Improved power for characterizing longitudinal amyloid-β PET changes and evaluating amyloid-modifying treatments with a cerebral white matter reference region.
In this article, we describe an image analysis strategy with improved power for tracking longitudinal amyloid-β (Aβ) PET changes and evaluating Aβ-modifying treatments.


METHODS
Our aims were to compare the power of template-based cerebellar, pontine, and cerebral white matter reference regions to track 24-mo florbetapir standardized uptake value (SUV) ratio (SUVR) changes; to relate those changes to 24-mo clinical declines; and to evaluate Aβ-modifying treatments in Aβ-positive (Aβ+) and Aβ-negative (Aβ-) patients with probable Alzheimer dementia (pAD), in patients with mild cognitive impairment (MCI), in cognitively normal controls (NCs), and in cognitively normal apolipoprotein E4 (APOE4) carriers and noncarriers. We used baseline and follow-up (∼24 mo) florbetapir PET scans from 332 Aβ+ and Aβ- subjects participating in the multicenter Alzheimer's Disease Neuroimaging Initiative. Each of the proposed analyses included 31 pAD patients, 187 MCI patients, and 114 NCs. Cerebral-to-white matter, cerebellar, and pontine SUVRs were characterized in terms of their longitudinal variability; their power to track longitudinal fibrillar Aβ increases in Aβ+ and Aβ- subgroups and cognitively normal APOE4 carriers and noncarriers; the sample sizes needed to detect attenuated accumulation of or clearance of fibrillar Aβ accumulation in randomized clinical trials; and their ability to relate 24-mo fibrillar Aβ increases to clinical declines.


RESULTS
As predicted, cerebral-to-white matter SUVR changes were significantly less variable and had significantly greater power to detect 24-mo fibrillar Aβ increases and evaluate Aβ-modifying treatment effects in Aβ+ pAD, MCI, and NC subjects and cognitively normal APOE4 carriers. They were also distinguished by the ability to detect significant associations between 24-mo Aβ increases and clinical declines.


CONCLUSIONS
A cerebral white matter reference region may improve the power to track longitudinal fibrillar Aβ increases, to characterize their relationship to longitudinal clinical declines, and to evaluate Aβ-modifying treatments in randomized clinical trials.
Banner Alzheimer's Institute, Phoenix, Arizona Department of Mathematics and Statistics, Arizona State University, Tempe, Arizona Department of Neurology, College of Medicine, University of Arizona, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona kewei.chen@bannerhealth.com.
Kewei
K
Chen
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Auttawut
A
Roontiva
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Pradeep
P
Thiyyagura
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Wendy
W
Lee
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Xiaofen
X
Liu
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Napatkamon
N
Ayutyanont
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Hillary
H
Protas
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Ji Luo
JL
Luo
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Robert
R
Bauer
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Cole
C
Reschke
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona.
Daniel
D
Bandy
Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan.
Robert A
RA
Koeppe
Arizona Alzheimer's Consortium, Phoenix, Arizona Eli Lilly and Company, Indianapolis, Indiana Department of Neuroscience, University of California-San Diego, San Diego, California.
Adam S
AS
Fleisher
Arizona Alzheimer's Consortium, Phoenix, Arizona Mayo Clinic, Scottsdale, Arizona.
Richard J
RJ
Caselli
School of Public Health and Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California.
Susan
S
Landau
School of Public Health and Helen Wills Neuroscience Institute, University of California-Berkeley, Berkeley, California.
William J
WJ
Jagust
Department of Radiology, University of California-San Francisco, San Francisco, California Department of Medicine, University of California-San Francisco, San Francisco, California Department of Psychiatry, University of California-San Francisco, San Francisco, California.
Michael W
MW
Weiner
Banner Alzheimer's Institute, Phoenix, Arizona Arizona Alzheimer's Consortium, Phoenix, Arizona Division of Neurogenomics, Translational Genomics Research Institute, Phoenix, Arizona; and Department of Psychiatry, University of Arizona, Tucson, Arizona.
Eric M
EM
Reiman
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis / Q000000981:diagnostic imaging; D016229:Amyloid beta-Peptides / Q000737:chemistry*; D000814:Aniline Compounds; D053327:Apolipoprotein E4 / Q000235:genetics; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D002531:Cerebellum / Q000000981:diagnostic imaging; D054022:Cerebrum / Q000000981:diagnostic imaging; D003072:Cognition Disorders / Q000175:diagnosis / Q000000981:diagnostic imaging; D005026:Ethylene Glycols; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D011149:Pons / Q000000981:diagnostic imaging; D049268:Positron-Emission Tomography / Q000379:methods*; D016032:Randomized Controlled Trials as Topic; D012016:Reference Values; D018401:Sample Size; D013997:Time Factors; D066127:White Matter / Q000000981:diagnostic imaging*
D016229:Amyloid beta-Peptides; D000814:Aniline Compounds; D053327:Apolipoprotein E4; D005026:Ethylene Glycols; C545186:florbetapir
Alzheimer disease; biomarkers; clinical trial sample size; florbetapir PET; image analysis; statistical power