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Voxel time-series within a specific functional ROI
by Ashley Cole 13 Dec '17

13 Dec '17

I am working on an fMRI-adaptation experiment and was wondering how to extract voxel time-series within a specific functional ROI. I have created a functional ROI mask. This mask has only one time-point. According to this thread https://mail.nmr.mgh.harvard.edu/pipermail/freesurfer/2014-October/040811.h… I need to I use the funcroi-table-sess command multiple times. Is this correct? So if I have 270 TRs. I have to run the command 270 times? Thanks, AC

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Re: [Freesurfer] PET partial volume correction:mri_gtmpvc error
by Herranz Muelas, Elena 13 Dec '17

13 Dec '17

Hi Doug, Thanks for your response. Actually, we do modify the aseg.mgz (Sorry, I didn't realized and I shouldn't have considered this a 'standard FS pipeline'). We work with Multiple Sclerosis patients and because of the size and number of lesions in some of them, the pial and WM surfaces that we obtain after a first run of “recon-all -all ” are not accurate. FreeSurfer pipeline for healthy subjects or small lesions requires to edit wm.mgz -- but these edits don't fix our issue of WM & GM surface getting pulled in by lesions. Given the size and number of lesions in some of our MS patients, using control points make the entire recon worse. So after repeated testing, the solution we arrived at was to insert manually drawn lesion masks into segmentation volumes as "WM-hypointensities". We label manually drawn lesion masks as "WM-hypointensities" on aseg.mgz, and wm.mgz. We then do a second run of recon-all and check the surfaces again. Once they are ok we run “recon-all -autorecon3” and check the final output. In principle, we only change voxels in aseg.mgz to "WM-hypointensities", so I don't know why these unexpected values appear. Just to check, I renamed the 'aseg.auto.mgz' as 'aseg.mgz' and re-run again the steps for PVC: 1. Segmentation for GTM: gtmseg --s $subj"_recon" --xcerseg In this step I get the following warnings: WARNING: segid 59 Right-Substancia-Nigra tissue type is not set WARNING: segid 61 Right-undetermined tissue type is not set WARNING: segid 64 Right-F3orb tissue type is not set WARNING: segid 73 Left-Interior tissue type is not set WARNING: segid 81 Left-non-WM-hypointensities tissue type is not set WARNING: segid 86 Left_future_WMSA tissue type is not set 2. Registration: mri_coreg --s $subj"_recon" --mov $path_to_suvr/SUVR.nii.gz --reg $path_to_suvr/SUVR.reg.lta 3. PVC: mri_gtmpvc --i $path_to_suvr/SUVR.nii.gz --reg $path_to_suvr/SUVR.reg.lta --psf 6 --seg gtmseg.mgz --default-seg-merge --auto-mask PSF .01 --mgx .01 --o $path_to_recon/$subj"_recon"/gtmpvc.output. And still get the same error (below) (maybe because there are other files that are based in the previous aseg.mgz? ) Checking tissue type ERROR: CheckSegTissueType() tissue type for seg 64 Right-F3orb not set Failed tissue type check Any help with this would be very much appreciate it! Thanks! Elena ________________________________________ From: freesurfer-bounces(a)nmr.mgh.harvard.edu [freesurfer-bounces(a)nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve(a)nmr.mgh.harvard.edu] Sent: Thursday, December 07, 2017 12:19 PM To: freesurfer(a)nmr.mgh.harvard.edu Subject: Re: [Freesurfer] PET partial volume correction:mri_gtmpvc error Hi Elena, it looks like the aseg.mgz has several unexpected segments in it. The aseg.auto.mgz looks ok, so I think FS is working properly. It looks like you made some changes to the aseg. What did you do? On 12/06/2017 03:51 PM, Douglas N Greve wrote: > Did you run this through the standard FS pipeline? If so, can you send > me the FS analysis for this subject? You can upload it here > > https://gate.nmr.mgh.harvard.edu/filedrop2 FileDrop v2.0 - Martinos Center for Biomedical Imaging<https://gate.nmr.mgh.harvard.edu/filedrop2> gate.nmr.mgh.harvard.edu Filedrop is for sending files work-related files up to 2GiB; For files over 2GiB, please use the Accellion File Transfer from Partners; Filedrop is not a secure ... > > > On 12/06/2017 09:46 AM, Herranz Muelas, Elena wrote: >> Dear Freesurfers, >> >> >> I am trying to apply partial volume correction to my PET images, >> following the steps explained in the PetSurfer wiki. >> >> >> When I run the mri_gtmpvc command, it works fine for most of the >> subjects but for some of them I get the following error message: >> >> >> /autofs/space/alicudi_002/users/mscat/users/caterina/MR-PET/MSPET06/PET/PET-space >> Loading input >> /autofs/space/alicudi_002/users/mscat/users/caterina/MR-PET/MSPET06/PET/PET-space/SUVR.nii.gz >> done loading input 1 frames >> $Id: mri_gtmpvc.c,v 1.69.2.1 2016/07/08 19:50:25 zkaufman Exp $ >> setenv SUBJECTS_DIR >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3 >> cd /autofs/space/alicudi_002/users/mscat/users/elena/scripts/PVC >> mri_gtmpvc --i >> /autofs/space/alicudi_002/users/mscat/users/caterina/MR-PET/MSPET06/PET/PET-space/SUVR.nii.gz >> --reg >> /autofs/space/alicudi_002/users/mscat/users/caterina/MR-PET/MSPET06/PET/PET-space/SUVR.reg.lta >> --psf 6 --seg gtmseg.mgz --default-seg-merge --auto-mask PSF .01 --mgx >> .01 --o >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/MSPET06_recon/gtmpvc.output >> sysname Linux >> hostname alicudi.nmr.mgh.harvard.edu >> machine x86_64 >> user ehmuelas >> vgthresh 0.001000 >> nReplace 18 >> 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 >> 40 avail.processors, using 1 >> Creating output directory >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/MSPET06_recon/gtmpvc.output >> Loading seg for gtm >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/MSPET06_recon/mri/gtmseg.mgz >> Loading seg ctab >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/MSPET06_recon/mri/gtmseg.ctab >> Reading >> /autofs/space/alicudi_002/users/mscat/users/caterina/3T/recons_fsv5.3/MSPET06_recon/mri/gtmseg.lta >> Replacing 18 >> Pruning ctab >> *Checking tissue type >> ERROR: CheckSegTissueType() tissue type for seg 64 Right-F3orb not set >> Failed tissue type check >> * >> >> >> And the command line that I ran: >> >> mri_gtmpvc --i $path_to_suvr/SUVR.nii.gz --reg >> $path_to_suvr/SUVR.reg.lta --psf 6 --seg gtmseg.mgz >> --default-seg-merge --auto-mask PSF .01 --mgx .01 --o >> $path_to_recon/$subj"_recon"/gtmpvc.output >> >> >> Could you please help me out with this? >> >> >> Many thanks in advance! >> >> >> Elena >> >> >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer Freesurfer -- Freesurfer support list - Harvard University<https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer> mail.nmr.mgh.harvard.edu To see the collection of prior postings to the list, visit the Freesurfer Archives. A searchable archive which of messages PRIOR to March 2004 is at ... -- Douglas N. Greve, Ph.D. MGH-NMR Center greve(a)nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 FileDrop v2.0 - Martinos Center for Biomedical Imaging<https://gate.nmr.mgh.harvard.edu/filedrop2> gate.nmr.mgh.harvard.edu Filedrop is for sending files work-related files up to 2GiB; For files over 2GiB, please use the Accellion File Transfer from Partners; Filedrop is not a secure ... www.nmr.mgh.harvard.edu/facility/filedrop/index.html<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> Martinos Center File Drop - nmr.mgh.harvard.edu<http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html> www.nmr.mgh.harvard.edu 11/15/2012 -- There is a new version of Filedrop. Please help us test it https://gate.nmr.mgh.harvard.edu/filedrop2/ Welcome to the Martinos Center file drop area ... Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ _______________________________________________ Freesurfer mailing list Freesurfer(a)nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer

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Dura classified as GM in brainmask
by FSL Analysis 13 Dec '17

13 Dec '17

Hi all, I have processed data using freesurfer and the output for most of my subjects did not remove all of the eye and dura around it during skull stripping. When I check the brainmask there is dura (or blood vessel) in the frontal lobe that is classified as GM. I am wondering if I have to manually edit the skullstrip and rerun recon-all or do I just edit the brainmask file by deleting non-brain voxels? Or do I have to do both? If I only edit the brainmask file does this skip any other important processing steps that may affect my results? I am planning on looking at brain volumes and cortical thickness and how they relate to behavioral measures. Kind Regards, Ciara

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Re: [Freesurfer] Hippocampal Subfield and Amyg Nuclei ICV Correction
by Maksimovskiy, Arkadiy 13 Dec '17

13 Dec '17

Hi Eugenio, Thank you so much for the helpful information! Best, Arkadiy

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Re: [Freesurfer] Dura classified as GM in brainmask
by FSL Analysis 13 Dec '17

13 Dec '17

Hi again, I realize my last question about the brainmask did not make sense. I meant to ask if I have to either manually delete all non-brain voxels around the eye area which is very time consuming per subject or just delete those misclassified as GM? ( I check this through the command: tkmedit subj_output brainmask.mgz -aux T1.mgz -surfs) Also for some subjects: 1. When I open freeview and look at the aseg file there is area around the eye misclassified as cerebral cortex for some subjects. 2. When I load the pial surface the aseg file shows cerebral cortex in the temporal poles and frontal lobes near the eye region outside of the pial surface outline. How do I edit this? I look forward to your response. Thanks On Tue, Dec 12, 2017 at 4:21 PM, FSL Analysis <fslanalysis(a)gmail.com> wrote: > Hi all, > > I have processed data using freesurfer and the output for most of my > subjects did not remove all of the eye and dura around it during skull > stripping. When I check the brainmask there is dura (or blood vessel) in > the frontal lobe that is classified as GM. > > I am wondering if I have to manually edit the skullstrip and rerun > recon-all or do I just edit the brainmask file by deleting non-brain > voxels? Or do I have to do both? > > If I only edit the brainmask file does this skip any other important > processing steps that may affect my results? > > I am planning on looking at brain volumes and cortical thickness and how > they relate to behavioral measures. > > > > > Kind Regards, > > Ciara >

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Re: [Freesurfer] Hippocampal Subfield and Amyg Nuclei ICV Correction
by Iglesias Gonzalez, Eugenio 13 Dec '17

13 Dec '17

Hi Arkadiy 1. Yes 2. If you’re correcting the subfields by hippocampal volume: a) the question is a different one (“which fraction of the hippo volume is attributed to each subfield”); and b) I wouldn’t correct by ICV, because the values are already fractions / normalized (see point a). Cheers, /Eugenio -- Juan Eugenio Iglesias ERC Senior Research Fellow Translational Imaging Group University College London http://www.jeiglesias.com http://cmictig.cs.ucl.ac.uk/ From: <freesurfer-bounces(a)nmr.mgh.harvard.edu> on behalf of "Maksimovskiy, Arkadiy" <AMAKSIMOVSKIY(a)mclean.harvard.edu> Reply-To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> Date: Wednesday, 13 December 2017 at 16:08 To: "freesurfer(a)nmr.mgh.harvard.edu" <freesurfer(a)nmr.mgh.harvard.edu> Subject: [Freesurfer] Hippocampal Subfield and Amyg Nuclei ICV Correction Dear Experts, I have seen this question pop up a few times in the forum, but have not seen a clear response, so I was wondering if someone might be able to clarify or offer their opinion. 1. Do the hippocampal subfields and amygdala nuclei need to be corrected for ICV (either by including ICV as a covariate or taking the ration if each subfield to the ICV)? 2. If so, might it make more sense to correct them (perhaps take the ratio of each subfield to the hippocampus) for the volume of the hippocampus (after the hipp. itself has been corrected for the ICV)? If the correction is recommended, I am wondering about whether the second option might be better, because the ICV correction might be introducing too much variability for such a small sub-structure, whereas, correcting for just the hippocampus volume might be a bit more accurate. I found two ways of dealing with this in the relevant papers for the hipp. Subfield and amyg nuclei, respectively, quoted below: “Then, we correct these estimates for age and intracranial volume (ICV) by regressing them out with a general linear model. This step is important because the subregion volumes are strongly correlated with these two variables, which can easily confound the analysis – subjects with large ICV and/or of younger age are expected to have larger hippocampi; see for instance (Mueller, Schuff, Yaffe, Madison, Miller, & Weiner, 2010). Moreover, such correction was used in (Mueller, et al., 2013), so we used this correction as well in order to directly compare the results” (Iglesias, 2015) “ICV was added as a covariate to all ANOVAs” (Saygin, 2017) I would love to hear any advice/perspective. Thank you in advance. Arkadiy

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Creating functional ROI
by Ashley Cole 13 Dec '17

13 Dec '17

Dear Doug/Bruce, I appreciate any insights on this. Thank you, Ashely ------------------------------------ I am new to FreeSurfer and I apologize in advance if my questions are too naiive. My main goal is to keep everything in the native space. Also, I am looking for percent signal change in selected ROIs. First, I ran recon-all command. Then, I preprocessed the functional data in native space. The command that I ran was: preproc-sess -s sess01 -fsd bold -stc odd -surface self lhrh -mni305 -fwhm 5 -per-session -force Then, I configured my analyses and contrasts in each hemisphere, as well as the volume. Finally, I ran the analyses for each hemispheres and the volume. I ran this command: selxavg3-sess -s sess01 -analysis ffa.native.rh Lastly, I visualized the results by running these commands: tksurfer-sess -s sess01 -hemi rh -analysis ffa.native.rh -c faces-vs-bodies -self tkmedit-sess -s sess01 -analysis ffa.native.mni -c faces-vs-bodies -self So far, I think I have done everything correctly. I am seeing the activation ROIs where I am supposed to. Now, I would like to be able to select these ROIs/clusters, take their voxel coordinates/numbers and create a mask. (These are my localizer nii files.) Then, use this mask on the main experiment (non localizer) nii files and get the percent signal change in those selected voxels. Is this possible? I have found this tutorial https://surfer.nmr.mgh.harvard.edu/fswiki/ CreatingROIs but unfortunately I am not following it. I don't see these options in tksurfer. Also is it possible to create an ROI on the surface? I appreciate any help. Thank you so much Ashley Cole

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Hippocampal Subfield and Amyg Nuclei ICV Correction
by Maksimovskiy, Arkadiy 13 Dec '17

13 Dec '17

Dear Experts, I have seen this question pop up a few times in the forum, but have not seen a clear response, so I was wondering if someone might be able to clarify or offer their opinion. 1. Do the hippocampal subfields and amygdala nuclei need to be corrected for ICV (either by including ICV as a covariate or taking the ration if each subfield to the ICV)? 2. If so, might it make more sense to correct them (perhaps take the ratio of each subfield to the hippocampus) for the volume of the hippocampus (after the hipp. itself has been corrected for the ICV)? If the correction is recommended, I am wondering about whether the second option might be better, because the ICV correction might be introducing too much variability for such a small sub-structure, whereas, correcting for just the hippocampus volume might be a bit more accurate. I found two ways of dealing with this in the relevant papers for the hipp. Subfield and amyg nuclei, respectively, quoted below: “Then, we correct these estimates for age and intracranial volume (ICV) by regressing them out with a general linear model. This step is important because the subregion volumes are strongly correlated with these two variables, which can easily confound the analysis – subjects with large ICV and/or of younger age are expected to have larger hippocampi; see for instance (Mueller, Schuff, Yaffe, Madison, Miller, & Weiner, 2010). Moreover, such correction was used in (Mueller, et al., 2013), so we used this correction as well in order to directly compare the results” (Iglesias, 2015) “ICV was added as a covariate to all ANOVAs” (Saygin, 2017) I would love to hear any advice/perspective. Thank you in advance. Arkadiy

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cortical thickness smoothing
by John Anderson 13 Dec '17

13 Dec '17

Dear Freesurfer experts, I ran recon-all with the flag -qcache to generate smoothed cortical thickness maps. In order to check how the flag "-qcache" is smoothing the cortical thickness data. I looked into the file $subj_dir/scripts/recon-all.log" which showed that the following command was applied: mri_surf2surf --prune --s fsaverage --hemi lh --fwhm 5--sval lh.sulc.fsaverage.mgh --tval lh.sulc.fwhm5.fsaverage.mgh --cortex Please I want to know whether the flag "--fwhm" applies similar smoothing method to the smoothing output of the command "fslmaths": fslmaths <input_image.nii> -kernel gauss 2.213 -fmean <output_image.nii> -odt float I want to smooth two different modality-images using the cortical thickness smoothing method. Thank you for any advice! John

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[Re] medial wall label in Freesurfer 6
by M del Mar Velasco 13 Dec '17

13 Dec '17

Hi Andrew, Thanks very much! I have tried the new version of make_average_surface and it works fine. I am very gratefull. Best, M del Mar

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