Hi Dr Greve,
Thanks again for the great explanation and for clarifying how smoothing may
exacerbate the partial volume effects.
I have additional question and I appreciate your answer:
In the literature of the voxel-wise analysis using FSL/randomise to study the
difference between two groups (e.g. TBSS, VBM, ASL, PET, .... etc). The authors
used to register their maps (FA, PET, ASL, ...etc) to a standard template
MNI152 then merge all the images using fslmerge and then run voxel-wise
comparison using randomise with a number of permutations and a method to
correct for multiple comparison.
In this type of analyses, the authors of these studies didn't applying any
kind of PVE on the data like how we do in PET surfer. Is this something related
to registration? meaning all the maps are in the standard space, so PVE has
trivial/no effect? While in PET surfer we feed to the analysis images in the
native space then we re sample the images to the brain surface that's why we
apply PVE? Is the registration to standard template exacerbates PVE?
On 08/10/2017 11:35 AM, John Anderson wrote:
>
> Dear Dr Greve,
>
> Thank you very much for the great explanation. I will definitely
> correct for PVC using PET surfer.
>
> Kindly I have one follow-up question and I highly appreciate your input.
>
> I have PET data for two groups. I studied the difference in PET signal
> using voxel-wise ( FSL/randomise) and surface-based using PET surfer.
>
> My question is about PVC. We correct for PVC in surface based because
> we re-sample PET data to the brain surface which is an output of
> segmentation process, meaning we expect partial volume effects between
> the grey/white for a possible contamination between them during
> segmentation.
>
> We don't do PVE in voxel-wise because we don't worry about the
> contamination meaning there are no segmentation lines to separate
> between brain regions.
>
> Kindly is my understanding for this fact correct ( i.e. why we correct
> in surface based and we don't correct in voxel-wise).
It is not correct. You do PVC to remove interactions between the anatomy and
the PET through PVEs. Those will be there in both surface-based and
volume-based analysis. If you perform smoothing in volume-based analysis, you
will make the PVEs worse. Doing MG PVC then volume-based smoothing will result
in a disaster. In my opinion, the only way to do PVC in a map-based analysis
(vs ROI) is to do it on the surface. For subcortical, you can do volume-based
smoothing within a GM mask.
> By the way, I ran voxel-wise using randomise with TFCE and 5000
> permutations.
For the surface, you can use mri_glmfit with the --perm option.
>
> Thank you again for any clarification
> John
>
>
>
>
> The PET signalcan change with a lot of anatomical changes in the brain
> including thickness, surface area, and gyrification. There is no known
> regressor that will account for this. Right right way to account for
> it is with partialvolume correction (PVC). It is best to do PVC
> simultaneously with the recon, but software is not available to
> perform this. You can do it on a post-hoc basis in PETsurfer using the
> PVC options in mri_gtmpvc. See the wiki.
>
>
>
> On 08/10/2017 04:11 AM, John Anderson wrote:
>
> >
>
> > Hi Dr Greve,
>
> >
>
> > I have PET data for two groups and I used PET surfer in FSV 6.0 to
> > run
>
> > the analyses. The pipeline is straightforward and the analysis ran
>
> > smoothly without any issues.
>
> >
>
> > Is it correct procedure to adjust PET signal to differences in gray
>
> > matter volume or cortical thinness between two groups?
>
> >
>
> > In other words, is it correct if gray matter volume or cortical
>
> > thickness for subjects be included as EVs in GLM or a nausiance
> > factor
>
> > in QDEC?
>
> >
>
> > Specifically, is the PET signal changeable depending ondifferences
>
> > in cortical thickness.
>
> > or differences in gray matter volume?
>
> >
>
> > Thank youfor any clarification
>
> >
>
> >> Thank you !
>
> >> Jon
>
> >>
>
> >
>
> >
>
> >
>
> > _______________________________________________
>
> > Freesurfer mailing list
>
> > Freesurfer@nmr.mgh.harvard.edu
> > <mailto:Freesurfer@nmr.mgh.harvard.edu>
>
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
> --
>
> Douglas N. Greve, Ph.D.
>
> MGH-NMR Center
>
> gr...@nmr.mgh.harvard.edu <mailto:gr...@nmr.mgh.harvard.edu>
>
> Phone Number: 617-724-2358
>
> Fax: 617-726-7422
>
>
> Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
> <http://surfer.nmr.mgh.harvard.edu/fswiki/BugReporting>
>
> FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2
>
> www.nmr.mgh.harvard.edu/facility/filedrop/index.html
> <http://www.nmr.mgh.harvard.edu/facility/filedrop/index.html>
>
> Outgoing:
> ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
>
>
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>
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J2
>
>> -------- Original Message --------
>> Subject: PET surfer
>> Local Time: August 10, 2017 4:11 AM
>> UTC Time: August 10, 2017 8:11 AM
>> From: john.ande...@protonmail.com
>> To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
>>
>> Hi Dr Greve,
>>
>> I have PET data for two groups and I used PET surfer in FSV 6.0 to
>> run the analyses. The pipeline is straightforward and the analysis
>> ran smoothly without any issues.
>>
>> Is it correct procedure to adjust PET signal to differences in gray
>> matter volume or cortical thinness between two groups?
>>
>> In other words, is it correct if gray matter volume or cortical
>> thickness for subjects be included as EVs in GLM or a nausiance
>> factor in QDEC?
>>
>> Specifically, is the PET signal changeable depending on differences
>> in cortical thickness.
>> or differences in gray matter volume?
>>
>> Thank you for any clarification
>>
>>> Thank you !
>>> Jon
>>>
>>
>
>
>
> _______________________________________________
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@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
www.nmr.mgh.harvard.edu/facility/filedrop/index.html
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