Re: [Freesurfer] Pet Surfer

[Greve, Douglas N.,Ph.D.]

It could make sense to apply it to WM. CSF I'm not so sure. Are you 
really trying to measure the signal in CSF?

On 10/10/18 6:08 PM, David.Mackarthy wrote:
>  External Email - Use Caution
>
> Dear Dr Greve, thank you for the response
> This is for a map-based study. Absolutely, this is clear, I appreciate the 
> response. I just have one additional question and I appreciate your patience.
>
> Is it recommended to apply PVC on white matter or csf? does it make sense to 
> apply PVC on WM and CSF?
>
> Thank you so much!
>
>
>
> ‐‐‐ Original Message ‐‐‐
> On Wednesday, October 10, 2018 2:17 PM, Greve, Douglas N.,Ph.D. 
>  wrote:
>
>> Is this for an ROI-based study or a map-based study? For ROI, we use the
>> GTM, and it PV corrects for all structures (including WM and CSF). For
>> map-based, we use MG. MG removes WM (and CSF) entirely. In theory, it
>> can be run in a way to keep WM and throw GM and CSF away, but that is
>> not implemented. Does this answer your questions?
>>
>> On 10/10/2018 07:31 AM, David.Mackarthy wrote:
>>
>>> Dear Dr Greeve,
>>> I am following petsurfer pipeline to do surface based analysis of
>>> PET-FDG data and I have interest in doing partial volume correction. I
>>> would like to inquire about:
>>>
>>> 1.  Can partial volume correction be applied on white mater, or just on
>>>  gray matter?
>>>
>>> 2.  Can partial volume correction be applied between gray matter and CSF?
>>>
>>>
>>> According to Muller-Gartner (MG) Method we segment the brain to
>>> gray/white and csf, then we apply partial volume correction only on
>>> gray matter. why not on the other parts.
>>> I apologies if my question is basics and I appreciate your input.
>>> Thanks for publishing this valuable manuscript
>>> https://www.ncbi.nlm.nih.gov/pubmed/26915497
>>> With all respect!
>>> Dev
>>>
>>> Freesurfer mailing list
>>> Freesurfer@nmr.mgh.harvard.edu
>>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>> Freesurfer mailing list
>> Freesurfer@nmr.mgh.harvard.edu
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
>
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Re: [Freesurfer] Pet Surfer

[David.Mackarthy]

External Email - Use Caution

Dear Dr Greve, thank you for the response
This is for a map-based study. Absolutely, this is clear, I appreciate the 
response. I just have one additional question and I appreciate your patience.

Is it recommended to apply PVC on white matter or csf? does it make sense to 
apply PVC on WM and CSF?

Thank you so much!



‐‐‐ Original Message ‐‐‐
On Wednesday, October 10, 2018 2:17 PM, Greve, Douglas N.,Ph.D. 
 wrote:

> Is this for an ROI-based study or a map-based study? For ROI, we use the
> GTM, and it PV corrects for all structures (including WM and CSF). For
> map-based, we use MG. MG removes WM (and CSF) entirely. In theory, it
> can be run in a way to keep WM and throw GM and CSF away, but that is
> not implemented. Does this answer your questions?
>
> On 10/10/2018 07:31 AM, David.Mackarthy wrote:
>
> > Dear Dr Greeve,
> > I am following petsurfer pipeline to do surface based analysis of
> > PET-FDG data and I have interest in doing partial volume correction. I
> > would like to inquire about:
> >
> > 1.  Can partial volume correction be applied on white mater, or just on
> > gray matter?
> >
> > 2.  Can partial volume correction be applied between gray matter and CSF?
> >
> >
> > According to Muller-Gartner (MG) Method we segment the brain to
> > gray/white and csf, then we apply partial volume correction only on
> > gray matter. why not on the other parts.
> > I apologies if my question is basics and I appreciate your input.
> > Thanks for publishing this valuable manuscript
> > https://www.ncbi.nlm.nih.gov/pubmed/26915497
> > With all respect!
> > Dev
> >
> > Freesurfer mailing list
> > Freesurfer@nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer



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Re: [Freesurfer] Pet Surfer

[Greve, Douglas N.,Ph.D.]

Is this for an ROI-based study or a map-based study? For ROI, we use the 
GTM, and it PV corrects for all structures (including WM and CSF). For 
map-based, we use MG. MG removes WM (and CSF) entirely. In theory, it 
can be run in a way to keep WM and throw GM and CSF away, but that is 
not implemented. Does this answer your questions?



On 10/10/2018 07:31 AM, David.Mackarthy wrote:
>
>
> Dear Dr Greeve,
> I am following petsurfer pipeline to do surface based analysis of 
> PET-FDG data and I have interest in doing partial volume correction. I 
> would like to inquire about:
>
> 1) Can partial volume correction be applied on white mater, or just on 
> gray matter?
>
> 2) Can partial volume correction be applied between gray matter and CSF?
>
> According to Muller-Gartner (MG) Method we segment the brain to 
> gray/white and csf, then we apply partial volume correction only on 
> gray matter. why not on the other parts.
>
> I apologies if my question is basics and I appreciate your input.
>
> Thanks for publishing this valuable manuscript
>
> https://www.ncbi.nlm.nih.gov/pubmed/26915497
>
> With all respect!
> Dev
>
>
>
>
>
> ___
> Freesurfer mailing list
> Freesurfer@nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer


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Re: [Freesurfer] pet surfer

[Douglas Greve]

PVC will increase signal in some regions and will decrease it in others. 
Eg, for FDG it will increase it in GM and decrease it in WM. The reason 
you are seeing such a wide range is that the MG correction subtracts the 
WM then divides by the GM  partial volume fraction (PVF, a number 
between 0 and 1).  This requires a mask of some sort because there will 
be some voxels where the GM PVF is 0 (and you can't divide by 0). When 
you ran mri_gtmpvc with the --mgx option, you had to supply a threshold 
(eg, .01). This is the minimum allowed PVF before the voxel is masked 
out. If you used .01, then the multiplier could be as large as 1/.10 = 
100, which agrees with the range you are seeing. Because of this 
problem, you must do the MG voxel-wise analysis on the surface where the 
GM PVF will be high. For subcortical analysis, you must use a mask of 
subcortical GM structures. The mask must be used when smoothing because 
you must only smooth within the mask (not such a problem on the 
surface). Note that there are many paper that use MG in a volume-based 
voxel-wise analysis; in my opinion, these studies are invalid.



On 8/18/17 11:47 AM, John Anderson wrote:


Hi Dr Greve, Thank you very much for the great answers.

Kindly, I have one last question.
The range of the signal intensity within the voxels in the original 
SUV maps is min=0.00 and max=3.017629

For the mgx images it is min=-43.74384 and max=88.468712

The difference in the range of signal intensity in the mgx images is 
largely wide. It seems that PVC increases the signal intensity. Is 
this correct?
Am I doing something wrong. I plan to include these images in 
voxel-wise analysis so I am curious about this difference between the 
images.


Thanks for any clarification!




On 8/18/17 10:20 AM, John Anderson wrote:

Hi Dr Greve,

I followed the steps in WIKI to do SUV-surface based analyses + PVC. I 
have the following questions and I highly appreciate your input:



1. Why the dimension of the images (mgx.gm, mgx.ctx.gm and 
 mgx.ctx.subgm) is not like the original SUV image that has been fed 
to the pipeline. i.e. I start with image-dimensions 128X128X128 : 
2X2X2 and end up with 79X113X102 : 2X2X2



Also FOV is different as  well between the original SUV image  /256/ 
and the output mgx images /158/. How this happen? I am I doing 
something wrong?


I set up mri_gtmpvc to reduce the field of view to a bounding box 
around the head to reduce memory and computational loads. You can turn 
this off with --no-reduce-fov



2. Some voxels in the mgx images has negative signal intensity. is 
this normal?


Yes. MG works by estimating the contribution of non-GM to GM and 
subtracting it out. If the estimate is too high, then it can cause 
negative values.



Thank you for any clarification.

John





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Re: [Freesurfer] pet surfer

[John Anderson]

Hi Dr Greve, Thank you very much for the great answers.

Kindly, I have one last question.
The range of the signal intensity within the voxels in the original SUV maps is 
min=0.00 and max=3.017629
For the mgx images it is min=-43.74384 and max=88.468712

The difference in the range of signal intensity in the mgx images is largely 
wide. It seems that PVC increases the signal intensity. Is this correct?
Am I doing something wrong. I plan to include these images in voxel-wise 
analysis so I am curious about this difference between the images.

Thanks for any clarification!

On 8/18/17 10:20 AM, John Anderson wrote:

Hi Dr Greve,

I followed the steps in WIKI to do SUV-surface based analyses + PVC. I have the 
following questions and I highly appreciate your input:

1. Why the dimension of the images (mgx.gm, mgx.ctx.gm and  mgx.ctx.subgm) is 
not like the original SUV image that has been fed to the pipeline. i.e. I start 
with image-dimensions 128X128X128 : 2X2X2 and end up with 79X113X102 : 2X2X2

Also FOV is different as  well between the original SUV image  /256/ and the 
output mgx images /158/. How this happen? I am I doing something wrong?

I set up mri_gtmpvc to reduce the field of view to a bounding box around the 
head to reduce memory and computational loads. You can turn this off with 
--no-reduce-fov

2. Some voxels in the mgx images has negative signal intensity. is this normal?

Yes. MG works by estimating the contribution of non-GM to GM and subtracting it 
out. If the estimate is too high, then it can cause negative values.

Thank you for any clarification.

John___
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contains patient information, please contact the Partners Compliance HelpLine at
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but does not contain patient information, please contact the sender and properly
dispose of the e-mail.

Re: [Freesurfer] pet surfer

[Douglas Greve]

On 8/18/17 10:20 AM, John Anderson wrote:

Hi Dr Greve,
I followed the steps in WIKI to do SUV-surface based analyses + PVC. I 
have the following questions and I highly appreciate your input:


1. Why the dimension of the images (mgx.gm, mgx.ctx.gm and 
 mgx.ctx.subgm) is not like the original SUV image that has been fed 
to the pipeline. i.e. I start with image-dimensions 128X128X128 : 
2X2X2 and end up with 79X113X102 : 2X2X2


Also FOV is different as  well between the original SUV image  /256/ 
and the output mgx images /158/. How this happen? I am I doing 
something wrong?
I set up mri_gtmpvc to reduce the field of view to a bounding box around 
the head to reduce memory and computational loads. You can turn this off 
with --no-reduce-fov


2. Some voxels in the mgx images has negative signal intensity. is 
this normal?
Yes. MG works by estimating the contribution of non-GM to GM and 
subtracting it out. If the estimate is too high, then it can cause 
negative values.


Thank you for any clarification.
John



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contains patient information, please contact the Partners Compliance HelpLine at
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but does not contain patient information, please contact the sender and properly
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Re: [Freesurfer] PET surfer

[John Anderson]

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

>

> 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

> 

>

> Outgoing:

> ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/

>

>

> __

Re: [Freesurfer] PET surfer

[Douglas N Greve]

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
>
> 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 
> 
>
> 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.ande...@protonmail.com
>> To: Freesurfer support list 
>>
>> 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 li

Re: [Freesurfer] PET surfer

[John Anderson]

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

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>  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 
>
> 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___
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Re: [Freesurfer] PET surfer

[Douglas N Greve]

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
>>
>
>
>
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> Freesurfer@nmr.mgh.harvard.edu
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-- 
Douglas N. Greve, Ph.D.
MGH-NMR Center
gr...@nmr.mgh.harvard.edu
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