The effect of amyloid pathology and glucose metabolism on cortical volume loss over time in Alzheimer’s disease
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Author(s)
Ossenkoppele, Rik
Tolboom, Nelleke
Yaqub, Maqsood
Boellaard, Ronald
Scheltens, Philip
Barkhof, Frederik
Adriaanse, Sofie M.
van Dijk, Koene R. A.
Zwan, Marissa D.
Windhorst, Albert D.
Date Issued
March 2014
Journal
European Journal of Nuclear Medicine and Molecular Imaging
Publisher
Springer Berlin Heidelberg
Citation
Adriaanse, Sofie M. et al. “The Effect of Amyloid Pathology and Glucose Metabolism on Cortical Volume Loss over Time in Alzheimer’s Disease.” European Journal of Nuclear Medicine and Molecular Imaging (2014): n. pag.
Version
Author's final manuscript
Abstract
Purpose: The present multimodal neuroimaging study examined whether amyloid pathology and glucose metabolism are related to cortical volume loss over time in Alzheimer’s disease (AD) patients and healthy elderly controls. Methods: Structural MRI scans of eleven AD patients and ten controls were available at baseline and follow-up (mean interval 2.5 years). Change in brain structure over time was defined as percent change of cortical volume within seven a-priori defined regions that typically show the strongest structural loss in AD. In addition, two PET scans were performed at baseline: [[superscript 11]C]PIB to assess amyloid-β plaque load and [[superscript 18]F]FDG to assess glucose metabolism. [[superscript 11]C]PIB binding and [[superscript 18]F]FDG uptake were measured in the precuneus, a region in which both amyloid deposition and glucose hypometabolism occur early in the course of AD.
Results: While amyloid-β plaque load at baseline was not related to cortical volume loss over time in either group, glucose metabolism within the group of AD patients was significantly related to volume loss over time (rho=0.56, p<0.05).
Conclusion:The present study shows that in a group of AD patients amyloid-β plaque load as measured by [[superscript 11]C]PIB behaves as a trait marker (i.e., all AD patients showed elevated levels of amyloid, not related to subsequent disease course), whilst hypometabolism as measured by [[superscript 18]F]FDG changed over time indicating that it could serve as a state marker that is predictive of neurodegeneration.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1007/s00259-014-2704-z
