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mris_preproc --qdec-long RossQdecFinal30May.txt --target fsaverage --hemi lh --meas volume --out lh.Rossvolume.mgh
The vertex-wise analyses were run with 5 mm smoothing, but the graph I showed below was created with the unsmoothed data.
Thanks for the help!
Mark
____________________ Mark Wagshul, PhD Associate Professor Gruss Magnetic Resonance Research Center Albert Einstein College of Medicine Bronx, NY 10461
Ph: 718-430-4011 FAX: 718-430-3399 Email: mark.wagshul@einsteinmed.orgmailto:mark.wagshul@einsteinmed.org
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From: freesurfer-bounces@nmr.mgh.harvard.edu freesurfer-bounces@nmr.mgh.harvard.edu On Behalf Of Douglas N. Greve Sent: Friday, January 29, 2021 11:41 AM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] Voxel-wise volumes vs APARC volumes
What is your mris_preproc comman? On 1/28/2021 5:34 PM, Mark Wagshul wrote:
External Email - Use Caution Dear Freesurfer experts,
I'm stuck on something which I think has to do with how Freesurfer calculates volumes, but can't quite wrap my head around it, hopefully you can enlighten me.
I have already produced robust results for our data using region-based cortical volumes, using aparcstats2table. This is in a group of 55 healthy older adults, modeling is using linear mixed effects models. All volumes were normalized with the eTIV.
We were hoping on exploring the same models with voxel-wise analyses, and are getting wildly different results. Data were created using mri_preproc, resampled onto fsaverage, and my assumptions was that because of this resampling, we should NOT be normalizing these values to the eTIV. The same regions which were highly significant on the region-based analyses and now not significant at all, and other regions are now showing up as significant.
Just as a sanity check, I attempted to reproduce the region-based analyses with these data using the following simple (I thought!) procedure:
1. Created an mgz mask of the region I'm interested in, using mri_annotation2label and mri_label2label
2. Read my volume data (#subjects x #vertices) into Matlab
3. Read my mask into Matlab (yes, I know I can probably do this in Freesurfer, but I'm more comfortable with Matlab!)
4. Multiply them together and take the sum across vertices.
5. Feed the resultant data back into my LME model.
Two things are puzzling to me. 1) The highly significant results from the old LME are no longer significant (at the moment, only checked for two of the cortical regions), and 2) The correlation between these new data and the aparc volume are OK, although far from perfect (R2 ~ 0.86).
So, I'm obviously missing something here. What is the difference between the two volume calculation methods which could explain these discrepancies?
Any help with this would be MOST appreciated!
Best,
Mark
[cid:image003.jpg@01D6F656.F260AA50]
____________________ Mark Wagshul, PhD Associate Professor Gruss Magnetic Resonance Research Center Albert Einstein College of Medicine Bronx, NY 10461
Ph: 718-430-4011 FAX: 718-430-3399 Email: mark.wagshul@einsteinmed.orgmailto:mark.wagshul@einsteinmed.org
[einstein-logo-rgb] This email message and any accompanying attachments may contain privileged information intended only for the named recipient(s). If you are not the intended recipient(s), you are hereby notified that the dissemination, distribution, and or copying of this message is strictly prohibited. If you receive this message in error, or are not the named recipient(s), please notify the sender at the email address above, delete this email from your computer, and destroy any copies in any form immediately.
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