Freesurfer

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16 participants
30084 discussions

Subtraction of Stroke Volumes
by Rellick, Stephanie 04 Nov '19

04 Nov '19

External Email - Use Caution Hi All, I am looking for some help. I am working with stroke subject MRIs. For initial processing, I have "healed" the brains by applying the mirror image of the unaffected side. Now what I want to do is to subtract out only the area in which my lesion overlaps with BA4 (anterior and posterior), and get the statistics for that area only. I have made all the surface labels, turned the lesion into a label, and even created the actual intersect label, but what I really need to do is take BA4, subtract out any overlap with my lesion label, create a new label with this overlap, and then use the mris_anatomical_stats command line to get the statistics for this area to check the change over time. I know there has to be a way to do this but I cannot seem to figure it out!! Thanks, Stephanie

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nuisance factors
by Georgina Angelopoulou 04 Nov '19

04 Nov '19

External Email - Use Caution Thank you very much Douglas, It worked! I have one last question: in case of Volume, age slope is not significant, yet eTIV slope appears significant. Is it possible to include both age and eTIV as nuisance variables, in order to control my analysis for age and eTIV? What would be the contrast in that case? Thanks once again, Georgina

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Fwd: Fw: glm error
by Amrita Bedi 01 Nov '19

01 Nov '19

External Email - Use Caution ---------- Forwarded message ---------- From: *abedi000(a)citymail.cuny.edu <abedi000(a)citymail.cuny.edu>* < abedi000(a)citymail.cuny.edu> Date: Thursday, October 31, 2019 Subject: Fw: glm error To: Amrita Bedi <amibedi273(a)gmail.com> Amrita Bedi *Biomedical Engineering - Class of 2018* *The City College of New York - CUNY* ------------------------------ *From:* abedi000(a)citymail.cuny.edu *Sent:* Thursday, October 31, 2019 12:02 PM *To:* Freesurfer(a)nmr.mgh.harvard.edu <Freesurfer(a)nmr.mgh.harvard.edu> *Subject:* glm error Hello Freesurfer developers, I ran a seed based resting stage functional analysis for 287 subjects using the isthmus of the cingulate as a seed and now have pcc.nii.gz files in each individual subject folder. I concatenated these pcc files and am trying to run an osgm but get the following error: ERROR: DOF = 0 The commands i ran for concatenating and glm are: for l in `cat sessidBOLD2`; do mri_concat --o 4D_VOLUME_OUTPUT.lh.nii.gz --i $l/Bold/PCC_Bold1_L/bilat*/pcc.nii.gz; done mri_glmfit --y 4D_VOLUME_OUTPUT.lh.nii.gz --osgm --surf fsaverage lh --cortex --label /run/media/amritabedilocal/DATA/Amrita/2389/abedi /FSFAST_1to547_TR3/fsaverage/label/lh.cortex.label --glmdir all_subjects_lh_ic_pcc.TR3.glmdir The mriglmfit.log gave me the following: $Id: mri_glmfit.c,v 1.196.2.8 2012/11/01 18:51:41 greve Exp $ cwd /run/media/amritabedilocal/DATA/Amrita/2389/abedi/FSFAST_ 1to547_TR3/FSFAST cmdline mri_glmfit --y 4D_VOLUME_OUTPUT.lh.nii.gz --osgm --surf fsaverage lh --cortex --label /run/media/amritabedilocal/ DATA/Amrita/2389/abedi/FSFAST_1to547_TR3/fsaverage/label/lh.cortex.label --glmdir all_subjects_lh_ic_pcc.TR3.glmdir sysname Linux hostname imaging5.vaboston.lan machine x86_64 user root FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 1 y /run/media/amritabedilocal/DATA/Amrita/2389/abedi/FSFAST_ 1to547_TR3/FSFAST/4D_VOLUME_OUTPUT.lh.nii.gz logyflag 0 usedti 0 labelmask /run/media/amritabedilocal/DATA/Amrita/2389/abedi/FSFAST_ 1to547_TR3/fsaverage/label/lh.cortex.label maskinv 0 glmdir all_subjects_lh_ic_pcc.TR3.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Thank you for your help.

2 7

make_average_subject error
by Maxime Perron 31 Oct '19

31 Oct '19

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Discrepancy between thresholded surface and cluster labels
by Bronwyn Overs 31 Oct '19

31 Oct '19

External Email - Use Caution Dear Freesurfer mailing list, I am trying to get to the bottom of a discrepancy between two surface based images generated from the output of an LME analysis. The surfaces in row 1 of the attached image were generated by loading the four FDR significant clusters that were >100mm^2 in the cluster summary file. The surfaces in row 2 of the attached image were generated by loading the significance map generated for the same fixed effect (saved from the LME), and thresholding at the FDR corrected p -value. The question I have is why are there such large swatches of the cortical surface in the row 2 images that are labelled as log10 p = 5, when they are not included in the most significant and largest clusters that were found in the cluster summary file? Kind regards, Bronwyn Overs Research Assistant Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1725 [ http://neura.edu.au/ | neura.edu.au ] [ https://twitter.com/neuraustralia | Twitter ] | [ https://www.facebook.com/NeuroscienceResearchAustralia | Facebook ] | [ http://www.neura.edu.au/help-research/subscribe | Subscribe ]

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Re: [Freesurfer] nuisance factors
by Georgina Angelopoulou 31 Oct '19

31 Oct '19

External Email - Use Caution Dear Douglas, Thank you once again for your reply and your help. Attached please find the fsgd file (CMTX_b.fsgd) including age row scores and the contrast file. The command line I used is the following: - mri_glmfit --y lh.CMTX_b.thickness.10.mgh --fsgd CMTX_b.fsgd --C Contrasts/age_sim.mtx --surf fsaverage lh --cortex --glmdir lh.CMTX_b_thickness.glmdir The output is the following: georgias-mbp:CMTX georgina$ mri_glmfit --y lh.CMTX_b.thickness.10.mgh --fsgd CMTX_b.fsgd --C Contrasts/age_sim.mtx --surf fsaverage lh --cortex --glmdir lh.CMTX_b_thickness.glmdir gdfRead(): reading CMTX_b.fsgd INFO: DeMeanFlag keyword not found, DeMeaning will NOT be done. Continuous Variable Means (all subjects) 0 age 45.2083 12.1603 Class Means of each Continuous Variable 1 patientmale 38.7778 2 patientfemale 53.0000 3 controlmale 40.1667 4 controlfemale 51.8462 INFO: gd2mtx_method is dods Reading source surface /Users/georgina/Dropbox/UP_TO_DATE/CMTX_STUDY/CMTX/fsaverage/surf/lh.white Number of vertices 163842 Number of faces 327680 Total area 65416.984375 AvgVtxArea 0.399269 AvgVtxDist 0.721953 StdVtxDist 0.195470 $Id: mri_glmfit.c,v 1.241.2.4 2016/12/08 22:02:40 zkaufman Exp $ cwd /Users/georgina/Dropbox/UP_TO_DATE/CMTX_STUDY/CMTX cmdline mri_glmfit.bin --y lh.CMTX_b.thickness.10.mgh --fsgd CMTX_b.fsgd --C Contrasts/age_sim.mtx --surf fsaverage lh --cortex --glmdir lh.CMTX_b_thickness.glmdir sysname Darwin hostname 192.168.1.32 machine x86_64 user georgina FixVertexAreaFlag = 1 UseMaskWithSmoothing 1 OneSampleGroupMean 0 y /Users/georgina/Dropbox/UP_TO_DATE/CMTX_STUDY/CMTX/lh.CMTX_b.thickness.10.mgh logyflag 0 usedti 0 FSGD CMTX_b.fsgd labelmask /Users/georgina/Dropbox/UP_TO_DATE/CMTX_STUDY/CMTX/fsaverage/label/lh.cortex.label maskinv 0 glmdir lh.CMTX_b_thickness.glmdir IllCondOK 0 ReScaleX 1 DoFFx 0 Creating output directory lh.CMTX_b_thickness.glmdir Loading y from /Users/georgina/Dropbox/UP_TO_DATE/CMTX_STUDY/CMTX/lh.CMTX_b.thickness.10.mgh ... done reading. INFO: gd2mtx_method is dods Saving design matrix to lh.CMTX_b_thickness.glmdir/Xg.dat Computing normalized matrix Normalized matrix condition is 160.248 Matrix condition is 182721 Found 149955 points in label. Pruning voxels by thr: 1.175494e-38 Found 148239 voxels in mask Saving mask to lh.CMTX_b_thickness.glmdir/mask.mgh Reshaping mriglm->mask... search space = 73702.448371 ERROR: dimension mismatch between X and contrast Contrasts/age_sim.mtx X has 8 cols, C has 5 cols Please note that an equivalent error appears with grey matter volume and surface area. Thank you once again, Best, Georgina

2 1

PETsurfer issue
by Mackenzie Leigh Carlson 31 Oct '19

31 Oct '19

External Email - Use Caution Hello, Wondering if anyone has had issues with PETsurfer partial volume correction. When I have used it, there are large 'holes' in the white matter. I am mostly interested in the hippocampal area, which seems unaffected by these holes, but I'm not sure if I should trust the outcome enough to still use PVC maps for the hippocampus! Any help is appreciated. Thank you! I am running this: mri_gtmpvc --i SUV-30-60-float-FixedSlope.nii.gz --reg SUVtoFS.reg.lta --psf 5 --seg gtmseg.mgz --default-seg-merge --auto-mask PSF .01 --mgx .01 --o gtmpvc.output.nopons --no-rescale -- Mackenzie L. Carlson PhD Candidate in Bioengineering | Stanford University BA Engineering Sciences | Dartmouth College (218) 269-7473

2 1

mac gcc builds
by Hoopes, Andrew 30 Oct '19

30 Oct '19

Notice to all mac FS developers, GCC builds on macOS have become increasingly difficult to maintain, mostly due to brew issues and gcc-version incompatibles with dependencies. Clang is now the "official" mac compiler for freesurfer. The external prebuilt packages (at https://surfer.nmr.mgh.harvard.edu/pub/data/fspackages/prebuilt/osx10.11-pa…) have been updated accordingly. best, Andrew

1 0

imperfect segmentation in the occipital lobe in epilepsy patient
by Xiaoqian Yan 30 Oct '19

30 Oct '19

External Email - Use Caution Dear Freesurfer experts, I am trying to do the segmentation on a patient's T1 image. I did not get error messages running the 'recon-all' (recon-all -i T1.nii -subjid PatientName -all), but the segmentation over the right occipital lobe was imperfect, which caused failures to map the functional activations in this region onto the surface. I tried to manually edit the wm.mgz several times, but the output did not change a lot (please see the attached image). The patient had depth EEG electrodes implanted in this region before, so there is a thermal lesion which I thought could have caused the bad segmentation. Do you have any ideas about what I can do next, or it is possible for you to help me editing the data? Thanks in advance, best wishes Xiaoqian

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nuisance factors
by Georgina Angelopoulou 30 Oct '19

30 Oct '19

External Email - Use Caution Thank you very much! That makes a lot of sense. However, when I tried to run the analysis using that contrast (0.5 0.5 -0.5 -0.5 0), the following error appears: dimension mismatch between X and contrast Contrasts/age_sim.mtx X has 4 cols, C has 5 cols My fsgd file contains the following info: Title CMTX Class patientmale Class patientfemale Class controlmale Class controlfemale Variables age Any ideas of how to resolve it? Thanks once again, Georgina

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