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1. --load-pathstats-from-file will ... | 1. --load-pathstats-from-file will load the statistics from all the subjects specifiec in lh_cst_priormni_overall_pathstats file |
Tract Statistics
Remember...
For each new terminal that you open, you must do:
setenv SUBJECTS_DIR $TUTORIAL_DATA/diffusion_recons cd $TUTORIAL_DATA/diffusion_tutorial
This section of the tutorial will teach you how to extract statistical measures for the major white-matter tracts reconstructed by TRACULA. There are two types of statistics files that are created for each white-matter tract:
- pathstats.overall.txt - This file contains measures averaged over the whole WM tract
- pathstats.byvoxel.txt - This files contains measures as a function of location along the length of the WM tract.
To view the statistics files from TRACULA for the left cortico-spinal tract of subject Diff001, cd into one subject's directory where the stats are located for this specific tract:
cd $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt
pathstats.overall.txt
You can view the overall path stats by doing:
gedit $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt &
Note that lines preceded by the # sign are "commented out". When looking at this file you will see something like this:
# Title Pathway Statistics # # generating_program /usr/local/freesurfer/dev/bin/dmri_pathstats # cvs_version # cmdline /usr/local/freesurfer/dev/bin/dmri_pathstats --intrc /autofs/cluster/f reesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14/initmni /regflt/lh.cst_AS_avg32_mni_flt --dtbase /autofs/cluster/freesurfer/subjects/dif fusion_tutorial/Diff001/dmri/dtifit --path lh.cst --subj Diff001 --out /autofs/c luster/freesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14 /initmni/regflt/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt --outvox /autofs/c luster/freesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14 /initmni/regflt/lh.cst_AS_avg32_mni_flt/pathstats.byvoxel.txt # sysname Linux # hostname compute-0-10.local # machine x86_64 # user ayendiki # anatomy_type pathway # # subjectname Diff001 # pathwayname lh.cst # Count 400 Volume 416 Len_Min 44 Len_Max 83 Len_Avg 59.0325 Len_Center 55 AD_Avg 0.00103 AD_Avg_Weight 0.00105892 AD_Avg_Center 0.00104386 RD_Avg 0.00047195 RD_Avg_Weight 0.000461937 RD_Avg_Center 0.000487178 MD_Avg 0.000657965 MD_Avg_Weight 0.000660932 MD_Avg_Center 0.000672737 FA_Avg 0.472827 FA_Avg_Weight 0.495202 FA_Avg_Center 0.457536
This text file contains various diffusion measures, averaged over the entire white-matter tract (for CST). The measures include:
- Number of sample paths in the WM tract
- Tract volume (in voxels)
- Maximum, minimum and average length of sample paths
- Length of the highest-probability (a.k.a. maximum a posteriori) path
- Axial diffusivity (average over the entire support of the path distribution, weighted average over the entire support of the path distribution, and average over highest-probability path only)
- Radial diffusivity (as above)
- Mean diffusivity (as above)
- Fractional anisotropy (as above)
pathstats.byvoxel.txt
Now take a look at the by voxel stats:
gedit $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/pathstats.byvoxel.txt &
It will look something like this:
# Title Pathway Statistics # # generating_program /usr/local/freesurfer/dev/bin/dmri_pathstats # cvs_version # cmdline /usr/local/freesurfer/dev/bin/dmri_pathstats --intrc /autofs/cluster/freesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14/initmni/regflt/lh.cst_AS_avg32_mni_flt --dtbase /autofs/cluster/freesurfer/subjects/diffusion_tutorial/Diff001/dmri/dtifit --path lh.cst --subj Diff001 --out /autofs/cluster/freesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14/initmni/regflt/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt --outvox /autofs/cluster/freesurfer/subjects/diffusion_tutorial/Diff001/dpath/5cpts/priormni/seg14/initmni/regflt/lh.cst_AS_avg32_mni_flt/pathstats.byvoxel.txt # sysname Linux # hostname compute-0-10.local # machine x86_64 # user ayendiki # anatomy_type pathway # # subjectname Diff001 # pathwayname lh.cst # # pathway start x y z AD RD MD FA 64 63 9 0.000948384 0.00073031 0.000803001 0.208943 64 63 10 0.000925661 0.000457926 0.000613837 0.421615 65 63 11 0.000894246 0.000381521 0.000552429 0.498782 66 64 12 0.000968373 0.000502922 0.000658072 0.433094 66 64 13 0.000863534 0.000414835 0.000564402 0.461517 66 64 14 0.000770136 0.000358582 0.000495767 0.49394 67 64 15 0.000816154 0.000359865 0.000511961 0.547635 67 65 16 0.000948329 0.000367791 0.000561303 0.547419 68 65 17 0.00106946 0.000358134 0.000595243 0.606953 68 65 18 0.00151718 0.000592101 0.000900461 0.534194 68 65 19 0.00135883 0.000377419 0.000704556 0.675608 69 65 20 0.00126399 0.000470638 0.000735089 0.57121 69 66 21 0.00145087 0.000448438 0.000782583 0.639517 70 66 22 0.00124617 0.000204701 0.000551856 0.816332 70 66 23 0.00138642 0.000415134 0.000738896 0.650657 71 66 24 0.00134187 0.000385197 0.000704089 0.678151 71 66 25 0.00108983 0.000289931 0.000556565 0.729769 71 66 26 0.00111074 0.000307493 0.000575241 0.693343 72 66 27 0.00117242 0.000398032 0.00065616 0.619191 72 66 28 0.00118738 0.000448541 0.000694819 0.568624 73 66 29 0.00116659 0.000379914 0.000642141 0.613363 73 66 30 0.00121899 0.000442094 0.000701061 0.578963 74 66 31 0.00122871 0.000405738 0.000680061 0.61046 74 66 32 0.00124634 0.000386429 0.000673065 0.632008 74 66 33 0.00114455 0.000346198 0.000612314 0.645275 75 66 34 0.00112261 0.000553555 0.000743239 0.42294 75 66 35 0.00110073 0.00039228 0.000628431 0.585723 75 66 36 0.00107757 0.000424713 0.000642332 0.547048 76 65 37 0.00118618 0.000364568 0.000638438 0.650797 76 65 38 0.00110045 0.000451365 0.000667728 0.549521 76 65 39 0.00106488 0.000434208 0.000644432 0.531777 77 65 40 0.000936571 0.000390726 0.000572674 0.504019 78 65 41 0.000790065 0.000547796 0.000628552 0.222685 79 64 41 0.000737992 0.000527606 0.000597735 0.200474 78 63 42 0.000864033 0.000533149 0.000643444 0.291817 78 63 43 0.000783214 0.000517068 0.000605783 0.256042 77 63 43 0.000805146 0.000489529 0.000594735 0.301222 77 62 44 0.000815787 0.000565983 0.000649251 0.224909 77 62 45 0.000750971 0.000602391 0.000651918 0.156881 76 62 45 0.000854533 0.000567732 0.000663332 0.252796 76 61 46 0.000677428 0.00050014 0.000559236 0.193441 75 61 47 0.000852325 0.000501722 0.00061859 0.339727 75 60 48 0.000760404 0.000537457 0.000611772 0.313612 74 60 49 0.000957188 0.000488566 0.000644774 0.472547 74 60 50 0.000904047 0.000427675 0.000586466 0.445552 73 59 51 0.00104383 0.000519813 0.000694486 0.428315 72 59 52 0.00104503 0.000475882 0.000665599 0.474443 72 59 53 0.00091483 0.00047261 0.000620017 0.409087 71 58 54 0.00108069 0.00052145 0.000707864 0.442797 71 58 55 0.00100269 0.00063635 0.000758462 0.300433 70 57 56 0.00104198 0.000577465 0.000732302 0.371814 70 57 57 0.000988028 0.000735057 0.000819381 0.208577 69 57 58 0.00118052 0.000811759 0.00093468 0.224508 69 56 59 0.00139945 0.00114833 0.00123204 0.117485 68 56 60 0.00123777 0.000847968 0.000977904 0.246951 # pathway end
This text file contains various diffusion measures in each voxel along the highest-probability path. The first three entries in each row are the x, y, z coordinates of the voxel. The remaining entries are the axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy at that voxel.
pathstats.overall.txt to Table Conversion
Measures can be extracted from these files to be analyzed further, e.g., for tract-based group analysis. Specifically, the text files can be converted into a table using the command tractstats2table for doing GLM analyses using mri_glmfit or any other statistical software (SPSS, Excel, Statview etc.)
To extract all diffusion measures into a table do the following:
tractstats2table --inputs $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt --overall --tablefile Diff001_LH.CST.All.table
- Notice we have specified the stats file with --inputs.
- The --overall flag tells tractstats2table to expect the overall path stats file (stats averaged over the entire WM tract) as opposed to the per voxel stats (specified with the --byvoxel flag instead).
- The output file will be called Diff001_LH.CST.All.table as specified by the --tablefile flag.
Take a look at the resulting table file:
gedit $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/Diff001_LH.CST.All.table &
Instead of extracting all the measures from pathstats.overall.txt for CST, we could grab just a few specific measures. For example, to extract only the Average Fractional Anisotropy along the Left Cortico-spinal tract, do the following:
tractstats2table --inputs $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt --overall --only-measures FA_Avg --tablefile Diff001_LH.CST.FA.table
- Notice the --only-measures flag followed by FA_Avg to indicate we are only interested in having the average FA over the path in table format for this path (CST).
For a group analysis that has multiple subjects, tractstats2table can be used to combine all the subjects' diffusion measures from the CST path.overall.txt files into a single table that can be used for analysis with mri_glmfit or any other statistics software
An easy way to do this is to create a text file that contains the names of the subjects and paths to their pathstats.overall.txt files. An example is given below:
$TUTORIAL_DATA/Diff001/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff002/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff003/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff004/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff005/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff006/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff007/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff008/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff009/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt $TUTORIAL_DATA/Diff010/dpath/lh.cst_AS_avg32_mni_flt/pathstats.overall.txt
Once this is created and saved as lh_cst_priormni_overall_pathstats, it can be passed as a parameter to the tractstats2table command. The following command will create a table with all the subjects specified in the lh_cst_priormni_overall_pathstats file and all the diffusion measures from pathstats.overall.txt for each subject.
tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh_cst_priormni_overall_pathstats --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/LH.CST.All.Priormni.table
To extract only specific measures like FA_Avg, do the following:
tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh_cst_priormni_overall_pathstats --overall --only-measures FA_Avg --tablefile $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/LH.CST.FA.Priormni.table
- Note the use of the --only-measures flag again.
- --load-pathstats-from-file will load the statistics from all the subjects specifiec in lh_cst_priormni_overall_pathstats file
You can look at these tables in OpenOffice (or any other spreadsheet program). For example, to open the table LH.CST.All.Priormni.table in OpenOffice, do the following:
oocalc $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/LH.CST.All.Priormni.table
From here, you could use these stats files to run a group analysis on the tracts.