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Neuroimage. 2016 May 15;132:334-343. doi: 10.1016/j.neuroimage.2016.02.042. Epub 2016 Feb 23.

Different partial volume correction methods lead to different conclusions: An (18)F-FDG-PET study of aging.

Author information

1
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Radiology Department, Harvard Medical School, Boston, MA, USA. Electronic address: greve@nmr.mgh.harvard.edu.
2
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Neuroimaging Research for Veterans Center, VA Boston Healthcare, USA.
3
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
4
Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.
5
Neurobiology Research Unit and Center for Integrated Molecular Brain Imaging, Rigshospitalet, Copenhagen, Denmark.
6
Neurobiology Research Unit and Center for Integrated Molecular Brain Imaging, Rigshospitalet, Copenhagen, Denmark; Faculty of Health and Medical Sciences, Copenhagen, Denmark.
7
Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
8
Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.

Abstract

A cross-sectional group study of the effects of aging on brain metabolism as measured with (18)F-FDG-PET was performed using several different partial volume correction (PVC) methods: no correction (NoPVC), Meltzer (MZ), Müller-Gärtner (MG), and the symmetric geometric transfer matrix (SGTM) using 99 subjects aged 65-87years from the Harvard Aging Brain study. Sensitivity to parameter selection was tested for MZ and MG. The various methods and parameter settings resulted in an extremely wide range of conclusions as to the effects of age on metabolism, from almost no changes to virtually all of cortical regions showing a decrease with age. Simulations showed that NoPVC had significant bias that made the age effect on metabolism appear to be much larger and more significant than it is. MZ was found to be the same as NoPVC for liberal brain masks; for conservative brain masks, MZ showed few areas correlated with age. MG and SGTM were found to be similar; however, MG was sensitive to a thresholding parameter that can result in data loss. CSF uptake was surprisingly high at about 15% of that in gray matter. The exclusion of CSF from SGTM and MG models, which is almost universally done, caused a substantial loss in the power to detect age-related changes. This diversity of results reflects the literature on the metabolism of aging and suggests that extreme care should be taken when applying PVC or interpreting results that have been corrected for partial volume effects. Using the SGTM, significant age-related changes of about 7% per decade were found in frontal and cingulate cortices as well as primary visual and insular cortices.

PMID:
26915497
PMCID:
PMC4851886
DOI:
10.1016/j.neuroimage.2016.02.042
[Indexed for MEDLINE]
Free PMC Article

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