Freesurfer July 2016

freesurfer@nmr.mgh.harvard.edu

143 participants
252 discussions

question about reslicing
by Dorsa Haji Ghaffari 26 Jul '16

26 Jul '16

Hi, I re-sliced my left thalamus so that the size and number of slices correspond with the original MRI, but when I open it in freeview, it shows an extra part( like a cube) on the bottom of the image ( I have attached the mask). do you have any idea how to solve that? Also how can I make sure that the position and size of the thalamus makes sense since the thalamus mask has a different slice size and number than the original mri? Thank you Dorsa

3 7

mri_glmfit problem/2 group 6 covariates
by miracle ozzoude 26 Jul '16

26 Jul '16

Hello doug, while running the mir_glmfit problem, i encountered this problem “ INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 Age 39.9375 17.3312 1 Education 15.5625 1.99902 2 Firstscore 1.03375 0.341785 3 Secondscore 1.03906 0.370678 4 Thirdscore 1.13844 0.4768 5 Averagescore 1.07375 0.364046 Class Means of each Continuous Variable 1 Group1 35.6316 15.0526 1.0342 1.2111 1.4289 1.2305 2 Group2 46.2308 16.3077 1.0331 0.7877 0.7138 0.8446 INFO: gd2mtx_method is dods Reading source surface /Users/paul/Desktop/improvervsdeclinermri/fsaverage/surf/lh.white Number of vertices 163842 Number of faces 327680 Total area 65416.648438 AvgVtxArea 0.399267 AvgVtxDist 0.721953 StdVtxDist 0.195470 $Id: mri_glmfit.c,v 1.196.2.6 2011/05/05 20:54:25 greve Exp $ cwd /Users/paul/Desktop/improvervsdeclinermri cmdline mri_glmfit --y lh.new.MOT.thickness.10B.mgh --fsgd new.MOT.fsgd dods --C new.firstmatrix.mtx --C new.secondmatrix.mtx --C new.thirdmatrix.mtx --C new.fourthmatrix.mtx --C new.fifthmatrix.mtx --C new.sixthmatrix.mtx --C new.seventhmatrix.mtx --C new.eightmatrix.mtx --C new.ninethmatrix.mtx --C new.tenthmatrix.mtx --surf fsaverage lh --cortex --glmdir lh.new.MOT.glmdir sysname Darwin hostname TC-CT-LAB4-iMAC.local machine x86_64 user paul FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /Users/paul/Desktop/improvervsdeclinermri/lh.new.MOT.thickness.10B.mgh logyflag 0 usedti 0 FSGD new.MOT.fsgd labelmask /Users/paul/Desktop/improvervsdeclinermri/fsaverage/label/lh.cortex.label maskinv 0 glmdir lh.new.MOT.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory lh.new.MOT.glmdir Loading y from /Users/paul/Desktop/improvervsdeclinermri/lh.new.MOT.thickness.10B.mgh INFO: gd2mtx_method is dods Saving design matrix to lh.new.MOT.glmdir/Xg.dat Normalized matrix condition is 1.27568e+06 Design matrix ------------------ 1.000 0.000 23.000 0.000 15.000 0.000 1.680 0.000 1.780 0.000 2.110 0.000 1.860 0.000; 1.000 0.000 43.000 0.000 16.000 0.000 0.840 0.000 0.890 0.000 1.190 0.000 0.970 0.000; 1.000 0.000 39.000 0.000 17.000 0.000 0.790 0.000 0.840 0.000 1.220 0.000 0.950 0.000; 1.000 0.000 19.000 0.000 13.000 0.000 0.840 0.000 1.060 0.000 1.260 0.000 1.050 0.000; 1.000 0.000 28.000 0.000 13.000 0.000 1.060 0.000 1.120 0.000 1.370 0.000 1.180 0.000 …………………………………………………………………………………………………………………... ERROR: matrix is ill-conditioned or badly scaled, condno = 1.27568e+06 -------------------------------- Possible problem with experimental design: Check for duplicate entries and/or lack of range of continuous variables within a class. If you seek help with this problem, make sure to send: 1. Your command line: mri_glmfit --y lh.new.MOT.thickness.10B.mgh --fsgd new.MOT.fsgd dods --C new.firstmatrix.mtx —C new.secondmatrix.mtx --C new.thirdmatrix.mtx --C new.fourthmatrix.mtx --C new.fifthmatrix.mtx --C new.sixthmatrix.mtx --C new.seventhmatrix.mtx --C new.eightmatrix.mtx --C new.ninethmatrix.mtx --C new.tenthmatrix.mtx --surf fsaverage lh --cortex --glmdir lh.new.MOT.glmdir 2. The FSGD file (if using one) 3. And the design matrix above” Below are my fsgd file and contrast matrix. I can’t add DeMeanFlag 1 because I am using dods and interested in group difference. Also, none of the responses from people with similar error helped me. I am using version 5.1 Thank you very much. Paul GroupDescriptorFile 1 Title MOT Class Group1 Class Group2 Variables Age Education Firstscore Secondscore Thirdscore Averagescore Input 01053p/fsdir Group1 23 15 1.68 1.78 2.11 1.86 Input 01054p/fsdir Group1 43 16 0.84 0.89 1.19 0.97 Input 01061p/fsdir Group1 39 17 0.79 0.84 1.22 0.95 Input 01062p/fsdir Group1 19 13 0.84 1.06 1.26 1.05 Input 01074p/fsdir Group1 28 13 1.06 1.12 1.37 1.18 Input 01080p/fsdir Group1 28 18 0.97 1.26 1.33 1.19 Input 01099p/fsdir Group1 37 16 0.87 1.15 1.37 1.13 Input 01101p/fsdir Group1 20 14 1.00 1.37 1.45 1.27 Input 01102p/fsdir Group1 58 16 0.97 1.12 1.41 1.27 Input 01121p/fsdir Group1 28 18 0.87 1.00 1.00 0.96 Input 01127p/fsdir Group1 46 16 0.77 1.06 1.58 1.14 Input 01128p/fsdir Group1 21 16 1.58 1.78 1.78 1.71 Input 01130p/fsdir Group1 22 16 1.50 1.22 1.63 1.45 Input 01131p/fsdir Group1 19 13 1.54 1.68 2.11 1.78 Input 01141p/fsdir Group1 17 12 1.00 1.09 1.30 1.13 Input 1044pp/fsdir Group1 51 16 0.94 1.54 1.68 1.39 Input 1053pp/fsdir Group1 44 16 1.22 1.30 1.50 1.34 Input 1058pp/fsdir Group1 78 12 0.61 1.12 1.15 0.96 Input 1060pp/fsdir Group1 56 13 0.60 0.63 0.71 0.65 Input 01047p/fsdir Group2 50 18 1.12 0.94 0.94 1.00 Input 01075p/fsdir Group2 20 15 1.12 0.84 0.60 0.85 Input 01077p/fsdir Group2 48 16 0.43 0.35 0.35 0.38 Input 01091p/fsdir Group2 23 16 1.58 1.22 1.22 1.34 Input 01096p/fsdir Group2 17 17 1.50 1.26 1.19 1.32 Input 01113p/fsdir Group2 51 18 0.75 0.69 0.60 0.68 Input 01124p/fsdir Group2 43 18 1.33 0.89 0.87 1.03 Input 01134p/fsdir Group2 59 16 0.82 0.60 0.60 0.67 Input 1004pp/fsdir Group2 46 19 0.82 0.79 0.71 0.77 Input 1040pp/fsdir Group2 64 13 0.92 0.55 0.46 0.64 Input 1043pp/fsdir Group2 49 16 1.58 1.03 0.89 1.17 Input 1064pp/fsdir Group2 78 12 0.40 0.11 0.10 0.20 Input 1067pp/fsdir Group2 53 18 1.06 0.97 0.75 0.93 first contrast matrix 1 -1 0 0 0 0 0 0 0 0 0 0 0 0 group1 greater than group 2 regressing out age, education, first, second, third and average second constrast matrix -1 1 0 0 0 0 0 0 0 0 0 0 0 0 group 2 greater than group 1 regressing out age, education, first, second, third and average third contrast matrix 0 0 0 0 0 0 0.5 -0.5 0 0 0 0 0 0 group 1 showing increasing correlation with first score compared to group 2 fourth contrast matrix 0 0 0 0 0 0 -0.5 0.5 0 0 0 0 0 0 group2 showing showing increasing correlation with first score compared to group 1 fifth contrast matrix 0 0 0 0 0 0 0 0 0.5 -0.5 0 0 0 0 group1 showing showing increasing correlation with second score compared to group 2 sixth contrast matrix 0 0 0 0 0 0 0 0 -0.5 0.5 0 0 0 0 group2 showing showing increasing correlation with second score compared to group 1 seventh contrast matrix 0 0 0 0 0 0 0 0 0 0 0.5 -0.5 0 0 group1 showing showing increasing correlation with third score compared to group 2 eighth contrast matrix 0 0 0 0 0 0 0 0 0 0 -0.5 0.5 0 0 group2 showing showing increasing correlation with third score compared to group 1 ninety contrast matrix 0 0 0 0 0 0 0 0 0 0 0 0 0.5 -0.5 group1 showing showing increasing correlation with average score compared to group 2 tenth contrast matrix 0 0 0 0 0 0 0 0 0 0 0 0 -0.5 0.5 group2 showing showing increasing correlation with average score compared to group 1

4 7

normalizing in fsgd
by miracle ozzoude 26 Jul '16

26 Jul '16

Hello freesurfer experts, I am trying to normalize my continuous variables in my fsgd file. Is this the correct term to add to my fsgd file in order for mri_glmfit to normalize it? GroupDescriptorFile 1 Title PCS Class group1 Class group2 Normalize 1 Variables Age Education Scoreone Scoretwo Input 053 group1 47 18 3.4 5.6 Input 054 group2 50 16 5.3 2.8 Thank you, Paul

3 5

Projecting AAL atlas to fsaverage
by Salim Arslan 26 Jul '16

26 Jul '16

Hi, We are trying to project the AAL labels from volume to surface in order to be able to include the AAL atlas to our surface-based experiments. What we have done so far is that we projected the volume labels to the fsaverage white surface using mri_vol2surf function in the following setting: mri_vol2surf --mov ROI_MNI_V5.nii --mni152reg --hemi lh --surf white --o $OUT_FOLDER/lh.fsaverage.white.ROI_MNI_V5.asc.w --out_type paint --trgsubject fsaverage where ROI_MNI_V5.nii corresponds to the ALL atlas in MNI space. After converting the output asc.w file first to a FreeSurfer-compatible format, and then to gifti, we realized that the result was garbage (Please see Fig. 1). Following a suggestion from a member of our research group, we applied dilation to the input atlas (ROI_MNI_V5.nii) and re-ran the function with the same setting as above. This way, the final cortical parcellation was not perfect but still seemed to be usable (Please see Fig. 2). The problem here is that, as you may have also noticed, some of the cortical parcellation boundaries do not follow the folding patterns across the surface. Besides, some parcels just do not seem to be right (see the arrows in the motor area). Having said that, I have the following questions:1- Why is not possible to properly project the labels onto the surface without first dilating the input atlas?2- If dilation is not a big issue, how would the experts in the mailing list interpret the distortions, especially in the motor area? Is it kind of a side effect we should expect after such process between volume and surface? >From the archive I can see that similar questions have been posted a few years back (https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg27586.html, https://www.mail-archive.com/freesurfer%40nmr.mgh.harvard.edu/msg23761.html) Although these messages are highly useful, apparently there is still not a standard solution to this problem. Please accept my sincere apologies if this is still considered as re-posting. Any feedback is greatly appreciated. Thanks for your attention. Kind regards,Salim

1 0

GLM significance table
by Caroline Beelen 26 Jul '16

26 Jul '16

Dear FS team, I tried to run GLM-analysis using aparc stats files. At first I created these files for a few subjects of interest (e.g. aparc_rh_thickness_stats.txt) and checked whether they looked ok, which they did (values were pretty similar). Then I used the following command (for example): Mri_glmfit -- table aparc_rh_thickness_stats.txt -- fsgd gender_dys.fsgd (see attached; example of a fsgd-file) -- C Int.mtx -- C Dys.mtx -- C Gender.mtx -- glmdir roi.gender_dyslect.rh.thickness.glmdir The file was created and it contained a sig.table.dat folder. However, the values in this folder are all quite low. According to information found on your website they should correspond to (-)log10(p) values. I found mainly values between -1 and 1, but even of -0.03, which would correspond to a p-value of 1.5 (non-existing). Could you please explain to me what I did wrong? Thank you very much! Kind regards, Caroline

2 1

GLM significance table
by Caroline Beelen 26 Jul '16

26 Jul '16

1 0

How to apply ACPC alignment to Freesurfer output
by Sandra Hanekamp 26 Jul '16

26 Jul '16

Dear Freesurfer community, I would like to apply ACPC alignment to Freesurfer output. Data was previously segmented with recon -all and a lot of manual editing using ITK. Unfortunately, the data was not aligned to ACPC and this causes errors in my pipeline (I am using the labels and white matter mask from Freesurfer for my DTI analysis). Re-doing the segmentation plus necessary edits would be very time-consuming due to a poor contrast between white and grey matter and the number of scans that I have, so I would prefer to align the current output to ACPC. Does anyone know a solution that does not involve re-doing the segmentation? How can I apply ACPC alignment to Freesurfer output? Thank you so much for any thoughts or recommendations you might be able to provide. Sandra Hanekamp Laboratory for Experimental Ophthalmology University Medical Center Groningen

2 2

mri_ca_label with high resolution data
by Falk Lüsebrink 26 Jul '16

26 Jul '16

Hi all, I'm currently processing a 250 µm MPRAGE with a dev build from mid of May. Running recon-all with default parameters ran flawlessly. Afterwards I added the -hires flag to process the data without conformation. However, since Saturday morning it is kind of stuck at mri_ca_label stating: saving sequentially combined intensity scales to aseg.auto_noCCseg.label_intensities.txt while consuming around 30 GB of memory. I ran something similar before and processing works, it's just terribly slow. Maybe this particular stage is just not very efficient as it does take a few minutes on 1 mm data only? Would it help to add the openmp flag in that case? Best, Falk ---------------------------------------- Falk Lüsebrink, M. Sc. Otto-von-Guericke-Universität Magdeburg Forschungscampus STIMULATE http://www.forschungscampus-stimulate.de/ Universitätsplatz 2 39106 Magdeburg Raum: ExFa - 4.06 Telefon: 0391-67-19366 Fax: 0391-67-19347

2 9

Hippocampal subfields total volume differences
by Mojmír Vinkler 26 Jul '16

26 Jul '16

Hi experts, I'm using Freesurfer 6.0 dev version (Mac) to perform hippocampal subfields segmentation. I only need to measure total hippocampus volume, but measurements from basic `recon-all` were too volatile and I was hoping that using subfields with T2 modality would reduce variance. However, volume measured by hippocampal subfields is significantly different from volume in aseg.stats. Here are volumes for right hippocampus from various methods: aseg.stats - 3312.8 rh.hippoSfVolumes-T1.v10.txt (Mode A - only T1 used) - 2883.8 rh.hippoSfVolumes-T2.v10.txt (Mode B - using only additional scan) - 2503.97 rh.hippoSfVolumes-T1-T1T2.v10.txt (Mode B - Multispectral segmentation) - 2596.09 I checked labeling visually and there were no obvious problems. Is such a large difference common? Am I missing something? What number should be most trusted? Thanks for any hints! Mojmir

2 4

Running Several Versions of fsfast GLM In Parallel Leads to "Stale File Handles"
by Taylor, Johnmark 25 Jul '16

25 Jul '16

Hello, I have been trying to run several versions of the same GLM analysis, trying out different parameters to see if they affect the results. For instance, I am running the GLM with different levels of smoothing, per-session versus per-run motion correction, etc. To speed this up, I am trying to do these GLMs in parallel. However, when I do this, I run into a "stale file handle" problem. As near as I can tell, this occurs because the analyses try to read and write to the same log files at the same time. A typical error message is "/net/rcss2/srv/export/ncf_vcn/share_root/jtaylor/mri-space/studies/fpoinfips01/scripts/glm/log/preproc-160718_xu_loc01_sub02-bold.log: Stale file handle". I have tried putting "-nolog" in the call to selxavg3-sess, but this doesn't prevent the creation of log files when it makes the sub-calls to the various pre-processing functions. Is there any way around this? It would be rather slow to try to run the GLMs sequentially, so I am wondering if anybody has figured out a way around this problem. Much obliged, JohnMark

2 1

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Freesurfer July 2016