Freesurfer March 2014

freesurfer@nmr.mgh.harvard.edu

147 participants
247 discussions

Re: [Freesurfer] Difference in volumes btw 5.1 and 5,3
by Ed Gronenschild 24 Mar '14

24 Mar '14

Dear Kim, This may be of interest to you: http://dx.plos.org/10.1371/journal.pone.0038234 Cheers, Ed On 24 Mar, 2014, at 17:00, freesurfer-request(a)nmr.mgh.harvard.edu wrote: > Message: 3 > Date: Mon, 24 Mar 2014 12:28:29 +0900 > From: jh kim <jhkim.merrf(a)gmail.com> > Subject: Re: [Freesurfer] Difference in volumes btw 5.1 and 5,3 > To: Freesurfer support list <freesurfer(a)nmr.mgh.harvard.edu> > Message-ID: > <CADiwdtbtNUbiXaaQgoR9bwLBrEwFDfu4 > +Zv5VhViDhz3nfQOCg(a)mail.gmail.com> > Content-Type: text/plain; charset="iso-8859-1" > > Dear Prof. Fischl > > Thanks for the valuable comments. > > Kim > > > 2014-03-23 3:26 GMT+09:00 Bruce Fischl <fischl(a)nmr.mgh.harvard.edu>: > >> Hi Kim >> >> we of course always strive to make things more accurate, but in >> the end >> it will depend on the details of your acquisition and such. I >> don't think >> I have a better answer than that, other than to say look at the >> segmentations and see if you think they are more accurate in one case >> than the other. >> >> sorry >> Bruce >> On Sun, 23 Mar 2014, jh kim wrote: >> >>> Dear Prof. Fischl >>> Thanks for the prompt response. >>> >>> The more specific reason of my query is that there was a >>> difference in >>> statistical significance between two FS versions. >>> For example, the result of group comparison of left thalamic volumes >> (ANCOVA >>> controlling for age and eICV) is statistically significant (p = >>> 0.04) >> when >>> using FS 5.1, whereas the result is no longer significant at all >>> (p = >> 0.28) >>> in case of FS 5.3. >>> I'm a little confused about this discrepancy. >>> Which result should I trust? >>> >>> Thank you in advance for your comments. >>> >>> Kim >>> >>> >>> 2014-03-23 2:59 GMT+09:00 Bruce Fischl <fischl(a)nmr.mgh.harvard.edu>: >>> Hi Kim >>> >>> there are probably lots of little reasons for the differences. >>> This is >>> always true for different versions, and the reason we never >>> mix >>> versions >>> >>> cheers >>> Bruce >>> On >>> Sun, 23 Mar 2014, jh kim wrote: >>> >>>> Dear FS lists >>>> When I measured subcortical GM volumes in the same subjects by >>> using both >>>> version 5.1 and 5.3, I have observed a considerable difference >>> in volumes >>>> between the two versions. >>>> For instance, please see the left thalamic volumes below. >>>> I cannot figure out why there is much difference between the >>> versions. >>>> Which result is more reliable? >>>> >>>> Left-Thalamus-Proper_5.3 >>>> Left-Thalamus-Proper_5.1 >>>> 10313 >>>> 9757 >>>> 8924.8 >>>> 7746 >>>> 9834.8 >>>> 8287 >>>> 7935.2 >>>> 7034 >>>> 8764.1 >>>> 7747 >>>> 9411.8 >>>> 8037 >>>> 7636.7 >>>> 8051 >>>> 9334.7 >>>> 8255 >>>> 10024.3 >>>> 8171 >>>> 8757.7 >>>> 6900 >>>> 9540.9 >>>> 8316 >>>> 9294.4 >>>> 8369 >>>> 8091 >>>> 7366 >>>> 9103.7 >>>> 7818 >>>> 9310.2 >>>> 7974 >>>> 7583 >>>> 6872 >>>> 9838.9 >>>> 8911 >>>> 8829.6 >>>> 8004 >>>> 9094.8 >>>> 6973 >>>> 9492.3 >>>> 8922 >>>> 8821.6 >>>> 7691 >>>> 7971.6 >>>> 7376 >>>> 9901.2 >>>> 8936 >>>> 9773.9 >>>> 8855 >>>> 9283.7 >>>> 7615 >>>> 8801.6 >>>> 7690 >>>> 8505.1 >>>> 7325 >>>> 8981 >>>> 7258 >>>> 9644.7 >>>> 8860 >>>> 9104.2 >>>> 8298 >>>> 8494.8 >>>> 7402 >>>> 9024.9 >>>> 7721 >>>> 8117.8 >>>> 7226 >>>> 8001.8 >>>> 7548 >>>> 8392.3 >>>> 7668 >>>> 8606.6 >>>> 8173 >>>> 9126.7 >>>> 7595 >>>> 8093 >>>> 7885 >>>> 8317.7 >>>> 7157 >>>> 10556 >>>> 9307 >>>> 8669.6 >>>> 8374 >>>> 8034.7 >>>> 7338 >>>> 8148.5 >>>> 7276 >>>> 9048.1 >>>> 8064 >>>> 8160.1 >>>> 7014 >>>> 8747.9 >>>> 7894 >>>> 8329.9 >>>> 6866 >>>> 8415.8 >>>> 8189 >>>> 9246.9 >>>> 8256 >>>> 8194.1 >>>> 7183 >>>> 9629.2 >>>> 9579 >>>> 7688.2 >>>> 6398 >>>> 8349.2 >>>> 8238 >>>> 8366.2 >>>> 7348 >>>> 8436.5 >>>> 7616 >>>> 8372.3 >>>> 6977 >>>> 9396.4 >>>> 7589 >>>> 9327.5 >>>> 7684 >>>> 10001.8 >>>> 8627 >>>> 9762.4 >>>> 9228 >>>> 8841 >>>> 8532 >>>> 8342.4 >>>> 8024 >>>> 8645.7 >>>> 7725 >>>> >>>> Any comment would be appreciated. >>>> Thank you. >>>> >>>> Kim >>>> >>>> >>> _______________________________________________ >>> Freesurfer mailing list >>> Freesurfer(a)nmr.mgh.harvard.edu >>> https://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 at >>> http://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. >>> >>> >>> >>> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >>

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Flipping left-right hemispheres
by Peggy Skelly 24 Mar '14

24 Mar '14

Hi All, Although the question of flipping hemispheres has come up before, I still struggling with it. I'm working on a longitudinal study with stroke subjects (half with lh lesions, half with rh lesions). We want to compare only the non-lesioned, healthy, hemispheres at 2 timepoints (pre- and post-therapy). Using the tutorial (http://freesurfer.net/fswiki/FsTutorial/LongitudinalTutorial_freeview) as a guide, I've completed the longitudinal analysis (cross-base-long steps) for both lh- and rh-lesioned subjects. I've done the thickness data qcache for the right/healthy hemi for the lh-lesioned group: long_mris_slopes --qdec long_qdec_lh_lesion_subjects_table.dat --meas thickness --hemi rh --do-avg --do-rate --do-pc1 --do-spc --do-stack --do-label --time my_time_var --qcache fsaverage_sym --sd $SUBJECTS_DIR Convert the long_qdec_lh_lesion_subjects_table.dat into a cross.qdec.table.dat to use in qdec. This works well---I can look for clusters where athe average thickness-rate is different from 0. How can I combine the rh-lesioned group with the first group? I thought I could flip hemispheres of the results at each subject's longitudinal output timepoint with: surfreg --s subj1_Tp1.long.subj1_base --t fsaverage_sym --rh --xhemi but this terminated with an error: > recon-all -sb s1311_15T_post.long.s1311_15T_base/xhemi -talairach > > ERROR: Are you trying to run or re-run a longitudinal time point? > If so, please specify the following parameters: > > \' -long <tpNid> <templateid> \' > > where <tpNid> is the time point id (SAME as cross sectional > ID) and <templateid> is the ID created in the -base run. > The directory <tpNid>.long.<templateid> will be created > automatically or used for output, if it already exists. I know it's recommended to flip hemispheres after processing (http://www.mail-archive.com/freesurfer%40nmr.mgh.harvard.edu/msg34040.html) When (and how) is it best done? Thanks, Peggy

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Hemisphere stats question
by _andreia_＠sapo.pt 24 Mar '14

24 Mar '14

Hello list, I have a question regarding what stats are more correct to use to get whole hemisphere surface area and mean thickness. The cortex.label values extracted using the two bottom command lines don't match aparc stats, however they match in the number of vertices between them, and using pial or white surface also results in values that make sense comparing each one (higher surface area using pial, same thickness, same volumes). In the past I've been using the two first command lines (in which values agree in the same way as cortex.label between them but are also in agreement with aparc.stats), however now I'm having this question: which one is the correct one to use? And why does this difference exists? mris_anatomical_stats -l ../label/lh.cortex.label -f lh.total.stats -b SUBJ lh white (matches aparcstats) mris_anatomical_stats -l ../label/lh.cortex.label -f lh.total_pial.stats -b SUBJ lh pial (matches aparcstats) mris_anatomical_stats -mgz -f ../stats/lh.cortex_pial.stats SUBJ lh pial (does not match aparcstats) mris_anatomical_stats -mgz -f ../stats/lh.cortex_white.stats SUBJ lh white (does not match aparcstats) Thank you in advance, Andreia

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Re: [Freesurfer] Group comparisons
by Tudor Popescu 24 Mar '14

24 Mar '14

Sorry, couple more questions: 1) I know that QDEC's/mri_glmfit's equivalent in FSL ("randomise") applies the GLM by doing permutations, and so already corrects for multiple comparisons in the process. How similar is this to what Monte-Carlo does (i.e. controlling FWE via repeated simulations) upon the initially uncorrected QDEC results? 2) In FSL, a comparison between groups A and B is tested by defining both a "A>B" as well as a "B>A" contrast - the reason being (as far as I understand) that taking the logical complement of "A>B", i.e. inverting the t-values in the statistical map, is *not* equal to the map produced by the cotnrast "B>A". How come, then, that QDEC phrases the group contrast in a "two-tailed" way (i.e. "do groups A and B differ")? Is the dichotomy not necessary in QDEC, or is it simply done behind the scenes? 3) I've read papers where the thickness from *native*-space was used in the analyses, even though initially T1-weighted images were initially aligned to the ICBM 152 template. Why isn't thickness from this *standard*-space used, as happens in FSLVBM with grey matter density? Why even register to the template in the first place if you're then going to go back and use native-space values? Thanks! On 6 March 2014 10:20, Tudor Popescu <tudor3(a)gmail.com> wrote: > Thank you very much Doug. > Tudor > > > On 6 March 2014 03:53, Douglas Greve <greve(a)nmr.mgh.harvard.edu> wrote: > >> >> On 3/5/14 5:25 PM, Tudor Popescu wrote: >> >> Hello, I have some questions on doing group comparisons with thickness, >> area and volume. Many thanks in advance for any help! >> >> 1) For a DOSS design with group and gender as categorical factors, I see >> that an interaction contrast ("Is there a group-gender interaction in the >> mean thickness?") still exists - but what does this contrast mean, given >> that DOSS by definition doesn't allow for interactions? >> >> Are you using QDEC? If so, don't use the DOSS as the contrasts are >> incorrect. It is possible to have an interaction among the categorical >> factors with a DOSS. >> >> >> 2) it makes sense that measures such as thickness are analysed >> vertex-wise in QDEC, however what does it mean when the dependent variable >> is area or volume - measures that do not make physical sense for a single >> vertex but only at the level of a region consisting of *several* vertices? >> >> The interpretation is a little more difficult. Each vertex is assigned an >> area equal to the average of the triangles adjacent to it. This is just a >> value that can be mapped to a common space like any other value (eg, >> thickness) (but there is a special jacobain correction to account for >> stretching or compression). Smoothing reduces the effect of having >> different sized triangles. One can think of it like this: in the common >> space (fsaverage) image having a patch of a certain size. When you mapped >> that patch back to each individual, how big would that patch be? You could >> then do group statistics on that number. In this way you could analyze the >> entire hemisphere. Now imagine doing this but making the patch smaller and >> smaller. >> >> >> 3) For values extracted from atlas regions with aparcstats2table, it >> seems that the product of the extracted CT and area is in the same order of >> magnitude as the extracted volume, but never really the same or even close >> - why, when the volume of a region should theoretically be the product of >> its surface area by its thickness? >> >> It is an issue of how it is computed. Sum(CT*Area) != Sum(CT)*Sum(Area). >> When computing volume, CT*Area is computed for each vertex then summed >> across vertices. >> doug >> >> >> Tudor >> >> >> _______________________________________________ >> Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> >> >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer(a)nmr.mgh.harvard.edu >> https://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 at >> http://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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Generating individual statistics on a manually traced segmentation/label
by Eileen Moore 24 Mar '14

24 Mar '14

Hello FreeSurfer experts, I am using freesurfer v5.3 on a linux os. I have a few questions regarding individual aseg statistics (volume, intensity) for a subcortical region that is not automatically segmented by freesurfer. Using tkmedit I have manually traced my subcortical ROI and saved it as a label. By looking at the label for each subject (i.e., less <subjid>/label/ROI.label ) I can see how many voxels are included in the label, the coordinates of each voxel in the label and the signal intensity of each of these voxels. 1. Is there anyway to transform the information in my label to individual statistics in a format similar to what I can obtain with the automatic segmentations and asegstats2table? And what additional steps are necessary to accomplish this? 2. Does the volume that was loaded when the label was created have an impact on any of the volume statistics computed? For example, I generated my label on each subject with the orig volume loaded (i.e., tkmedit <subjid> orig.mgz ) - if I label the same voxels on the norm.mgz, will the intensity values generated for each subject be different? And should I have used a different volume to create my labels? 3. In the label, what coordinate system is used to identify the labeled voxels? Are these coordinates in native space? Thanks, Eileen. Sent from my iPad

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Re: [Freesurfer] reconstruction problem with pediatric images
by Lilla Zollei 24 Mar '14

24 Mar '14

Hi Francesco, Given that the recon pipeline is built on an adult atlas it is not expected to work for such young subjects. In the past, with high quality images, we managed to get reasonable recons for ages down to 4 (or sometimes 3). For the younger population though it will not work. We are in the process of creatig a pipeline for them, but it is not yet ready for distribution. Lilla On Thu, 20 Mar 2014, Francesco Baldacchini wrote: > Hi Lilla, > > They range from neonates to 6 years old, > > Francesco > > > 2014-03-19 19:21 GMT+01:00 Lilla Zollei <lzollei(a)nmr.mgh.harvard.edu>: > > Hi Francesco, > > How old are your subjects? > > Lilla > > On Wed, 19 Mar 2014, Francesco Baldacchini wrote: > > I have some quality problems with my scans. I'm trying to run recon-all on pediatric brain images but, given the low contrast between cortical regions and the white matter, I do consistently get some problem in the reconstruction of the cortical surface as well as of the segmentation. I > was wondering whether > there is a tool making use of i.e. the T2 not only to improve the surface (by the way I cannot see the –T2 option in the help of recon –all to do so) but particularly to improve the contrast of the T1. In a nutshell, there is a way to increase quality and contrast by using T1 together > with T2 weighted images > during recon-all? Another question is how important it is to use the mprage option in recon-all? Thanks, > > Francesco Baldacchini > > > > > 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 at > http://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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How to do parcellation in the inflate brain?
by gong jinnan 24 Mar '14

24 Mar '14

Dear FreeSurfer experts, Hello everyone. I am a beginner of Freesurfer. And I want to do parcellation using some templates (are there any accurate templates in surface space?) in the inflate brain after “recon -all” . After that I wish to get some individual areas like M1,SMA and so on in surface space, and then transform then to voxel space. I think it will be more accurate than segment the T1 image in MNI space directly. But unfortunately, after studying for a few weeks I didn’t find a way to do that. So the only way is asking for help…I hope someone could give me some advises or tutorials. If you can help me to solve this problem,I would be very grateful! Sincerely， Jinnan Gong Best wishes for you! Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China

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Difference in volumes btw 5.1 and 5,3
by jh kim 23 Mar '14

23 Mar '14

Dear FS lists When I measured subcortical GM volumes in the same subjects by using both version 5.1 and 5.3, I have observed a considerable difference in volumes between the two versions. For instance, please see the left thalamic volumes below. I cannot figure out why there is much difference between the versions. Which result is more reliable? Left-Thalamus-Proper_5.3 Left-Thalamus-Proper_5.1 10313 9757 8924.8 7746 9834.8 8287 7935.2 7034 8764.1 7747 9411.8 8037 7636.7 8051 9334.7 8255 10024.3 8171 8757.7 6900 9540.9 8316 9294.4 8369 8091 7366 9103.7 7818 9310.2 7974 7583 6872 9838.9 8911 8829.6 8004 9094.8 6973 9492.3 8922 8821.6 7691 7971.6 7376 9901.2 8936 9773.9 8855 9283.7 7615 8801.6 7690 8505.1 7325 8981 7258 9644.7 8860 9104.2 8298 8494.8 7402 9024.9 7721 8117.8 7226 8001.8 7548 8392.3 7668 8606.6 8173 9126.7 7595 8093 7885 8317.7 7157 10556 9307 8669.6 8374 8034.7 7338 8148.5 7276 9048.1 8064 8160.1 7014 8747.9 7894 8329.9 6866 8415.8 8189 9246.9 8256 8194.1 7183 9629.2 9579 7688.2 6398 8349.2 8238 8366.2 7348 8436.5 7616 8372.3 6977 9396.4 7589 9327.5 7684 10001.8 8627 9762.4 9228 8841 8532 8342.4 8024 8645.7 7725 Any comment would be appreciated. Thank you. Kim

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use 1 vs. 2 T1 acquisitions
by Stacey M Schaefer 22 Mar '14

22 Mar '14

Hello freesurfer gurus, We acquire 2 BRAVO T1s on a GE 3T during the same scan session on most of our study participants, but because of various issues, occasionally only get 1 T1/participant. I've been processing the data combining both T1s when we have 2 and using just 1 T1 when that was all we had thinking it would be best to use the highest quality data as possible (more is better rational), especially given the old FS recommendation that multiple acquisitions were better. However, after perusing recent course materials, I came across the suggestion in one of the powerpoints to always be consistent across subjects using either 1 or 2. Is that the most recent recommendation - if we don't have 2 acquisitons on everyone to pick the one with best contrast and only use 1 T1/participant? If so, can you explain why? Thanks for your advice! Stacey Schaefer -- --------------------------------------------------- Stacey M. Schaefer, Ph.D. Waisman Laboratory for Brain Imaging and Behavior University of Wisconsin - Madison 1500 Highland Ave Rm T127 Madison, WI 53705 Waisman Phone: 608-263-9321

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Calculating Total White Matter
by Adeyemi, Elizabeth (NIH/NIMH) [C] 21 Mar '14

21 Mar '14

Hello, I need assistance calculating Total White Matter. Can I simply add Cortical White Matter + Unsegmented White Matter (given in the aseg wmparc output)? Thanks Elizabeth Adeyemi

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Freesurfer March 2014