Dear,

Many thanks for these explanations!

Further, I do have 4 additional questions linked to the mask option when applying RBV PVC in Freesurfer.

(1)   Could you please tell me how the brainmask is generated when using the –auto-mask option, eg –-auto-mask 5 0.01. From which image is the generation of the mask started? (brain.mgz, brainmask.auto.mgz, brainmask.mgz, or something else?)

(2)   I noticed that the amount of segments (used in RBV PVC) is reduced (compared to amount of roi’s in gtmseg) after using the mask. Can you explain this?

(3)   Could you please tell me when in the RBV PVC calculations this mask is applied?

(4)   I guess this mask has nothing to do with the ‘masking rbv to brain’, which is applied in the end when running the RBV PVC? Can you elaborate on this final step?

Many thanks for your help.

Kind regards,

Nathalie Mertens

On 8/19/2020 2:42 AM, Nathalie Mertens wrote:

        External Email - Use Caution

Dear,

I am not sure if the questions below were sent correctly to you, since I did not receive any copy of it.

Please find my message below.

Many thanks, looking forward to your reply.

Kind regards,

Nathalie Mertens

sorry, did not see the original posting

*Van: *Nathalie Mertens <nathalie.mert...@kuleuven.be>

*Datum: *dinsdag 18 augustus 2020 om 09:33

*Aan: *"freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>

*Onderwerp: *RBV PVC

Dear,

I do have some questions linked to RBV PVC implemented in Freesurfer:

 1. Could you please tell me how the RBV PVC is acquired? Is the RBV

    PVC acquired based on Muller-Gartner (on a region-level, and based

    on only using gray- versus white matter), or when and how are the

    different regions from gtm_seg applied to obtain GTM?

See the RBV paper. Thomas, B.A., Erlandsson, K., Modat, M., Thurfjell, L., Vandenberghe, R., Ourselin, S., Hutton, B.F., 2011. The importance of appropriate partial volume correction for PET quantification in Alzheimer's disease. Eur. J. Nucl. Med. Mol. Imaging 38, 1104\u20131119.

1.

 2. What would be the advantage of using your technique compared to

    for instance sGTM?

sGTM is ROI-only, RBV is voxelwise.

1.

 2. Could you please tell me the difference in region-definition

    between aparc+aseg and the gtm_seg? (I saw that the latter

    contains less regions compared to aparc+aseg.) What is the reason

    to use the latter compared to the aparc+aseg, based on the

    definitions of the regions? (I know that gtm_seg is used which has

    a high resolution, but not quite sure, apart from the resolution,

    why you are not using aparc+aseg for the RBV PVC.)

gtmseg.mgz is higher resolution (using the subvoxel surfaces). It also has pons and vermis defined. It has a few regions merged with others.  It also has extracerebral structures.

1.

 2. Is there a mask applied to the gtm_seg to exclude regions that are

    located outside the brain?

No, it is a full head model.

1.

Many thanks for your answers.

Kind regards,

Nathalie

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