Data Processing


 

Instructions for downloading data from BMAP’s DNS0 server

 

  1. Confirm the data has been pushed to the server and is in the correct location by completing the following in the Terminal window
    1. Log into DNS0:
      ssh –Y username@dns0.bmap.ucla.edu
    2. Find data located in the following directory:
      cd /Volumes/BMC9/dicom4/KNARRGROUP/ (before mid-June 2014)
      cd /Volumes/BMC9/dicom5/KNARRGROUP/ (as of mid-June 2014)
  2. Log into ssh.bmap server and copy data to server:
    ssh –Y username@ssh.bmap.ucla.edu
    cd /ifs/faculty/narr/schizo/DEPRESSION/
    scp –r username@dns0.bmap.ucla.edu:/Volumes/BMC9/dicom4/KNARRGROUP/<SUBJECT_ID>.
    scp –r username@dns0.bmap.ucla.edu:/Volumes/BMC9/dicom5/KNARRGROUP/<SUBJECT_ID>.
  3. Change permissions for new files
    chmod 775 -R /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>

Instructions for preprocessing new data

 

Convert all new patient MPRAGE’s to nifti.

  1. Log into the cerebro-mp1 server
    ssh –Y username@cerebro-mp1.bmap.ucla.edu
  2. Change directory to DEPRESSION/SCRIPTS: (all scripts and pipelines should be found in this directory)
    cd /ifs/faculty/narr/schizo/DEPRESSION/SCRIPTS
  3. Run the step_1_dcm_to_nifti.sh script:
    sh step_1_dcm_to_nifti.sh
    • This script will look through the DEPRESSION directory for any files with DE_###_## names and run dcm2nii for those that have not yet been converted.
    • The output file will be
      /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>/nifti/<SUBJECT_ID>_mprage.nii.gz
    • To run this script on other subject group, adjust the SUBJECTS_DIR variable:
      SUBJECTS_DIR='<new_subject_directory>'
    • If a subject has two MPRAGE files, manually convert the correct dicom to nifti:
      1. Create a nifti directory within the subject’s main directory (DE_###_##)
        mkdir /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>/nifti
      2. Change directory to where the dicom files are located and run MRIcron’s DCM2NII:
        cd /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>/ALLEGRA_MRC20108/2*/NARR_*/
        dcm2nii –o /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>/nifti/ TFL_MGH_ME_VNAV_RMS_#
      3. Change the output file name:
        mv /ifs/faculty/narr/schizo/DEPRESSION/<SUBJECT_ID>/nifti/2*.nii.gz <SUBJECT_ID>_mprage.nii.gz

Instructions to run FreeSurfer’s Reconstruction pipeline

 

Use the step_2_freesurfer.sh script.

  1. Edit step_2_freesurfer.sh within DEPRESSION/SCRIPTS to include subjects to run:
    vim step_2_freesurfer.sh
    1. To begin editing in Vim, press the "i" key for "insert mode"
    2. Change the subject list, to only include new subjects you would like to process:
      subj_list="<SUBJECT_ID_1> <SUBJECT_ID_2>..."
    3. To run this script on other subject group, adjust the SUBJECTS_DIR variable:
      SUBJECTS_DIR='<new_subject_directory>'
    4. Save changes to the script by pressing the esc key and typing :wq and hitting return
  2. Run script:
    sh step_2_freesurfer.sh
    • step_2_freesurfer.sh script will complete the initialize steps within the terminal (approximately 1 minute) and submit the complete recon-all script to the qsub server to run in parallel; do not
    • recon-all takes take approximately 15hrs to complete.

Instructions to complete FreeSurfer masking/fill holes

 

Pipeline and conversion to nifti.

  1. Download and open /ifs/faculty/narr/schizo/DEPRESSION/SCRIPTS/step_4_FS_masking_1.pipe using Pipeline
  2. Open Variables window by pressing "command"+"2" or going to Windows > Variables in the top menu bar
  3. Change the subject ID to the new subject to be run
  4. Press the "play" button to start the script
    • Due to the rigidity of the pipeline structure, the number of subjects to be run is determined by the inputs and output modules. There are 3 scripts (step_4_FS_masking_1.pipe, step_4_FS_masking_5.pipe, step_4_FS_masking_15.pipe) saved that will run 1, 5, and 15 subjects respectively
    • The output files will be found in /DEPRESSION/FS_temp/<SUBJECT_ID>/mri/:
      aseg.nii.gzmask_LH.nii.gzPVC_RH.nii.gz
      brainmask_auto.nii.gzmask_RH.nii.gzribbon.nii.gz
      combined_mask.nii.gzmask_WM_LH.nii.gzT1_automasked.nii.gz
      dist_q_LH.nii.gzmask_WM_RH.nii.gzT1_masked.nii.gz (used for structural analysis)
      dist_q_RH.nii.gzPVC_LH.nii.gzT1.nii.gz

Instructions to run DTI preprocessing for TBSS

 

  1. Within the DEPRESSION/SCRIPTS directory, edit step_3_dti.sh to include subjects to run:
    vim step_3_dti.sh
    1. To begin editing in Vim, press the "i" key for "insert mode"
    2. Change the subject list, to only include new subjects you would like to process:
      subj_id="<SUBJECT_ID_1> <SUBJECT_ID_2>..."
    3. To run this script on other subject group, adjust the SUBJECTS_DIR variable
      dep_home="/ifs/faculty/narr/schizo/DEPRESSION"
    4. Save changes to the script by pressing the esc key and typing :wq and hitting return
  2. Run script:
    sh step_3_dti.sh
    • The DTI script completes all three sections of the previous pipeline by submitting a DTI_all.sh script to the qsub server
    • The following output files should be created within the <SUBJECT_ID>/DTI directory:
      34rawDICOMdir2ANA_2.SlicepresAIR-1.air*md.hdr
      37rawdti2_temp*md.img
      axial.hdrDTIStudio_tensors.hdrradial.hdr
      axial.imgDTIStudio_tensors.imgradial.img
      BETdti2_tempra.hdr
      bval.txtfa.hdr ra.img
      DE_309_04_4D_bet.hdrfa.imgRstats.hdr
      DE_309_04_4D_bet.imggrad71.diffRstats.img
      DICOMdir2ANA_1.SlicepresAIR-1.air*Gradient_Table.txt
      *temporary files

Instructions to Compute Voxel Composition

 

  1. Open Voxel_Calculation_Sample.xlsx spread sheet
  2. Create a list of subjects to calculate voxel composition for
  3. Complete each column using actual data locations (do not assume it exists). Use the sample table below to locate the correct data;
    • Subjects may have multiple T1's or MRS runs for a particular ROI. Use the DE_SCAN_LOG database to identify which run to use. If there are no notes, use the last run MRS (DICOM which ends with the largest number)
    • For subjects without a MRS for an ROI, type "None"
    Pipeline Input ModulesSample Data
    Subj IDDE_121_02
    Hippo L (NWS)/ifs/faculty/narr/schizo/DEPRESSION/DE_121_02/ALLEGRA_MRC20108/20120914/NARR_DEPRESSION_1/SVS_VNAV_NWS_LT_HIPPO_19/1
    Hipp R (NWS)/ifs/faculty/narr/schizo/DEPRESSION/DE_121_02/ALLEGRA_MRC20108/20120914/NARR_DEPRESSION_1/SVS_VNAV_NWS_RT_HIPPO_25/1
    Dorcing (NWS)/ifs/faculty/narr/schizo/DEPRESSION/DE_121_02/ALLEGRA_MRC20108/20120914/NARR_DEPRESSION_1/SVS_VNAV_NWS_DORCING_31/1
    Subcing (NWS)/ifs/faculty/narr/schizo/DEPRESSION/DE_121_02/ALLEGRA_MRC20108/20120914/NARR_DEPRESSION_1/SVS_VNAV_NWS_SUBCING_37/1
    sMRI dicom/ifs/faculty/narr/schizo/DEPRESSION/DE_121_02/ALLEGRA_MRC20108/20120914/NARR_DEPRESSION_1/TFL_MGH_ME_VNAV_RMS_4
    T12T2fs_air*/ifs/faculty/narr/schizo/DEPRESSION/MRS_TISSUE_SEG/T1native2T2fs_invert.air
    T1 masked/ifs/faculty/narr/schizo/DEPRESSION/FS_temp/DE_121_02/mri/T1_masked.nii.gz
    Voxel Mask Directory*/ifs/faculty/narr/schizo/DEPRESSION/MRS_TISSUE_SEG/tmp/
    Pipeline Output Modules
    Output directory/ifs/faculty/narr/schizo/DEPRESSION/MRS_TISSUE_SEG/DE_121_02
    All Tissue Volumes CSV File&/ifs/faculty/narr/schizo/DEPRESSION/MRS_TISSUE_SEG/all_volumes_MMDDYY.csv
    * Entries for these modules should be the same on each line but equal to the total number of subjects
    & Only requires one entry
  4. Download and open step_5_MRSvoxelcalculate_MMDDYY.pipe using pipeline (located in the DEPRESSION/SCRIPTS directory)
  5. Paste in each column from the spreadsheet to the appropriate module, checking that the number of inputs on each module is the same.
  6. Press "Play" button to begin pipeline
  7. Output CSV file can be found in /ifs/faculty/narr/schizo/DEPRESSION/MRS_TISSUE_SEG/

Instructions to complete TBM processing pipeline

 

  1. TBM pipelines are located in /ifs/faculty/narr/schizo/DEPRESSION/SCRIPTS/TBM/
  2. Within the DEPRESSION directory, create a TBM directory to place all newly generated files
    mkdir /ifs/faculty/narr/schizo/DEPRESSION/TBM
  3. Making a TBM Atlas:
    1. Download and open TBM_Make_Atlas.pipe in pipeline
    2. Open the "Raw Data" module and paste in a list of each subjects' T1_masked.nii.gz with complete directory location:
      ex: /ifs/faculty/narr/schizo/DEPRESSION/FS_temp/DE_143_02/mri/T1_masked.nii.gz
    3. Open the "1st Subject" module and paste in the first entry of the "Raw Data" module
    4. Open the Variables window by pressing "command"+ "2" or going to Windows > Variables in the top menu bar. Change the dir variable to /ifs/faculty/narr/schizo/DEPRESSION/
    5. Make sure the pipeline will be run on the BMAP server:
      1. Open the Server Changer by pressing "command"+ "d" or by going to Tools > Server Changer
      2. Change the Select option to All Components
      3. Select medulla.bmap.ucla.edu from the drop down and press Change
    6. Press the "Play" button to start the script
  4. Creating Jacobians:
    1. a. Download and open TBM_make_jacobians.pipe in pipeline
    2. b. Open the "original input (Data)" module and paste in a list of each subjects' T1_masked.nii.gz with complete directory location. This will be the same list of input as the "Raw Data" module of TBM_Make_Atlas.pipe
  5. Volume Regression Analysis: requires jacobians for all the subjects you want to include.

Instructions for Freesurfer Segmentation Edits & Stats

 

Checking freesurfer files:

  • Open a terminal window and log in to the NRB server
  • ssh -XY @ssh.bmap.ucla.edu
  • ssh cerebro-mp1:
    ssh -XY <user_id>@cerebro-mp1.bmap.ucla.edu
  • go to freesurfer file directory: (the command "cd" changes directory)
    cd /ifs/faculty/narr/schizo/DEPRESSION/FS_temp
  • set the directory to your current one:
    setenv SUBJECTS_DIR /ifs/faculty/narr/schizo/DEPRESSION/FS_temp
    (if using bash shell, use: SUBJECTS_DIR=/ifs/faculty/narr/schizo/DEPRESSION/FS_temp)
  • open freesurfer's image viewer Tkmedit
    tkmedit brainmask.mgz -surface lh.pial -aux-surface rh.pial

Checking freesurfer files:

  • Open a terminal window and log in to the NRB server
    ssh -XY <user_id>@cerebro-mp1.bmap.ucla.edu
  • go to freesurfer file directory: (the command "cd" changes directory)
    cd /ifs/faculty/narr/schizo/DEPRESSION/FS_temp
  • set the directory to your current one:
    setenv SUBJECTS_DIR /ifs/faculty/narr/schizo/DEPRESSION/FS_temp
    submit the following commands:
    • aparcstats2table --subjects DE_???_?? --hemi rh --meas thickness --skip --tablefile rh_aparc_stats_MMDDYY.txt
    • aparcstats2table --subjects DE_???_?? --hemi lh --meas thickness --skip --tablefile lh_aparc_stats_MMDDYY.txt

Instructions For GABA LCModel Processing

Transferring Data to Offline

  1. MEGA-PRESS data should be collected directly from the scanner host computer after each acquisition either with an external flash drive or burning the spectroscopy data onto a CD.
  2. Highlight the study at the top level shown below.
  3. On the top of the patient browser, select 'Transfer', then select 'Export to OFF-line'.
  4. Select the correct path to save data file.
  5. If an external USB drive is used, the 'F:\' should be selected before saving the data.
  6. Check the 'Local Job Status' window to make sure all files have been saved before leaving.

LCModel Processing Steps

  1. Check the version of LCModel before processing data.
  2. The older LCModel should be named '.lcmodel-old' before processing MEGA-PRESS data.
  3. Open command prompt and execute LCModel software.
  4. Select profile 'NARR_Pilot' to process edited GABA spectra.
  5. Select water suppressed edited GABA spectrum.
  6. Check if the correct basis-set is used.
  7. Then select the non-water suppressed spectral data.
  8. The processing time is very short for the MEGA-PRESS data.
  9. Click 'Next Analysis' to process another data set.
  10. Three files are output by the software.
  11. Use command 'ps2pdf' to convert the ps file to pdf file format.
  12. The ps file contains GABA concentration, % SD, and the actual processed spectrum plot.
  13. When exiting LCModel, it is best NOT to save, so click 'Exit & Forget', unless you know what you are doing.

Instructions for LCModel

 

LCMODEL DATA ANALYSIS:
 
General login: *****
Launch VMware
Open Fedora –wait, click play
Login: ******
Launch a terminal
cd .lcmodel/
 
To open lcmodel:
./lcmgui
Select user Profile –
Select Siemens file – go to root and media to open flash
Open 1st WS file
Asks for NWS file – go to root and open file
run lcmodel – next analysis
Exit
 
Notes:
 
Can preview the data
3 outputs- ps, csv and table
covert ps to pdf in another terminal
drag ps to desktop
ps2pdf
 
For rating data:
SNR < 4 is bad
FWHM > .1 ppm is bad