Wow, longitudinal segmentation is absolutely awesome! It reduced our measurement error by more than 30%. I can't wait when the hippocampal longitudinal segmentation is ready.

By the way, I want to run (cross-sectional) hippocampal subfields on longitudinal data using additional T2 with lower resolution and I was wondering if I should use multispectral segmentation
recon-all -s <subject_name> -hippocampal-subfields-T1T2 <file name of additional scan> <analysisID>
or just additional scan
recon-all -s <subject_name> -hippocampal-subfields-T2 <file name of additional scan>  <analysisID> 
Since my T1 and T2 scans are quite well aligned, I wanted to use -hippocampal-subfields-T2, but I saw you recommending T1T2 in mailing list. Thanks!

(I'm also blocked by a bug with .ctf files https://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg48412.html, but I'm fine with waiting for fix)
 
Thanks!
Mojmir

On Fri, Jul 15, 2016 at 12:33 PM Iglesias, Eugenio <e.iglesias@ucl.ac.uk> wrote:
Dear Mojmir,
using ~400 subjects, we found that the subfield module was a bit better than the ASEG volumes at discriminating Alzheimer’s patients from controls (see the Neuorimage paper). But, in any case, the difference is small. 
Regarding longitudinal segmentation: we just got a paper about this accepted, see
http://www.nmr.mgh.harvard.edu/~iglesias/pdf/Neuroimage_2016_longitudinal.pdf
I still need to find time to clean up the code and put it up on FreeSurfer. For the time being, you can run the subfield module on the longitudinally analyzed recons (method “L-INIT” in the paper).
Cheers,
Eugenio

Juan Eugenio Iglesias
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 15 Jul 2016, at 09:00, Mojmír Vinkler <mojmir.vinkler@gmail.com> wrote:

Hi Juan,

Thanks! You're right, they really are tightly correlated (although their absolute values differ by 30%). We tried it on couple of subjects, but didn't find subfields to be significantly better than aseg stats though. By the way, is Freesurfer capable of using multiple scans from the same subject (longitudinal study, same modality) to make more precise measurements? For example by using T1 from the same subject / different time instead of T2 in subfields?

Thanks!
Mojmir

On Wed, Jul 13, 2016 at 5:15 PM Iglesias, Eugenio <e.iglesias@ucl.ac.uk> wrote:
Hi Mojmir,
ASEG typically gives a larger estimate of the volume, though highly correlated with that from the subfield package. We have found the measurements from the subfield package to be a bit more reliable, though.
Cheers,
Eugenio

Juan Eugenio Iglesias
Translational Imaging Group
University College London
http://www.jeiglesias.com
http://cmictig.cs.ucl.ac.uk/


On 13 Jul 2016, at 16:07, Mojmír Vinkler <mojmir.vinkler@gmail.com> wrote:

Hi experts,

I'm using Freesurfer 6.0 dev version (Mac) to perform hippocampal subfields segmentation. I only need to measure total hippocampus volume, but measurements from basic `recon-all` were too volatile and I was hoping that using subfields with T2 modality would reduce variance. However, volume measured by hippocampal subfields is significantly different from volume in aseg.stats.

Here are volumes for right hippocampus from various methods:
aseg.stats - 3312.8
rh.hippoSfVolumes-T1.v10.txt (Mode A - only T1 used) - 2883.8
rh.hippoSfVolumes-T2.v10.txt (Mode B - using only additional scan) - 2503.97
rh.hippoSfVolumes-T1-T1T2.v10.txt (Mode B - Multispectral segmentation) - 2596.09

I checked labeling visually and there were no obvious problems. Is such a large difference common? Am I missing something? What number should be most trusted?

Thanks for any hints!
Mojmir
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