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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.

Relationship between segmentation, parcellation and LookUp Table (LUT)

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


Run the following command to display the contents of LUT


less $FREESURFER_HOME/FreeSurferColorLUT.txt


Click on a point on the image loaded in tkmedit. You can see the structure name in the tkmedit toolbar. Look at the Aux value, find value in LUT, which you have opened using the command mentioned above. See that it is the same structure as listedin tkmedit.

Click on a point in tksurfer and see structure name. Note that the name does not have lh or rh in it. Click on the Save Point tool button icon_cursor_save.gif, and then click on Goto Point tool button icon_cursor_goto.gif on the tkmedit toolbar. You will notice that the structure name in tkmedit has lh or rh in it.

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.cortex.label, run


less 004/label/lh.cortex.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 tkmedit toolbar, go to File-> Label --> Load Label --> lh.BA45.label

To load the label in tksurfer, make sure you load the subject in tksurfer.


tksurfer 004 lh inflated


On the tksurfer toolbar, go to File --> Label --> Load Label --> lh.BA45.label You can also load the label from the tksurfer tool bar using Ctrl - right mouse button on the 'Show labels' tool button icon_label_off.gif. Browse the label you want to load and click 'OK'

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.


cd $SUBJECTS_DIR/004/stats
less aseg.stats


Details are as follows when you run the command line above.

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.

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:

# Title Segmentation Statistics
#
# generating_program mri_segstats
# cvs_version $Id: mri_segstats.c,v 1.11.2.5 2006/04/13 18:57:07 nicks Exp $
# cmdline mri_segstats --seg mri/aseg.mgz --sum stats/aseg.stats --pv mri/norm.mgz --ctab-default 
--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
# sysname  Linux
# hostname node0350
# machine  x86_64
# user     FS-user
# anatomy_type volume
#
# SUBJECTS_DIR /buckner_data/group_study
# subjectname 004
# BrainMaskFile  mri/brainmask.mgz
# BrainMaskFileTimeStamp  2006/24/03 13:47:46
# Measure BrainMask, BrainMaskNVox, Number of Brain Mask Voxels, 1744896, unitless
# Measure BrainMask, BrainMaskVol, Brain Mask Volume, 1744896.000000, mm^3
# Measure BrainSeg, BrainSegNVox, Number of Brain Segmentation Voxels, 1255291, unitless
# Measure BrainSeg, BrainSegVol, Brain Segmentation Volume, 1255291.000000, mm^3# Measure IntraCranialVol, ICV, Intracranial Volume, 1679242.759627, mm^3
# SegVolFile mri/aseg.mgz
# SegVolFileTimeStamp  2006/24/03 21:52:14
# ColorTable /space/freesurfer/centos4.0_x86_64/stable/FreeSurferColorLUT.txt
# ColorTableTimeStamp 2006/22/03 05:48:11
# InVolFile  mri/norm.mgz
# InVolFileTimeStamp  2006/24/03 13:55:16
# InVolFrame 0
# PVVolFile  mri/norm.mgz
# PVVolFileTimeStamp  2006/24/03 13:55:16
# ExcludeSegId 0
# VoxelVolume_mm3 1

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:

# 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
# TableCol  6 ColHeader normMean
# TableCol  6 FieldName Intensity normMean
# TableCol  6 Units     MR
# TableCol  7 ColHeader normStdDev
# TableCol  7 FieldName Itensity normStdDev
# TableCol  7 Units     MR
# TableCol  8 ColHeader normMin
# TableCol  8 FieldName Intensity normMin
# TableCol  8 Units     MR
# TableCol  9 ColHeader normMax
# TableCol  9 FieldName Intensity normMax
# TableCol  9 Units     MR
# TableCol 10 ColHeader normRange
# TableCol 10 FieldName Intensity normRange
# TableCol 10 Units     MR
# NRows 403
# NTableCols 10

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:

# ColHeaders  Index SegId NVoxels Volume_mm3 StructName normMean normStdDev normMin normMax normRange
  2   2    237201   237201.0  Left-Cerebral-White-Matter       107.5612    11.3261    31.0000   188.0000   157.0000
  3   3    249096   249096.0  Left-Cerebral-Cortex              69.8956    11.0623     0.0000   139.0000   139.0000
  4   4     31329    31329.0  Left-Lateral-Ventricle            23.0385    11.1648     7.0000    91.0000    84.0000
  5   5      1735     1735.0  Left-Inf-Lat-Vent                 42.2160    15.5492    14.0000    94.0000    80.0000
  7   7     13767    13767.0  Left-Cerebellum-White-Matter      87.6124     7.8224    43.0000   116.0000    73.0000
  8   8     48245    48245.0  Left-Cerebellum-Cortex            60.1777     9.4993    25.0000    94.0000    69.0000
 10  10      7025     7025.0  Left-Thalamus-Proper              89.5336    11.9082    19.0000   126.0000   107.0000
 11  11      5252     5252.0  Left-Caudate                      77.3650    11.3959    45.0000   105.0000    60.0000
 12  12      7993     7993.0  Left-Putamen                      81.3400     9.7069    28.0000   115.0000    87.0000
 13  13      2144     2144.0  Left-Pallidum                     97.6942    11.7513    36.0000   121.0000    85.0000
.
.
.
.

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:

# Table of FreeSurfer cortical parcellation anatomical statistics
#
# CreationTime 2006/04/25-09:31:20-GMT
# generating_program mris_anatomical_stats
# cvs_version $Id: mris_anatomical_stats.c,v 1.35.2.1 2006/04/21 19:45:19 nicks Exp $
# mrisurf.c-cvs_version $Id: mrisurf.c,v 1.441.2.3 2006/04/12 02:03:02 nicks Exp  $
# cmdline mris_anatomical_stats -mgz -f ../stats/lh.aparc.stats -b -a ../label/l h.aparc.annot -c ../stats/aparc.annot.ctab 004 lh
# sysname  Linux
# hostname node0350
# machine  x86_64
# user     FS-user
#
# SUBJECTS_DIR /buckner_data/group_study
# anatomy_type surface
# subjectname 004
# hemi lh
# AnnotationFile ../label/lh.aparc.annot
# AnnotationFileTimeStamp 2006/25/03 05:31:10
# TotalWhiteMatterVolume  634178 mm^3
# Measure Cortex, NumVert, Number of Vertices, 150889, unitless
# Measure Cortex, SurfArea, Surface Area,  102409, mm^2

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:

# NTableCols 10
# 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
# TableCol  6 ColHeader ThickStd
# TableCol  6 FieldName Thickness StdDev
# TableCol  6 Units     mm
# TableCol  7 ColHeader MeanCurv
# TableCol  7 FieldName Integrated Rectified Mean Curvature
# TableCol  7 Units     mm^-1
# TableCol  8 ColHeader GausCurv
# TableCol  8 FieldName Integrated Rectified Gaussian Curvature
# TableCol  8 Units     mm^-2
# TableCol  9 ColHeader  FoldInd
# TableCol  9 FieldName  Folding Index
# TableCol  9 Units      unitless
# TableCol 10 ColHeader CurvInd
# TableCol 10 FieldName Intrinsic Curvature Index
# TableCol 10 Units     unitless

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:

# ColHeaders StructName NumVert SurfArea GrayVol ThickAvg ThickStd MeanCurv GausCurv FoldInd CurvInd
unknown                                 15085  10384  21630  2.006 1.096     0.123     0.038  168.313  26.766
bankssts                                 1126    770   1563  2.132 0.462     0.103     0.024    7.056   1.004
caudalanteriorcingulate                   931    636   2125  2.721 0.675     0.127     0.031   15.801   0.991
caudalmiddlefrontal                      3577   2403   6575  2.447 0.535     0.120     0.028   34.901   3.674
corpuscallosum                           1035    680   1215  2.123 0.902     0.136     0.023   17.731   0.799
cuneus                                   2966   1958   3769  1.740 0.473     0.140     0.033   37.320   3.630
entorhinal                                683    419   1620  2.819 0.632     0.090     0.021    5.349   0.429
fusiform                                 6622   4607  11486  2.190 0.634     0.130     0.032   77.276   7.884
.
.
.
.

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 location where you have your subjects to be analyzed.

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


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


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


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