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Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group.

Authors :
Yi Su
Tyler M Blazey
Christopher J Owen
Jon J Christensen
Karl Friedrichsen
Nelly Joseph-Mathurin
Qing Wang
Russ C Hornbeck
Beau M Ances
Abraham Z Snyder
Lisa A Cash
Robert A Koeppe
William E Klunk
Douglas Galasko
Adam M Brickman
Eric McDade
John M Ringman
Paul M Thompson
Andrew J Saykin
Bernardino Ghetti
Reisa A Sperling
Keith A Johnson
Stephen P Salloway
Peter R Schofield
Colin L Masters
Victor L Villemagne
Nick C Fox
Stefan Förster
Kewei Chen
Eric M Reiman
Chengjie Xiong
Daniel S Marcus
Michael W Weiner
John C Morris
Randall J Bateman
Tammie L S Benzinger
Dominantly Inherited Alzheimer Network
Source :
PLoS ONE, Vol 11, Iss 3, p e0152082 (2016)
Publication Year :
2016
Publisher :
Public Library of Science (PLoS), 2016.

Abstract

Amyloid imaging plays an important role in the research and diagnosis of dementing disorders. Substantial variation in quantitative methods to measure brain amyloid burden exists in the field. The aim of this work is to investigate the impact of methodological variations to the quantification of amyloid burden using data from the Dominantly Inherited Alzheimer's Network (DIAN), an autosomal dominant Alzheimer's disease population. Cross-sectional and longitudinal [11C]-Pittsburgh Compound B (PiB) PET imaging data from the DIAN study were analyzed. Four candidate reference regions were investigated for estimation of brain amyloid burden. A regional spread function based technique was also investigated for the correction of partial volume effects. Cerebellar cortex, brain-stem, and white matter regions all had stable tracer retention during the course of disease. Partial volume correction consistently improves sensitivity to group differences and longitudinal changes over time. White matter referencing improved statistical power in the detecting longitudinal changes in relative tracer retention; however, the reason for this improvement is unclear and requires further investigation. Full dynamic acquisition and kinetic modeling improved statistical power although it may add cost and time. Several technical variations to amyloid burden quantification were examined in this study. Partial volume correction emerged as the strategy that most consistently improved statistical power for the detection of both longitudinal changes and across-group differences. For the autosomal dominant Alzheimer's disease population with PiB imaging, utilizing brainstem as a reference region with partial volume correction may be optimal for current interventional trials. Further investigation of technical issues in quantitative amyloid imaging in different study populations using different amyloid imaging tracers is warranted.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
11
Issue :
3
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.3c1e448b15fa468cb6de83c58a76a317
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0152082