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
The PET signal can 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 partial volume 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 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
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). By the way, I ran voxel-wise using randomise with TFCE and 5000 permutations.
Thank you again for any clarification John
The PET signal can 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 partial volume 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 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
greve@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
Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer /A��J2�
-------- Original Message -------- Subject: PET surfer Local Time: August 10, 2017 4:11 AM UTC Time: August 10, 2017 8:11 AM From: John.anderso@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
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
greve@nmr.mgh.harvard.edu mailto:greve@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/
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer /A��J2�
-------- Original Message -------- Subject: PET surfer Local Time: August 10, 2017 4:11 AM UTC Time: August 10, 2017 8:11 AM From: John.anderso@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
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
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Douglas N. Greve, Ph.D.
MGH-NMR Center
greve@nmr.mgh.harvard.edu mailto:greve@nmr.mgh.harvard.edu
Phone Number: 617-724-2358
Fax: 617-726-7422
Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
www.nmr.mgh.harvard.edu/facility/filedrop/index.html
Outgoing:
ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer /A
J2
-------- Original Message --------
Subject: PET surfer
Local Time: August 10, 2017 4:11 AM
UTC Time: August 10, 2017 8:11 AM
From: John.anderso@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
greve@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
Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
freesurfer@nmr.mgh.harvard.edu
-
Douglas N Greve -
John Anderson