TY - JOUR
T1 - Ventricular maps in 804 ADNI subjects
T2 - Correlations with CSF biomarkers and clinical decline
AU - Chou, Yi Yu
AU - Leporé, Natasha
AU - Saharan, Priyanka
AU - Madsen, Sarah K.
AU - Hua, Xue
AU - Jack, Clifford R.
AU - Shaw, Leslie M.
AU - Trojanowski, John Q.
AU - Weiner, Michael W.
AU - Toga, Arthur W.
AU - Thompson, Paul M.
N1 - Funding Information:
Data collection and sharing for this project was funded by the ADNI ( National Institutes of Health , Grant U01 AG024904 ). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Abbott, AstraZeneca AB, Bayer Schering Pharma AG, Bristol-Myers Squibb, Eisai Global Clinical Development, Elan Corporation, Genentech, GE Healthcare, GlaxoSmithKline, Innogenetics, Johnson and Johnson, Eli Lilly, and Co, Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer, Inc., F. Hoffman-La Roche, Schering-Plough, Synarc, Inc., and Wyeth, as well as nonprofit partners the Alzheimer's Association and Alzheimer's Drug Discovery Foundation, with participation from the US Food and Drug Administration. Private sector contributions to ADNI are facilitated by the Foundation for the National Institutes of Health ( http://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 of Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 , K01 AG030514 , and the Dana Foundation .
PY - 2010/8
Y1 - 2010/8
N2 - Ideal biomarkers of Alzheimer's disease (AD) should correlate with accepted measures of pathology in the cerebrospinal fluid (CSF); they should also correlate with, or predict, future clinical decline, and should be readily measured in hundreds to thousands of subjects. Here we explored the utility of automated 3D maps of the lateral ventricles as a possible biomarker of AD. We used our multi-atlas fluid image alignment (MAFIA) method, to compute ventricular models automatically, without user intervention, from 804 brain MRI scans with 184 AD, 391 mild cognitive impairment (MCI), and 229 healthy elderly controls (446 men, 338 women; age: 75.50 ± 6.81 [SD] years). Radial expansion of the ventricles, computed pointwise, was strongly correlated with current cognition, depression ratings, Hachinski Ischemic scores, language scores, and with future clinical decline after controlling for any effects of age, gender, and educational level. In statistical maps ranked by effect sizes, ventricular differences were highly correlated with CSF measures of Aβ1-42, and correlated with ApoE4 genotype. These statistical maps are highly automated, and offer a promising biomarker of AD for large-scale studies.
AB - Ideal biomarkers of Alzheimer's disease (AD) should correlate with accepted measures of pathology in the cerebrospinal fluid (CSF); they should also correlate with, or predict, future clinical decline, and should be readily measured in hundreds to thousands of subjects. Here we explored the utility of automated 3D maps of the lateral ventricles as a possible biomarker of AD. We used our multi-atlas fluid image alignment (MAFIA) method, to compute ventricular models automatically, without user intervention, from 804 brain MRI scans with 184 AD, 391 mild cognitive impairment (MCI), and 229 healthy elderly controls (446 men, 338 women; age: 75.50 ± 6.81 [SD] years). Radial expansion of the ventricles, computed pointwise, was strongly correlated with current cognition, depression ratings, Hachinski Ischemic scores, language scores, and with future clinical decline after controlling for any effects of age, gender, and educational level. In statistical maps ranked by effect sizes, ventricular differences were highly correlated with CSF measures of Aβ1-42, and correlated with ApoE4 genotype. These statistical maps are highly automated, and offer a promising biomarker of AD for large-scale studies.
KW - Alzheimer's disease
KW - Biomarkers
KW - Lateral ventricles
KW - Magnetic resonance imaging
KW - Neuroimaging
UR - http://www.scopus.com/inward/record.url?scp=77954025033&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77954025033&partnerID=8YFLogxK
U2 - 10.1016/j.neurobiolaging.2010.05.001
DO - 10.1016/j.neurobiolaging.2010.05.001
M3 - Article
C2 - 20620663
AN - SCOPUS:77954025033
SN - 0197-4580
VL - 31
SP - 1386
EP - 1400
JO - Neurobiology of aging
JF - Neurobiology of aging
IS - 8
ER -