TY - JOUR
T1 - MRI-based brain atrophy rates in ADNI phase 2
T2 - acceleration and enrichment considerations for clinical trials
AU - Hua, Xue
AU - Ching, Christopher R.K.
AU - Mezher, Adam
AU - Gutman, Boris A.
AU - Hibar, Derrek P.
AU - Bhatt, Priya
AU - Leow, Alex D.
AU - Jack, Clifford R.
AU - Bernstein, Matt A.
AU - Weiner, Michael W.
AU - Thompson, Paul M.
N1 - Funding Information:
Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative (ADNI) ( National Institutes of Health [NIH] grant U01 AG024904 ) and DOD ADNI (Department of Defense award number W81XWH-12-2–0012). ADNI is funded by the National Institute on Aging , the National Institute of Biomedical Imaging and Bioengineering , and through generous contributions from the following: Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc; Biogen Idec, Inc; Bristol-Myers Squibb Company; Eisai, Inc; Elan Pharmaceuticals Inc; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc; Fujirebio; GE Healthcare; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC; Johnson & Johnson Pharmaceutical Research & Development LLC; Medpace, Inc; Merck & Co, Inc; Meso Scale Diagnostics, LLC; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer, Inc; Piramal Imaging; Servier; Synarc, Inc; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California , San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. BG is partially supported by the Biomarkers across Neurodegenerative Diseases award, by the Michael J. Fox Foundation & the Alzheimer's Association. This work was supported in part by a consortium grant ( U54 EB 020403 ) to the ENIGMA Center (PI: Paul Thompson) , from the NIH Institutes contributing to the Big Data to Knowledge (BD2K) Initiative.
PY - 2016/1/1
Y1 - 2016/1/1
N2 - The goal of this work was to assess statistical power to detect treatment effects in Alzheimer's disease (AD) clinical trials using magnetic resonance imaging (MRI)–derived brain biomarkers. We used unbiased tensor-based morphometry (TBM) to analyze n = 5,738 scans, from Alzheimer's Disease Neuroimaging Initiative 2 participants scanned with both accelerated and nonaccelerated T1-weighted MRI at 3T. The study cohort included 198 healthy controls, 111 participants with significant memory complaint, 182 with early mild cognitive impairment (EMCI) and 177 late mild cognitive impairment (LMCI), and 155 AD patients, scanned at screening and 3, 6, 12, and 24 months. The statistical power to track brain change in TBM-based imaging biomarkers depends on the interscan interval, disease stage, and methods used to extract numerical summaries. To achieve reasonable sample size estimates for potential clinical trials, the minimal scan interval was 6 months for LMCI and AD and 12 months for EMCI. TBM-based imaging biomarkers were not sensitive to MRI scan acceleration, which gave results comparable with nonaccelerated sequences. ApoE status and baseline amyloid-beta positron emission tomography data improved statistical power. Among healthy, EMCI, and LMCI participants, sample size requirements were significantly lower in the amyloid+/ApoE4+ group than for the amyloid–/ApoE4– group. ApoE4 strongly predicted atrophy rates across brain regions most affected by AD, but the remaining 9 of the top 10 AD risk genes offered no added predictive value in this cohort.
AB - The goal of this work was to assess statistical power to detect treatment effects in Alzheimer's disease (AD) clinical trials using magnetic resonance imaging (MRI)–derived brain biomarkers. We used unbiased tensor-based morphometry (TBM) to analyze n = 5,738 scans, from Alzheimer's Disease Neuroimaging Initiative 2 participants scanned with both accelerated and nonaccelerated T1-weighted MRI at 3T. The study cohort included 198 healthy controls, 111 participants with significant memory complaint, 182 with early mild cognitive impairment (EMCI) and 177 late mild cognitive impairment (LMCI), and 155 AD patients, scanned at screening and 3, 6, 12, and 24 months. The statistical power to track brain change in TBM-based imaging biomarkers depends on the interscan interval, disease stage, and methods used to extract numerical summaries. To achieve reasonable sample size estimates for potential clinical trials, the minimal scan interval was 6 months for LMCI and AD and 12 months for EMCI. TBM-based imaging biomarkers were not sensitive to MRI scan acceleration, which gave results comparable with nonaccelerated sequences. ApoE status and baseline amyloid-beta positron emission tomography data improved statistical power. Among healthy, EMCI, and LMCI participants, sample size requirements were significantly lower in the amyloid+/ApoE4+ group than for the amyloid–/ApoE4– group. ApoE4 strongly predicted atrophy rates across brain regions most affected by AD, but the remaining 9 of the top 10 AD risk genes offered no added predictive value in this cohort.
KW - Alzheimer's disease
KW - Amyloid
KW - ApoE
KW - Enrichment
KW - Imaging biomarker
KW - Longitudinal
KW - Mild cognitive impairment
UR - http://www.scopus.com/inward/record.url?scp=84953336433&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84953336433&partnerID=8YFLogxK
U2 - 10.1016/j.neurobiolaging.2015.09.018
DO - 10.1016/j.neurobiolaging.2015.09.018
M3 - Article
C2 - 26545631
AN - SCOPUS:84953336433
VL - 37
SP - 26
EP - 37
JO - Neurobiology of Aging
JF - Neurobiology of Aging
SN - 0197-4580
ER -