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Dear Lauren,
This is a very interesting question!
Site harmonization matters aside (there’s a vast literature on it), whether you correct by ICV or whole hippocampal volume essentially answers to different questions:
- ICV: you’re asking whether there’s an effect of X on subfield Y.
- whole hippo volume: you’re asking whether X has an effect on the fraction of hippocampal volume attributed to Y.
Both questions are interesting; it depends on what you’re trying to answer.
Of course, if you’re correcting by whole hippocampal volume, then don’t correct by ICV…
I hope this helps!
/Eugenio
--
Juan Eugenio Iglesias
Centre for Medical Image Computing (CMIC)
Department of Medical Physics and Biomedical Engineering
University College London
http://www.jeiglesias.com
From: <freesurfer-bounces@nmr.mgh.harvard.edu> on behalf of Lauren Salminen <lespr4@gmail.com>
Reply-To: Freesurfer support list <freesurfer@nmr.mgh.harvard.edu>
Date: Friday, 26 October 2018 at 22:40
To: "freesurfer@nmr.mgh.harvard.edu" <freesurfer@nmr.mgh.harvard.edu>
Subject: [Freesurfer] subfield normalization vs. covarying for whole hippocampal volume
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Hello,
I’m working on a multi-site hippocampal subfields project (FSv. 6) and am wondering if it is “better” to normalize subfield volumes by dividing each subfield by whole hippocampal volume, or covary for hippocampal volume as an independent
predictor variable in the regression models.
Ultimately the goal is to determine the degree that each subfield may be uniquely associated with my target predictor variable, and we would like to know if this effect can be observed independent of potential differences in the whole hippocampus. Traditionally
we have covaried for whole hippocampal volume, but I’ve found more interesting effects by normalizing each subfield to their hippocampal volume.
Any guidance is appreciated.
Thank you!
____________________
Lauren E. Salminen, Ph.D.
Imaging Genetics Center
Stevens Neuroimaging and Informatics Institute
Keck School of Medicine
University of Southern California