Evidence map›Paper›PMID 26915497›Full record

ArticleNeuroImage2016

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

Douglas N Greve, David H Salat, Spencer L Bowen, David Izquierdo-Garcia, Aaron P Schultz, Ciprian Catana, J Alex Becker, Claus Svarer, Gitte M Knudsen, Reisa A Sperling and 1 more

Open access · greenAbstract read
In one paragraph

Article in NeuroImage, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 213 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
213citing papers in PubMed, 3 pooled it
17.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

213 citing papers in PubMed, 3 syntheses or guidelines pooled it, 317 citations in OpenAlex.

  1. Elevated temporal tau PET predicts faster cognitive decline in women than men: A meta-analysis.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Pooled it
  2. Pooled it
  3. Cerebral serotonin transporter measurements with [Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2019
    Pooled it
  4. Changes in synaptic density in the subacute phase after ischemic stroke: AJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2022
    Trial
  5. Different preprocessing strategies lead to different conclusions: A [Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2020
    Trial
  6. Article
  7. Article
  8. Building an open infrastructure for molecular neuroimaging: Standards and tools from the OpenNeuroPET initiative.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. In vivo mapping of cortical amyloid beta-myelin coupling in preclinical Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
    Article
  16. Observational
  17. Article
  18. Brain glucodynamic variability is an essential feature of the metabolism-cognition relationship.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  19. Review
  20. Article

153 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 6 institutions in 2 countries.

Douglas N GreveDepartment 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.
David H SalatDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA; Neuroimaging Research for Veterans Center, VA Boston Healthcare, USA.
Spencer L BowenDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
David Izquierdo-GarciaDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
Aaron P SchultzDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
Ciprian CatanaDepartment of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, MA, USA.
J Alex BeckerDepartment of Radiology, Massachusetts General Hospital, Boston, MA, USA.
Claus SvarerNeurobiology Research Unit and Center for Integrated Molecular Brain Imaging, Rigshospitalet, Copenhagen, Denmark.
Gitte M KnudsenNeurobiology Research Unit and Center for Integrated Molecular Brain Imaging, Rigshospitalet, Copenhagen, Denmark; Faculty of Health and Medical Sciences, Copenhagen, Denmark.
Reisa A SperlingDepartment of Radiology, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA.
Keith A JohnsonDepartment 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.
Massachusetts General Hospital · USBrigham and Women's Hospital · USCopenhagen University Hospital · DKHarvard University · USRigshospitalet · DKVA Boston Healthcare System · US

Funding

Vascular factors, physical activity, and inflammation as modulators of neurodegenerative and cognitive trajectories (Project 2)P01AG036694 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI REISA A. SPERLING · 2010 to 2026
$50.2M
ULTRAHIGH FIELD TECHNOLOGY FOR FUNCTIONAL IMAGINGP41RR014075 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 1999 to 2011
$16.4M
MR-assisted PET data optimization for neuroimaging studiesR01EB014894 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CATANA, CIPRIAN · 2013 to 2016
$2.6M
Tools for Analyzing Cortical Structure and ConnectivityR01NS052585 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2006 to 2010
$2.5M
A Storage Area Network for Structural and Functional Image AnalysisS10RR023401 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2009 to 2009
$2.0M
Inferring in Vivo Cytoarchitectural Borders in the Medial Temporal LobeR01EB006758 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2007 to 2010
$1.9M
Automated Analysis of Healthy and Diseased Brain TissueR01RR016594 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2002 to 2005
$1.7M
SILICON GRAPHICS PRISM EXTREME 128P/1TBS10RR023043 · NCRR · MASSACHUSETTS GENERAL HOSPITAL · PI SORENSEN, ALMA GREGORY · 2006 to 2006
$1.5M
Mentoring Imaging Research in Early ADK24AG035007 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI SPERLING, REISA A. · 2010 to 2020
$1.4M
Accelerated Software Tools for Neuroimaging AnalysisR21NS072652 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI FISCHL, BRUCE · 2010 to 2011
$473k
Multimodal brain imaging of serotoninR21EB018964 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI GREVE, DOUGLAS NOWLIN, KNUDSEN, GITTE MOOS · 2014 to 2015
$423k
NCRR NIH HHS P41 RR014075NCRR NIH HHS R01 RR016594NCRR NIH HHS S10 RR023043NCRR NIH HHS S10 RR023401NIA NIH HHS K24 AG035007NIA NIH HHS P01 AG036694NIBIB NIH HHS R01 EB006758NIBIB NIH HHS R01 EB014894NIBIB NIH HHS R21 EB018964NINDS NIH HHS R01 NS052585NINDS NIH HHS R21 NS072652
6 · The paper itself

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.

Indexed as

AgingAgedAged, 80 and overAlgorithmsBrainBrain MappingFemaleFluorodeoxyglucose F18HumansImage Processing, Computer-AssistedMalePositron-Emission TomographyReproducibility of ResultsSignal Processing, Computer-AssistedFluorodeoxyglucose F18

Identifiers

PMID26915497
PMCPMC4851886
OpenAlexW2273698149

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.