Hi Bruce

I suspected this might be the case, since assessing 3D surfaces from a succession of 2D slices can be tricky, which is why I was wondering whether there's a better way to do these visual inspections. I checked those apparent artefacts in the other 2 planes (axial, saggital), but did not find it helpful in deciding whether the surfs was as they should or not.

Something that I think is more likely to be a real problem (i.e., more than just a viewing plane disorientation), is that for many subjects, posterior slices only start to be followed by the surfaces quite late, e.g. from coronal slice 80 onward. This seems to be because those slices only appear in the brainmask.mgz, but not also in the wm.mgz (see screenshots attached).

Also, after having run the cross and base steps, and ended up with folders of the type subj1_scanA, subj1_scanB etc, for the "long" step I launched simultaneously (for all subjects&scans) commands of the type
   recon-all -long subj1_scanA subj1 -all
   recon-all -long subj1_scanB subj1 -all
however these resulted in two types of error messages:
    mghRead(/vols/Scratch/tpopescu/learning/FS/subj1_scanA.long.subj1/mri/aseg.mgz, -1): read error
(those particular aseg.mgz files had size 0kB), and
   (standard_in) 2: Error: comparison in expression
I initially had disk space issues, but after making space I relaunched the same commands with the  -no-isrunning flag, but with the same results. Is it the case that the long commands for the different scans of a subject have to be launched sequentially rather than in parallel, i.e. the command for scanB should be run after the command for scanA has finished? Otherwise, what could the problem be?

Thanks again for your help.

Tudor
  


On 1 June 2014 15:17, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:
Hi Tudor

are you assessing the thickness visually? If so, you are probably being misled by the orientation of the surface w.r.t. the viewing plane. Same fo the apparent bubbles. You need to look in a different orientation

cheers
Bruce


On Sun, 1 Jun 2014, Tudor Popescu wrote:

Many thanks Martin and Nick! The rendering option was already checked, but
the freeview inspection commands were still very very slow, so I used
commands of the following form, which as far as I understand should be
equivalent:
     tkmedit subjID norm.mgz -surfs
For several subjects (maybe 20 out of the total of 72), I noticed that the
surfaces don\t seem to quite follow the GM/WM demarcation line as expected -
for instance, by having portions of white surface (yellow line, see attached
screenshots) surrounded by pial surface (red line), or by having very large
cortical thickness in some parts of the brain. Is it possible that these
apparent artefacts make sense "in context" (by looking at the adjacent
slides), or is it the case that I need to go back and do white surface
correction, and then redo all 3 steps of the longitudinal process?

Thanks again for your help!
Tudor


On 29 May 2014 17:39, Nick Schmansky <nicks@nmr.mgh.harvard.edu> wrote:
      Tudor,

      in your virtual machine, make sure the 3D rendering option, or
      'use
      hardware rendering' (or something like that) is enabled.  this
      would be on
      the Windows VM config side of things.  otherwise it will do
      software
      rendering which is painfully slow.

      Nick


      > Hi Tudor,
      >
      > I don't think there is a way to speed things up.
      > Let me know if you find a case where the template is blurry or
      has
      > ghosts. It should not happen, but if it does it indicates a
      bad
      > registratration, you'd have to run the mri_robust_template
      command with
      > different parameters manually then.
      >
      > Best, Martin
      >
      > On 05/27/2014 06:13 PM, Tudor Popescu wrote:
      >>
      >> Hi Martin,
      >> Wasn't sure whether you'd seen my reply below, look forward
      to hear
      >> back your thoughts, thanks!
      >> Tudor
      >>
      >> On 25 May 2014 21:40, "Tudor Popescu" <tudor3@gmail.com
>> <mailto:tudor3@gmail.com>> wrote:
>>
>>     Thanks very much Martin and Bruce. I guess I'd misread the Wiki
>>     (my own fault, not the text's), and am glad to hear that the
>>     longitudinal pipeline is in fact perfectly suitable for my
needs
>>     here.
>>
>>     Having run the first 2 steps (cross and base), I'm a bit
unclear
>>     how the output so far has to be manually inspected. It says in
the
>>     tutorial
>>     <http://freesurfer.net/fswiki/FsTutorial/LongitudinalTutorial>
>>     that you should load each subject's base volume + surfs in
>>     freeview and then "move back and forth a few slices". However,
>>     even just loading each base in this manner takes ~1 min on my
PC
>>     (CoreDuo, 4GB, Ubuntu Virtualbox in Windows 7), and then moving
>>     with PgUp/PgDn between all coronal slices (starting from the
>>     default slice=128, going all the way posterior and then all the
>>     way anterior) is excruciatingly slow. All of this would have to
be
>>     repeated for all my 72 subjects - is there any way to optimise
>>     this manual inspection?
>>
>>     Also, if the surfs turn out to not follow the volume correctly,
>>     presumably the thing to do is white surface correction +
>>     re-running recon. But what should one do if, due to an
erroneous
>>     averaging between timepoints, you see blurs/ghosts in your base
>>     template?
>>
>>     Many thanks!
>>     Tudor
>>
>>
>>     On 9 May 2014 21:33, Martin Reuter <mreuter@nmr.mgh.harvard.edu
>>     <mailto:mreuter@nmr.mgh.harvard.edu>> wrote:
>>
>>         Hi Tudor,
>>
>>         the longitudinal pipeline in FS is actually one of the best
on
>>         the planet as far as I know :-). If there is any
contradictory
>>         information on the wiki, can you point me to that so I can
see
>>         what causes the misconception. Really: compared to
independent
>>         processing, it significantly increases sensitivity. Also we
>>         have designed it to be unbiased with respect to a single
time
>>         point or directionality. It is quite mature by now.
>>
>>         You should definitely use the longitudinal pipeline for the
>>         analysis of your data. Now to your questions
>>
>>         1. QDEC: I am not too familiar with qdec. You can
definitely
>>         try the 2-stage approach described on the wiki. There you
>>         first compute a measure of change (e.g. hippocampal volume
>>         change during your week) and then compare that measure
across
>>         groups similar to a cross sectional volume/thickness
analysis.
>>         You can also use our tools to run a linear mixed effects
model
>>         if you want to do that (it is more involved and requires
you
>>         to use matlab tools). In your case, you probably have 2
time
>>         points for all subjects and the time distance is probably
the
>>         same for all subjects, so the 2-stage approach should be
fine.
>>
>>         2. The image processing is done via the longitudinal
pipeline
>>         (three steps: cross, base, long), to prepare the data look
at
>>         the description of the 2-stage model
>>         http://freesurfer.net/fswiki/LongitudinalTwoStageModel
>>         and also the longitudinal tutorial
>>        
http://freesurfer.net/fswiki/FsTutorial/LongitudinalTutorial
>>
>>         3. At the recon all level in FS you get (after the 3 steps)
>>         measurement for all time points. So you would compare those
>>         results across time in the stats.
>>
>>         Hope that helps, Martin
>>
>>
>>         On 05/08/2014 08:14 AM, Tudor Popescu wrote:
>>>         Sorry for the repeat, wasn't sure whether this was
received
>>>         the first time.
>>>         Tudor
>>>
>>>
>>>         On 6 May 2014 19:55, Tudor Popescu <tudor3@gmail.com
>>>         <mailto:tudor3@gmail.com>> wrote:
>>>
>>>             Dear FS list,
>>>
>>>             I have structural data from a learning study
>>>             (pre&post-training scans, with 3 groups). Although the
>>>             training was only one week, I'm guessing from an
analysis
>>>             point of view, this still qualifies as longitudinal. I
>>>             want to check for
>>>
>>>               * the main within-subjects effect of time point
>>> (pre&post)
>>>               * the main between-subjects effect of group
(treatment
>>>                 A, treatment B, control),
>>>               * the time x group interaction
>>>
>>>             I intend to look at thickness, surface area, volume,
and
>>> lGI.
>>>
>>>             I read on the wiki
>>>            
<http://surfer.nmr.mgh.harvard.edu/fswiki/LongitudinalProcessing>
>>>             that FS is currently not optimal for longitudinal
>>>             analyses. I intend my FreeSurfer analysis to
supplement a
>>>             VBM analysis done in FSL. In case it is in fact a good
>>>             idea to do this, my questions (not covered in the
>>>             'longitudinal' wiki page) are:
>>>
>>>             1) Can QDEC be used for such an analysis, and if so,
what
>>>             would be different as compared to a cross-sectional
(no
>>>             temporal/within factor) study?
>>>
>>>             2) Also, is the pre-processing stage any different?
>>>
>>>             3) In FSL, for longitudinal designs you do stats on
>>>             images obtained as the difference between consecutive
>>>             time points. Does this have to be done in FreeSurfer
as
>>>             well, and if so, is it done at the recon-all level or
>>>             only at the stats (QDEC) level?
>>>
>>>             Thanks!
>>>
>>>             Tudor
>>>
>>>
>>>
>>>
>>>
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>>
>>         --
>>         Martin Reuter, Ph.D.
>>
>>         Instructor in Neurology
>>            Harvard Medical School
>>         Assistant in Neuroscience
>>            Dept. of Radiology, Massachusetts General Hospital
>>            Dept. of Neurology, Massachusetts General Hospital
>>         Research Affiliate
>>            Computer Science and Artificial Intelligence Lab,
>>            Dept. of Electrical Engineering and Computer Science,
>>            Massachusetts Institute of Technology
>>
>>         A.A.Martinos Center for Biomedical Imaging
>>         149 Thirteenth Street, Suite 2301
>>         Charlestown, MA 02129
>>
>>         Phone:+1-617-724-5652  <tel:%2B1-617-724-5652>
>>         Email:
>>             mreuter@nmr.mgh.harvard.edu
>> <mailto:mreuter@nmr.mgh.harvard.edu>
>>             reuter@mit.edu  <mailto:reuter@mit.edu>
>>         Web  :http://reuter.mit.edu
>>
>>
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>>         The information in this e-mail is intended only for the
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>
> --
> Martin Reuter, Ph.D.
>
> Instructor in Neurology
>    Harvard Medical School
> Assistant in Neuroscience
>    Dept. of Radiology, Massachusetts General Hospital
>    Dept. of Neurology, Massachusetts General Hospital
> Research Affiliate
>    Computer Science and Artificial Intelligence Lab,
>    Dept. of Electrical Engineering and Computer Science,
>    Massachusetts Institute of Technology
>
> A.A.Martinos Center for Biomedical Imaging
> 149 Thirteenth Street, Suite 2301
> Charlestown, MA 02129
>
> Phone: +1-617-724-5652
> Email:
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