Freesurfer January 2019

freesurfer@nmr.mgh.harvard.edu

119 participants
167 discussions

Beta extraction
by Jahan, Bushra 28 Feb '19

28 Feb '19

I am wondering how to extract beta values from the clusters of task functional data, particularly output of the multiple comparisons correction? Aava Jahan

2 3

partial FoV - registration failure
by Francesca Strappini 19 Feb '19

19 Feb '19

External Email - Use Caution Dear freesurfer experts, I am using freesurfer to analyze some fMRI data collected on two monkeys. My runs have a partial field of view, since just the posterior part of the brain was scanned. Unfortunately, no full-head EPI was collected. The registration between the processed functional data and the T1 is bad. All the values in the register.dof6.mincost file are above 0.8 and also visually I can see some mismatch. I though to run bbregister, could you suggest me which is the best procedure and which steps of the preprocessing I should re-run after? Thanks -- Francesca Strappini, Ph.D. Neurobiology Department Weizmann Institute of Science 234 Herzl Street, Rehovot 7610001 Israel Tel.: +972 58 444 2584 E-mail: francesca.strappini(a)weizmann.ac.il

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mri_segstat: same output with two different label
by Francesca Strappini 12 Feb '19

12 Feb '19

External Email - Use Caution Dear Freesurfer's experts, I'm trying to run a ROIs mean intensity analysis using mri_segstat. I'm using as an input contrast maps created with mkcontrast-sess and selxavg3-sess (block-design experiment) and as masks, some labels created on the surface with a retinotopic analysis. I noticed that all my outputs with the same label have the same values, regardless of the contrast map that I'm giving as an input. However, if I plot the contrast maps on the surface I can clearly see that there are differences, so also the mean signal should be different. Maybe I'm not running the command correctly: mri_segstats --i z.nii.gz --slabel sub1 lh lh.V2dorsal_sub1.label --sfavg lh.V2dorsal_sub1_condition1_avg --snr --sum lh.V2dorsal_sub1_condition1_sum These are two outputs from the same regions but with two different z maps as inputs. I can also see that are indicated two different values as mean intensity, -0.95028 and 1.31525, what's the difference between them? # Title Segmentation Statistics # # generating_program mri_segstats # cvs_version $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ # cmdline mri_segstats --i disorder/z.nii.gz --slabel AB lh /home/labs/malach/frastra/freesurfer/subjects/AB/label/lh.V2dorsal_AB.label --sfavg lh.V2dorsal_AB_disorder_avg --snr --sum lh.V2dorsal_AB_disorder_sum # sysname Linux # hostname access4.wexac.weizmann.ac.il # machine x86_64 # user frastra # anatomy_type surface # # SUBJECTS_DIR /home/labs/malach/frastra/freesurfer/subjects # subjectname AB # Label AB lh /home/labs/malach/frastra/freesurfer/subjects/AB/label/lh.V2dorsal_AB.label # InVolFile disorder/z.nii.gz # InVolFileTimeStamp 2018/12/08 20:12:18 # InVolFrame 0 # ExcludeSegId # Only reporting non-empty segmentations # VertexArea_mm2 0.657815 # 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 NVertices # TableCol 3 FieldName Number of Vertices # TableCol 3 Units unitless # TableCol 4 ColHeader Area_mm2 # TableCol 4 FieldName Area # TableCol 4 Units mm^2 # TableCol 5 ColHeader Mean # TableCol 5 FieldName Intensity Mean # TableCol 5 Units unknown # TableCol 6 ColHeader StdDev # TableCol 6 FieldName Itensity StdDev # TableCol 6 Units unknown # TableCol 7 ColHeader Min # TableCol 7 FieldName Intensity Min # TableCol 7 Units unknown # TableCol 8 ColHeader Max # TableCol 8 FieldName Intensity Max # TableCol 8 Units unknown # TableCol 9 ColHeader Range # TableCol 9 FieldName Intensity Range # TableCol 9 Units unknown # NRows 2 # NTableCols 9 # ColHeaders Index SegId NVertices Area_mm2 StructName Mean StdDev Min Max Range SNR 1 0 161272 106116.2 Seg0000 -0.9503 2.4005 -13.2314 11.4302 24.6617 -0.3959 2 1 1369 871.1 Seg0001 1.3153 3.8989 -8.2296 10.3666 18.5962 0.3373 # Title Segmentation Statistics # # generating_program mri_segstats # cvs_version $Id: mri_segstats.c,v 1.75.2.9 2013/02/16 00:09:33 greve Exp $ # cmdline mri_segstats --i order/z.nii.gz --slabel AB lh /home/labs/malach/frastra/freesurfer/subjects/AB/label/lh.V2dorsal_AB.label --sfavg lh.V2dorsal_AB_order_avg --snr --sum lh.V2dorsal_AB_order_sum # sysname Linux # hostname access4.wexac.weizmann.ac.il # machine x86_64 # user frastra # anatomy_type surface # # SUBJECTS_DIR /home/labs/malach/frastra/freesurfer/subjects # subjectname AB # Label AB lh /home/labs/malach/frastra/freesurfer/subjects/AB/label/lh.V2dorsal_AB.label # InVolFile order/z.nii.gz # InVolFileTimeStamp 2018/12/08 20:12:49 # InVolFrame 0 # ExcludeSegId # Only reporting non-empty segmentations # VertexArea_mm2 0.657815 # 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 NVertices # TableCol 3 FieldName Number of Vertices # TableCol 3 Units unitless # TableCol 4 ColHeader Area_mm2 # TableCol 4 FieldName Area # TableCol 4 Units mm^2 # TableCol 5 ColHeader Mean # TableCol 5 FieldName Intensity Mean # TableCol 5 Units unknown # TableCol 6 ColHeader StdDev # TableCol 6 FieldName Itensity StdDev # TableCol 6 Units unknown # TableCol 7 ColHeader Min # TableCol 7 FieldName Intensity Min # TableCol 7 Units unknown # TableCol 8 ColHeader Max # TableCol 8 FieldName Intensity Max # TableCol 8 Units unknown # TableCol 9 ColHeader Range # TableCol 9 FieldName Intensity Range # TableCol 9 Units unknown # NRows 2 # NTableCols 9 # ColHeaders Index SegId NVertices Area_mm2 StructName Mean StdDev Min Max Range SNR 1 0 161272 106116.2 Seg0000 -0.9503 2.4005 -13.2314 11.4302 24.6617 -0.3959 2 1 1369 871.1 Seg0001 1.3153 3.8989 -8.2296 10.3666 18.5962 0.3373 Thanks a lot for the help Best Francesca -- Francesca Strappini, Ph.D. Neurobiology Department Weizmann Institute of Science 234 Herzl Street, Rehovot 7610001 Israel Tel.: +972 58 444 2584 E-mail: francesca.strappini(a)weizmann.ac.il

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[PETSurfer] Intensity normalization of PET images without PVE correction
by Matthieu Vanhoutte 08 Feb '19

08 Feb '19

External Email - Use Caution Dear Douglas, Is it possible to use mri_gtmpvc command in order to intensity normalize PET images without applying PVE correction by setting --psf to 0 ? Best, Matthieu

3 18

Vertex-wise area anlaysis
by Klaas Bahnsen 07 Feb '19

07 Feb '19

External Email - Use Caution Dear Freesurfer Experts, First of all: Thank you so much for your work and your fantastic product. I turn to you with a short question, I hope it is not too unnecessary and can be answered quickly. My interest lies in vertex wise longitudinal investigation of cortex surface area. The paper 'False positive rates in surface-based anatomical analysis' (Greve, Fischl 2018) briefly describes how Freesurfer calculates cortex surface areas: First the transfer to the target atlas with "Jacobian Correction" and second the division by eTIV (ICV) to include the factor of different head sizes. Finally, a smoothing should be applied. My question is where these data are stored in the Freesurfer data structure or where they are generated. My understanding is that first recon-all stores this data per scan under SubjectID/surf/?h.area. These could then be picked up by mris_preproc and smoothed with mri_surf2surf. This smoothed file could then be used for example for a GLM model (mri_glmfit). Are the steps described in the paper covered with this workflow? Or must a special option be selected at some point, e.g. to perform the division by the eTIV. I'm a bit unsure at the moment because I also found a collection of questions from previous courses on the FreeSurfer Wiki page. In course 2014 Copenhagen the question is asked which units are used in the output files which are calculated by mris_preproc. Part of the answer states that the data in ?h.area.mgh on vertex level do not have much meaning, because they are dependent on the triangle mesh. Hopefully you can help me and hopefully I won't steal you too much time with my question. With kind regards, Klaas Bahnsen

2 1

Maximum vertex value
by Marina Fernández 07 Feb '19

07 Feb '19

External Email - Use Caution Dear Freesurfer Team, How can I get the maximum vertex value for each subject in a particular cluster? Thank you very much. Marina.

2 1

Functional connectivty walkthrough step 8 error
by Amrita Bedi 07 Feb '19

07 Feb '19

External Email - Use Caution Hello Freesurfer developers, I was following the functional connectivity walkthrough for resting stage BOLD data and I got the attached error when I ran step 8 (selxavg3-sess). Does anyone have any thoughts on how to trouble shoot this? Not sure if it’s of any use but I ran this using Freesurfer 6.0 on Centos 7.4 Thank You. Best Amrita

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Combination of multiple PET projection: "mri_vol2surf --projfrac" vs. "mris_expand"
by Matthieu Vanhoutte 07 Feb '19

07 Feb '19

External Email - Use Caution Dear Freesurfer’s experts, I have read the paper from Marcoux, et al. « An Automated Pipeline for the Analysis of PET Data on the Cortical Surface ». Frontiers in Neuroinformatics 12 (10 décembre 2018). https://doi.org/10.3389/fninf.2018.00094 <https://doi.org/10.3389/fninf.2018.00094>. In this paper, they propose a robust PET signal projection based on weighting multiple PET projections at different fractions of the cortical thickness. They used « mris_expand" instead of "mri_vol2surf --projfrac" based on the following comments: "We mainly rely on the mris_expand function of FreeSurfer rather than on vol2surf. The vol2surf function allows the user to project volume data onto the cortical surface by sampling along the normal of the white surface, by steps corresponding to fractions of the cortical thickness. We observed that the main issue with this approach is its lack of accuracy and robustness, as there is no constraint to ensure that the last sample will be on the corresponding vertex of the pial surface. Another solution proposed by FreeSurfer is to use the normal fromthemid surface, starting on the side of the white surface and going toward the pial surface, sampling by steps proportional to the thickness. Here again we observed that, because of different folding patterns, sampling points could be located outside the cortical ribbon. Our approach, using deformable surfaces obtained with mris_expand, ensures that the seven surfaces that are used to project the signal follow the folding patterns and stay within the cortical ribbon." Is "mris_expand" more accurate and robust than "mri_vol2surf --projfrac" according to you ? Best, Matthieu

2 1

problem using recon-all
by Shachar Gal 07 Feb '19

07 Feb '19

External Email - Use Caution hello, I using the HCP FreeSurfer Pipeline (using FreeSurfer 5.3-HCP version) on ubuntu, and I encounter this error (copying from the recon-all.log) _______________________________________ #@# Talairach Sun Jan 13 17:35:07 IST 2019 /home/shachar/piano_hcp/102/102/mri mri_nu_correct.mni --n 1 --proto-iters 1000 --distance 50 --no-rescale --i orig.mgz --o orig_nu.mgz Linux maestro 4.15.0-43-generic #46-Ubuntu SMP Thu Dec 6 14:45:28 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux recon-all -s 102 exited with ERRORS at Sun Jan 13 17:35:08 IST 2019 _______________________________________ i'm a bit confused by the lack of error descriptions, and would appreciate any leads for solving it :) Shachar

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PET PVC transforms and MG voxels
by Adam Martersteck 07 Feb '19

07 Feb '19

External Email - Use Caution Hi FreeSurfer team, I have two comments/questions about PET PVC & Doug’s 2016 Neuroimage paper: 1) It looks like the 2 rigid transforms created during mri_gtmpvc found at [$pvc_directory/aux/anat2bbpet.lta] and [$pvc_directory/aux/bbpet2anat.lta] are misnamed and the file names should be swapped. I noticed this isn’t a problem during mri_vol2surf (e.g. the PetSurfer wiki) because mri_vol2surf is “smart” and will automatically detect and invert the transform -- but it was causing problems for me when I used them during mri_vol2vol thinking the bbpet2anat.lta was from pet space to anat space. I apologize if you already knew about this – I couldn’t find anything in the FSv6 “Known Issues” or on the PetSurfer page. 2) I am using the MG PVC stream and a fairly conservative GM PVF threshold of 30% (similar to Doug’s paper). I noticed when the PVF is < 0.3 it sets the corrected [mg.nii.gz] image to zero in those voxels. Intuitively, I would have thought this would just “cap” all values < 0.3 to 0.3 and divide voxels by 0.3 to get a MG corrected voxel. I went back to Doug’s paper and found, indeed, the paper says, *“In this study, we varied the threshold from 1% to 50%. The TACs in voxels that did not meet this criterion were set to zero.”* So when I take the mg.nii.gz and use vol2surf as Doug did, I get a significant number of “patches” of zero values across the cortex (see attached image; every voxel along the normal is zero). I would then have smoothed this surface -- artificially lowering the entire neighborhood of vertices. Did you guys do something else for the Neuroimage paper when you were going from vol2surf? Or did you smooth the zeroes into the surrounding vertices? Maybe this isn't a problem in healthy brains and the projfrac 0.5 voxel is always a non-zero? Since I am working with significantly atrophied Alzheimer brains -- would “capping” the PVF make sense here to balance over correcting noise while avoiding non-zero vertices? Is there a command in fscalc to set all values between 0.0001 and 0.3 to 0.3 so I could do this? Thanks! Adam

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Freesurfer January 2019