Anatomical ROI analysis
This tutorial gives a brief introduction to anatomical ROI analysis which includes working with label files, extracting ROI measures from the anatomical data, group statistics etc. Make sure you have set your SUBJECTS_DIR to correct location as
setenv SUBJECTS_DIR <path_to_data>
Relationship between segmentation, parcellation and LookUp Table (LUT)
In this exercise, you will examine a segmentation, parcellation, and color lookup table to understand how they are related.
Open the subject in tkmedit using the following command
tkmedit 004 orig.mgz -aux aparc+aseg.mgz \ -seg aparc+aseg.mgz $FREESURFER_HOME/FreeSurferColorLUT.txt
Open another terminal to load the subject in tksurfer, using the following command.
tksurfer 004 lh inflated -annot aparc.annot
Finally, run the following command to display the contents of LUT
less $FREESURFER_HOME/FreeSurferColorLUT.txt
Click here to view the contents of the file.
Navigating between tkmedit and LUT -- things to do:
- Click on a point on the image loaded in tkmedit.
- See the structure name in the tkmedit Tools window.
- Look at the Aux value in the tkmedit Tools window.
- Find value in the LUT, which you have opened using the command mentioned above.
- Verify that it is the same structure as listed in tkmedit.
Navigating between tksurfer, tkmedit and LUT -- things to do:
- Click on a point in tksurfer in the superior temporal gyrus.
- Note that the name displayed in the tksurfer Tools window does not have lh or rh in it.
In tksurfer, click on the Save Point button
In tkmedit, click on Goto Point button
. - Verify the structure name in the tkmedit Tools window. Note that it DOES have an lh or rh in it.
- The Aux value should be 1030.
- In FreeSurferColorLUT.txt, verify that 1030 is ctx-lh-superiortemporal
Label files
This section gives the details of commands to load an existing label file in text editor, tkmedit, and tksurfer.
To load an existing label, for example lh.BA45.label, run
less 004/label/lh.BA45.label
To load a label in tkmedit, first load the subject you want to work on, in tkmedit.
tkmedit 004 orig.mgz
Then on the menu bar at the top of tkmedit tools window, go to File --> Label --> Load Label --> lh.BA45.label
To load the label in tksurfer, first load the subject.
tksurfer 004 lh inflated
On the menu bar at the top of tksurfer tools window, go to File --> Label --> Load Label --> lh.BA45.label
Individual Stats files
During the normal FreeSurfer processing stream, via the recon-all script, (a freesurfer tutorial is available.) some statistical output files are generated. They are kept in each subjects stats/ subdirectory, and are a result of the subcortical segmentation, aseg, and the cortical parcellation, aparc. These tables include information on each labeled region for the individual subject.
aseg.stats
The statistical output from the subcortical segmentation, called aseg.stats, is a regular text file and will contain the volumes of specific structures. For example, you can obtain information such as the volume of left hippocampus and it's mean intensity from this file.
cd $SUBJECTS_DIR/004/stats less aseg.stats
At the head of the text file there will be information about the command that was run, the version used, the user who ran it and a time stamp. Following this there is information about the volume of the entire brain. This shows the number of voxels in the brainmask (BrainMaskNVox), the volume of the brainmask (BrainMaskVol), the number of voxels in the brainseg (BrainSegNVox), the volume of the brainseg (BrainSegVol), and the intracranial volume (ICV). This part of the file also tells us that the brainmask.mgz volume is being used as BrainMask (BrainMaskFile mri/brainmask.mgz) and the aseg.mgz segmentation is being used as the SegVol (SegVolFile mri/aseg.mgz). The number of voxels and the volumes should be the same for this subject, since this part of the file also tells us that the voxel volume is 1 mm3 (VoxelVolume_mm3 1) - and volume is measured in mm3.
The next section of this file defines the column headers, field name, and units for the rest of the table. We can expect to see the Segmentation Id, Number of Voxels, Volume, Structure Name, Intensity normMean, Itensity normStdDev, Intensity normMin, Intensity normMax, and Intensity normRange for each entry in the table.
The remainder of the table shows this information for all the structures that are labeled in the aseg.
# Title Segmentation Statistics
# generating_program mri_segstats
# cvs_version $Id: mri_segstats.c,v 1.33.2.4 2008/12/21 18:04:48 greve Exp $
# cmdline mri_segstats --seg mri/aseg.mgz --sum stats/aseg.stats --pv mri/norm.mgz --excludeid 0 --brain-vol-from-seg --brainmask mri/brainmask.mgz --in mri/norm.mgz --in-intensity-name norm --in-intensity-units MR --etiv --subject
004 --surf-wm-vol --ctab /usr/local/freesurfer/stable4/ASegStatsLUT.txt
# sysname Linux
# hostname node0304
# machine x86_64
# user FS-user
# anatomy_type volume
# SUBJECTS_DIR /autofs/space/birn_045/users/BWH/buckner_data/tutorial_subjs
# subjectname 004
# BrainMaskFile mri/brainmask.mgz
# BrainMaskFileTimeStamp 2009/01/11 15:41:05
# Measure BrainMask, BrainMaskNVox, Number of Brain Mask Voxels, 1750402, unitless
# Measure BrainMask, BrainMaskVol, Brain Mask Volume, 1750402.000000, mm^3
# Measure BrainSegNotVent, BrainSegVolNotVent, Brain Segmentation Volume Without Ventricles, 1175182.000000, mm^3
# Measure BrainSeg, BrainSegNVox, Number of Brain Segmentation Voxels, 1235011, unitless
# Measure BrainSeg, BrainSegVol, Brain Segmentation Volume, 1235011.000000, mm^3
# Measure IntraCranialVol, ICV, Intracranial Volume, 1796495.343836, mm^3
# SegVolFile mri/aseg.mgz
# SegVolFileTimeStamp 2008/11/22 04:53:19
# ColorTable /usr/local/freesurfer/stable4/ASegStatsLUT.txt
# ColorTableTimeStamp 2009/01/11 07:09:19
# InVolFile mri/norm.mgz
# InVolFileTimeStamp 2008/11/21 19:10:07
# InVolFrame 0
# PVVolFile mri/norm.mgz
# PVVolFileTimeStamp 2008/11/21 19:10:07
# surface-based-volume mm3 lh-cerebral-white-matter 256451.250000
# surface-based-volume mm3 rh-cerebral-white-matter 256024.875000
# surface-based-volume mm3 tot-cerebral-white-matter 512476.125000
# ExcludeSegId 0
# VoxelVolume_mm3 1
-
-
-
# TableCol 1 ColHeader Index
# TableCol 1 FieldName Index
# TableCol 1 Units NA
# TableCol 2 ColHeader SegId
# TableCol 2 FieldName Segmentation Id
# TableCol 2 Units NA
# TableCol 3 ColHeader NVoxels
# TableCol 3 FieldName Number of Voxels
# TableCol 3 Units unitless
# TableCol 4 ColHeader Volume_mm3
# TableCol 4 FieldName Volume
# TableCol 4 Units mm^3
# TableCol 5 ColHeader StructName
# TableCol 5 FieldName Structure Name
# TableCol 5 Units NA
-
-
-
#ColHeaders Index SegId NVoxels Volume_mm3 StructName normMean normStdDev normMin normMax normRange
1 2 219775 219775.0 Left-Cerebral-White-Matter 104.1449 9.6298 23.0000 180.0000 157.0000
2 3 249186 249186.0 Left-Cerebral-Cortex 68.4475 10.9191 19.0000 154.0000 135.0000
3 4 31217 31217.0 Left-Lateral-Ventricle 21.2879 9.9687 6.0000 82.0000 76.0000
4 5 1380 1380.0 Left-Inf-Lat-Vent 37.2319 12.6153 13.0000 85.0000 72.0000
5 7 13337 13337.0 Left-Cerebellum-White-Matter 86.1768 7.6600 42.0000 124.0000 82.0000
6 8 49087 49087.0 Left-Cerebellum-Cortex 58.4803 9.5375 19.0000 96.0000 77.0000
-
-
-
aparc.stats
The statistical output from the cortical parcellation, called lh.aparc.stats and rh.aparc.stats, is a regular text file and will contain the thickness of specific structures. For example, you can obtain information such as, how big is left superior temporal gyrus and it's average thickness from this file.
cd $SUBJECTS_DIR/004/stats less lh.aparc.stats
At the head of the text file there will be information about the command that was run, the version used, the user who ran it and a time stamp. Following this there is information about the volume of the entire brain. This shows the total white matter volume (TotalWhiteMatterVolume), the number of vertices in the cortex (NumVert), and the surface area of the cortex (SurfArea). This part of the file also tells us that the lh.aparc.annot is being used as the annotation file (AnnotationFile ../label/lh.aparc.annot).
The next section of this file defines the column headers, field name, and units for the rest of the table. We can expect to see the Structure Name, Number of Vertices, Surface Area, Gray Matter Volume, Average Thickness, Thickness StDev, Integrated Rectified Mean Curvature, Integrated Rectified Gaussian Curvature, Folding Index and Intrinsic Curvature Index for each entry in the table.
The remainder of the table shows this information for all the structures that are labeled in the aseg.
# Table of FreeSurfer cortical parcellation anatomical statistics # CreationTime 2009/01/13-02:24:40-GMT # generating_program mris_anatomical_stats # cvs_version $Id: mris_anatomical_stats.c,v 1.54.2.4 2009/01/09 22:23:40 nicks Exp $ # mrisurf.c-cvs_version $Id: mrisurf.c,v 1.557.2.17 2009/01/08 17:16:51 nicks Exp $ # cmdline mris_anatomical_stats -mgz -f ../stats/lh.aparc.stats -b -a ../label/lh.aparc.annot -c ../label/aparc.annot.ctab 004 lh # sysname Linux # hostname node0323 # machine x86_64 # user FS-user # SUBJECTS_DIR /autofs/space/birn_045/users/BWH/buckner_data/tutorial_subjs # anatomy_type surface # subjectname 004 # hemi lh # AnnotationFile ../label/lh.aparc.annot # AnnotationFileTimeStamp 2009/01/12 02:40:55 # Measure Cortex, NumVert, Number of Vertices, 151295, unitless # Measure Cortex, SurfArea, Surface Area, 100640, mm^2 - - - # TableCol 1 ColHeader StructName # TableCol 1 FieldName Structure Name # TableCol 1 Units NA # TableCol 2 ColHeader NumVert # TableCol 2 FieldName Number of Vertices # TableCol 2 Units unitless # TableCol 3 ColHeader SurfArea # TableCol 3 FieldName Surface Area # TableCol 3 Units mm^2 # TableCol 4 ColHeader GrayVol # TableCol 4 FieldName Gray Matter Volume # TableCol 4 Units mm^3 # TableCol 5 ColHeader ThickAvg # TableCol 5 FieldName Average Thickness # TableCol 5 Units mm - - - #ColHeaders StructName NumVert SurfArea GrayVol ThickAvg ThickStd MeanCurv GausCurv FoldInd CurvInd unknown 13332 8382 11785 1.313 1.553 0.117 0.146 1134 56.2 bankssts 1372 939 2157 2.249 0.512 0.138 0.048 17 2.9 caudalanteriorcingulate 1188 783 2316 2.561 0.829 0.176 0.102 38 4.9 caudalmiddlefrontal 3278 2160 6170 2.555 0.565 0.143 0.056 45 7.8 cuneus 2460 1561 3093 1.800 0.406 0.165 0.071 47 6.9 entorhinal 544 371 1617 3.130 0.717 0.183 0.177 36 4.2 fusiform 5421 3746 10126 2.281 0.708 0.155 0.067 98 14.7 inferiorparietal 7558 5112 13237 2.269 0.589 0.154 0.066 154 19.6 - - -
Group stats files
This section will run you through using the stats directory in the subjects to perform group stats of certain structures that may be of interest to your study. The following commands will help you combine the data of the subjects you are analyzing into one table that will be easily read into a spreadsheet program. We have considered 6 subjects as examples (004, 021, 040, 067, 080, 092) in the following sections.
Set your SUBJECTS_DIR to the path where you have your subjects to be analyzed.
setenv SUBJECTS_DIR <path_to_data>
Table of segmentation volumes
This section explains how to create a table of segmentation volumes using the 6 subjects mentioned above.
asegstats2table --subjects 004 021 040 067 080 092 \ --segno 11 17 18 \ --t aseg.vol.table
where 11, 17 and 18 correspond to the segmentation label of left caudate, left hippocampus and left amygdala respectively. You can get the segmentation labels and the corresponding subcortical structures using the following command.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
For tutorial purposes, click here to view the contents of the file.
After running the asegstats2table command, to load the resulting table into a spreadsheet, run
oocalc aseg.vol.table
and then select Space in the Separated by menu.
Please note that the oocalc command is meant to be run on a Linux machine. In the table, the first cell is volume indicating that the measure is a volume in mm3. In addition to segmentations, you can also get IntraCranialVol (ICV) and BrainSegVol into the table.
About the subject IDs, you'll notice that in the examples we've considered here, each subject is a 3 digit number. Therefore oocalc thinks it is a number and removes leading 0s. This is an oocalc issue but probably it would not happen if subject names has characters in them instead of integers.
Table of segmentation mean intensities
Purpose of this section is to demonstrate how you can change the measure from volume to mean intensity using asegstats2table command.
asegstats2table \ --subjects 004 021 040 067 080 092 \ --segno 11 17 18 \ --meas mean \ --t aseg.mean-intensity.table
You can load the table into a spread sheet as explained in the previous section. Please refer to the file FreeSurferColorLUT.txt for the segmentation labels and the corresponding subcortical structures.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
For tutorial purposes, click here to view the contents of the file.
Table of white matter parcellation volumes
The purpose of this section is to show how you can change the segmentation atlas
asegstats2table \ --subjects 004 021 040 067 080 092 \ --segno 3007 3021 3022 4022 \ --stats wmparc.stats \ --t wmparc.vol.table
Please refer to the file FreeSurferColorLUT.txt for the segmentation labels and the corresponding subcortical structures.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
For tutorial purposes, click here to view the contents of the file.
Table of the surface area of each cortical parcellation in the Desikan atlas
This section explains how to create a table of the surface area of each cortical parcellation in the Desikan atlas.
aparcstats2table --hemi lh \ --subjects 004 021 040 067 080 092 \ --t lh.aparc.area.stats
Table of the average thickness of each cortical parcellation in the Destrieux atlas
The purpose of this section is to show how to change the summary measure and the parcellation atlas.
aparcstats2table --hemi lh \ --subjects 004 021 040 067 080 092 \ --meas thickness \ --parc aparc.a2005s \ --t lh.aparc.a2005.thickness.stats