Freesurfer August 2023

freesurfer@nmr.mgh.harvard.edu

89 participants
126 discussions

Unit of the Numbers in cache.th40.neg.y.ocn.dat
by Na, Xiaoxu 17 Feb '24

17 Feb '24

External Email - Use Caution Dear Freesurfer Experts, As I'd like to extract the average value of each subject in the cluster after running group analysis, may I know the unit of these numbers? Since the one I'm running is surface area, and the cluster is 444mm^2, all the numbers in the file cache.th40.neg.y.ocn.dat is in the range of [0.55 1.05], may I know if this is correct and if so, how the unit is for those? Thanks a lot! ClusterNo Max VtxMax Size(mm^2) MNIX MNIY MNIZ CWP CWPLow CWPHi NVtxs WghtVtx 1 -4.8321 40067 444.11 -58.1 -16.6 -23.9 0.0002 0 0.0004 670 -2784.11 Regards, Xiaoxu ---------------------------------------------------------------------- Confidentiality Notice: This e-mail message, including any attachments, is for the sole use of the intended recipient(s) and may contain confidential and privileged information. Any unauthorized review, use, disclosure or distribution is prohibited. If you are not the intended recipient, please contact the sender by reply e-mail and destroy all copies of the original message.

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mri_watershed and improvements of skullstripping
by Michelangelo Fabbrizzi 01 Feb '24

01 Feb '24

External Email - Use Caution Dear Freesurfer experts, I am new to FS, and I would have couple of questions. I used in sequence: A- recon-all -i sub-01_T1w.nii.gz -s sub-01_recon -autorecon1 B- recon-all -skullstrip -wsthresh 5 -clean-bm -s sub-01_recon C- recon-all -skullstrip -clean-bm -gcut -subjid sub-01_recon The brainmask.mgz obtained is good (no skull, brain is okay), however if I now use mri_watershed to obtain the bem surfaces, it looks the brainmask.mgz is not used and it is created a new one called ws.mgz that still contain some piece of skull that generate wrong BEM surfaces; even using -h 5 the result is not optimal: mri_watershed -h 5 -useSRAS -surf /Users/michelangelo/Test_skullstripping/sub-01_recon/bem/watershed/sub-01_recon /Users/michelangelo/Test_skullstripping/sub-01_recon/mri/T1.mgz /Users/michelangelo/Test_skullstripping/sub-01_recon/bem/watershed/ws.mgz I am wondering: - how can I force the mri_watershed command to use the brainmask.mgz already created after step C above, instead of creating a new one? - is it possible to use the -gcut command also for mri_watershed? Thanks, appreciated, Miche

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Tkregister2 GUI not responding fully
by Viktorija Pratuseviciute 02 Nov '23

02 Nov '23

External Email - Use Caution Hello, We are trying to process a scan with a failed talairach. We have been able to visualize the misalignment and attempted to use the following command (tkregister2 --s PI163 –fstal) to manual adjust the talairach.xfm based on the tutorial (https://secure-web.cisco.com/1acx6rTd53-Vz7knc_wTrpqifC8PTuiKKanQydzd8QVOyX…) The tkregister2 GUI opens up, however only certain functions work: I can switch between target and moveable, I can also double click on sliding scales to switch coronal, saggital and horizontal views, however I am not able to move any of the sliders including the rotate or translate brain and hence unable to fix the talairach. Is there a way to fix this issue? Or an alternative way to fix the bad talairach output? We are using freesurfer/7.3.1 and have attempted the command on our server command line on both mac and windows with same results. Many thanks, Viki

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Re: [Freesurfer] MANCOVA + Posthoc Testing Design Matrix Setup
by Cristina A. F. Román 15 Oct '23

15 Oct '23

External Email - Use Caution Hello, I am looking to run a MANCOVA to examine cortical gray matter differences across three groups (accounting for several covariates), and I was hoping to get input on whether I am setting up my design matrix correctly. Groups: 3 Covariates: Age (demeaned), disease duration (DD; demeaned), sex Simplified Example: Group EV1(Grp1) EV2(Grp2) EV3(Grp3) EV4(age) EV5(DD) EV6(sex) 1 1 0 0 0.25 0.75 -1 1 1 0 0 0.25 0.25 -1 1 0 1 0 -0.75 -0.25 1 1 0 1 0 0.5 -0.75 1 1 0 0 1 -0.5 0.5 1 1 0 0 1 0.25 0.25 -1 Questions: 1. Is this an appropriate way to do a three-group comparison with covariates? Or, is it better to just run three separate t-tests (including covariates)? 2. Regarding post-hoc testing, would I just do three separate t-tests? This issue here, I imagine, is that the individual t-test results may not reflect the original MANCOVA results (e.g., post-hoc testing reveals a new significant area that was not significant in the MANCOVA). 3. One other option is to run the initial MANCOVA within a statistical program (i.e., using global cortical gray matter volumes) and then follow up with postdoc testing within FSL (i.e., t-tests). Would this make sense? Thanks in advance for your time and help, Cristina

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Question about mri_nu_correct.mni
by ruifeng14＠gmail.com 15 Oct '23

15 Oct '23

External Email - Use Caution Hi all, I am running Freesurfer 7.3.2 on T1 images (LPI orientation) with 176*256*256 FOV, 1mm isotropic resolution. I saw that the Ants N4 bias correction is done after the FOV is expanded to 256*256*256, not on the original image. Shouldn't the zeros in the expanded image affect the bias correction? Thanks. Best, Ruifeng

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Follow up question on group analysis (mri_glmfit)
by inbal paran 23 Sep '23

23 Sep '23

External Email - Use Caution Thanks for the quick response. So I followed the steps of the tutorial and performed group analysis by running mris_preproc, then mri_surf2surf and then mri_glmfit. Is that the correct way to do that? and in this case, can I include multiple continuous variables in my analysis (in the fsgd file)? Thanks again Inbal -------- It is worse -- we do not support qdec anymore On 8/5/2023 6:04 AM, inbal paran wrote: External Email - Use Caution Hello FreeSurfer Developers, I have a question regarding group analysis: When I followed the instructions on how to build my FSGD file, it said that:"FSGD files are created automatically by qdec, but qdec is currently (12/9/08) limited to two continuous variables and two discrete variables with two levles. Is this still the case, or is it possible to include more than 2 continuous variables? The freesurfer version I am using: freesurfer-linux-centos7_x86_64-7.1.1-20200723-8b40551 Thank you Inbal -- *Inbal Paran, M.PT <http://secure-web.cisco.com/1w6eByVfQtHP57lPYq2r_KIYGKXnqPLFlDOaO0p2X1WZmr0…>.* Schwartz Movement analysis & Rehabilitation Laboratory, Physical Therapy Department, Recanati School for Community Health Professions. Faculty of Health Sciences at Ben-Gurion University of the Negev.

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TRACULA cluster visualization - mri_glmfit-sim issue?
by Goeckner, Bryna 18 Sep '23

18 Sep '23

External Email - Use Caution Hi Freesurfer Developers, I am having an issue similar to two posted earlier this year with the visualization of significant clusters from tracula not seeming to match the data. (link to first posting here: https://secure-web.cisco.com/1YIyp3Yo44Yjw3sCRGiQdzImJfJAVEC8lOoyUpu2pWJi9R…) Specifically, when mri_glmfit is first run, the data and initial visualization of the significant voxels along the lh cingulum bundle (dorsal) make it appear that the area with the most significant effect is in the anterior part of the tract (see sig_overlay.png). When mri_glmfit-sim is run, the text file of the significance values masked by clusters that survive correction also makes it appear that the significant effects would be in the anterior portion of the tract because they are at the top of the text file (see perm.th13.abs.sig.masked.txt), and earlier data, in agreement with information on the tracula page, is given anteriror to posterior along this tract. This matched what I would expect given the data before clusterwise correction. However, the visualization of the masked significance values seems to show only posterior areas with effects (see sigmasked_overlay.png) I am wondering if there is something in the mri_glmfit-sim process that woucl be causing this apparent flip in the visualization or if there is something I need to be doing differently. Please let me know if you need any additional information and thanks in advance for your help! My code: mri_glmfit --y ${STATDIR}/${TRACT}.avg16_syn_bbr.${MET}.nii.gz --fsgd ${STATDIR}/${STUDY}/inputs/${FSGD}.fsgd doss --C ${STATDIR}/${STUDY}/inputs/${C}.mtx --o ${STATDIR}/${STUDY}/${C}/${TRACT}.${MET}.glmdir --save-eres mri_glmfit-sim --glmdir ${STATDIR}/${STUDY}/${C}/${TRACT}.${MET}.glmdir --cwp 0.05 --perm 1000 1.3 abs To create visualizations: dmri_trk2trk --in /opt/freesurfer/trctrain/hcp/syn/${TRACT}.display.trk --out ${STATDIR}/${STUDY}/${C}/${ResFol}/${TRACT}.${MET}.maskedoverlay.trk --over ${STATDIR}/${STUDY}/${C}/${TRACT}.${MET}.glmdir/${C}/perm.th13.abs.sig.masked.mgh To create text file from mri_glmfit-sim makes output: mri_convert --ascii perm.th13.abs.sig.masked.mgh perm.th13.abs.sig.masked.txt Bryna Goeckner (she/her) Graduate Student Meier Lab<https://secure-web.cisco.com/1L0DdRAsArvZ7gyFkPi0YnO8htwQ03fLvWrtjVgm-rwoJR…> Medical College of Wisconsin Neuroscience Doctoral Program

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lme and single random effect estimates
by Antonio Napolitano 12 Sep '23

12 Sep '23

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Discrepancy in vertex counts between resampled and recon-all generated annot files
by Leonardo Cardoso Saraiva 10 Sep '23

10 Sep '23

External Email - Use Caution Dear Freesurfer Experts, I am using .annot files to extract parcellated vertex-wise morphometric features from surf files (e.g., area value from ?h.area file). For each vertex, I want to determine the parcel it belongs to and its associated morphometric features. During this process, I exclude vertices labeled as ‘unknown’ or ‘medial wall’. In addition to the aparc parcellation, I am also using other parcellations computed on fsaverage. Therefore, I need to resample these parcellations onto native surfaces. To do this, I am using commands such as the one below: mri_surf2surf --srcsubject fsaverage \ --sval-annot ${SUBJECTS_DIR}/fsaverage/label/lh.test\ --trgsubject sub-test \ --trgsurfval ${SUBJECTS_DIR}/sub-test/label/lh.test \ --hemi lh As a sanity check, I used the above command to resample the aparc parcellation onto native surfaces (which is already done by recon-all). However, when I use the .annot files generated by the above command to extract morphometric features from surf files, I get a different number of vertices than when I use the .annot files generated by recon-all. Is this behavior expected? Am I doing something wrong? Thank you for your time and attention. Best, Leo

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SAMSEG choice of the input
by Giulio Siracusano 10 Sep '23

10 Sep '23

External Email - Use Caution Dear Experts, I'm trying to understand what is the best input choice for running SAMSEG --recon in order to have the closest results as possible when compared against ASEG after executing (separately) an instance of recon-all all (and the raw input files in NIFTI format). I'm very well aware that ASEG and SAMSEG are different methods. I'm using the aseg.stats file as a results of the recon-all all command (here renamed as aseg.recon-all.stats for an easier identification). These stats should be my reference. Currently I've run the samseg command using the following input variants: 1) raw input file (brain MP-RAGE sequence) converted into a mgz archive (Raw.mgz). samseg --t1w ./Raw.mgz --s 002_S_0685_DIRECT --recon --refmode t1w The corresponding results are attached into (samseg.direct.stats) 2) This time I've used the file T1.mgz which is one of the intermediate results generated after running recon-all -autorecon 1. Specifically, this is the output of (mri_normalize <https://secure-web.cisco.com/1JV3nYNrViePm1qpOtzuMUtCndnVtCut-gp7OyXxNuXIOk…> -g 1 -mprage nu.mgz T1.mgz). samseg --t1w ./T1W/T1.mgz --s 002_S_0685_DIRECT_T1W --recon --refmode t1w The corresponding samseg.stats file is attached and called (samseg.direct.t1.stats). 3) this time I've used the file brainmask.mgz which is the last intermediate result generated after running recon-all -autorecon 1. Specifically, this is the output of mri_watershed <https://secure-web.cisco.com/1DjG5BDGTEbHYOWKmd4lc63SOmX8IrmziV9_NRWhpCskwO…>. samseg --t1w ./brainmask.mgz --s 002_S_0685_DIRECT_BRAIN --recon --refmode t1w The corresponding samseg.stats file is attached and called (samseg.brain.stats). I've noticed that the SAMSEG stats file (samseg.brain.stats) as obtained when using the brainmask.mgz as input file is the closest with the ASEG statistics (aseg.recon-all.stats). I also observe that the unknown volume is the lowest (# Measure Unknown, 5329.102436, mm^3) when using brainmask.mgz as input for SAMSEG, whereas is higher (Measure Unknown, 325302.894793, mm^3) when using T1.mgz as input file and is the highest (Measure Unknown, 946924.354060, mm^3) for the raw input. I know that for running recon-all we use the raw input files (for example, in NIFTI format), but I wanted to know what is the best possible configuration for SAMSEG in terms of input file in order to have the closest match between SAMSEG and ASEG statistics. Could it be possible to use the intermediate result T1.mgz or brainmask.mgz as input file for running samseg command? Is it a technically correct procedure? Do we need to use only the raw data as input for running samseg --recon command? Hope this is clear Regards GS

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Freesurfer August 2023