Diffusion Tensor Imaging: The Nitty Gritty Brought to you by: Meenal and Erica November 2, 2010.

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Presentation transcript:

Diffusion Tensor Imaging: The Nitty Gritty Brought to you by: Meenal and Erica November 2, 2010

Terms FA: Fractional Anisotropy – The eccentricity of the ellipsoid MD: Mean Diffusivity – The mean of the three principle eigenvectors DTI Terminology Reference:

DTI Step 1: Convert Your Data Convert the DTI DICOM files to NIFTI format

DTI Step 1.A Change your FSL Output Type – Cd: /usr/local/fsl-4.1.4/etc/fslconf – Run: sudo nano fsl.csh – Change FSLOUTPUTTYPE TO NIFTI – Control X – Save? “y” – Relaunch the terminal and check the change

DTI Step 1.B Edit script as needed – Script: /Volumes/sasquatch/DataManagement/Workspace/P rocessing/MatlabCode/”MY”Matlab/main_dtipreproc ess.m Make sure your account system preferences are set to /bin/tcsh Open matlab Run: main_dtipreprocess.m

DTI Step 2 Move all folders – done, dti,ec,fsl, medinria, ninfo.txt,reg, vc and vl From: – /StudyName/Original_Data/nii/subjid/dti To: – /StudyName/Original_Data/DTI/subjid/dti/

DTI Step 3 Rename files in: – StudyName/Original_Data/DTI/subj/dti/fsl/ – From: *rec* – To: *$subjID*

DTI Step 4 Create folders: – Studyname/DTI_Analysis – Studyname/DTI_Analysis/StudyName_MD – Studyname/DTI_Analysis/StudyName_MD/origd ata – Studyname/DTI_Analysis/StudyName_FA – Studyname/DTI_Analysis/StudyName_FA/FA

DTI Step 5 Copy data – Files ending in *FA* – From: StudyName/Original_Data/DTI/subj/dti/fsl – To: Studyname/DTI_Analysis/StudyName_FA/FA – Files ending in *MD* – From: StudyName/Original_Data/DTI/subj/dti/fsl – To: Studyname/DTI_Analysis/StudyName_MD/origd ata

DTI Step 6 Run Tract Based Spacial Statistics using the FSL Package – CD into DTI_Analysis/StudyName_FA/ – Copy dti_tbss1-3.sh – Run script – Note: Errors may occur here if fsl is not set up correctly

TBSS To Learn More – preprocessing - create FA images from your diffusion study data tbss_1_preproc - prepare your FA data in your TBSS working directory in the right format tbss_2_reg - apply nonlinear registration of all FA images into standard space tbss_3_postreg - create the mean FA image and skeletonise it tbss_4_prestats - project all subjects' FA data onto the mean FA skeleton stats (e.g., randomise) - feed the 4D projected FA data into GLM modelling and thresholding in order to find voxels which correlate with your model.

DTI Step 6 Check mean_FA

DTI Step: 7 Create sublist in DTI_Documentation Create folders: – DTI_Analysis/WM2DTI2Template – DTI_Analysis/GM2DTI2Template

DTI Step 8 Separate mean_FA and mean_MD into gray and white matter – Set up and Run: dti_combined_StudyName.sh – This script: #Step 1: Reorient the hires to Match the DTI #Step 2: Create Average Bo #Step 3: Register hires to Average Bo #Step 4: Apply warp of hires in DTI space and MD to MNI152 – # Threshold the MD Map > 0 – # Apply the warp (Subject FA to FMRIB_FA template) on MD map # Step 5: Segment the hires in MNI152 space # Step 6: Threshold just the WM and GM (Whole-brain) # Step 9: Multiple registered FA map and mask (WM and GM) # Step 10: Calculate the Mean FA for WM/ mean MD for WM and GM

DTI Results Bo+12 directions – FAtarget_WM – MDtarget_WM – MDtarget_GM