfer_5TT.mif

  2. Visualise 5TT
    5tt2vis i_freesurfer_5TT.mif i_freesurfer_5TT_vis.mif
    @rsmith: Does this look right? The white spots (intensity = 2) correspond to locations of lesions on the WM. How can I deal with them?

    Screen Shot 2016-08-11 at 18.37.04.png978×759 53.5 KB

    I have also tried 5ttgen -fsl but the I am struggling to get good BETs for the 5TT with over-invasive cuts into the cortical GM…

  3. Modify the integer values in the parcellated image so that the numbers in the image corresponds to the rows and cols of the connectome
    labelconvert i_aparc+aseg_mrtransformed.mgz /Applications/freesurfer/FreeSurferColorLUT.txt /Users/MacPro/mrtrix3/src/connectome/tables/fs_default.txt i_nodes.mif

C. Connectome generation

  1. Streamline tractography
    tckgen i_fod.mif i.tck -act i_FS_5TT.mif -backtrack -crop_at_gmwmi -seed_dynamic i_fod.mif -number 1M -maxlength 250

  2. Perform SIFT
    tcksift i.tck i_fod.mif i_sift.tck -act i_FS_5TT.mif -term_number 500000

    Screen Shot 2016-08-11 at 18.46.18.png856×699 643 KB

  3. Map the streamlines to the parcellated T1 to produce the connectivity matrix
    tck2connectome i.tck i_nodes.mif i_connectome.csv -zero_diagonal
    Transform the matrix into a symmetric form where M is your matrix
    M = M + triu(M,1)' <-- Thanks, @rsmith ! [see MRtrix thread]

  4. View the connectome
    mrview i_nodes.mif -connectome.init i_nodes.mif -connectome.load i_connectome.csv

  5. Load connectivity matrices in MATLAB for analyses with Brain Connectivity Toolbox

2 Likes