Freesurfer November 2016

freesurfer@nmr.mgh.harvard.edu

120 participants
214 discussions

Re: [Freesurfer] Cohen's D = gamma.mgh / rstd.mgh?
by Elijah Mak 28 Nov '16

28 Nov '16

Hi Doug, This is my main objective. 1. PET in Group 1 vs Group 2 2. Thickness in the same sample, Group 1 vs Group 2 3. ASL in the same sample of Group 1 vs Group 2 4. Create a binary mask of the overlapping corrected sig voxels from 1-3. 5. This mask is therefore a site of co-localised atrophy, perfusion and PET changes in Group wrt Group 2. Now, I would like to look at how the effect sizes of 1-3 compare against one another, above and beyond the spatial overlap. I hope this is clearer, but let me know if I could provide more information. I thought about looking at *Z-scores* like some other studies, but I find that it is highly dependent on the range of the SD, which differed to a large extent (PET having a range of 1-10 vs 1-3 in atrophy). Hence I thought the Cohen's *D *might represent a more plausible workaround by pooling the SD across both groups, Thanks. Best Wishes, Elijah

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Re: [Freesurfer] Cohen's D = gamma.mgh / rstd.mgh?
by Elijah Mak 28 Nov '16

28 Nov '16

Dear Doug, Thanks. Do you mean use ROI averages as the samples and then test across ROIs? This would be unusual as the interpretation is problematic. I would probably compute a single number per subject that is a weighted sum/difference of the ROI values, then test whether this one number is different across subjects. Probably a silly question.. but how can I get the data at the subject-level as the effectsize.mgh is derived at the group-level after mri_glmft? On a similar note, if I want to simply report the effect size of a significant cluster, could I use mri_glmfit to extract the averaged effect size for the cluster by feeding it as a mask to mri_segstats? Best Wishes, Elijah

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Re: [Freesurfer] LME: contrast questions
by jorge luis 28 Nov '16

28 Nov '16

Yes, it was arbitrary. A linear trajectory was a sufficiently good model for the mean response over time for most of the cortex points in my analyses. Also if you only have at most three time points per user then you can only have at most two random effects in your mixed-model (intercept and time). Time squared, if considered, would be just a fixed effect. Best-Jorge De: Jordi Pegueroles <jordi(a)pegueroles.cat> Para: jorge luis <jbernal0019(a)yahoo.es> CC: Freesurfer <freesurfer(a)nmr.mgh.harvard.edu> Enviado: Lunes 28 de noviembre de 2016 11:34 Asunto: Re: LME: contrast questions Thank you for your quickly answer Jorge. What is the rule for decide if we have to use a quadratic term in the model? That is, in your example you use the 80% of the length of the lh.cortex as a threshold. Is this value an arbitrary one? Thank you again, A 2016-11-28 16:05, jorge luis escrigué: > Hi Jordi > > You have implicitly included the reference group in your statistical > model by including an intercept term and a time variable: > > group0 intercept: ß1 > group0 time: ß2 > group1 intercept: ß1+ß3 > group1 time: ß2+ß4 > group2 intercept: ß1+ß5 > group2 time: ß2+ß6 > > From here you can quickly see that your proposed contrast for the > differences in the mean response over time between group1 and group2 > is correct. > > Finally the region growing estimation method should yield more > precise (lower variance) estimates for the ßs but I think it’s (might > be) too complicated to setup with the current scripts. The vw method > will produce good estimates too. So I recommend the vw estimation > method if things get too complicated for you with the region-wise > method. > > Cheers > -Jorge > >> ------------------------- >> DE: Jordi Pegueroles <jordi(a)pegueroles.cat> >> PARA: Freesurfer <freesurfer(a)nmr.mgh.harvard.edu>; >> jbernal0019(a)yahoo.es >> ENVIADO: Lunes 28 de noviembre de 2016 5:11 >> ASUNTO: LME: contrast questions >> >> Dear FS experts, >> >> I am trying to run a LME model for three groups (group0, group1 and >> group2) and (almost all) with three time points, all processed using >> the >> Longitudinal FS stream. >> >> Our intention is to compare the differences between group0 against >> group1 and group0 against group2. I have followed the online LME >> tutorial and I have adapted your code to my data. However, I think I >> have not well understood the steps and I have few questions that you >> will be able to answer me... >> >> i) In the X matrix I put the following columns: >> >> 1) intercept >> 2) time (years from baseline) >> 3) group1 (binary variable: 1 if belongs to group1) >> 4) group1.*time >> 5) group2 (binary variable: 1 if belongs to group2) >> 6) group2.*time >> >> I don't understand why I do not have to include the reference group >> (in my case group0 and group0.*time) in the design matrix. How I can >> see >> the progresion of the reference group if I did not include it in the >> design matrix? How I can compare both progressions if the time of the >> group0 subjects is not taking into account? >> >> ii) Linked to the previous question, if I want to compare the >> differences in time between group1 and group2... Should the contrast >> be >> C = [0 0 0 1 0 -1]? >> >> iii) Finally, between the vw method and the region growing method >> which >> one is more accurate? In other words, which one do you recommend to >> use? >> >> Thank you, >> >> -- >> Jordi. -- Jordi.

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using different versions of Freesurfer?
by Lee Subin Kristine 28 Nov '16

28 Nov '16

Hi Freesurfer team, I have currently used version 5.3. for all my cortical parcellations of MRI data, but for PET images of those same subjects I used the gtmseg, mri_coregister, gtmpvc of the 6.0 beta version to get partial volume effect-corrected SUVR(standard uptake value ratios). I am aware and heard that using different versions of Freesurfer is not recommended, and that any results from the developmental version should not be used for publication yet until it is officially released. However I was wondering if in my case(with the commands I used above), this would not be such an issue. Thanks a bunch, Kristine

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qdec question
by Yaakub, Siti Nurbaya 28 Nov '16

28 Nov '16

Dear Experts, I'm looking at differences in area between two groups of subjects in FreeSurfer using qdec. I've delineated an ROI based on a cluster that showed significant differences in surface area between the two groups (taking gender into account, and with age and ICV as nuisance covariates). As a sanity check, I extracted the total surface area values for that ROI for each subject in native space (using mri_label2label and mris_anatomical_stats) When I plot these values (and do an ANCOVA with the same covariates, or even just a simple t-test) there is almost no difference between the groups. Did I do something wrong? How do I get the average surface area values for each subject (in that ROI that shows a difference) so I can see the spread of values in each group? Thanks, Siti

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Multiple Frames Error
by James Wilks 28 Nov '16

28 Nov '16

Hello, I’ve been having a problem with recon-all lately. I’m relatively new to FreeSurfer and the processes that I have done in the past have been done on sample individualized scans in my lab and I ran into an issue once I started trying to run FreeSurfer on fMRI data provided by our lab. Whenever I try to run the command this is the generated output: #@# MotionCor Wed Nov 23 11:01:54 EST 2016 Found 1 runs /export/home/jawilks/Desktop/freesurfer/subjects/run_02/mri/orig/001.mgz Checking for (invalid) multi-frame inputs... ERROR: input(s) cannot have multiple frames! /export/home/jawilks/Desktop/freesurfer/subjects/run_02/mri/orig/001.mgz has 160 frames Linux tykwer.engin.umich.edu 2.6.18-416.el5 #1 SMP Wed Oct 26 12:04:18 EDT 2016 x86_64 x86_64 x86_64 GNU/Linux recon-all -s run_02 exited with ERRORS at Wed Nov 23 11:01:57 EST 2016 The archives have not been of any help and I would greatly appreciate it if someone would be able to help point me in the right direction. Thank You

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QDEC versus R
by Lisa Delalande 28 Nov '16

28 Nov '16

Hello, As a PhD student, I send you this mail because i am meeting a misunderstanding with QDEC. In a few words : I made an analysis thanks to the QDEC tool : * I tested a correlation between an inhibition score and cortical thickness, corrected for age (continuous = inhibition score ; nuisance = age ; smoothing = 25 and FDR corrected) *** ***** ** *********** * *********** ******* *** ********** ***** *** ******** ********* ** ***** ****** ************** ***** * then, I realised a ROI analysis. I extracted different statistic values from this orbito-frontal region following your wiki (aparcstat2table). Thus, I obtained for each participant, the average value of medial orbitofrontal cortical thickness. Finally, I made a multiple linear regression analysis on R software which is a statistical software. Surprisingly, « R », indicated that it doesn't exist any correlation between the right medialorbito frontal thickness values and the inhibition scores. I don't understand why. Can you help shed some light on this issue ? Yours sincerely Marine Moyon

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Re: [Freesurfer] ASL processing in Freesurfer?
by Elijah Mak 28 Nov '16

28 Nov '16

Apologies, please ignore the other email response. I believe this should be tagged to the right thread (hopefully!) ----- Many thanks for the information, Doug! I will give it a go. Actually, I would like to carry out the following analyses: Get regional estimates of perfusion within a region of interest as defined by a significant cluster after mri_glmfit-sim. as well as other cortical regions that are connected to that cluster in terms of WM paths. Is it possible to do that in Freesurfer environment? How can I do PVC for perfusion in ROIs? Will the -pv ppvol flag be crucial during the mri_segstats stage? Thanks again for help. Best Wishes, Elijah Re: [Freesurfer] ASL processing in Freesurfer? <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=subje…> Douglas Greve <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=from:…> Mon, 21 Nov 2016 12:31:41 -0800 <http://www.mail-archive.com/search?l=freesurfer@nmr.mgh.harvard.edu&q=date:…> No, not really. If you're not doing anything fancy (eg, just computing mean of tag-control) and mapping to the surface, it is easy enough to do (mri_concat --paired-diff --sum, then bbregister to register to the anat, then mri_vol2surf or mris_preproc to map to fsaverage, then mri_glmfit and mri_glmfti-sim. If you're trying to correct for decay, intensity gradients, etc, then no. On 11/21/16 1:40 PM, Foo Keat Mak wrote: > Hi Freesurfer Team, > > Is there an ASL-friendly processing pipeline embedded in Freesurfer? > Something like an equivalent to that of PetSurfer? Thanks. > > Best Wishes, > Elijah > > Sent from my iPad > _______________________________________________ > Freesurfer mailing list > Freesurfer(a)nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > _______________________________________________ Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Partners Compliance HelpLine athttp://www.partners.org/complianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail.

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Cohen's D = gamma.mgh / rstd.mgh?
by Elijah Mak 28 Nov '16

28 Nov '16

Hi there, What is the correct way to plot, at each vertex, the Cohen's *D* after a *mri_glmfit* comparison? I've seen a few variations posted on the mailing list. Is gamma.mgh / rstd.mgh is the correct formula? Does rstd.mgh represent pooled SD across both groups (patients and controls)? Secondly, after plotting the effect size across the whole brain, is it feasible to test whether there are regional differences in effect size by using *mri_segstats* and *aparc* to extract the ROI-averaged effect size in *fsaverage* space, and then perform a paired t-test between say, frontal vs occipital ROIs? Thank you. Best Wishes, Elijah

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Re: [Freesurfer] how does the content of the curv files compare to that of smoothwm.H.crv
by Bernardoni, Fabio 28 Nov '16

28 Nov '16

Dear Bruce, thanks a lot for your answer. I am still a bit confused. I followed your suggestion to use msris_curvature to compute the curvature on the white surface (unsmoothed) instead of on smoothwm: mris_curvature -w -a 10 $subj/surf/lh.white mris_preproc -s $subj --target fsaverage --hemi lh --meas white.H --out ./measures/lh.white.H.mgh mri_surf2surf --hemi lh --s fsaverage --sval ./measures/lh.white.H.mgh --tval ./measures/lh.white.H_sm10.mgh --fwhm-trg 10 --cortex --noreshape (mri_surf2surf smoothing was applied also to other curvatures) If I understood right, mris_curvature uses a hessian method to compute the curvature, while mris_curvature_stats uses the Gauss-Bonnet theorem (I extracted this information from your email to this mailing list from: Fri, 26 Feb 2010 05:54:32 -0800). In an email from Wed, 30 Mar 2011 12:40:58 -0700, Rudolph says that gauss-bonnet procedure is more robust against noise. Does this also hold for the mean/extrinsic curvature? I ask because in the Gauss-Bonnet theorem only the gaussian curvature is mentioned. For the extrinsic/mean curvature (see attachment) I obtain that actually the smoothwm.H.crv seems to be the noisiest quantity (red in the histogram), followed by the classical method applied on the unsmoothed white matter surface (blu) and by the classical method applied on the smoothed wm surface (green, corresponds to the ?h.curv files produced by recon-all). This observation also holds when comparing the curvature in ?h.curv.pial and ?h.pial.H.crv (histogram sent in my previous email). In that case, on many vertices the mean curvature computed with the gauss-Bonnet method was ~1/mm which makes me think to unrealistically small 'hollows' on the pial surface. Finally, to compare curvature vertexwise between a group of patients and controls, which should be the right numerical quantity to look at: 1- curv.pial (classic method on smoothed pial surface - from recon-all) 2- pial.H (classic method on smoothed pial surface - from mris_curvature) 3- pial.H.crv (gauss-bonnet method on the pial surface - from mris_curvature_stats)? Thank you very much for any help, Fabio Dr. Fabio Bernardoni wiss. Mitarbeiter Psychosoziale Medizin und Entwicklungsneurowissenschaften Tel. +49 (0)351 458-5245 Fax +49 (0)351 458-7206 URL http://www.uniklinikum-dresden.de/psm; www.transdenlab.de Universitätsklinikum Carl Gustav Carus & Medizinische Fakultät an der Technischen Universität Dresden Anstalt des öffentlichen Rechts des Freistaates Sachsen Fetscherstraße 74, 01307 Dresden http://www.uniklinikum-dresden.de Vorstand: Prof. Dr. med. D. M. Albrecht (Sprecher), Wilfried E. B. Winzer Vorsitzender des Aufsichtsrates: Prof. Dr. med. Peter C. Scriba USt.-IDNr.: DE 140 135 217, St.-Nr.: 203 145 03113

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Freesurfer November 2016