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| = Tract Statistics = | = Tract statistics = |
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| 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: |
This section of the tutorial will teach you how to extract statistics on anisotropy and diffusivity measures for the white-matter pathways reconstructed by TRACULA. There are two types of statistics files that are created for each white-matter pathway: * pathstats.overall.txt - This file contains measures averaged over the whole pathway * pathstats.byvoxel.txt - This file contains measures as a function of position along the trajectory of the pathway. For example, the statistics files for the left inferior longitudinal fasciculus (ILF) of subject elmo.2012, showing measures for the entire left ILF or along the left ILF, are, respectively: {{{ $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt }}} == Anisotropy and diffusivity averaged over an entire pathway == You can view an example of the overall pathway stats by doing: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt & }}} This file will look like this: |
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| # 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 |
# cvs_version # cmdline /usr/local/freesurfer/dev/bin/dmri_pathstats --intrc /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr --dtbase /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dmri/dtifit --path lh.ilf --subj elmo.2012 --out /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --outvox /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt |
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| # hostname compute-0-10.local | # hostname compute-0-29 |
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| # 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: |
# subjectname elmo.2012 # pathwayname lh.ilf # Count 1500 Volume 167 Len_Min 29 Len_Max 64 Len_Avg 45.008 Len_Center 37 AD_Avg 0.00131194 AD_Avg_Weight 0.00139891 AD_Avg_Center 0.001268 RD_Avg 0.000686486 RD_Avg_Weight 0.000770628 RD_Avg_Center 0.000635293 MD_Avg 0.00089497 MD_Avg_Weight 0.000980054 MD_Avg_Center 0.000846196 FA_Avg 0.414059 FA_Avg_Weight 0.392266 FA_Avg_Center 0.408256 }}} This text file contains various diffusion measures, averaged over the entire white-matter tract. The measures include: |
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| == 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: |
=== Converting pathstats.overall.txt files to a table for group analyses === 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}}} and then used for doing GLM analyses with [[mri_glmfit]] or any other statistical software (SPSS, Excel, Statview etc.) To extract all diffusion measures for the left ILF from subject elmo.2012 into a table, do the following: {{{ tractstats2table --inputs $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.elmo.2012.All.table }}} * The argument to the {{{--inputs}}} option specifies the input stats file. * The {{{--overall}}} option tells tractstats2table to expect the overall path stats file (stats averaged over the entire left ILF), as opposed to the stats along the trajectory of the tract (which would be specified with the {{{--byvoxel}}} option instead). * The argument to the {{{--tablefile}}} option specifies the output file. Take a look at the resulting table file: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.elmo.2012.All.table & }}} For a group analysis, {{{tractstats2table}}} can be used to combine the diffusion measures in {{{pathstats.overall.txt}}} from multiple subjects into a single table, which can then be used for analysis with [[mri_glmfit]] or any other statistical software. To do this, you will have to create a text file that lists the full path to every subject's {{{pathstats.overall.txt}}} file. An example of such a list for all 3 tutorial subjects is shown below: {{{ $TUTORIAL_DATA/diffusion_tutorial/elmo.2005/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2008/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt }}} Create a text file that contains the list above and name it as follows: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list & }}} The following command will use this list to create a table with the diffusion measures from all the files listed above: {{{ tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table }}} * The argument to the {{{--load-pathstats-from-file}}} option specifies the text file that contains the list of all the statistics files that will be loaded. Take a look at the resulting table file: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table & }}} Instead of extracting all measures included in the tract statistics files, we may be interested only in a few specific measures. For example, to extract only the average FA for each subject, do the following: {{{ tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list --overall --only-measures FA_Avg --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.FA_Avg.table }}} * The argument to the {{{--only-measures}}} option specifies which measure we want to extract from the statistics files. Instead of FA_Avg, this could be the name of any of the measures included in {{{pathstats.overall.txt.}}} You can look at these tables in !OpenOffice (or any other spreadsheet program). For example, to open the file {{{lh.ilf.All.table}}} in !OpenOffice, do the following: {{{ oocalc $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table }}} From here, you could use these stats tables to run a group analysis on the tracts. == Anisotropy and diffusivity along the trajectory of a pathway == Now take a look at the stats as a function of position along the trajectory of the same tract: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt & }}} It will look like this: |
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| # 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 |
# cvs_version # cmdline /usr/local/freesurfer/dev/bin/dmri_pathstats --intrc /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr --dtbase /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dmri/dtifit --path lh.ilf --subj elmo.2012 --out /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --outvox /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt |
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| # hostname compute-0-10.local | # hostname compute-0-29 |
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| # subjectname Diff001 # pathwayname lh.cst |
# subjectname elmo.2012 # pathwayname lh.ilf |
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| 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 |
x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 86 71 16 0.00124639 0.000810355 0.000955702 0.296343 0.00124166 0.000683586 0.000869599 0.375502 86 72 15 0.000758499 0.000690337 0.000713058 0.0665528 0.00120352 0.000674202 0.00085063 0.365702 85 72 14 0.000819579 0.000601256 0.00067403 0.196614 0.00111348 0.000618912 0.00078378 0.353662 84 72 13 0.000970979 0.00067094 0.000770953 0.227346 0.00115739 0.000679319 0.000838683 0.329086 84 71 13 0.0010519 0.000845654 0.000914402 0.174291 0.00117946 0.000675255 0.000843332 0.342993 84 70 13 0.00122524 0.00075747 0.000913395 0.295734 0.00127004 0.000700568 0.00089039 0.368428 84 69 13 0.0013762 0.000607907 0.000864005 0.475513 0.00130121 0.000666051 0.000877759 0.405086 83 68 14 0.00117165 0.000572571 0.000772264 0.433612 0.00127088 0.000631783 0.000844803 0.427719 83 67 14 0.00122987 0.000573616 0.000792367 0.452554 0.00123866 0.000625767 0.000830053 0.422219 83 66 14 0.00120132 0.000599483 0.000800095 0.411401 0.00118774 0.00062832 0.000814796 0.408966 83 65 14 0.00130532 0.000741545 0.000929471 0.341101 0.00117765 0.000649599 0.000825623 0.38951 83 64 15 0.00113069 0.000744614 0.000873306 0.303024 0.00124994 0.000716112 0.000894054 0.35574 83 63 15 0.00145392 0.000843014 0.00104665 0.338389 0.00160184 0.000956015 0.00117128 0.342898 83 62 15 0.00150758 0.000704525 0.000972208 0.454268 0.00184354 0.00110231 0.0013494 0.361096 82 61 15 0.00168556 0.000719335 0.00104141 0.500387 0.00187725 0.00105482 0.00132898 0.413339 82 60 16 0.00149165 0.000655993 0.000934546 0.482961 0.00174103 0.000915708 0.00119082 0.459582 82 59 16 0.00178469 0.000676534 0.00104592 0.547817 0.00181009 0.000942766 0.00123188 0.47797 82 58 16 0.00187731 0.000555021 0.000995783 0.650825 0.00176598 0.000879462 0.00117498 0.482668 82 57 17 0.00136583 0.000342585 0.000683666 0.706805 0.00183719 0.00101521 0.00128919 0.444575 82 56 17 0.00149454 0.000361014 0.000738857 0.718399 0.00172875 0.000879471 0.00116258 0.466697 82 55 17 0.00164246 0.000404404 0.000817091 0.714028 0.00143606 0.000654734 0.000915172 0.485324 81 54 17 0.00110069 0.000505138 0.000703656 0.462108 0.00123971 0.000546461 0.000777551 0.491684 81 53 18 0.00149581 0.000503958 0.000834577 0.601599 0.00138836 0.000547033 0.000827479 0.539068 81 52 18 0.00130913 0.000454745 0.00073954 0.597531 0.00133457 0.000539894 0.000804789 0.533393 81 51 18 0.00131507 0.000631822 0.000859572 0.448947 0.00131177 0.000606845 0.000841826 0.469117 81 50 18 0.00135444 0.000747886 0.000950069 0.362522 0.00129975 0.000659834 0.000873148 0.416883 81 49 18 0.00120955 0.000643043 0.000831879 0.404422 0.00126551 0.00064144 0.000849466 0.418424 80 48 19 0.00140649 0.000619495 0.000881827 0.476057 0.00134196 0.000607405 0.000852266 0.47251 80 47 19 0.00124703 0.00054436 0.000778584 0.493392 0.00129913 0.000595745 0.000830194 0.470203 80 46 19 0.00123713 0.000562425 0.000787325 0.473597 0.00131166 0.000608192 0.000842689 0.465411 80 45 19 0.00131702 0.000638351 0.000864576 0.436198 0.00131184 0.000638683 0.000863079 0.443722 79 44 20 0.000961184 0.000655564 0.000757438 0.251941 0.00120554 0.000691043 0.000862543 0.349984 79 43 20 0.00104516 0.000760429 0.000855339 0.211843 0.00118236 0.000713172 0.000869568 0.323664 79 42 20 0.0010671 0.000695726 0.000819518 0.290868 0.00118518 0.000688767 0.000854257 0.347132 79 41 20 0.000951325 0.000643122 0.000745857 0.290616 0.00115072 0.000662836 0.000825473 0.352023 80 40 20 0.00111846 0.000771887 0.00088741 0.232294 0.00118544 0.000701789 0.000863008 0.328079 81 40 20 0.000989299 0.000649715 0.00076291 0.283576 0.00114976 0.000669422 0.000829546 0.343642 |
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| 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 for Left Cortico-Spinal tract 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 $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/lh.cst_AS.All.table }}} 1. Notice we have specified the stats file with --inputs. 1. 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). 1. 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/lh.cst_AS.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 $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/lh.cst_AS.FA_Avg.table }}} 1. 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 (Left CST). Take a look at the resulting table file: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/Diff001/dpath/lh.cst_AS_avg32_mni_flt/lh.cst_AS.FA_Avg.table & }}} 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/diffusion_tutorial/TraculaStatFiles/Diff001/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff002/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff003/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff004/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff005/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff006/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff007/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff008/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff009/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/Diff010/dpath/priormni/lh.cst_AS_avg32_mni_bbr/pathstats.overall.txt }}} Once this is created and saved as lh.cst_AS.overall.pathstats.list, it can be passed as a parameter to the tractstats2table command. This file has already been created for you. To open this file and view it's contents, do the following {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh.cst_AS.overall.pathstats.list & }}} The following command will create a table with all the subjects specified in the lh.cst_AS.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_AS.overall.pathstats.list --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh.cst_AS.All.table }}} We've generated tables of all Diffusion measures for the 10 tutorial subjects for all the 18 tracts. They can be found here: {{{ ls $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/*.All.table }}} To extract only specific measures like FA_Avg, do the following: {{{ tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh.cst_AS.overall.pathstats.list --overall --only-measures FA_Avg --tablefile $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh.cst_AS.FA_Avg.table }}} 1. Note the use of the --only-measures flag again. 1. --load-pathstats-from-file will load the statistics from all the subjects specific in lh.cst_AS.overall.pathstats.list file 1. The FA_Avg parameter for the --only-measures flag can be replaced with other measures specified in pathstats.overall.txt file You can look at these tables in !OpenOffice (or any other spreadsheet program). For example, to open the table '''lh.cst_AS.All.table''' in !OpenOffice, do the following: {{{ oocalc $TUTORIAL_DATA/diffusion_tutorial/TraculaStatFiles/lh.cst_AS.All.table }}} From here, you could use these stats files to run a group analysis on the tracts. |
This text file contains various diffusion measures, one row for each position along the trajectory of the path. The first three entries in each row are the x, y, z coordinates in native diffusion space. The next four entries are the axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy at that position on the maximum a posteriori path. The last four entries are the axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy at the same position, averaged over all sampled paths. === Converting pathstats.byvoxel.txt files to a table for group analyses === The pathstats.byvoxel.txt files will generally not contain the same number of positions (rows) for each subject because the tracts are reconstructed in each subject's native diffusion space and not in a template space. Thus they are not ready for performing group analyses yet. To combine these files from multiple subjects, interpolating the anisotropy and diffusivity values at corresponding positions along the tract for all subjects, run the following: {{{ trac-all -stat -c $TUTORIAL_DATA/diffusion_tutorial/dmrirc.tutorial }}} This will create a directory named '''stats''' under the main TRACULA output directory and save one table per tract per diffusion measure. In these tables, each row is a different position along the trajectory of the tract and each column is a different subject. To examine the table of average FA along the left ILF, do the following: {{{ gedit $TUTORIAL_DATA/diffusion_tutorial/stats/lh.ilf_AS.avg33_mni_bbr.FA_Avg.txt & }}} The contents of this file will look like this: {{{ elmo.2005 elmo.2008 elmo.2012 NaN 0.335817 NaN 0.373068 0.35773 0.263802 0.37555 0.372835 0.280039 0.389334 0.373771 0.304207 0.403752 0.36399 0.340167 0.418984 0.363519 0.333422 0.433291 0.378936 0.356918 0.441835 0.397896 0.355258 0.432407 0.398355 0.356802 0.428443 0.399408 0.381642 0.428464 0.406425 0.410158 0.417515 0.415535 0.428911 ... }}} The first row tells you the subject name for the corresponding column of FA values. Note that for some data sets, there will be some NaN ("not a number") values in the beginning or end of the tract, because the tract has a slightly different length for each data set and the endings will not always correspond. For the purposes of a statistical analysis, you can ignore the endings, use only the data points that are not NaN, or pool together the data points from the first few or last few positions. From here, you could use these stats tables to run a group analysis on the tracts. |
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 statistics on anisotropy and diffusivity measures for the white-matter pathways reconstructed by TRACULA. There are two types of statistics files that are created for each white-matter pathway:
- pathstats.overall.txt - This file contains measures averaged over the whole pathway
- pathstats.byvoxel.txt - This file contains measures as a function of position along the trajectory of the pathway.
For example, the statistics files for the left inferior longitudinal fasciculus (ILF) of subject elmo.2012, showing measures for the entire left ILF or along the left ILF, are, respectively:
$TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt
Anisotropy and diffusivity averaged over an entire pathway
You can view an example of the overall pathway stats by doing:
gedit $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt &
This file will look 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 /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr --dtbase /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dmri/dtifit --path lh.ilf --subj elmo.2012 --out /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --outvox /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt # sysname Linux # hostname compute-0-29 # machine x86_64 # user ayendiki # anatomy_type pathway # # subjectname elmo.2012 # pathwayname lh.ilf # Count 1500 Volume 167 Len_Min 29 Len_Max 64 Len_Avg 45.008 Len_Center 37 AD_Avg 0.00131194 AD_Avg_Weight 0.00139891 AD_Avg_Center 0.001268 RD_Avg 0.000686486 RD_Avg_Weight 0.000770628 RD_Avg_Center 0.000635293 MD_Avg 0.00089497 MD_Avg_Weight 0.000980054 MD_Avg_Center 0.000846196 FA_Avg 0.414059 FA_Avg_Weight 0.392266 FA_Avg_Center 0.408256
This text file contains various diffusion measures, averaged over the entire white-matter tract. 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)
Converting pathstats.overall.txt files to a table for group analyses
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 and then used for doing GLM analyses with mri_glmfit or any other statistical software (SPSS, Excel, Statview etc.)
To extract all diffusion measures for the left ILF from subject elmo.2012 into a table, do the following:
tractstats2table --inputs $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.elmo.2012.All.table
The argument to the --inputs option specifies the input stats file.
The --overall option tells tractstats2table to expect the overall path stats file (stats averaged over the entire left ILF), as opposed to the stats along the trajectory of the tract (which would be specified with the --byvoxel option instead).
The argument to the --tablefile option specifies the output file.
Take a look at the resulting table file:
gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.elmo.2012.All.table &
For a group analysis, tractstats2table can be used to combine the diffusion measures in pathstats.overall.txt from multiple subjects into a single table, which can then be used for analysis with mri_glmfit or any other statistical software.
To do this, you will have to create a text file that lists the full path to every subject's pathstats.overall.txt file. An example of such a list for all 3 tutorial subjects is shown below:
$TUTORIAL_DATA/diffusion_tutorial/elmo.2005/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2008/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt
Create a text file that contains the list above and name it as follows:
gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list &
The following command will use this list to create a table with the diffusion measures from all the files listed above:
tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list --overall --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table
The argument to the --load-pathstats-from-file option specifies the text file that contains the list of all the statistics files that will be loaded.
Take a look at the resulting table file:
gedit $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table &
Instead of extracting all measures included in the tract statistics files, we may be interested only in a few specific measures. For example, to extract only the average FA for each subject, do the following:
tractstats2table --load-pathstats-from-file $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.list --overall --only-measures FA_Avg --tablefile $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.FA_Avg.table
The argument to the --only-measures option specifies which measure we want to extract from the statistics files. Instead of FA_Avg, this could be the name of any of the measures included in pathstats.overall.txt.
You can look at these tables in OpenOffice (or any other spreadsheet program). For example, to open the file lh.ilf.All.table in OpenOffice, do the following:
oocalc $TUTORIAL_DATA/diffusion_tutorial/lh.ilf.All.table
From here, you could use these stats tables to run a group analysis on the tracts.
Anisotropy and diffusivity along the trajectory of a pathway
Now take a look at the stats as a function of position along the trajectory of the same tract:
gedit $TUTORIAL_DATA/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt &
It will look 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 /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr --dtbase /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dmri/dtifit --path lh.ilf --subj elmo.2012 --out /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.overall.txt --outvox /space/freesurfer/subjects/diffusion_tutorial/elmo.2012/dpath/lh.ilf_AS_avg33_mni_bbr/pathstats.byvoxel.txt # sysname Linux # hostname compute-0-29 # machine x86_64 # user ayendiki # anatomy_type pathway # # subjectname elmo.2012 # pathwayname lh.ilf # # pathway start x y z AD RD MD FA AD_Avg RD_Avg MD_Avg FA_Avg 86 71 16 0.00124639 0.000810355 0.000955702 0.296343 0.00124166 0.000683586 0.000869599 0.375502 86 72 15 0.000758499 0.000690337 0.000713058 0.0665528 0.00120352 0.000674202 0.00085063 0.365702 85 72 14 0.000819579 0.000601256 0.00067403 0.196614 0.00111348 0.000618912 0.00078378 0.353662 84 72 13 0.000970979 0.00067094 0.000770953 0.227346 0.00115739 0.000679319 0.000838683 0.329086 84 71 13 0.0010519 0.000845654 0.000914402 0.174291 0.00117946 0.000675255 0.000843332 0.342993 84 70 13 0.00122524 0.00075747 0.000913395 0.295734 0.00127004 0.000700568 0.00089039 0.368428 84 69 13 0.0013762 0.000607907 0.000864005 0.475513 0.00130121 0.000666051 0.000877759 0.405086 83 68 14 0.00117165 0.000572571 0.000772264 0.433612 0.00127088 0.000631783 0.000844803 0.427719 83 67 14 0.00122987 0.000573616 0.000792367 0.452554 0.00123866 0.000625767 0.000830053 0.422219 83 66 14 0.00120132 0.000599483 0.000800095 0.411401 0.00118774 0.00062832 0.000814796 0.408966 83 65 14 0.00130532 0.000741545 0.000929471 0.341101 0.00117765 0.000649599 0.000825623 0.38951 83 64 15 0.00113069 0.000744614 0.000873306 0.303024 0.00124994 0.000716112 0.000894054 0.35574 83 63 15 0.00145392 0.000843014 0.00104665 0.338389 0.00160184 0.000956015 0.00117128 0.342898 83 62 15 0.00150758 0.000704525 0.000972208 0.454268 0.00184354 0.00110231 0.0013494 0.361096 82 61 15 0.00168556 0.000719335 0.00104141 0.500387 0.00187725 0.00105482 0.00132898 0.413339 82 60 16 0.00149165 0.000655993 0.000934546 0.482961 0.00174103 0.000915708 0.00119082 0.459582 82 59 16 0.00178469 0.000676534 0.00104592 0.547817 0.00181009 0.000942766 0.00123188 0.47797 82 58 16 0.00187731 0.000555021 0.000995783 0.650825 0.00176598 0.000879462 0.00117498 0.482668 82 57 17 0.00136583 0.000342585 0.000683666 0.706805 0.00183719 0.00101521 0.00128919 0.444575 82 56 17 0.00149454 0.000361014 0.000738857 0.718399 0.00172875 0.000879471 0.00116258 0.466697 82 55 17 0.00164246 0.000404404 0.000817091 0.714028 0.00143606 0.000654734 0.000915172 0.485324 81 54 17 0.00110069 0.000505138 0.000703656 0.462108 0.00123971 0.000546461 0.000777551 0.491684 81 53 18 0.00149581 0.000503958 0.000834577 0.601599 0.00138836 0.000547033 0.000827479 0.539068 81 52 18 0.00130913 0.000454745 0.00073954 0.597531 0.00133457 0.000539894 0.000804789 0.533393 81 51 18 0.00131507 0.000631822 0.000859572 0.448947 0.00131177 0.000606845 0.000841826 0.469117 81 50 18 0.00135444 0.000747886 0.000950069 0.362522 0.00129975 0.000659834 0.000873148 0.416883 81 49 18 0.00120955 0.000643043 0.000831879 0.404422 0.00126551 0.00064144 0.000849466 0.418424 80 48 19 0.00140649 0.000619495 0.000881827 0.476057 0.00134196 0.000607405 0.000852266 0.47251 80 47 19 0.00124703 0.00054436 0.000778584 0.493392 0.00129913 0.000595745 0.000830194 0.470203 80 46 19 0.00123713 0.000562425 0.000787325 0.473597 0.00131166 0.000608192 0.000842689 0.465411 80 45 19 0.00131702 0.000638351 0.000864576 0.436198 0.00131184 0.000638683 0.000863079 0.443722 79 44 20 0.000961184 0.000655564 0.000757438 0.251941 0.00120554 0.000691043 0.000862543 0.349984 79 43 20 0.00104516 0.000760429 0.000855339 0.211843 0.00118236 0.000713172 0.000869568 0.323664 79 42 20 0.0010671 0.000695726 0.000819518 0.290868 0.00118518 0.000688767 0.000854257 0.347132 79 41 20 0.000951325 0.000643122 0.000745857 0.290616 0.00115072 0.000662836 0.000825473 0.352023 80 40 20 0.00111846 0.000771887 0.00088741 0.232294 0.00118544 0.000701789 0.000863008 0.328079 81 40 20 0.000989299 0.000649715 0.00076291 0.283576 0.00114976 0.000669422 0.000829546 0.343642 # pathway end
This text file contains various diffusion measures, one row for each position along the trajectory of the path. The first three entries in each row are the x, y, z coordinates in native diffusion space. The next four entries are the axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy at that position on the maximum a posteriori path. The last four entries are the axial diffusivity, radial diffusivity, mean diffusivity, and fractional anisotropy at the same position, averaged over all sampled paths.
Converting pathstats.byvoxel.txt files to a table for group analyses
The pathstats.byvoxel.txt files will generally not contain the same number of positions (rows) for each subject because the tracts are reconstructed in each subject's native diffusion space and not in a template space. Thus they are not ready for performing group analyses yet. To combine these files from multiple subjects, interpolating the anisotropy and diffusivity values at corresponding positions along the tract for all subjects, run the following:
trac-all -stat -c $TUTORIAL_DATA/diffusion_tutorial/dmrirc.tutorial
This will create a directory named stats under the main TRACULA output directory and save one table per tract per diffusion measure. In these tables, each row is a different position along the trajectory of the tract and each column is a different subject.
To examine the table of average FA along the left ILF, do the following:
gedit $TUTORIAL_DATA/diffusion_tutorial/stats/lh.ilf_AS.avg33_mni_bbr.FA_Avg.txt &
The contents of this file will look like this:
elmo.2005 elmo.2008 elmo.2012 NaN 0.335817 NaN 0.373068 0.35773 0.263802 0.37555 0.372835 0.280039 0.389334 0.373771 0.304207 0.403752 0.36399 0.340167 0.418984 0.363519 0.333422 0.433291 0.378936 0.356918 0.441835 0.397896 0.355258 0.432407 0.398355 0.356802 0.428443 0.399408 0.381642 0.428464 0.406425 0.410158 0.417515 0.415535 0.428911 ...
The first row tells you the subject name for the corresponding column of FA values. Note that for some data sets, there will be some NaN ("not a number") values in the beginning or end of the tract, because the tract has a slightly different length for each data set and the endings will not always correspond. For the purposes of a statistical analysis, you can ignore the endings, use only the data points that are not NaN, or pool together the data points from the first few or last few positions.
From here, you could use these stats tables to run a group analysis on the tracts.