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WORLD WIDE ADNI BOSTON
INTRODUCTION
Michael Weiner
Michael W. Weiner, M.D.
Disclosures Scientific Advisory Boards Honoraria ADNI Support
Pfizer Pfizer
BOLT Inter-national Tohoku University Abbott
Danone Trading, BV Alzheimer’s Association
Consulting Alzheimer’s Drug Discovery Foundation
Pfizer Commercial Research Support Anonymous Foundation
Janssen Merck Innogenetics
KLJ Associates Avid Wyeth
Easton Associates Schering Plough
Harvard University Stock Options Roche
inThought Elan
B&N Associates, LLC Synarc Bayer Healthcare
INC Research, Inc. BioClinica, Inc. (ADNI2)
University of California, Los Angeles Bristol-Myers Squibb
Alzheimer’s Drug Discovery Foundation Cure Alzheimer’s Fund
Eisai
Funding for Travel Elan
GeneNetwork Sciences
ADPD Pfizer
CTAD ANY Congres (Clinical Trials on Alzheimer’s Disease) GE Healthcare
University of California, Los Angeles GlaxoSmithKline
Travel eDreams, Inc. Pfizer, Inc.
Paul Sabatier University Novartis
Tohoku University Merck
Novartis Medpace
Neuroscience School of Advanced Studies (NSAS) Eli Lilly & Company
Danone Trading, BV Johnson & Johnson
MCI Group, France Astra Zeneca
University of California, San Diego; ADNI Genentech
Synarc
M. Weiner, P. Aisen, R. Petersen, C. Jack, W. Jagust, J.
Trojanowski, L. Shaw, A. Toga, L. Beckett, D. Harvey, M. Donohue,
R. Green, A. Saykin, J. Morris, N. Cairns, T. Sather, L. Thal (D)
John Hsiao, Neil Buckholz, Adam Schwartz
Private Partners Scientific Board (PPSB)
And Site PIs, Study Coordinators and over 1500 subjects enrolled
in 58 Sites in US and Canada
FUNDED BY NATIONAL INSTITUTE ON AGING
NIBIB,NIMH,NINR,NINDS,NCRR,NIDA and CIHR
ADNI: over 1500 subjects 2004-2017
Naturalistic study of AD progression
• 413 NORMAL
• 49 SMC+ 40?
• 565 L MCI
• 301 E MCI
• 323 AD
• longitudinal
• 57 sites
• Clinical, blood, LP
• Cognitive Tests
• MRI: multimodal
• FDG PET
• PIB PET
• Florbetapir PET
• Genetics, genomics
All data in public database:
UCLA/LONI/ADNI: No
embargo of data
EFFECTS OF APOE 4 ON
AMYLOID POSITIVITY
• AD patients with APOE4 are 99% likely to
be amyloid positive
• AD patients without APOE4 are much less
like to be amyloid positive
– Perhaps only 55-75% of APOE4 negative AD
subjects are amyloid positive
Hippocampal atrophy rate in Controls
multivariate regression model
R2=0.0372
Effect of Age on Rate of Hippocampal Atrophy in Controls by
Amyloid Positivity
Hip
poca
mpal
Atr
op
hy R
ate
(%/y
ear)
Age
Rates of regional atrophy in
subjects classified as β-amyloid (+)
or (-)
Philip Insel
Lm with reference region, sex and age as covariates, P-values for DX vs NL (all subjects in model)
ASL-CBF in NL, EMCI, LMCI and AD
Lm with reference region, sex and age as covariates, overall similar slopes between DX
Associations between ASL-CBF and Aβ in pre-hoc defined ROI
NL EMCI LMCI AD
Effects of Aβ on ASL-CBF within groups
Lm with reference region, sex and age as covariates, AV45 used as continuous predictor
Effects of Aβ on volume within groups
Lm with icv, sex and age as covariates, AV45 used as continuous predictor
Groups Region ES ASL ES VOL DiffES p
NL (N=51)
Entorhinal 0.23 0.06 -0.17 0.17
Hippocampus 0.01 0.07 0.06 0.63 Inferior parietal 0.18 0.24 0.05 0.58
Inferior temporal 0.32 0.01 -0.31 0.03 Posterior cingulate 0.15 0.04 -0.10 0.36
Precuneus 0.09 0.06 -0.03 0.82
EMCI
(N=65)
Entorhinal 0.27 0.14 -0.13 0.20 Hippocampus 0.21 0.29 0.07 0.50
Inferior parietal 0.11 0.15 0.04 0.70
Inferior temporal 0.14 0.04 -0.09 0.34
Posterior cingulate 0.17 0.06 -0.10 0.30
Precuneus 0.12 0.10 -0.01 0.90
LMCI
(N=41)
Entorhinal 0.28 0.48 0.20 0.12 Hippocampus 0.11 0.42 0.30 0.04
Inferior parietal 0.42 0.49 0.07 0.50
Inferior temporal 0.41 0.11 -0.30 0.03
Posterior cingulate 0.19 0.10 -0.09 0.46
Precuneus 0.18 0.26 0.08 0.57
Aβ has stronger effects on ASL-CBF than volume in inferior temporal cortex in NL and LMC
Comparing effects of Aβ pathology on ASL-CBF and volume
ASL-CBF, all groups compared to Aβ-negative NL
Volume, all groups compared to Aβ-negative NL
Groups Region ES ASL ES VOL Diff ES P
NL Aβ- (n=41) vs.
NL Aβ+ (n=10)
entorhinal 0.17 0.13 -0.04 0.67 hippocampus 0.01 0.08 0.07 0.51
inferior parietal 0.15 0.16 0.02 0.85 inferior temporal 0.25 0.04 -0.21 0.08
posterior cingulate 0.07 0.04 -0.03 0.77
precuneus 0.13 0.05 -0.09 0.47
NL Aβ- (n=41) vs.
EMCI Aβ+ (n=33)
entorhinal 0.10 0.09 -0.01 0.88
hippocampus 0.16 0.08 -0.08 0.41 inferior parietal 0.12 0.13 0.01 0.89
inferior temporal 0.28 0.02 -0.25 0.02 posterior cingulate 0.05 0.02 -0.03 0.77
precuneus 0.12 0.09 -0.03 0.73
NL Aβ- (n=41) vs.
LMCI Aβ+ (n=20)
entorhinal 0.14 0.47 0.34 0.01 hippocampus 0.12 0.53 0.41 0.00
inferior parietal 0.40 0.27 -0.13 0.23 inferior temporal 0.35 0.27 -0.08 0.39
posterior cingulate 0.04 0.01 -0.03 0.74 precuneus 0.16 0.06 -0.10 0.36
NL Aβ- (n=41) vs.
AD Aβ+ (n=20)
entorhinal 0.25 0.79 0.53 0.00
hippocampus 0.21 0.81 0.60 0.00 inferior parietal 0.36 0.46 0.10 0.37
inferior temporal 0.45 0.53 0.08 0.44 posterior cingulate 0.14 0.21 0.07 0.47
precuneus 0.37 0.20 -0.17 0.12
Aβ has different effects on ASL-CBF and volume during disease progression
Conclusions • Aβ pathology has strong effects on ASL-CFB
• Aβ effects ASL-CBF in all patient groups including normal controls
• Structural MRI of ERC and hippo is more sensitive than ASL-CBF to detect effects of Aβ-pathology in late disease stages
• ASL-CBF in some brain regions (inf temp ctx) may be more sensitive than structural MRI to detect early effects of Aβ-pathology
Aβ+ vs Aβ- classification accuracy
(10-fold cross validation)
18
Predictors ACC PPV NPV
Demographics 0.65±0.03 0.67±0.03 0.66±0.04
Demographics & ApoE 0.69±0.08 0.73±0.09 0.70±0.10
Demographics & sMRI* 0.79±0.05 0.81±0.06 0.80±0.07
Demographics & ASL-MRI* 0.75±0.11 0.76±0.12 0.78±0.10
Demographics & sMRI &
ApoE*
0.83±0.03 0.85±0.02 0.83±0.04
Demographics & ASL-MRI &
ApoE*
0.80±0.06 0.82±0.06 0.82±0.02
Effects of traumatic brain injury
(TBI) and post traumatic stress
disorder (PTSD) on Alzheimer's
disease (AD) in veterans using
imaging and biomarkers in the AD
Neuroimaging Initiative (ADNI)
Michael Weiner, MD
San Francisco VA Medical Center
University of California, San Francisco
EFFECTS OF TRAUMATIC BRAIN
INJURY AND PTSD ON AD IN
VIETNAM WAR VETERANS: ADNI
TWO GRANTS FROM THE DOD
• We have two grants from the DOD
– Effects of traumatic brain Injury and Post
traumatic stress disorder on AD in Vietnam
veterans using ADNI
– Effects of traumatic brain Injury and Post
traumatic stress disorder on AD in Vietnam
veterans with MCI using ADNI
– Total of 400 subjects in both grants together
Recruitment Effort
Effort
Call
Effort
Status of
673
Screens
Status
214
Consents
Status
123
Received
4,728
Brochures
Mailed
1,894
Subjects
Called
459
(68.2%)
Excluded
40 (18.7%)
Declined
27 (22.0%)
Excluded
589
(12.4%)
“YES”
302
(15.9%)
Decline
214
(31.8%)
Sent
Consent
51 (23.8%)
Waiting
96 (78%)
SCID CAPS
201 (4.3%)
“NO ”
673
(35.5%)
Screened
123
(57.5%)
Received
Enrollment Effort
Status of
96 SCID/CAPS
Cohort of
44 Referrals
Clinic of 44
Referrals
31 (32.3%) Failed
7 (15.9%)
TBI only
•Banner, N=2
•Rush, N=4
•Stanford, N=4
•UCSD, N=1
•UCSF, N=22
•URMC, N=7
•USC, N=3
•Wisconsin, N=1
21 (21.9%)
Scheduled
29 (65.9%)
PTSD only
44 (45.8%)
Referred to Clinic
8 (18.2%)
Both TBI & PTSD
DATA SHARING
• All ADNI raw and processed data is shared
on the internet with no embargo
• UCLA/LONI/ADNI under direction of Dr
Arthur Toga
• ADNI has resulted in 636 manuscripts, 329
of which are now published
• This unprecedented data sharing is a model
for future science
NA-ADNI
J-ADNI EADNI
WW-ADNI
A-ADNI
C-ADNI K-ADNI
T-ADNI
Arg-
ADNI
B-ADNI
I-ADNI
ADNI IS FUNDED BY NIA
These slides and much more at
ADNI-INFO.ORG
All data at
www.loni.ucla.edu/ADNI/
Current PPSB Partners
Private partners committed more than $45 million
to AD research through ADNI1 and ADNI2
ADCS/ADNI CLINICAL CORE ADCS Director Paul Aisen, M.D.
Clinical Operations
Director
Devon Gessert
Project Manager Tamie Sather, M.S
Project Coordinator Archana Balasubramanian,
Ph.D.
Data Manager Melissa Davis
Data Analyst Earlita Rattei
Data Analyst Edgar Alminar
Biostatistician Mike Donohue, Ph.D.
Medical and Safety
Co-Director
Rema Raman, Ph.D.
Medical and Safety
Co-Director
Adam Fleisher, M.D.
Medical and Safety
Manager
Curtis Taylor, Ph.D.
Medical and Safety
Operations
Kaye David
Medical and Safety
Operations
Ken Kim, M.S.
Administrative
Core Director
Deborah Tobias
Informatics Core
Director
Gustavo Jimenez
Informatics Mei Qui
Finance Director Jeremy Pizzola
Finance Manager Nancy Bastian
Finance Steve Stokes
Contracts Barbara Bartocci
Regulatory
Affairs Director
Kristin Woods
Regulatory
Affairs Specialist
Elizabeth Shaffer
Regulatory
Affairs Specialist
Ronelyn Chavez
Regulatory
Affairs Specialist
Debbie Stice
Sr. Clinical Trial
Comm & Recruit.
Jeffree Itrich
Clinical Trial
Comm & Recruit
Genny Mathews
ADCS IT Baoyuan Zhao
ADCS/ADNI CLINICAL CORE ADCS Director Paul Aisen, M.D.
Clinical Operations
Director
Devon Gessert
Project Manager Tamie Sather, M.S
Project Manager Jennifer Salazar
Project Coordinator Archana Balasubramanian,
Ph.D.
Data Manager Melissa Davis
Data Analyst Edgar Alminar
Biostatistician Mike Donohue, Ph.D.
Medical and Safety
Co-Director
Rema Raman, Ph.D.
Medical and Safety
Co-Director
Adam Fleisher, M.D.
Medical and Safety
Manager
Curtis Taylor, Ph.D.
Administrative
Core Director
Deborah Tobias
Informatics Core
Director
Gustavo Jimenez
Informatics Mei Qui
Finance Director Jeremy Pizzola
Finance Manager Nancy Bastian
Finance Steve Stokes
Contracts Barbara Bartocci
Regulatory
Affairs Director
Kristin Woods
Regulatory
Affairs Specialist
Elizabeth Shaffer
Regulatory
Affairs Specialist
Ronelyn Chavez
Sr. Clinical Trial
Comm & Recruit.
Jeffree Itrich
Clinical Trial
Comm & Recruit
Genny Mathews
ADCS IT Baoyuan Zhao
ADCS/ADNI CLINICAL CORE
Program Manager of
Monitor Group
Dianne Dalton
Lead Monitor Gina Camilo, M.D.
ADCS Clinical Monitor Ayse Kayali
Edwin Canas, B.S.
Janet Kastelan, M.A.
Karen Croot, B.A.
Lynda Nevarez
Lindsay Cotton, MPH
Melissa McThomas, B.A.
Pam Saunders, Ph.D.
Rebecca Jones, Ph.D.
Sarah Carr, M.S.
Site PI Study Coordinator (s)
Oregon Health and Science University Jeffrey Kaye, MD Raina Carter and Betty Lind
USC Lon Schneider, MD Mauricio Becerra
UCSD James Brewer, MD, PhD Helen Vanderswag, RN
U Mich Judith Heidebrink, MD Joanne Lord, BA, CCRC, LPN
Mayo Clinic, Rochester Ronald Petersen, MD, PhD Kris Johnson, RN
Baylor College of Medicine Rachelle Doody, MD, PhD Munir Chowdhury, MBBS, MS, CCRC
Columbia Yaakov Stern, PhD Philip Yeung
Washington University, St. Louis Beau Ances, MD, Ph.D Maria Carroll and Sue Leon
U Alabama, Birmingham Daniel Marson, JD, PhD Denise Ledlow, RN
Mount Sinai School of Medicine Hillel Grossman, MD Helene Geramian
Rush University Medical Center Leyla deToledo-Morrell, PhD Patricia Samuels
Wien Center Ranjan Duara, MD Maria Greig-Custo
Johns Hopkins University Marilyn Albert, PhD Daniel D’Agostino II
New York University Medical Center James Galvin, MD Dana Pogorelec
Duke University Medical Center P. Murali Doraiswamy, MBBS, MD Cammie Hellegers
U Penn Steven Arnold, MD Jessica Nunez-Lopez
U Kentucky Charles Smith, MD Barbara Martin
U Pitt Oscar Lopez, MD MaryAnn Oakley, MA
U Rochester Medical Center Anton Porsteinsson, MD Bonnie Goldstein
UC Irvine Ruth Mulnard, RN, DNSc Catherine McAdams-Ortiz, RN, MSN
U Texas, Southwestern MC Kyle Womack, MD Kristin Martin-Cook, MS
Emory University Allan Levey, MD, PhD Lavezza Zanders
U Kansas Jeffrey Burns, MD Becky Bothwell and Tim Welch
UCLA Liana Apostolova, MD Jennifer Eastman
Site PI Study Coordinator (s)
Mayo Clinic, Jacksonville Neill Graff-Radford, MD Tracy Kendall
Indiana University Martin Farlow, MD Scott Herring, RN and Cynthia
Hunt
Yale School of Medicine Christopher van Dyck, MD Martha MacAvoy
McGill University/Jewish Memory Clinic Howard Chertkow, MD Chris Hosein, Med
Sunnybrook Health Sciences, Ontario Sandra Black, MD Joanne Lawrence
U.B.C. Clinic for AD & Related, B.C. Robin Hsiung, MD Benita Mudge BSc
Cognitive Neurology - St. Joseph’s, Ontario Elizabeth Finger, MD Charlene Bartha
Cleveland Clinic Lou Ruvo Center for Brain Health Charles Bernick, MD Michelle Sholar, BA
Northwestern University Diana Kerwin, MD Kristine Lipowski
Medical University of South Carolina Jacobo Mintzer, MD Arthur Williams
Premiere Research Institute Carl Sadowsky, MD Teresa Villena, M.D. and Daisy
Acevedo
UCSF Howard Rosen, MD Jonathan Elofson
Georgetown University Brigid Reynolds, ANP Kelly Behan
Brigham and Women’s Hospital Gad Marshall, MD Jonathan Bruno
Stanford University Jerome Yesavage, MD Michael Nolasco
Sun Health/Arizona Consortium Marwan Sabbagh, MD Sherye Sirrel, MS
Boston University Neil Kowall, MD Meenakshi Chivukula
Howard University Thomas Obisesan, MD, MPH Saba Wolday
Case Western Reserve University Alan Lerner, MD Parianne Fatica and Susie Sami
UC Davis – Sacramento John Olichney, MD Katharine Vieira, RN,NP
Dent Neurologic Institute Horacio Capote, MD Michelle Rainka, PhD and
Kristin Surdam, CCRC
Site PI Study Coordinator
Parkwood Hospital Michael Borrie, MD Charlene Bartha
Nathan Kline Institute Nunzio Pomara, MD Vita Pomara
University of Wisconsin Sterling Johnson, PhD Sandra Harding
UC Irvine – BIC Steven Potkin, MD Ioana Popica
Banner Alzheimer’s Institute Adam Fleisher, MD Nadira Trncic
Ohio State University Douglas Scharre, MD Jennifer Icenhour
Albany Medical College Earl Zimmerman, MD Paula Malone
University of Iowa Susan Schultz, MD Karen Ekstam-Smith
Dartmouth-Hitchcock Medical Center Robert Santuli, MD Tamar Kitzmiller
Wake Forest University Health Sciences Kaycee Sink, MD, MS Leslie Gordineer
Rhode Island Hospital Brian Ott, MD Dana Ayoub
Weill Cornell Memory Disorders Program Norman Relkin, MD Erin Hibbard
Butler Hospital Memory and Aging Program Stephen Salloway, MD Morgan Brescia
University of South Florida, Tampa Amanda Smith, MD Jill Ardila
Publications 1) Mueller SG, Weiner MW, Thal LJ, Petersen RC, Jack CR, Jagust W, Trojanowski JQ, Toga
AW, Becket L: Ways toward an early diagnosis in Alzheimer's disease: The Alzheimer's
Disease Neuroimaging Initiative (ADNI), Alzheimer's Dementia, 1: 55-66, 2005.
2) Leow AD, Klunder AD, Jack CR, Jr., Toga AW, Dale AM, Bernstein MA, Britson PJ, Gunter
JL, Ward CP, Whitwell JL, Borowski BJ, Fleisher AS, Fox NC, Harvey D, Kornak J, Schuff
N, Studholme C, Alexander GE, Weiner MW, Thompson PM, for the ADNI Prepatory Phase
Study: Longitudinal stability of MRI for mapping brain change using tensor-based
morphometry. NeuroImage. 31: 627-640, 2006.
3) Tsolaki MN, Papaliagkas VT, Jones R, Touchon J, Spiru L, Visser PJ, Verhey F, and
DESCRIPA Study Group: Medication in patients with mild cognitive impairment in Europe:
The development of screening guidelines and clinical criteria of predementia Alzheimer's
disease (DESCRIPA) study. Alzheimer's and Dementia. 4: T683-T684, 2008.
4) Nestor SM, Rupsingh R, Borrie M, Smith M, Accomazzi V, Wells JL, Fogarty J, Bartha R,
and the ADNI: Ventricular enlargement as a possible measure of Alzheimer's disease
progression validated using the Alzheimer's disease neuroimaging initiative database. Brain
131: 2443-2454, 2008.
5) Mueller SG, Weiner MW, Thal LJ, Peterson RC, Jack C, Jagust W, Trojanowski JQ, Toga
AW, Beckett L: Alzheimer's Disease Neuroimaging Initiative. Advances in Alzheimer's and
Parkinson's Disease. 183-189, 2008.
6) Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Hua X,
Toga AW, Jack CR Jr, Weiner MW, Thompson PM, the Alzheimer’s Disease Neuroimaging
Initiative. Validation of a fully automated 3D hippocampal segmentation method using
subjects with Alzheimer’s disease mild cognitive impairment , and elderly controls.
Neuroimage, 43(1): 59-68, 2008.
7) Hua, X, Leow AD, parishak N, Lee S, Chiang MC, Toga AW, Jack CR, Weiner MW,
Thompson PM, and ADNI: Tensor-based morphometry as a neurimaging biomarker for
Alzheimer's disease: An MRI study of 676 AD, MCI, and normal subjects. Neuroimage. 43:
458-469, 2008.
8) Hua X, Leow AD, Lee S, Klunder AD, Toga AW, Lepore N, Chou YY, Brun C, Chiang MC,
Barysheva M, Jack CR, Berstein MA, Britson PJ, Ward CP, Whitewell JL, Borowski B,
Felsiher AS, Fox NC, Boyes RG, Barnes J, Harvey D, Kornak J, Schuff N, Boreta L,
Alexander GE, Weiner MW, Thompson PM, and ADNI: 3D characterization of brain atrophy
in Alzheimer's disease and mild cognitive impairment using tensore-based morphometry.
Neuroimage. 41: 19-34, 2008.
9) Gunter, JL, Borowski B, Britson P, Berstein M, Ward C, Felmlee J, Schuff N, Weiner M,
Jack C: Alzheimer's Disease Neuroimaging Initiative phantom and scanner longitudinal
performance. Alzheimer's and Dementia. 4: T370, 2008.
10) Fan Y, Batmanghelich N, Clark CM, Davatzikos C, and ADNI: Spatial patterns of brain
atrophy in MCI patients, identified via high-dimensional pattern classification, predict
subsequent cognitive decline. Neuroimage. 39: 1731-1743, 2008.
11) Vemuri P, Wiste HJ, Weigand SD, Shaw LM, Trojanowski JQ et al: MRI and CSF
biomarkers in normal, MCI, and AD subjects: Predicting future clinical change. Neurology,
73: 294-301, 2009.
12) Vemuri P, Lowe VJ, Weigand SD, Wiste HJ, Senjem ML, Knopman DS, Shiung MM, Gunter
JL, Boeve BF, Kemp BJ, Weiner M, Petersen RC, Jack Jr CR and the Alzheimer’s Disease
Neuroimaging Initiative: Serial MRI and CSF biomarkers in normal, MCI and AD. Brain,
132:1355-1365, 2009.
13) Shaw LM, Vanderstichele H, Knapnik-Czajka M, Clark CM, Aisen PS, Petersen RC,
Blennow K, Soares H, Simon A, Lewczuk P, Dean R, Siemers E, Potter W, Lee VMY,
Trojanowski JQ and the ADNI: Cerebrospinal fluid biomarker signature in Alzheimer's
Disease Neuroimaging Initiative subjects. Annals of Neurology. 65: 403-413, 2009.
14) Risacher SL, Saykin AJ, West JD, Shen L, Firpi HA, McDonald BC, and the Alzheimer’s
Disease Neuroimaging Initiative: Baseline MRI Predictors of Conversion from MCI to
Probable AD in the ADNI Cohort. Current Alzheimer Research, 6:347-361, 2009.
15) Querbes O, Aubry F, Pariente J, Lotterie J-A, Demonet JF, Duret V, Puel M, Berry I, Fort J-
C, Celsis P, ADNI: Early diagnosis of Alzheimer's disease using cortical thickness: impact of
cognitive reserve. BRAIN. 132: 2036-2047, 2009.
16) Qiu A, Fennema-Notestine C, Dale AM, Miller MI. Alzheimer's Disease Neuroimaging
Initiative. Regional shape abnormalities in mild cognitive impairment and Alzheimer's
disease. Neuroimage. 45(3):656-61, 2009.
17) Morra JH, Zhuwen T, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N,
Hua X, Toga AW, Jack CR, Schuff N, Weiner MW, Thompson PM, and ADNI: Automated
3D Mapping of Hippocampal Atrophy and its clinical correlates in 490 subjects with
Alzheimer's disease, mild cognitive impairment, and elderly controls. Neuroimage. 45: S3-
S15, 2009.
18) Morra JH, Zhuwen T, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N,
Hua X, Toga AW, Jack CR, Schuff N, Weiner MW, Thompson PM, and ADNI: Automated
3D Mapping of Hippocampal Atrophy and its clinical correlates in 400 subjects with
Alzheimer's disease, mild cognitive impairment, and elderly controls. Human Brain Mapping.
30: 2766-2788, 2009.
19) Morra JH, Tu Z, Apostolova LG, Green AE, Avedissian C, Madsen SK, Parikshak N, Toga
AW, Jack CR, Schuff N, Weiner MW, Thompson PM and the ADNI: Automated mapping of
hippocampal atrophy in 1-year repeat MRI data from 490 subjects with Alzheimer's disease,
mild cognitive impairment, and elderly controls. Neuroimage. 45: S3-15, 2009.
20) Misra C, Fan Y, Davatzikos C: Baseline and longitudinal patterns of brain atrophy in MCI
patients, and their use in prediction of short-term conversion to AD: Results from ADNI.
Neuroimage. 44: 1415-1422, 2009.
21) McEvoy L.K., Fennema-Notestine C., Cooper, J.C., Hagler, D. Jr., Holland, D., Karow D.S.,
Pung, C.J. Brewer J.B., Dale A.M. for the Alzheimer's Disease Neuroimaging Initiative.
Alzheimer's Disease: Quantitative structural neuroimaging for detection and prediction of
clinical and structural changes in mild cognitive impairment. Radiology, 251(1):195-205,
2009.
22) McDonald CR, McEvoy LK, Gharapetian L, Fennema-Notestine C, Hagler DJ, Holland D,
Koyama A, Brewer JB, Dale AM, for the Alzheimer’s Disease Neuroimaging Initiative:
Regional rates of neocortical atrophy from normal aging to early Alzheimer disease.
Neurology, 73: 457-465, 2009.
23) Leow AD, Yanovsky I, Parikshak N, Hua X, Lee S, Toga AW, Jack CR, Bernstein MA,
Britson PJ, Gunter JL, Ward CP, Borowski B, Shaw LM, Trojanowski JQ, Fleisher AS,
Harvey D, Kornak J, Schuff N, Alexander GE, Weiner MW, Thompson PM, and ADNI:
Alzheimer's Disease Neuroimaging Initiative: A one-year follow-up study using tensor-based
morphometry degenerative rates, biomarkers and cognition. Neuroimage. 45: 645-655, 2009.
24) Langbaum JBS, Chen K, Lee W, Reschke C, Bandy D, Fleisher AS, Alexander GE, Foster
NL, Weiner MW, Koeppe RA, Jagust WJ, Foster NL, Weiner MW, Koeppe RA, Jagust WJ,
Reiman EM, and ADNI: Categorical and correlational analyses of baseline fluodeoxyglucose
positron emission tomography images from the Alzheimer's Disease Neuroimaging Initiative
(ADNI). NeuroImage. 45: 1107-1116, 2009.
25) Kovacevic S, Rafii MS, Brewer BJ and the Alzheimer’s Disease Neuroimaging Initiative.
High-throughput, Fully-automated Volumetry for Prediction of MMSE and CDR Decline in
Mild Cognitive Impairment. Alzheimer Disease and Associated Disorders, 23(2):139-145,
2009.
26) King RD, George AT, Jeon T, Hynan LS, Youn TS, Kennedy DN, Dickerson B, and the
Alzheimer’s Disease Neuroimaging Initiative: Characterization of Atrophic Changes in the
Cerebral Cortex Using Fractal Dimensional Analysis. Brain Imaging and Behavior, 3:154-
166, 2009.
27) Joyner AH, Roddey CJ, Cinnamon SB, Bakken TE, Rimol LM et al: A Common MECP2
Haplotype Associates With Reduced Cortical Surface Area in Two Independent Populations.
PNAS, 106: 15483-15488, 2009.
28) Jagust, WJ, Landau, SM, Shaw, LM, Trojanowski, JQ, Koeppe RA, et al: Relationships
between biomarkers in aging and dementia. Neurology, 73: 1193-1199, 2009.
29) Huang A, Abugharbieh R, Tam R and ADNI, A Hybrid Geometric-Statistical Deformable
Model for Automated 3-D Segmentation in Brain MRI. IEEE, 56: 1838-1848, 2009.
30) Hua X, Lee S, Yanovsky I, Leow AD, Ho AJ et al: Optimizing Power to Track Brain
Degeneration in Alzheimer’s Disease and Mild Cognitive Impairment with Tensor-Based
Morphometry: An ADNI Study of 515 Subjects. Neuroimage, 48: 668-681, 2009.
31) Holland D, Brewer JB, Hagler DJ, Fenema-Nostestine C, Dale AM, and the ADNI:
Subregional neuroanatomical change as a biomarker for Alzheimer's disease. PNAS. 106:
20954-20959, 2009.
32) Hinrichs C, Sing V, Mukherjee L, Xu G, Chung MK, Johnson SC, and the Alzheimer’s
Disease Neuroimagin Initiative: Spatially augmented LP boosting for AD classification with
evaluations on the ADNI dataset. NeuroImage, 48:138-149, 2009.
33) Haense C, Herholz K, Jagust WJ, Heiss WD: Performance of FDG PET for detection of
Alzheimer’s disease in two independent multicentre samples (NEST-DD and ADNI).
Dement and Geriatric Cogn Disord, 28: 259-266, 2009.
34) Gunter JL, Berstein MA, Borowski BJ, Ward CP, Britson PJ, Felmlee JP, Schuff N, Weiner
MW, Jack CR: Measurement of MRI performance with the ADNI phantom. Meds. Phys. 36:
2193, 2009.
35) Fleisher AS, Donahue M, Chen K, Brewer JB, Aisen PS, the Alzheimer’s Disease
Neuroimaging Initiative: Applications of neuroimaging to disease-modification trials in
Alzheimer’s disease. Behavioural Neurology, 21:129-136, 2009.
36) Fjell AM, Walhovd KB, Fennema-Notestine C, McEvoy LK, Hagler DJ, Holland D, Brewer
JB, Dale AM: One-Year Brain Atrophy Evident in Healthy Aging. The Journal of
Neuroscience, 29(48):15223-15231, 2009.
37) Fennema-Notestine C, Hagler DJ, McEvoy LK, Fleisher AS, Wu EH, Karow DS, Dale AM,
and ADNI: Structural Biomarkers for precilnical and mild Alzheimer's disease. Human Brain
Mapping, 30: 3238-3253, 2009.
38) Cruchaga C, Kauwe JS, Bertelsen S, Nowotny P, Shah AR et al: SNPs in the regulatory
subunit of calcineurin are associated with CSF tau protein levels, brain mRNA levels.
Alzheimer’s and Dementia, 5: 471-472, 2009.
39) Chupin M, Gerardin E, Cuingnet R, Boutet C, Lemieux L, Lehericy S, Benal H, Garnero L,
Colliot O, and the ADNI: Fully automatic hippocampus segmentation and classification in
Alzheimer's disease and mild cognitive impairment applied on data from ADNI.
Hippocampus. 19: 579-587, 2009.
40) Chou YY, Lepore N, Avedissian C, Madsen SK, parishak N, Hua X, Shaw LM, Trojanowski
JQ, Weiner MW, Toga AW, Thompson PM, and ADNI: Mapping correlations between
ventricular expansion and CSF amyloid and tau biomarkers in 240 subjects with Alzheimer's
disease, mild cognitive impairment, and elderly controls. Neuroimage.46: 394-410, 2009.
41) Calvini P, Chincarini A, Gemme G, Penco MA, Squarcla S et al: Automatic analysis of
Medial Temporal Lobe atrophy from structural MRIs for the early assessment of Alzheimer
disease. Medical Physics, 36: 3737-3747, 2009.
42) Buerger K, Frisoni G, Uspenskaya O, Ewers M, Zetterberg H, Geroldi C, Binetti G,
Johannsen P, Rossini PM, Wahlund LO, Vellas B, Blennow K, Hampel H: Validation of
Alzheimer's disease CSF and plasma biological markers: The multicentre reliability study of
the pilot European Alzheimer's Disease Neuroimaging Initiative (E-ADNI). Experimental
Gerontology. 44: 579-585, 2009.
43) Brewer JB, Magda S, Airriess C, Smith ME: Fully-automated quantification of regional brain
volumes for improved detection of focal atrophy in Alzheimer disease. American J of
Neuroradiology. 3: 578-580. 2009.
44) Bauer CM, Jara H, Killiany R and ADNI: Whole brain T2 MRI across multiple scanners with
dual echo FSE: Applications to AD, MCI, and normal aging. Neuroimage 52: 508-514, 2009.
45) Acosta O, Bourgeat P, Zuluaga MA, Fripp J, Salvado O, Ourselin S, and ADNI: Automated
voxel-based 3D cortical thickness measurement in a combined Lagrangian-Eulerian PDE
approach using partial volume maps. Medical Image Analysis. 12: 730-743, 2009.
46) Zhang T, Davatzikos C: Optimally-Discriminative Voxel-Based Analysis. Lecture Notes in
Computer Science. 6362: 257-265, 2010.
47) Yushkevich PA, Avants BB, Das SR, Pluta J, Altinay M et al: Bias in estimation of
hippocampal atrophy using deformation-based morphometry arises from asymmetric global
mormalization: An illustration in ADNI 3 T MRI data. NeuroImage, 50: 434-445, 2010.
48) Yang W, Chen X, Hong X, and Huang X: ICA-Based automatic classification of magnetic
resonance images from ADNI data. Lecture Notes in Computer Science. 6330: 340-347,
2010.
49) Xu C, Wang Z, Fan M, Liu B, Song M, Zhen X, Jiang T, ADNI: Effects of BDNF val66met
polymorphism on brain metabolism. Molecular Neuroscience., 21: 802-807, 2010.
50) Wu X, Chen K, Yao L, Ayutyanont N, Langbaum JB, Fleisher A, Reschke C, Lee W, Liu X,
Alexander GE, Bandy D, Foster NL, Thompson PM, Harvey DJ, Weiner MW, Koeppe EM,
the ADNI: Assessing the reliability to detect cerebral hypometabolism in probable
Alzheimer's disease and amnestic mild cognitive impairment. Journal of Neuroscience
Methods. 192: 277-285, 2010.
51) Wolz R, Heckemann RA, Alijabar P, Hajnal JV, Hammers A, Lotjonen J, Rueckert D, and
the ADNI: Measurement of hippocampal atrophy using 4D graph-cut segmentation:
Application to ADNI. Neuroimage. 52: 109-118, 2010.
52) Wolz R, Aljabar P, Hajnal JV, Hammers A, Rueckert D, and the Alzheimer’s Disease
Neuroimaging Initiative: LEAP: Learning embeddings for atlas propogation. NeuroImage,
49:1316-1325, 2010.
53) Wolk DA, Dickerson BC, and the Alzheimer's Disease Neuroimaging Initiative:
Apolipoprotein E (APOE) genotype has dissociable effects on memory and attentional-
executive network fucntion in Alzheimer's disease. PNAS 107: 10256-10261, 2010.
54) Weiner MW, Aisen PS, Jack CR, Jagust WJ, Trojanowski JQ, Shaw L, Saykin AJ, Morris JC,
Cairns N, Beckett LA, Toga A, Green RC, Walter S, Soares H, Snyder P, Siemens E, Potter
W, Cole PE, Schmidt M, and the ADNI: The Alzhiemer's Disease Neurimaging Initiative:
Progress report and future plans. Alzheimer's & Dementia. 6: 202-211, 2010.
55) Wang H, Das S,Pluta J, Craige C, Altinay M, Avants B, Weiner M, Mueller S, Yushkevich P:
Standing on the shoulders of giants: Improving medical image segmentation via learning
based bias correction. Med Image Comput Assist Interv. 13: 105-112, 2010.
56) Walhovd, KB, Fjell AM, Dale AM, McEvoy LK, Brewer J, Karow DS, Salmon DP,
Fennema-Notestine C, the ADNI: Multi-modal imaging predicts memory performance in
normal aging and cognitive decline. Neurobiology of Aging. 31: 1107-1121, 2010.
57) Walhovd KB, Fjell AM, Brewer J, McEvoy LK, Fennema-Notestine C, Hagler DJ, Jennings
RG, Karow D, Dale AM, and the ADNI: Combining MRI, PET and CSF biomarkers in
diagnosis and prognosis of Alzheimer's disease. American Journal of Neuroradiology. 31:
347-354, 2010.
58) Vounou M, Nichols TE, Montana G, and the ADNI: Discovering genetic associations with
high-dimensional neuroimaging phenotypes: A sparse reduced-rank regression approach.
NeuroImage. 15: 1147-1159, 2010.
59) Trojanowski JQ, Vandeerstichele H, Korecka M, Clark CM, Aisen PS, Petersen RC, Blennow
K, Soares H, Simon A, Lewczuk P, Dean R, Siemers E, Potter WZ, Weiner MW, Jack CR,
Jagust W, Toga AW, Lee VM, Shaw LM, and the ADNI: Update on the biomarker core of the
Alzheimer's Disease Neuroimaging Initiative subjects. Alzheimer's & Dementia. 6: 230-238,
2010.
60) Tosun D, Schuff N, Truran-Sacrey D, Shaw LM, Trojanowski JQ, Aisen P, Peterson R,
Weiner MW, and the ADNI: Relations between brain tissue loss, CSF biomarkers, and the
APOE genetic profile: A longitudinal MRI study. Neurobiology of Aging. 31: 1340-1354,
2010.
61) Stonnington CM, Chu C, Kloppel S, Jack CR Jr, Ashburner J, Frackowiak RS, the ADNI:
Predicting clinical scores from magnetic resonance scans in Alzheimer’s disease.
Neuroimage, 51: 1405-1413, 2010.
62) Stein JL, Hua X, Morra JH, Lee S, Hibar DP, Ho AJ, Leow AD, Toga AW, Sul JH, Kang
HM, Eskin E, Saykin AJ, Shen L, Faroud T, Pankratz N, Huentelman MJ, Craig DW, Gerber
JD, Allen AN, Corneveaux JJ, Stephan DA, Webster J, DeChairo BM, Potkin SG, Jack CJ,
Jr., Weiner MW, Thompson PM, and the ADNI: Genome-wide analysis reveals novel genes
influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's
disease. Neuroimage. 51: 542-554, 2010.
63) Stein JL, Hua X, Lee S, Ho A, Leow AD, Toga AW, Saykin AJ, Shen L, Foroud T, Pankratz
N, Huentelman MJ, Craig DW, Gerber JD, Allen AN, Corneveaux JJ, DeChairo BM, Potkin
SG, Weiner MW, Thompson PM, ADNI: Voxelwise genome-wide association study
(vGWAS). Neuroimage, 15: 1160-1174, 2010.
64) Stein JL, Hibar DP, Madsen SK, Khamis M, McMahon KL, de Zubicaray GI, Hansel NK,
Montgomery GW, Matin NG, Wright MJ, Saykin AJ, Jack CR, Jr., Weiner MW, Toga AW,
Thompson PM: Discovery and replication of dopamine-related gene effects on caudate
volume in young and elderly populations (N=1198) using genome-wide search. Mol Psych.
16:927-937, 2011.
65) Shen L, Qi Y, Kim S, Nho K, Wan J, Risacher SL, Saykin AJ; ADNI. Sparse bayesian
learning for identifying imaging biomarkers in AD prediction. Med Image Comput Comput
Assist Interv. 2010a;13(Pt 3):611-8.
66) Shen L, Kim S, Risacher S, Nho K, Waminathan S et al: Whole Genome Association Study
of Brain-Wide Imaging Phenotypes for Identifying Quantitative Trait Loci in MCI and AD: A
Study of the ADNI Cohort. NeuroImage, 53: 1051-1063, 2010.
67) Schuff N, Woerner N, Boreta L, Kornfield T, Shaw LM, Trojanowski JQ, Thompson PM,
Jack CR, Weiner MW, the ADNI: MRI of hippocampal volume loss in early Alzheimer's
disease in relation to ApoE genotype and biomarkers. BRAIN. 132: 1067-1077, 2010.
68) Schott JM, Bartlett JW, Fox NC, Barnes J and the ADNI: Increased brain atrophy rates in
cognitively normal older adults with low cerebrospinal fluid Aβ1-42. Annals of Neurology.
68: 825-834, 2010.
69) Schott JM, Bartlett JW, Barnes J, Leung KK, Ourselin S, Fox NC; Alzheimer's Disease
Neuroimaging Initiative investigators. Reduced sample sizes for atrophy outcomes in
Alzheimer's disease trials: baseline adjustment. Neurobiol Aging. Aug; 31(8):1452-1462,
2010.
70) Schneider LS, Kennedy RE, Cutter GR and ADNI: Requiring an amyloid-β1-42 biomarker
for prodromal Alzheimer disease or mild cognitive impairment does not lead to more efficient
clinical trials. Alzheimer's and Dementia. 6: 367-377, 2010.
71) Saykin, AJ, Shen L, Foroud TM, Potkin SG, Swaminathan S, Kim S, Risacher SL, Kwangsik
N, Huentelman MJ, Craig DW, Thompson PM, Stein JL, Moore JH, Farrer LA, Green RC,
Bertram L, Jack CR, Weiner MW, and the ADNI: Alzheimer's Disease Neuroimaging
biomarkers as quatitative phenotypes: Genetics core aims, progress, and plans. Alzheimer's &
Dementia. 6: 265-273, 2010.
72) Salas-Gonzalez D, Gorriz JM, Ramirez J, Illan IA, Lopez M, Segovia F, Chaves R and
Padilla P: Feature selection using factor analysis for Alzheimer’s diagnosis using F-FDG PET
images. Medical Physics. 37: 6084-6095, 2010.
73) Rousseau F, ADNI: A non-local approach for image super-resolution using intermodality
priors. Med Image Anal. 14: 594-605, 2010.
74) Risacher, SL, Shen L, West JD, Kim S, McDonald BC, Beckett LA, Harvey DJ, Jack CR,
Weiner MW, Saykin AJ: Longitudinal MRI atrophy biomarkers: Relationship to conversion
in the ADNI cohort. Neurobiology of Aging. 31: 1401-1418, 2010.
75) Rimol LM, Agartz I, Djurovic S, Brown AA, Roddey JC et al: Sex-Dependent Association of
Common Variants of Microcephaly Genes with Brain Structure. PNAS, 107: 384-388, 2010.
76) Ott BR, Cohen RA, Gongvatana A, Okonkwo OC, Johanson CE, Stopa EG, Donahue JE,
Silverberg GD, and the ADNI: Brain ventricular volume and cerebrospinal fluid biomarkers
of Alzheimer's disease. Journal of Alzheimer's Disease. 20: 1387-2877, 2010.
77) Okonkwo OC, Alosco ML, Griffith HR, Mielke MM, Shaw LM, Trojanowski JQ, Tremont
G, ADNI: Cerebrospinal fluid abnormalities and rate of decline in everyday function across
the dementia spectrum. Archives of Neurology. 67: 688-696, 2010.
78) Okonkow OC, Alosco ML, Jerskey BA, Sweet LH, Orr BR, Tremont G, and the ADNI:
Cerebral atrophy, apolipoprotein E 4, and the rate of decline in everyday function among
patients with amnestic mild cognitive impairment. Alzheimer's & Dementia. 6: 404-411,
2010.
79) Nettiksimmons J, Harvey D, Brewer J, Carmichael O, DeCarli C, Jack CR, Petersen R, Shaw
LM, Trojanowski JQ, Weiner MW, Beckett L: Subtypes based on cerebrospinal fluid and
magnetic resonance imaging markers in normal elderly predict cognitive decline.
Neurobiology on Aging. 31: 1419-1428, 2010.
80) Murphy EA, Holland D, Donohue M, McEvoy LK, Hagler DJ, Dale AM, Brewer JB and the
ADNI: Six-Month atrophy in MTL structures is associated with subsequent memory decline
in elderly controls. NeuroImage. 53: 1310-1317, 2010.
81) McEvoy LK, Edland SD, Hollan D, Hagler DJ, Roddey JC, Fennema-Notestine C, Salmon
DP, Koyama AK, Aisen PS, Brewer JB, Dale AM, for the ADNI: Neuroimaging enrichment
strategy for secondary prevention trials in Alzheimer disease. Alz Dis & Assoc Dis. 24: 269-
277, 2010.
82) McDonald CR, Gharapetian L, McEvoy LK, Fennema-Notestine C, Hagler DJ Jr, Holland D,
Dale AM; Alzheimer's Disease Neuroimaging Initiative. Relationship between regional
atrophy rates and cognitive decline in mild cognitive impairment. Neurobiol Aging: 33:242-
253, 2012
83) Madsen SK, Ho AJ, Saharan PS, Toga AW, Jack CR, Weiner MW, Thompson PM, The
ADNI: 3D maps localize caudate nucleus atrophy in 400 Alzheimer's disease, mild cognitive
impairment, and healthy elderly subjects. Neurobiology of Aging. 31: 1312-1325, 2010.
84) Lötjönen JMP, Wolz R, Koikkalainen JR, Thurfjell L, Waldemar G, Soininen H, Rueckert D,
and the Alzheimer’s Disease Neuroimaging Initiative: Fast and robust multi-atlas
segmentation of brain magnetic resonance images. NeuroImage, 49:2352-2365, 2010.
85) Leung KK, Clarkson MJ, Bartlett JW, Clegg S, Jack CR, Weiner MW, Fox NC, Ourselin S,
and the Alzheimer’s Disease Neuroimaging Initiative: Robust atrophy rate measurement in
Alzheimer’s disease using multi-site serial MRI: Tissue-specific intensity normalization and
parameter selection. NeuroImage, 50: 516-523, 2010.
86) Leung KK, Barnes J, Ridgway GR, Bartlett JW, Clarkson MJ, Macdonald K, Schuff N, Fox
NC, Ourselin S, ADNI: Automated cross-sectional and longitudinal hippocampal volume
measurement in mild cognitive impairment and Alzheimer’s disease. Neuroimage, 51: 1345-
1359, 2010.
87) Lemoine B, Rayburn S, Benton R: Data fusion and feature selection for Alzheimer's disease.
Lec Notes in Comp Sci. 6334: 320-327, 2010.
88) Landau SM, Harvey D, Madison CM, Reiman EM, Foster NLS, Aisen PS, Petersen RC,
Shaw LM, Torjanowski JQ, Jack Jr. CR, Weiner MW, Jagust WJ, and the ADNI: Comparing
predictors of conversion and decline in mild cognitive impairment. Neurology. 75: 230,
2010.
89) Kruggel F, Turner J, Muftuler LT: Impact of scanner hardware and imaging protocol on
image quality and compartment volume precision in the ADNI cohort. NeuroImage, 49:
2123-2133, 2010.
90) Kohannim O, Hua X, Hibar DP, Lee S, Chou YY, Toga AW, Jack CR, Weiner MW,
Thompson PM, and the ADNI: Boosting power for clinical trials using classifiers based on
multiple biomarkers. Neurobiology of Aging. 31: 1429-1442, 2010.
91) King RD, Brown B, Hwang M, Jeon T, George AT, and the ADNI: Fractal dimension
analysis of the cortical ribbon in mild Alzheimer's disease. NeuroImage. 52: 471-479, 2010.
92) Kauwe JSS, Bertelson S, Cruchaga C, Abraham R, Hollingworth P, Harold D, Owen MJ,
Williams J, Lovestone S, Morris JC, Goate AM, and the ADNI: Suggestive synergy between
genetic variants in TF and HFE as risk factors for Alzheimer's disease. American Journal of
Medical Genetics. 153B: 955-959, 2010.
93) Kauwe JS, Cruchaga C, Bertelsen S, Mayo K, Latu W, Notwotny P, Hinrichs AL, Fagan AM,
Holtzman DM ADNI, Goate AM: Validating predicted biological effects of Alzheimer's
disease associated SNPs using CSF biomarker levels. J Alzheimers Dis., 21: 833-842, 2010.
94) Karow DS, McEvoy L, Fennema-Notestine C, Hagler DJ, Jennings RG, Brewer JB, Hoh CK,
Dale AM and the ADNI: Relative capability of MR imaging and FDG PET to depict changes
associated with prodromal and early Alzheimer disease. Radiology. 256:932-942, 2010
95) Jun G, Naj AC, Beecham GW, Wang LS, Buros J…. et al: Meta-Analysis confirms CR1,
CLU, and PICALM as Alzheimer’s disease risk loci and reveals interactions with APOE
genotypes. Arch Neurol. 67: 1473-1484, 2010.
96) Jagust WJ, Bandy D, Chen K, Foster NL, Landau SM, Mathis CA, Price JC, Reiman EM,
Skovronsky D, Koeppe RA, and the ADNI: The Alzhimer's Disease Neuroimaging Initiative
positron emission tomography core. Alzheimer's & Dementia. 6: 221-229, 2010.
97) Ito K, Ahadleh S, Corrigan B, French J, Fullerton T et al: Disease Progression Meta-Analysis
Model in Alzheimer’s Disease. Alz and Dement, 6: 39-53, 2010.
98) Huang S, Li J, Sun L, Ye J, Fleisher A, Wu T, Chen K, Reiman E, Alzheimer's Disease
Neuroimaging Initiative: Learning brain connectivity of Alzheimer's disease by sparse inverse
covariance estimation. Neuroimage, 50:935-949, 2010.
99) Hua X, Lee S, Hibar DP, Yanovsky I, Leow AD, Toga AW, Jack CR, Bernstein MA, Reiman
EM, Harvey DJ, Kornak J, Schuff N, Alexander GE, Weiner MW, Thompson PM, and the
ADNI: Mapping Alzheimer's disease progression in 1309 MRI scans: Power estimates for
different inter scan intervals. Neuroimage. 51: 63-75, 2010.
100)Hua X, Hibar DP, Lee S, Toga AW, Jack CR, Weiner MW, Thompson PM, and the ADNI:
Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans.
Neurobiology of Aging. 31: 1463-1480, 2010.
101)Hua X, Hibar DP, Lee S, Toga AW, Jack CR, Weiner MW, Thompson PM, and the ADNI:
Sex and age differences in atrophic rates: an ADNI study with n=1368 MRI scans.
Neurobiology of Aging. 31: 1463-1480, 2010.
102)Ho AJ, Stein JL, Hua X, Lee S, Hibar DP…. and the Alzheimer’s Disease Neuroimaging
Initiative: A commonly carried allele of the obesity-related FTO gene is associated with
reduced brain volume in the healthy elderly. PNAS. 107: 8404-8409, 2010.
103)Ho AJ, Raji CA, Becker JT, Lopez OL, Kuller LH, Hua X, Lee S, Hibar D, Dinov ID, Stein
JL, Jack CR, Weiner MW, Toga AW, Thompson PM, the Cardiovascular Health Study, and
the ADNI: Obesity is linked with lower brain volume in 700 AD and MCI patients.
Neurobiology of Aging. 31: 1326-1339, 2010.
104)Ho AJ, Hua X, Lee S, Leow A, Yanovsky I et al: Comparing 3 Tesla and 1.5 Tesla MRI for
Tracking Alzheimer’s Disease Progression with Tensor-Based Morphometry. Human Brain
Mapping, 31: 499-514, 2010.
105)Han M, Schellenberg G, and Wang L: Genome-wide association reveals genetic effects on
human Ab42 and τ protein levels in cerebrospinal fluids: a case control study. BMC
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106)Habeck C.G. Basics of Multivariate Analysis of Neuroimaging Data. J Vis Exp. (41). pii:
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107)Habeck C, Stern Y, ADNI: Multivariate data analysis for neuroimaging data: overview and
application to Alzheimer's disease. Cell Biochem Biophys. 58: 53-67, 2010.
108)Greene SJ, Killiany RJ, The ADNI: Subregions of the inferiro parietal lobule are affected in
the progression to Alzheimer's disease. Neurobiology of Aging. 31: 1304-1311, 2010.
109)Franke K, Ziegler G, Klöppel S, Gaser C, and the Alzheimer’s Disease Neuroimaging
Initiative: Estimating the age of healthy subjects from weighted MRI scans using kernel
methods: Exploring the influence of various parameters. NeuroImage,50: 883-892, 2010.
110)Fjell AM, Westlye LT, Espeseth T, Reinvang I, Dale AM, Holland D, Walhovd KB: Cortical
gray matter atrophy in healthy aging connot be explained by undetected incipient cognitive
disorders: A comment on Burgmans et al. Journal of Neuropsychology, 24: 258-263, 2010.
111)Fjell AM, Walhovd KB, Fennema-Notestine C, McEvoy LK, Hagler DJ et al: Brain atrophy
in healthy aging is related to CSF levels of Aβ1-42. Cerebral Cortex, 20: 2069-2079, 2010.
112)Fjell A, Walhovd KB, Fennema-Notestine C, McEvoy LK, Hagler DJ, Hollan D, Brewer JB,
Dale AM: CSF biomarkers in prediction of cerebral and clinical change in mild cognitive
impairment and Alzheimer’s disease: The Journal of Neuroscience, 30: 2088-2101, 2010.
113)Fan M, Liu B, Zhou Y, Zhen X, Xu C, Jiang T, and the ADNI: Cortical thickness is
associated with different apolipoprotein E genotypes in healthy elderly adults. Neuroscience
Letters. 479: 332-336, 2010.
114)Evans, MC, Barnes J, Nielsen C, Kim LG, Blair M, Leung KK, Douiri A, Boyes RG,
Ourselin S, Fox NC, and ADNI: Volume changes in Alzheimer’s disease and mild cognitive
impairment: Cognitive associations. Eur Radiol, 20: 674-682, 2010.
115)Evans MC, Barnes J, Nielson C, Kim, L Clegg SL et al: Volume changes in Alzheimer’s
disease and mild cognitive impairment: cognitive associations. Eur Radiol, 71: 441-447,
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116)Epstein NU, Saykin AJ, Riscacher SL, Gao S, Farlow MR, and the ADNI: Differences in
baseline medication use in the Alzheimer Disease Neuroimaging Study: Analysis of baseline
characteristics. Drugs Aging. 27: 677-686, 2010.
117)Epstein NU, Saykin AJ, Risacher SL, Gao S, Farlow MR; Alzheimer's Disease
Neuroimaging Initiative (ADNI). Differences in medication use in the Alzheimer's disease
neuroimaging initiative: analysis of baseline characteristics. Drugs Aging. 2010 Aug
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118)Desikan RS, Sabuncu MR, Schmansky NJ, Reuter M, Cabral HJ, Hess CP, Weiner MW,
Biffi A,Anderson CD, Rosand J, Salat DH, Kemper TL, Dale AM, Sperling RA, Fischl B;
Selective disruptive of the cerebral neocortex in Alzheimer's disease. Plos One. 2010.
119)De Meyer G, Shapior F, Vanderstichele H, Vanmechelen E, Engelborghs S, De Deyn PP,
Coart E, Hansson O, Minthon L, Zetterberg H, Blennow K, Shaw L, Trojanowski JQ, the
ADNI: Diagnosis-Independent Alzheimer disease biomarker signature in cognitively normal
elderly people. Archives of Neurology, 67: 949-956, 2010.
120)Cuingnet R, Gerardin E, Tessieras J, Auzias G, Lehericy S, Habert MO, Chupin M, Benali
H, Colliot O, and the ADNI: Automatic classification of patients with Alzheimer's disease
from structural MRI: A comparison of then methods using the ADNI database. Neuroimage.
56(2):766-781. 2010.
121)Cuingnet R, Chupin M, Benali H, Colliot O: Spatial prior in SVM-based classification of
brain images. SPIE. 7624: 76241L-76241L-9, 2010.
122)Cronk BB, Johnson DK, Burns JM, and the Alzheimer’s Disease Neuroimaging Initiative:
Body Mass Index and Cognitive Decline in Mild Cognitive Impairment. Alzheimer’s Disease
& Associated Disorders, 24: 126-130, 2010.
123)Chou YY, Lepore N, Saharan P, Madsen SK, Hua X, Jack CR, Shaw LM, Trojanowski JQ,
Weiner MW, Toga AW, Thompson PM, and the ADNI: Ventricular maps in 804 ADNI
subjects: Correlations with CSF biomarkers and clinical decline. Neurobiology of Aging. 31:
1386-1400, 2010.
124)Chiang GC, Insel PS, Tosun D, Schuff N, Truran-Sacrey D, Raptensetang ST, Jack CR,
Aisen PS, Petersen RC, Weiner MD, and the ADNI: Hippocampal atrophy rates and CSF
biomarkers in elderly APOE2 normals. Neurology. 75: 1976-1981, 2010.
125)Chen W, Song X, Zhang Y, Darvesh S, Ningnannan Z, D'Arcy R, Black S, Rockwood K: An
MRI-Based Semiquantitative Index for the Evaluation of Brain Atrophy and Lesions in
Alzheimer’s Disease, Mild Cognitive Impairment and Normal Aging. Dement. And Geri Cog
Disord. 30: 121-130, 2010.
126)Chen K, Langbaum JBS, Fleisher AS, Ayutyanot N, Rescke C, Lee W, Liu X, Bandy D,
Alexander GE, Thompson PM, Foster NL, Harvey DJ, deLeon MJ, Koeppe RA, Jagust WJ,
Weiner MW, Reiman EM, and ADNI: Twelve-month metabolic declines in probably
Alzheimer’s disease and amnestic mild cognitive impairment assessed using an empirically
pre-defined statistical region of interest: Findings from the Alzheimer’s Disease
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127)Chang YL, Jacobson MW, Fennema-Notestine C, Hagler DJ, Jennings RG et al: Level of
executive function influences verbal memory in amnestic mild congnitive impairment and
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128)Chang Y-L, Bondi MW, Fennema-Notestine C, McEvoy LK, Hagler DJ, Jacobson MW,
Dale AM, the Alzheimer’s Disease Neuroimaging Initiative: Brain substrates of learning and
retention in mild cognitive impairment diagnosis and progression to Alzheimer’s disease.
Neuropsychologia, 48: 1237-1247, 2010.
129)Casanova R, Wagner B, Whitlow CT, Williamson JD, Shumaker SA, Maldjian JA, Espeland
MA: High dimensional classification of structural MRI Alzheimer's disease data based on
large scale regularization. Frontiers in Neuroinformatics, 5:1-9, 2011.
130)Caroli A, Frisoni GB, The ADNI: The dynamics of Alzheimer's disease biomarkers in the
Alzheimer's Disease Neuroimaging Inititative cohort. Neurobiology of Aging. 31: 1263-1274,
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131)Carmicahel O, Schwarz C, Drucker D, Fletcher E, Harvey D, Beckett L, Jack CR, Weiner M,
DeCarli C, and the ADNI: Longitudinal changes in white matter disease and cognition in the
first year of the Alzheimer Disease Neuroimaging Initiative. Archives of Neurology. 67:
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132)Cairns NJ, Taylor-Reinwald L, Morris JC; Alzheimer's Disease Neuroimaging Initiative.
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133)Bossa M, Zacur E, Olmos S, Alzheimer's Disease Neuroimaging Initiative. Tensor-based
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134)Biffi A, Anderson CD, Desikan RS, Sabuncu M, Cortellini L, Schmansky N, Salat D, Rosan
J, for the ADNI: Genetic Variation and Neuroimaging Measures in Alzheimer disease.
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135)Beckett LA, Harvey DJ, Gamst A, Donohue M, Kornak J, Zhang H, Kuo JH; Alzheimer's
Disease Neuroimaging Initiative. The Alzheimer's Disease Neuroimaging Initiative: Annual
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136)Apostolova LG, Hwang KS, Andrawis JP, Green AE, Babakchanian S, Morra JH,
Cummings JL, Toga AW, Trojanowski JQ, Shaw LM, Jack CR, Petersen RC, Aisen PS,
Jagust WJ, Koeppe RA, Mathis CA, Weiner MW, Thompson PM, the ADNI: 3D PIB and
CSF biomarker associations with hippocampal atrophy in ADNI subjects. Neurobiology of
Aging. 31: 1284-1303, 2010.
137)Zhang T, Davatzikos C: ODVBA: Optimally-discriminiative voxel-based analysis. IEEE
Trans Med Imaging, 30:1441-1454, 2011.
138)Zhang N, Song X, Zhang Y, Chen W, D'Arcy RC, Darvesh S, Fisk JD, Rockwood K,
Alzheimer's Disease Neuroimaging Initiative: An MRI brain atrophy and lesion index to
assess the progression of structural changes in Alzheimer's disease, mild cognitive
impairment, and normal aging: A follow-up study. Journal of Alzheimer's Disease.
Supplement 3:359-367, 2011.
139)Yesavage JA, Noda A, Hernandez B, Friedman L, Cheng JJ, Tinkleberg JR, Hallmayer J,
O'hara R, David R, Robert P, Landsverk E, Zeitzer JM, the Alzheimer's Disease
Neuroimaging Initiative: Cicadian clock gene polymorphisms and sleep-wake disturbance in
Alzheimer's disease. American Journal of Geriatric Psychiatry, 19:635-643, 2011
140)Yang W, Lui RL, Gao JH, Chan TF, Yau ST, Sperling RA, Huang X: Independent
component analysis-based classification of Alzheimer's disease MRI data, Journal of
Alzheimer's Disease, 24:775-785, 2011
141)Wolz, Julkunen V, Koikkalainen J, Niskanen E, Zhang DP, Rueckert D, Soininen H,
Lotjonen J, Alzheimer's Disease Neuroimaging Initiative: Multi-method analysis of MRI
images in early diagnostics of Alzheimer's disease. PLoS One, 6:e25446, 2011.
142)Wolk DA, Dickerson BC, ADNI: Fractionating verbal episodic memory in Alzheimer's
disease. Neuroimage, 54:1530-1539, 2011
143)Westman E, Simmons A, Muehlboeck JS, Mecocci P, Vellas B, Tsolaki M, Kloszewska I,
Soininen H, Weiner MW, Lovestone S, Spenger C, Wahlund LO, for the AddNeuroMed
consortium and the Alzheimer's Disease Neuroimaging Initiative: AddNeuroMed and ADNI:
Similar patterns of Alzheimer's atrophy and automated MRI classifiation accuracy in Europe
and North America. Neuroimage, 58:818-828, 2011.
144)Wang H, Nie F, Huang H, Risacher SL, Ding C, Saykin AJ, Shen L. A new sparse multi-task
regression and feature selection method to identify brain imaging predictors for memory
performance. ICCV 2011: IEEE Conference on Computer Vision, November 6-13 2011,
Barcelona, Spain.
145)Vidoni ED, Townley RA, Honea RA, Burns JM; Alzheimer's Disease Neuroimaging
Initiative: Alzheimer disease biomarkers are associated with body mass index. Neurology,
77:1913-20, 2011.
146)Thomson WK, Holland D, the Alzheimer's Disease Neuroimaging Initiative: Bias in tensor
based morphometry Stat-ROI measures may result in unrealistic power estimates.
Neuroimage, 57:5-14, 2011.
147)Thompson WK, Hallmayer J, O'Hara R, Alzheimer's Disease Neuroimaging Initiative:
Design considerations for characterizing psychiatric trajectories across the lifespan:
Application to effects of APOE e4 on cerebral cortical thickness in Alzheimer's disease.
American Journal of Psychiatry, 168:894-903, 2011.
148)Swaminathan S, Shen L, Risacher SL, Yoker KK, West JD, Kim Sungeun, Nho K, Foroud T,
Inlow M, Potkin SG, Huentelman MJ, Craig DW, Jagust WJ, Koeppe RA, Mathis CA, Jack
CR Jr, Weiner MW, Sayking AJ, the Alzheimer's Disease Neuroimaging Initative (ADNI):
Amyloid pathway-based candidate gene analysis of [11C]PiB-PET in the Alzheimer's Disease
Neuroimaging Initiative (ADNI) cohort, Brain Imaging and Behavior. 6:1-15, 2011.
149)Stricker NH, Chang YL, Fennema-Notestine C, Delano-Wood L, Salmon DP, Bondi MW,
Dale AM, for the Alzheimer's Disease Neuroimaging Initiative: Distinct profiles of brain and
cognitive changes in the very old with Alzheimer disease. Neurology, 77:713-721, 2011.
150)Spiegel R, Berres M, Miserez AR, Monsch AU, the Alzheimer's Disease Neuroimaging
Initiative. Alzheimers Res Ther.3:9, 2011.
151)Spampinato MV, Rumboldt Z, Hosker RJ, Mintzer JE, Alzheimer's Disease Neuroimaging
Initiative: Apolipoprotein E and gray matter volume loss in patients with mild cognitive
impairment and Alzheimer disease. Radiology, 258:843-852, 2011.
152)Skup M, Zhu H, Wang Y, Giovanello KS, Lin JA, Shen D, Shi F, Gao W, Lin W, Fan Y,
Zhang H, the Alzheimer's Disease Neuroimaging Initiative: Sex differences in grey matter
atrophy patterns among AD and MCI patients: Results from ADNI. Neuroimage. 56:890-906,
2011.
153)Silver M, Montana G, Nichols TE, the ADNI: False positives in neuroimaging genetics using
voxel-based morphometry data. NeuroImage. 54: 992-1000, 2011.
154)Shen L, Kim S, Qi Y, Inlow M, Swaminathan S, Nho K, Wan J, Risacher S, Shaw L,
Trojanowski J, Weiner M, Saykin A, ADNI. Identifying neuroimaging and proteomic
biomarkers for MCI and AD via the elastic net. MBIA 2011: International Workshop on
Multimodal Brain Image Analysis (MBIA), Sept. 18, 2011, Toronto, Canada.
155)Shen KK, Fripp J, Mériaudeau F, Chételat G, Salvado O, Bourgeat P; The Alzheimer's
Disease Neuroimaging Initiative: Detecting global and local hippocampal shape changes in
Alzheimer's disease using statistical shape models. Neuroimage. 59:2155-2166, 2011.
156)Shaw LM, Vanderstichele H, Knapik-Czajka M, Figurski M, Coart E, Blennow K, Soares H,
Simon AJ, Lewczuk P, Dean RA, Siemers E, Potter W, Lee VM, Trojanowski JQ, the
Alzheimer's Disease Neuroimaging Initiative: Qualification of the analytical and clinical
performance of CSF biomarker analyses in ADNI. Acta Neuropathol. 5:597-609, 2011.
157)Schneider LS, Insel PS, Weiner MW and the ADNI: Treatment with Cholinesterase
inhibitors and memantine of patients in the Alzheimer's Disease Neuroimaging Initiative.
Arch Neuro. 68: 58-66, 2011.
158)Schmand B, Eikelenboom P, van Gool WA, the Alzheimer's Disease Neuroimaging
Initiative: Value of neuropsychological tests, neuroimaging, and biomarkers for diagnosing
Alzheimer's disease in younger and older age cohorts. Journal of the American Geriatric
Society, 59:1705-1710, 2011.
159)Rajagopalan P, Hua X, Toga AW, Jack CR Jr, Weiner MW, Thompson PM; Homocysteine
effects on brain volumes mapped in 732 elderly individuals. Neuroreport. 391-5, 2011.
160)Poulin SP, Dautoff R, Morris JC, Barrett LF, Dickerson BC, Alzheimer's Disease
Neuroimaging Initiative: Amygdala atrophy is prominent in early Alzheimer's disease and
relates to symptom severity. Psychiatry Res. 194:7-13, 2011
161)Pelaez-Coca M, Bossa M, Olmos S and the ADNI: Discrimination of AD and normal
subjects from MRI: Anatomical versus statistical regions. Neuroscience Letters. 487: 113-
117, 2011.
162)Park H, Seo J and the ADNI: Application of Multidimensional Scaling to Quantify Shape in
Alzheimer’s Disease and Its Correlation with Mini Mental State Examination: A Feasibility
Study. Journal of Neuroscience Methods. 15: 380-385, 2011.
163)Pachauri D, Hinrichs C, Chung M, Johnson S, Singh V: Topology based Kernels with
application to inference problems in Alzheimer's disease. IEEE Trans Med Imaging. 30:1760-
70, 2011.
164)Mattila J, Koikkalainen J, Virkki A, Simonsen A, van Gils M, Waldermar G, Soininen H,
Lotjonen J: A disease state fingerprint for evaluation of Alzheimer's disease. Journal of
Alzheimer's Disease, 27: 163-176.
165)Marshall GA, Olson LE, Frey MT, Maye J, Becker JA, Rentz DM, Sperling RA, Johnson
KA, Alzheimer's Disease Neuroimaging Initiative: Instrumental activities of daily living
impairment is associated with increased amyloid burden. Dementia and Geratric Cognitive
Disorders, 31:443-450, 2011.
166)Marshal GA, Rentz DM, Frey MT, Locascio JJ, Johnson KA, Sperling RA, Alzheimer's
Diease Neuroimaing Initiative: Executive function and instrumental activities of daily living
in mild cognitive impairment and Alzheimer's disease. Alzheimer's & Dementia, 7:300-308,
2011.
167)Markiewicz PJ, Matthews JC, Declerck J, Herholz K, for the Alzheimer's Disease
Neuroimaging Initiative. Verification of predicted robustness and accuracy of multivariate
analysis. Neuroimage, 56:1382-1385, 2011.
168)Lötjönen J, Wolz R, Koikkalainen J, Julkunen V, Thurfjell L, Lundqvist R, Waldemar G,
Soininen H, Rueckert D; The Alzheimer's Disease Neuroimaging Initiative: Fast and robust
extraction of hippocampus from MR images for diagnostics of Alzheimer’s disease.
Neuroimage. 56, 185-196, 2011.
169)Lopez M, Ramirez J, Gorriz JM, Alvarez I, Salas-Gonzalez D, Segovia F, Chaves R, Padilla
P, Gomez-Rio M, and the ADNI: Principal component analysis-based techniques and
supervised classification schemes for the early detection of Alzheimer’s disease.
Neurocomputing. 74: 1260-1271, 2011.
170)Lo RY, Hubbard AE, Shaw LM, Trojanowski JQ, Petersen RC, Aisen PS, Weiner MW,
Jagust WJ; Arch Neurol. Longitudinal Change of Biomarkers in Cognitive Decline. Epub
ahead of print, 2011.
171)Llano DA, Laforet G, Devanarayan V, ADNI: Derivation of a new ADAS-cog Composite
Using Tree-based Multivariate Analysis: Prediction of Conversion From Mild Cognitive
Impairment to Alzheimer Diseaes. Alz. Dis. Assoc. Disord. 25:73-84, 2011.
172)Li Y, Wang Y, Wu G, Shi F, Zhou L, Lin W, Shen D, The ADNI: Discriminant analysis of
longitudinal cortical thickness changes in Alzheimer's disease using dynamic and network
features. Neurobiology of Aging. 33:427.e15-30, 2011.
173)Leung KK, Barnes J, Modat M, Ridgway GR, Bartlett JW, Fox NC, Ourselin S, the ADNI:
Brain MAPS: An automated, accurate and robust brain extraction technique using a template
library. Neuroimage, 55:1091-1108, 2011.
174)Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM et al: Associations between
cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiology of
Aging, 32:1207-1218, 2011.
175)Koikkalainen J, Laotjaonen J, Thurfjell L, Rueckert D, Waldemar G, Soininen H, the
Alzheimer's Disease Neuroimaging Initiative. Multi-template tensor-based morphometry:
Application to analysis of Alzheimer's disease. Neuroimage, 56, 1134-1144, 2011.
176)Kim S, Swaminathan S, Shen L et al.: Genome-wide association study of CSF biomarkers
Ab1-42, t-tau, and p-tau181p in the ADNI cohort. Neurology. 76: 69-79, 2011.
177)Kauwe JSK, Cruchaga C, Karch CM, Sadler B, Lee M, Mayo K, Latu W, Su'a M, Fagan
AM, Holtman DM, Morris JC, ADNI, Goate AM: Fine mapping of genetic variants in BIN1,
CLU, CR1 and PICALM. Plos One. 6: e15918, 2011.
178)Illan IA, Gorriz JM, Ramirez J, Salas-Gonzalez D, Lopez MM, Segovia F, Chaves R,
Gomez-Rio M, Puntonet CG, the ADNI: 18F-FDG PET Imaging for computer aided
Alzheimer’s diagnosis. Information Sciences. 181: 903-916, 2011.
179)Hua X, Gutman B, Boyle CP, Rajagopalan P, Leow AD, Yanovsky I, Kumar AR, Toga AW,
Jack CR Jr., Schuff N, Alexander GE, Chen K, Reiman EM, Weiner MW, Thompson PM, the
Alzheimer's Disease Neuroimaging Initiative: Accurate measurement of brain changes in
longitudinal MRI scans using tensor-based morphometry. Neuroimage. 57:5-14, 2011.
180)Hu X, Pickering E, Liu YC, Hall S, Fournier H, Dechairo B, John S, Van Eerdewegh PV,
Soares H, the ADNI: Meta-analysis for Genome-wide association study identifies multiple
variants at the BIN1 locus associated with late-onset Alzheimer’s disease. PLOS ONe. 6:
e16616, 2011.
181)Holland D, Dales A and the ADNI: Nonlinear Registration of Longitudinal Images and
Measurement of Change in Regions of Interest. Medical Image Analysis.4:489-497, 2011.
182)Hinrichs C, Singh V, Xu G, Johnson SC, The ADNI: Predicitve markers for AD in a multi-
modality framework: An analysis of MCI progression in the ADNI population. Neuroimage.
55:574-589, 2010.
183)Hibar DP, Stein JL, Kohannim O, Jahanshad N, Saykin AJ, Shen L, Kim S, Pankratz N,
Foroud T, Huentelman MJ, Potkin SG, Jack CR Jr, Weiner MW, Toga AW, Thompson PM,
the Alzheimer’s Disease Neuroimaging initiative. Voxelwise gene-wide association study
(vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects.
Neuroimage. 56:1875-1891, 2011.
184)Herholz K, Westwood S, Haense C and Dunn G: Evaluation of a calibrated F-FDG PET
score as a biomarker for progression in Alzheimer disease and Mild Cognitive Impairment.
Journal of Nuclear Medicine, 52:1218-1226, 2011.
185)Heister D, Brewer JB, Magda S, Blennow K, McEvoy LK; For the Alzheimer's Disease
Neuroimaging Initiative: Predicting MCI outcome with clinically available MRI and CSF
biomarkers. Neurology, 77: 1619-1628
186)Heckemann RA, Keihaninejad S, Aljabar P, Gray KR, Neilsen C, Rueckert D, Hajnal JV,
Hammers A, the ADNI: Automatic morphometry in Alzheimer's disease and mild cognitive
impairment. Neuroimage. 56:2024-2037, 2011.
187)Greene SJ, Killiany RJ; The Alzheimer's Disease Neuroimaging Initiative: Hippocampal
Subregions are Differentially Affected in the Progression to Alzheimer's Disease.
Anatomical Record, 295(1):132-140, 2012.
188)Gray KR, Wolz R, Heckemann RA, Aljabara P, Hammers A, Rueckert D; for the
Alzheimer's Disease Neuroimaging Initiative: Multi-region analysis of longitudinal FDG-PET
for the classification of Alzheimer's disease. Neuroimage, 60:221-229, 2012
189)Gomar JJ, Bobes-Bascaran MT, Conejero-Goldberg C, Davies P, Goldberg TE; for the
Alzheimer's Disease Neuroimaging Initiative: Utility of combinations of biomarkers,
cognitive markers, and risk factors to predict conversion from mild cognitive impairment to
Alzheimer disease in patients in the Alzheimer's Disease Neuroimaging Initiative. Archives
of General Psychiatry, 68: 961-969, 2011.
190)Furney SJ, Simmons A, Breen G, Pedroso I, Lunnon K, Proitsi P, Hodges A, Powell J,
Wahlund LO, Loszewska I, Mecocci P, Soinnen H, Tsolaki M, Vellas B, Spenger C, Lathrop
M, Shen L, Kim S, Saykin AJ, Weiner MW, Lovestone S: Genome wide association with
MRI atrophy measures as a quantitative trait locus for Alzheimer’s disease. Molecular
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191)Filipovych R, Davatzikos C for the ADNI: Semi-supervised pattern classification of medical
images: Application to mild cognitive impairment (MCI). Neuroimage. 55:1109-1119, 2011.
192)Erten-Lyons D, Wilmot B, Anur P, McWeeney S, Westaway SK, Silbert L, Kramer P, Kaye
J: Microcephaly genes and risk of late onset Alzheimer Disease. Alzheimer Dis Assoc Disord.
25:276-282, 2011.
193)Dukart J, Schroeter ML, Mueller K, The Alzheimer's Disease Neuroimaging Initiative: Age
correction in dementia - Matching to a healthy brain. PLoS One, 6:e22193, 2011.
194)Dukart J, Mueller K, Horstmann A, Barthel H, Mooler HE, Villringer A, Sabri O, Schroeter
ML: Combined evaluation of FDG-PET and MRI improves detection and differentiation of
dementia.PLoS One, 6:e18111, 2011.
195)Donohue MC, Gamst AC, Thomas RG, Xu R, Beckett L, Petersen RC, Weiner MW, Aisen
P; for the Alzheimer's Disease Neuroimaging Initiative. The relative efficiency of time-to-
threshold and rate of change in longitudinal data. Contemp Clin Trials.32:685-693, 2011.
196)Dickerson BC, Wolk DA; the Alzheimer's Disease Neuroimaging Initiative. Dysexecutive
versus amnesic phenotypes of very mild Alzheimer's disease are associated with distinct
clinical, genetic and cortical thinning characteristics. J Neurol Neurosurg Psychiatry. 82:45-
51, 2011.
197)Dickerson BC, Wolk DA, the Alzheimer's Disease Neuroimaging Initiative: MRI cortical
thickness biomarker predicts AD-like CSF and cognitive decline in normal adults. Neurology,
78:84-90, 2012
198)Cuingnet R, Rosso C, Chupin M, Lehericy S, Dormont D, Bennal H, Samson Y, Colliot O:
Spatial regularization of SVM for the detection of diffusion alterations associated with stroke
outcome. Med Image Anal, 15(5):729-37, 2011.
199)Cui Y, Liu B, Luo S, Zhen X, Fan M, Liu T, Zhu W, Park M, Jiang T, Jin JS, the
Alzheimer's Disease Neuroimaging Initiative: Identification of conversion from mild
cognitive impairment to Alzheimer's disease using multivariate predictors. PLoS One,
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200)Cruchaga C, Nowotny P, Kauwe JS, Ridge PG, Mayo K, Bertelsen S, Hinrichs A, Fagan
AM, Holtzman DM, Morris JC, Goate AM; Alzheimer's Disease Neuroimaging Initiative:
Association and expression analyses with single-nucleotide polymorphisms in TOMM40 in
Alzheimer disease. Archives of Neurology. 68:1013-9, 2011.
201)Cover KS, van Schijndel RA, van Dijk BW, Redolfi A, Knol DL, Frisoni GB, Barkhof F,
Vrenken H, neuGRID, the Alzheimer's Disease Neuroimaging Initiative: Assessing the
reproducibility of the SienaX and Siena brain atrophy measures using the ADNI back-to-back
MP-Rage MRI scans. Psychiatry Res, 193:182-190, 2011.
202)Clark DG, for the Alzheimer's Disease Neuroimaging Initiative: Residual vectors for
Alzheimer disease diagnosis and prognostication. Brain and Behavior, 1:142-152, 2011.
203)Chincarini A, Bosco P, Calvini P, Gemme G, Esposito M, Oliveri C, Rei L, Squarcia S,
Rodriguez G, Bellotti R, Cerello P, De Mitri I, Retico A, Nobili F, The Alzheimer's Disease
Neuroimaging Initiative: Local MRI analysis approach in the diagnosis of early and
prodromal Alzheimer's disease. Neuroimage, 58:469-480, 2011.
204)Chen K, Ayutyanont N, Langbaum JB, Fleisher AS, Reschke C, Lee W, Liu X, Bandy D,
Alexander GE, Thompson PM, Shaw L, Trojanowski JQ, Jack CR Jr, Landau SM, Foster NL,
Harvey DJ, Weiner MW, Koeppe RA, Jagust WJ, Reiman EM; Alzheimer's Disease
Neuroimaging Initiative: Characterizing Alzheimer’s Disease Using a Hypometabolic
Convergence Index. Neuroimage, 56:52-60, 2011.
205)Chaing GC, Insel PS, Tosun D, Schuff N, Truran-Sacrey D, Raptentsetsang S, Jack CR Jr,
Weiner MW, Alzheimer's Disease Neuroimaging Initiative: Identifying cognitively healthy
elderly individuals with subsequent memory decline by using automated MR temporoparietal
volumes. Radiology, 259:844-851, 2011.
206)Cardoso MJ, Clarkson MJ, Ridgway GR, Modat M, Fox NC, Ourselin S, the Alzheimer's
Disease Neuroimaging Initiative: LoAd: A locally adaptive cortical segmentation algorithm.
Neuroimage. 56:1386-1397, 2011
207)Brown PJ, Devanand DP, Liu X, Caccappolo E, Alzheimer's Disease Neuroimaging
Initiative: Functional impairment in elderly patients with mild cognitive impairment and mild
Alzheimer disease. Arch Gen Psychiatry, 68:617-626, 2011.
208)Bossa M, Zacur E, Olmos S and the ADNI: Statistical analysis of relative pose information
of subcortical nuclei: Application on ADNI data. Neurimage.55:999-1008, 2011.
209)Bakken TE, Dale AM, Schork NJ: A geographic cline of skull and brain morphology among
individuals of European ancestry. Human Heredity, 72:35-44, 2011.
210)Antunez C, Boada M, Lopez-Arrieta J, Moreno-Rey C, Hernandez I, Marin J, Gayan J,
Alzheimer's Disease Neuroimaging Initiative, Gonzalez-Perez A, Real LM, Alegret M,
Tarraga L, Ramirez-Lorca R, Ruiz A: Genetic association of complement receptor 1
polymorphism rs3818361 in Alzheimer's disease. Alzheimer's Dementia, 7:e124-e129, 2011.
211)Antunez C, Boada M, Gonzalez-Perez A, Gayan J, Ramirez-Lorca R, Marin J, Hernandez I,
Moreno-Rey C, Moron FJ, Lopez-Arrieta J, Mauleon A, Rosende-Roca M, Noguera-Perea F,
Legaz-Garcia A, Vivancos-Moreau L, Velasco J, Carrasco JM, Alegret M, Antequera-Torres
M, Manzanares S, Romo A, Blanca I, Ruiz S, Espinosa A, Castano S, Garcia B, Martinez-
Herrada B, Vinyes G, Lafuente A, Becker JT, Galan JJ, Serrano-Rios M; The membrane-
spanning 4-domains, subfamily A (MS4A) gene cluster contains a common variant associated
with Alzheimer's Disease. Genome Med. 3:33, 2011.
212)Alexopoulos P, Guo LH, Kratzer M, Westerteicher C, Kurz A, Perneczky R: Impact of
SORL1 Single Nucleotide Polymorphisms on Alzheimer's Disease Cerebrospinal Fluid
Markers. Dementia and Geriatric Cognitive Disorders, 32:164-170
213)Aksu Y, Miller DJ, Kesidis G, Bigler DC, Yang QX: An MRI-Derived Definition of MCI-
to-AD Conversion for Long-Term, Automatic Prognosis of MCI Patients. PLoS one,
6:e25074, 2011.
214)Abdulkadir A, Mortamet B, Vemuri P, Jack CR Jr, Krueger G, Kloopel S, The Alzheimer's
Disease Neuroimaging Initiative: Effects of hardware heterogeneity on the performance of
SVM Alzheimer's disease classifier. Neuroimage, 58:785-792, 2011.
215)Rasmussen JM, Lakatos A, van Erp TG, Kruggel F, Keator DB, Fallon JT, Macciardi F,
Potkin SG; Alzheimer's Disease Neuroimaging Initiative: Empirical derivation of the
reference region for computing diagnostic sensitive (18)fluorodeoxyglucose ratios in
Alzheimer's disease based on the ADNI sample. Biochimica et Biophysica acta, 1822:457-
66, 2011
216)Padilla P, Gorriz J, Ramirez J, Salas-Gonzalez D, Illan I: NMF-SVM Based CAD Tool
Applied to Functional Brain Images for the Diagnosis of Alzheimer's Disease, IEEE Trans
Med Imaging. 31:207-16, 2011.
217)Murphy EA, Roddey JC, McEvoy LK, Holland D, Hagler DJ Jr, Dale AM, Brewer JB,
Alzheimer's Disease Neuroimaging Initiative: CETP polymorphisms associate with brain
structure, atrophy rate, and Alzheimer's disease risk in an APOE-dependent manner. Brain
Imaging Behavior, 6:16-26, 2012.
218)Leung KK, Ridgway GR, Ourselin S, Fox NC; The Alzheimer's Disease Neuroimaging
Initiative: Consistent multi-time-point brain atrophy estimation from the boundary shift
integral. Neuroimage, 59:3995-4005, 2012.
219)Chu C, Hsu AL, Chou KH, Bandettini P, Lin CP; for the Alzheimer's Disease Neuroimaging
Initiative: Does feature selection improve classification accuracy? Impact of sample size and
feature selection on classification using anatomical magnetic resonance images. Neuroimage,
60:59-70, 2011.
220)Cho Y, Seong JK, Jeong Y, Shin SY; for the Alzheimer's Disease Neuroimaging Initiative:
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a spatial frequency representation of cortical thickness data. Neuroimage. 59:2217-2230,
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ADNI: Nonlinear time course of brain volume loss in cognitively normal and impaired elders.
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2) Henley DB, Sundell KL, Sethuraman G, Siemers ER, Alzheimer's Disease Neuroimaging
Initiative: Safety profile of Alzheimer's disease populations in Alzheimer's Disease
Neuroimaging Initiative and other 18-month studies. Alzheimer's and Dementia, epub ahead
of print, 2011.
3) Wolz R, Aljabar P, Hajnal JV, Lotjonen J, Rueckert D, The Alzheimer's Disease
Neuroimaging Initiative: Nonlinear dimensionality reduction combining MR imaging with
non-imaging information. Medical Image Analysis, Epub ahead of print, 2011.
4) Wang H, Nie F, Huang H, Kim S, Nho K, Risacher SL, Sayking AJ, Shen L, for the
Alzheimer's Disease Neuroimaigng Initiative: Identifying quantitative trait loci via group-
sparse multi-task regression and feature selection: An imaging genetics study of the ADNI
cohort. Bioinformatics, 2011, in press.
5) Swaminathan S, Kim S, Shen L, Risacher SL, Foroud T, Pankratz N, Potkin SG, Huentelman
MJ, Craig DW, Weiner MW, Saykin AJ, and the Alzheimer's Disease Neuroimaging
Initiative: Genomic copy number analysis in Alzheimer's disease and MCI: An ADNI Study.
International Journal of Alzheimer's Disease, epub ahead of print, 2011.
6) Soininen H, Mattila J, Koikkalainen J, van Gils M, Hviid Simonsen A, Waldemar G,
Rueckert D, Thurfjell L, Lötjönen J: Software Tool for Improved Prediction of Alzheimer's
Disease. Neuro-degenerative diseases, Epub, 2011.
7) Schrag A, Schott JM; Alzheimer's Disease Neuroimaging Initiative: What is the clinically
relevant change on the ADAS-Cog? Journal of neurology, neurosurgey, and psychiatry,
Epub, 2011.
8) Schott JM, Adni Investigators. Using CSF biomarkers to replicate genetic associations in
Alzheimer's disease. Neurobiology of Aging, Epub ahead of print, 2011.
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the Alzheimer's Disease Neuroimaging Initiative: An improved model for disease progression
in subjects from Alzheimer's Disease Neuroimaging Initiative. Journal of Clinical
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Doody R, Diaz-Arrastia, for the Texas Alzheimer's Research & Care Consortium, for the
Alzheimer's Disease Neuroimaging Initiative: A blood-based screening tool for Alzheimer's
disease that spans serum and plasma: Findings from TARC and ADNI. PLoS One, epub
ahead of print, 2011.
11) Meda SA, Narayanan B, Liu J, Perrone-Bizzozero NI, Stevens MC, Calhoun VD, Glahn DC,
Shen L, Risacher SL, Saykin AJ, Pearlson GD: A large scale multivariate parallel ICA
method reveals novel imaging-genetic relationships for Alzheimer's disease in the ADNI
cohort. Neuroimage, Epub, 2012
12) Mackin RS, Insel P, Aisen PS, Geda YE, Weiner MW: Longitudinal stability of
subsyndromal symptoms of depression in individuals with mild cognitive impairment:
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Psychiatry, epub ahead of print, 2011.
13) Li X, Long X, Laurienti P, Wyatt C: Registration of images with varying topology using
embedded maps. IEEE Transactions in Medical Imaging. Epub ahead of print, 2011.
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Weiner MW, Bartzokis G, Thompson PM, and the Alzheimer's Disease Neuroimaging
Initiative: Depressive symptoms in mild cognitive impairment predict greater atrophy in
Alzheimer's disease-related regions. Biological Psychiatry, epub ahead of print.
15) Kamboh MI, Barmada MM, Demirci FY, Minster RL, Carrasquillo MM, Pankratz VS,
Younkin SG, Saykin AJ; The Alzheimer's Disease Neuroimaging Initiative, Sweet RA,
Feingold E, Dekosky ST, Lopez OL: Genome-wide association analysis of age-at-onset in
Alzheimer's disease. Molecular Psychiatry, Epub, 2011.
16) Holland D, McEvoy LK, Dale AM, the Alzheimer's Disease Neuroimaging Initiative:
Unbiased comparison of sample size estimates from longitudinal structural measures in
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17) De Jager PL, Shulman JM, Chibnik LB, Keenan BT, Raj T, Wilson RS, Yu L, Leurgans SE,
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Disease Neuroimaging Initiative, Rosand J, Daly MJ, Myers AJ, Reiman EM, Bennett DA,
Evans DA: A genome-wide scan for common variants affecting the rate of age-related
cognitive decline. Neurobiology of Aging, Epub, 2011.
18) Carmichael O, Xie J, Fletcher E, Singh B, Decarli C, Alzheimer's Disease Neuroimaging
Initiative: Localized hippocampus measures are associated with Alzheimer pathology and
cognition independent of total hippocampal volume. Neurobiology of Aging, epub ahead of
print, 2011
19) Bonner-Jackson A, Okonkwo O, Tremont G, and the Alzheimer's Disease Neuroimaging
Initiative: Apolipoprotein E e2 and functional decline in amnestic mild cognitive impairment
and Alzheimer disease. American Journal of Geriatric Psychiatry, epub ahead of print, 2011.
20) Jennings JR, Mendelson DN, Muldoon MF, Ryan CM, Gianaros PJ, Raz N, Aisenstein H:
Regional grey matter shrinks in hypertensive individuals despide successful lowering of
blood pressure. Journal of Human Hypertension, epub ahead of print, 2011.
21) Bakken TE, Roddey JC, Djurovic S, Akshoomoff N, Amaral DG, Bloss CS, Casey BJ, Chang
L, Ernst TM, Gruen JR, Jernigan TL, Kaufmann WE, Kenet T, Kennedy DN, Kuperman JM,
Murray SS, Sowell ER, Rimol LM, Mattingsdal M, Melle I, Agartz I, Andreassen OA,
Schork NJ, Dale AM; for the Alzheimer's Disease Neuroimaging Initiative; Pediatric
Imaging, Neurocognition, and Genetics Study: Association of common genetic variants in
GPCPD1 with scaling of visual cortical surface area in humans. Proceedings of the National
Academy of Sciences of the United States of America. Epub, 2012.
22) Caroli A, Prestia A, Chen K, Ayutyanont N, Landau SM, Madison CM, Haense C, Herholz
K, Nobili F, Reiman EM, Jagust WJ, Frisoni GB; and the EADC-PET Consortium, NEST-
DD, and Alzheimer's Disease Neuroimaging Initiative: Summary Metrics to Assess
Alzheimer Disease-Related Hypometabolic Pattern with 18F-FDG PET: Head-to-Head
Comparison. Journal of nuclear medicine. Epub, 2012.
23) Park H; the ADNI: ISOMAP induced manifold embedding and its application to Alzheimer's
disease and mild cognitive impairment. Neuroscience letters, Epub, 2012,
24) Schmand B, Eikelenboom P, van Gool WA: Value of Diagnostic tests to Predict Conversion
to Alzheimer's Disease in Young and Old Patients with Amnestic Mild Cognitive
Impairment. Journal of Alzheimer's Disease. Epub 2012
25) Reiner P, Jouvent E, Duchesnay E, Cuingnet R, Mangin JF, Chabriat H: Sulcal Span in
Azheimer's Disease, Amnestic Mild Cognitive Impairment, and Healthy Controls. Journal of
Alzheimer's Disease. Epub 2012.
1) Casanova R, Maldjian JA, Espeland MA, for the Alzheimer's Disease Neuroimaging
Initiative: Evaluating the impact of different factors on voxel-based classification methods of
ADNI structural MRI brain images. International Journal of Biomedical Data Mining, in
press.
2) Silver M, Montana G, and the Alzheiemer's Disease Neuroimaging Initiative: Fast
identification of biological pathways associated with a quantitative trait using group lasso
with overlaps.
3) Maldjian JA, Whitlow CT: Whither the Hippocampus? FDG PET Hippocampal
Hypometabolism in Alzheimer's Disease Revisited, American Journal of Neuroradiology, in
press 2012.
In press
1) Hubbard R et al. Estimating risk of progression to Alzheimer’s disease using decision trees
with an AUC-based split criterion. Submitted, 2009.
2) Jennings R et al. Longitudinal reductions in grey matter volume in successfully treated
hypertensives. Submitted, 2009.
3) Spampinato M et al. Correlation between Apolipoprotein ε Genotype and Regional Gray
Matter Volume Loss with Voxel-Based Morphometry: Two-year Follow-up in Patients with
Stable Mild Cognitive Impairment and Patients with Conversion from Mild Cognitive
Impairment to Alzheimer’s Disease. Submitted, 2009.
4) Saykin A et al. Baseline Medication Use in the Alzheimer’s Disease Neuroimaging Initiative:
Associated Variables and Potential Adverse Effects. Submitted, 2009.
5) Marshall G et al. Executive function and instrumental activities of daily living in MCI and
AD, Submitted, 2009.
6) Wu M et al. The Use Of Multiple Templates For Improved Automated Alignment Of
Geriatric Brain MRIs. Submitted, 2009.
7) Marzloff G et al. Improving PET/CT Imaging in Alzheimer’s Disease Studies. Journal of
Radiology. Submitted, 2009.
8) Saykin A et al. Neuroanatomical Substrates of Language Performance. Journal of the
International Neuropsychological Society. Submitted, 2009.
9) Ewers M, Walsh C, Trojanowski JQ, Shaw LM, Petersen RC, Jack CR, Jr, Bokde AWL,
Feldman H, Alexander G, Sheltens P, Vellas B, Dubois B, Hampel H, and the Alzheimer’s
Disease Neuroimaging Initiative (ADNI). Multi-modal biological marker based signature and
diagnosis of early Alzheimer’s disease. Submitted to Neurobiology of Aging, 2009.
10) Ewers, M., Faluyi, Y.O., Bennett, D., Trojanowski, J.Q., Shaw, L.M., Petersen, R.,
Fitzpatrick,A., Vellas, B., Buerger, K., Teipel, S.J., Hampel, H., and the Alzheimer’s Disease
Neuroimaging Initiative (ADNI). Body mass index associated with biological CSF markers of
core brain pathology in mild cognitive impairment and Alzheimer’s disease. Submitted to
Neurology, 2009.
11) Ahmet E et al. Mining MRI Image Data by discriminative methods for the diagnosis of
dementia. Submitted, 2009.
12) Friedman L et al. Circadian Clock Gene Polymorphisms and Sleep/Wake Disturbance in
Alzheimer's Disease. Submitted, 2009.
13) Chertkow H et al. Correlating Cortical thickness with cognitive and neuropsychiatric
symptoms in Alzheimer’s Disease. Submitted, 2009.
14) Schneider L et al. Cholinesterase Inhibitors and Memantine Use in the Alzheimer’s Disease
Neuroimaging Initiative (ADNI) Cohort. Submitted, 2009.
15) Okonkwo, O.C., Mielke, M.M., Griffith, H.R., Moghekar, A.R., O’Brien, R.J., Shaw, L.M.,
Trojanowski, J.Q., Albert, M.S. and the Alzheimer's Disease Neuroimaging Initiative.
Patterns of cerebrospinal fluid abnormality: Implications for prospective course and outcome
among persons with amnestic mild cognitive impairment. Neurol., Submitted, 2009.
16) Okonkwo O, et. al. Cerebral atrophy, Apolipoprotein E epsilon4, and rate of decline in
everyday function among patients with amnestic mild cognitive impairment. Submitted, 2009.
17) Carmichael O et al. Longitudinal Changes In White Matter Disease and Cognition in the First
Year of ADNI. Submitted, 2010.
18) Cuingnet R et al. Spatial prior in SVM-based classification of brain images. Submitted, 2010.
19) McDonald M et al. ABCA7 and BIN1 are susceptibility genes for Alzheimer’s disease.
Submitted, 2010.
20) Wang L-S et al. Genome-wide association reveals genetic effects on human A!42 and " CSF
levels. Submitted, 2010.
Submitted
20) Chiang G et al. Baseline automated MR volumetry predicts future memory decline in normal
elderly. Submitted, 2010.
21) Montana G et al. False positives in neuroimaging genetics using cluster-size inference.
Submitted, 2010.
22) Chertkow H et al. Nine Questions about normal aging of the human cortex: Insights gained
from the ADNI dataset. Submitted, 2010.
23) Kaneta T et al. Alzheimer’s disease clinical drug trials with longitudinal FDG PET: Can the
image processing improve the statistical process. Submitted, 2010.
24) Schuff N et al. Nonlinear time courses of the brain volume loss in cognitive normal and
impaired elderly. Submitted, 2010.
25) Swaminathan S et al. Genomic copy number analysis in Alzheimer’s disease and MCI: An
ADNI study. Submitted, 2010.
26) Thiele F et al. Metabolic heterogeneity in subjects with probable Alzheimer’s disease.
Submitted, 2010.
27) Wei C et al. An MRI-based Semiquantitative index for the evaluation of brain lesions in
normal aging and Alzheimer’s disease. Submitted, 2010.
28) Chiang G et al. Association between ApoE2 and higher CSF –amyloid: A cross-sectional
ADNI analysis. Submitted, 2010.
29) Chiang G et al. Cognitively normal ApoE2 carriers have slower rates of hippocampal atrophy
Submitted, 2010.
30) Bossa M et al. Statistical analysis of the subcortical nuclei pose information: application on
ADNI data. Submitted, 2010.
31) Paleaz-Coca, M et al. Feature section for discrimination of AD and normal subjects from
MRI images: anatomical versus statistical regions. Submitted, 2010.
32) Chiang, G et al. Accelerated 1-year hippocampal volume loss in normal elderly ApoE4
carriers may be explained by amyloid. Submitted, 2010.
33) Dickerson, B et al. Fractionating Memory in Alzheimer’s Disease. Submitted, 2010.
34) Nho, K et al. Automatic Prediction of MCI conversion to probable AD using baseline
structural MRI in the ADNI cohort. Submitted, 2010.
35) Fan, M et al. Two loci associated with late-onset Alzheimer’s disease identified by genome-
wide copy number variations. Submitted, 2010.
36) Furney, S et al. Genome wide association with MRI atrophy measures as a quantitative trait
locus for Alzheimer’s disease. Submitted, 2010.
37) Kim, S et al. Genome-wide association study of CSF biomarkers Ab1-42, t-tau, and p-tau181p in
the ADNI cohort. Submitted, 2010.
38) Gorriz, J et al. Principal component analysis-based techniques and supervised classification
schemes for the early detection of Alzheimer’s disease. Submitted, 2010.
39) Gorriz, J et al. F-FDG PET Imaging for computer aided Alzheimer’s diagnosis. Submitted,
2010.
41) Wang, Z et al. Effects of BDNF val66met polymorphism on brain metabolism. Submitted,
2010.
42) Brown, P et al. Specific types of functional deficits characterize elderly subjects with mild
cognitive impairment and mild Alzheimer’s disease. Submitted, 2010.
43) Gorriz, J et al. Improving the convergence rate in affine registration of tomography brain
images using histogram equalization. Submitted, 2010.
44) Gorriz, J et al. Feature selection using factor analysis for Alzheimer’s diagnosis using F-FDG
PET images. Submitted, 2010.
45) Wang, H et al. Standing on the shoulders of giants: Improving medical image segmentation
via learning based bias correction. Submitted, 2010.
46) McEvoy, L et al. Enhanced Predictive Prognosis of Mild Cognitive Impairment Outcome
using Baseline and Longitudinal Structural Neuroimaging Biomarkers. Submitted, 2010.
47) Zhen, X et al. Cortical thinning of default network indicates cognitive impairment in
Alzheimer's disease. Submitted, 2010.
48) McKay, C et al. Integrated Test Information. Submitted, 2010.
49) Chang, Y et al. Impacts of Restriction in Functional Ability Assessed by Clinical Dementia
Rating in Mild Cognitive Impairment. Submitted, 2010.
50) Jackson, B et al. Apolipoprotein ε2 and Functional Decline in Mild Cognitive Impairment and
Alzheimer’s Disease. Submitted, 2010.
51) Goldberg, T et al. Utility of Combinations of Biomarkers, Cognitive Markers, and Risk
Factors to Predict Conversion from MCI to AD and Magnitude of Functional Decline in
ADNI Subjects. Submitted, 2010.
52) Greene, S et al. Is it correct to correct for head size in volumetric MRI? Data from the ADNI.
Submitted, 2010.
53) Karow, D et al. Relative Ability of MRI and FDG-PET to Detect Changes Associated with
Prodromal and Early Alzheimer’s Disease. Submitted, 2010.
54) Park, H et al. Application of Multidimensional Scaling to Quantify Shape in Alzheimer’s
Disease and Its Correlation with Mini Mental State Examination: A Feasibility Study.
Submitted, 2010.
55) Desikan, R et al. Selective vulnerability of the cerebral neocortex in Alzheimer’s disease.
Submitted, 2010.
56) Cover, K et al. Assessing the reproducibility of the SienaX and Siena brain atrophy measures
using the ADNI MP-RAGE MRI scans. Submitted, 2010.
57) Yoo, B et al. Evaluation of Two Common Statistical Methods in Randomized Delayed-Start
Designs of Progressive Disease Clinical Trials. Submitted, 2010.
58) Chen, K et al. Characterizing Alzheimer’s Disease Using a Hypometabolic Convergence
Index. Submitted, 2010.
59) Stein, J et al. Discovery and replication of dopamine-related gene effects on caudate volume
in young and elderly populations (N=1198) using genome-wide search. Submitted, 2010.
60) Osario Suarez, R et al. Glucose metabolism in PIB positive brain regions. A complex
relationship. Submitted, 2010.
61) Benton, R et al. Data Fusion and Feature Selection for Alzheimer's Diagnosis. Submitted,
2010.
62) Benton, R et al. Exploitation of 3D Stereotactic Surface Projection for Automated
Classification of Alzheimer’s Disease according to Dementia Levels. Submitted, 2010.
63) Mackin, S et al. The Effect of Subsyndromal Symptoms of Depression on Disability for
Individuals with Mild Cognitive Impairment. Submitted, 2010.
64) Song, X et al. Evaluation of brain structural changes and the outcome in Alzheimer's disease
and normal aging: A follow-up study. Submitted, 2010.
65) Carmichael, O et al. Localized hippocampus markers change earlier in the Alzheimer
pathological cascade than total hippocampus volume does. Submitted, 2010.
66) Dickerson, B et al. Amygdala atrophy is prominent in early Alzheimer’s disease and relates to
symptom severity. Submitted, 2010.
67) Lyons, D et al. Microcephaly genes and risk of late onset Alzheimer Disease. Submitted,
2010.
68) Hua, X et al. Meta-analysis for Genome-wide association study identifies multiple variants at
the BIN1 locus associated with late-onset Alzheimer’s disease. Submitted, 2010.
69) Ruiz, A et al. Genetic association of CR1 polymorphism rs3818361 in Alzheimer’s disease.
Submitted, 2010.
70) Cardoso, M et al. LoAd: A locally adaptive cortical segmentation algorithm. Submitted, 2010.
71) Wang, H et al. On Multi-Atlas Based Segmentation. Submitted, 2010.
72) Bakken, T et al. A Geographic Cline of Skull and Brain Morphology Among Individuals of
European Ancestry. Submitted, 2010.
73) Leung, K et al. Automated brain extraction using a template library: a comparison of
methods. Submitted, 2010.
74) Schmand, B et al. Value of neuropsychological tests, neuroimaging, and biomarkers for
diagnosing Alzheimer’s disease in younger and older age cohorts. Submitted, 2010.
75) Schott, J et al. Increased rates of brain atrophy in healthy controls with low CSF Aβ1-42:
Evidence for prodromal Alzheimer’s disease. Submitted, 2010.
76) Spiegel, R et al. The Placebo Group Simulation Approach: Substituting Placebo Controls in
Long-term Alzheimer Prevention Trials. Submitted, 2010.
77) Tatsuoka, C et al. Predicting conversion from Mild Cognitive Impairment to Alzheimer’s
Disease using partially ordered models. Submitted, 2010.
78) Zhang, T et al. Optimally-Discriminative Voxel-Based Analysis. Submitted, 2010.
79) Markiewicz, P et al. Verification of predicted robustness and accuracy of multivariate
analysis. Submitted, 2010.
80) Kauwe, J et al. Fine mapping of SNPs in BIN1, CLU, CR1 and PICALM for association with
CSF biomarkers for Alzheimer’s disease. Submitted, 2010.
81) Stricker, N et al. Distinct Profiles of Brain and Behavioral Changes in the Very-Old with
Alzheimer’s Disease. Submitted, 2010.
82) Rogers, J et al. Simultaneous Modeling of Patient-level and Summary-level Data to Describe
Progression of Alzheimer’s Disease. Submitted, 2010.
83) Mackin, RS et al. Longitudinal Stability of Subsyndromal Symptoms of Depression in
Individuals with Mild Cognitive Impairment: Relationship to Conversion to Dementia at
Three Year Follow Up. Submitted, 2010.
84) Luis, R et al. High dimensional classification analysis of ADNI structural data using L2
penalized logistic regression. Submitted, 2010. 85) Schott, J et al. Using CSF biomarkers to replicate genetic associations in Alzheimer’s disease.
Submitted, 2010.
1) Weiner MW, Thal L, Jack C, Jagust W, Toga A, Beckett L, Peterson R: Alzheimer’s disease
neuroimaging initiative, Alzheimer’s Disease and Parkinson’s Diseases: Insights, Progress
and Perspectives 7th International Conference, Sorrento, Italy March 9-13, 2005.
2) Weiner MW, Thal L, Petersen R, Jagust W, Trojanowski J, Toga A, Beckett L, Jack C.:
Alzheimer’s disease neuroimaging initiative. Poster from 2nd Congress of the International
Society for Vascular Behavioural and Cognitive Disorders, Florence, Italy, June 8-12, 2005.
3) Weiner MW, Thal LJ, Petersen RC, Jack Jr. CR, Jagust W, Trojanowski JQ, Beckett LA.
Imaging biomarkers to monitor treatment effects for Alzheimer’s Disease trials: The
Alzheimer’s Disease Imaging Initiative. Alzheimer’s Association 10th International
Conference on Alzheimer’s Disease and Related Disorders. Madrid, Spain. 2(3 Suppl 1):
S311 (P2-254). July 15-20, 2006.
4) Weiner MW, Thal L, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A, Beckett
L, Stables L, Mueller S, Lorenzen P, Schuff N. MRI of Alzheimer’s and Parkinson’s: The
Alzheimer’s Disease Neuroimaging Initiative (ADNI-Info.Org). Neurodegenerative Dis,
4(Suppl 1):276, 832, 2007.
5) Gunter JL, Bernstein MA, Britson PJ, Felmlee JP, Schuff N, Weiner M, Jack CR.: MRI
system tracking and correction using the ADNI phantom. Alzheimer’s & Dementia, 3(3
Suppl 2):S109 P-038. Second Alzheimer’s Association International Conference on
Prevention of Dementia, Washington, DC. June 9-12, 2007.
6) Fletcher PT, Wang AY, Tasdizen T, Chen K, Jagust WJ, Koeppe RA, Reiman EM, Weiner
MW, Minoshima S, Foster NL.: Variability of Normal Cerebral Glucose Metabolism from the
Alzheimer’s Disease Neuroimaging Initiative (ADNI): Implication for Clinical Trials. Annals
of Neurology, 62(Suppl 11):S52-3. American Neurological Association 132nd Annual
Meeting, Washington, DC. October 7-10, 2007.
7) Chen K, Reiman EM, Alexander GE, Lee W, Reschke C, Smilovici O, Bandy D, Weiner
MW, Koeppe RA, Jagust WJ.: Six-month cerebral metabolic declines in Alzheimer’s Disease,
amnestic mild cognitive impairment and elderly normal control groups: Preliminary findings
from the Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia, 3(3 Suppl
2):S174 O1-04-05. Second Alzheimer’s Association International Conference on Prevention
of Dementia, Washington, DC. June 9-12, 2007.
8) Chen K, Reiman EM, Alexander GE, Smilovici O, Lee W, Reschke C, Bandy D, Foster NL,
Weiner MW, Koeppe RA, Jagust WJ.: The pattern and severity of FDG PET abnormalities in
Alzheimer’s Disease and amnestic mild cognitive impairment: Preliminary findings from the
Alzheimer’s Disease Neuroimaging Initiative. Alzheimer’s & Dementia, 3(3 Suppl 2):S103
P-024. Second Alzheimer’s Association International Conference on Prevention of
Dementia, Washington, DC. June 9-12, 2007.
9) Alexander GE, Chen K, Reiman EM, Aschenbrenner M, Merkley TL, Hanson KD, Dale AM,
Berstein MA, Kornak J, Schuff N, Fox NC, Thompson PM, Weiner MW, Jack CR Jr.:
Regional gray matter reductions in Alzheimer’s dementia and amnestic mild cognitive
impairment: Preliminary findings from the Alzheimer’s Disease Neuroimaging Initiative
using voxel-based morphomety. Alzheimer’s & Dementia, 3(3 Suppl 2):S102 P-020. Second
Alzheimer’s Association International Conference on Prevention of Dementia, Washington,
DC, June 9-12, 2007.
10) Weiner MW, Thal L, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A, Beckett
L.: The Alzheimer’s Disease Imaging Initiative: Progress report. Alzheimer’s & Dementia,
3(3 Suppl 2):S174 O1-04-04. Second Alzheimer’s Association International Conference on
Prevention of Dementia, Washington, DC. June 9-12, 2007.
Abstracts
11) Weiner MW, Aisen P, Petersen R, Jack C, Jagust W, Trojanowski J, Shaw L, Toga A,
Beckett L, Gamst A. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Progress Report.
11th International Conference on Alzheimer’s Disease, Chicago, IL, 2008.
12) Weiner MW. Alzheimer’s Disease Neuroimaging Initiative (ADNI): Progress Report. S1-01-
01, Page T99, 11th International Conference on Alzheimer’s Disease and Related Disorders,
Chicago, IL, 2008.
13) Reiman EM, Chen K, Ayutyanont N, Lee W, Bandy D, Reschke C, Alexander GE, Weiner
MW, Koeppe RA, Foster NL, Jagust WJ. Twelve-Month Cerebral Metabolic Declines in
Probable Alzheimer’s Disease and Amnestic Mild Cognitive Impairment: Preliminary
Findings From the Alzheimer’s Disease Neuroimaging Initiative (ADNI), 11th International
Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
14) Schuff N, Woerner N, Boreta L, Kornfield T, Jack Jr. CR, Weiner MW. Rate of Hippocampal
Atrophy in the Alzheimer’s Disease Neuroimaging Initiative (ADNI): Effects of ApoE4 and
Value of Additional MRI Scans. O3-03-06, Page T164, 11th International Conference on
Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
15) Donohue M, Aisen P, Gamst A, Weiner M. Using the Alzheimer’s Disease Neuroimaging
Initiative (ADNI) Data to Improve Power For Clinical Trials, 11th International Conference
on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
16) Alexander GE, Hanson KD, Chen K, Reiman EM, Bernstein MA, Kornak J, Schuff NW, Fox
NC, Thompson PM, Weiner MW, Jack CR. Six-Month MRI Gray Matter Declines in
Alzheimer Dementia Evaluated by Voxel-Based Morphometry with Multivariate Network
Analysis: Preliminary Findings from the Alzheimer’s Disease Neuroimaging Initiative
(ADNI). IC-03-06, Page T8, & P1-216, Page T273, 11th International Conference on
Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
17) Landau SM, Madison C, Wu D, Cheung C, Foster N, Reiman E, Koeppe R, Weiner M, Jagust
WJ. Pinpointing Change in Alzheimer’s Disease: Longitudinal FDG-PET Analysis From the
Alzheimer’s Disease Neuroimaging Initiative (ADNI). PI-258, Page T291, 11th International
Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
18) Landau SM, Madison C, Wu D, Cheung C, Foster N, Reiman E, Koeppe R, Weiner M, Jagust
WJ. Pinpointing Change in Alzheimer’s Disease: Longitudinal FDG-PET Analysis From the
Alzheimer’s Disease Neuroimaging Initiative (ADNI). PI-258, Page T291, 11th International
Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
19) Gunter JL, Borowski B, Bernstein M, Ward C, Britson P, Felmlee J, Schuff N, Weiner M,
Jack C. Systematics of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Phantom.
P2-011, Page T369, 11th International Conference on Alzheimer’s Disease and Related
Disorders, Chicago, IL, 2008.
20) Gunter JL, Borowski B, Britson P, Bernstein M, Ward C, Felmlee J, Schuff N, Weiner M,
Jack C. Alzheimer’s Disease Neuroimaging Initiative (ADNI) Phantom and Scanner
Longitudinal Performance. P2-012, Page T370, 11th International Conference on Alzheimer’s
Disease and Related Disorders, Chicago, IL, 2008.
21) Lee W, Langbaum JBS, Chen K, Recshke C, Bandy D, Alexander GE, Foster NL, Weiner
MW, Koeppe RA, Jagust WJ, Reiman EM. Categorical and Correlational Analyses of
Baseline Fluorodeoxyglucose Positron Emission Tomography Images from the Alzheimer’s
Disease Neuroimaging Initiative (ADNI). IC-P1-036, Page T23 & P2-037, Page T379, 11th
International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
22) Petersen RC, Aisen P, Beckett L, Donohue M, Weng Q, Salmon D, Weiner M. Alzheimer’s
Disease Neuroimaging Initiative (ADNI): Baseline Characteristics. P3-040, Page T528, 11th
International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
23) Gunter JL, Borowski B, Britson P, Bernstein M, Ward C, Felmlee J, Schuff N, Weiner M,
Jack CR, the Alzheimer’s Disease Neuroimaging Initiative. ADNI Phantom & Scanner
Longitudinal Performance. IC-P3-181, Page T80, 11th International Conference on
Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
24) Schuff N, Woerner N, Boreta L, Kornfield T, Jack Jr. CR, Weiner MW. Rate of
Hippocampal Atrophy in the Alzheimer’s Disease Neuroimaging Initiative (ADNI): Effects
of APOE4 and Value of Additional MRI Scans. IC-P3-213, Page T91, 11th International
Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
25) Vanderstichele H, De Meyer G, Shapiro F, Engelborghs B, DeDeyn PP, Shaw LM, and
Trojanowski JQ. Alzheimer’s disease biomarkers: From concept to clinical utility. In:
Biomarkers For Early Diagnosis Of Alzheimer’s Disease, D. Galimberti, E. Scarpini (Eds.),
Nova Science Publishers, Inc., Hauppauge, NY, pp. 81-122, 2008.
26) Chen K, Reschke C, Lee W, Bandy D, Foster NL, Weiner MW, Koeppe RA, Jagust WJ,
Reiman EM. The Pattern of Cerebral Hypometablism in Amnestic Mild Cognitive
Impairment and Its Relationship to Subsequent Conversion to Probable Alzheimer’s Disease:
Preliminary Findings from the Alzheimer’s Disease Neuroimaging Initiative. IC-P2-086,
Page T42, 11th International Conference on Alzheimer’s Disease and Related Disorders,
Chicago, IL, 2008.
27) Reiman EM, Chen K, Ayutyanont N, Lee W, Bandy D, Reschke C, Alexander GE, Weiner
MW, Koeppe RA, Foster NL, Jagust WJ. Twelve-Month Cerebral Metabolic Declines in
Probable Alzheimer’s Disease and Amnestic Mild Cognitive Impairment: Preliminary
Findings from the Alzheimer’s Disease Neuroimaging Initiative. IC-P2-128, Page T58, 11th
International Conference on Alzheimer’s Disease and Related Disorders, Chicago, IL, 2008.
28) Posner H, Cano S, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S,
Hobart J. The ADAS-cog’s Performance as a Measure - Lessons from the ADNI Study: Part
1 – Evaluation Using Traditional Psychometric Methods. AAN 61st Annual Meeting, Seattle,
WA, April 25-May 2, 2009.
29) Hobart J, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S,
Cano S. The ADAS-cog’s Performance as a Measure – Lessons from the ADNI Study: Part 3
– Do the Scale Modifications Add Value? AAN 61st Annual Meeting, Seattle, WA, April 25-
May 2, 2009.
30) Apostolova LG, Green AE, Hwang K, Morra JH, Cummings JL, Toga AW, Jack CR, Weiner
MW, Thompson PM. Mapping correlations between serum Abeta and tau and hippocampal
atrophy measures in 282 ADNI subjects. AAN 61st Annual Meeting, Seattle, WA, April 25-
May 2, 2009.
31) Tosun D, Schuff N, Raptentsetsang S, Truran-Sacrey D, Shaw L, Trojanowski J, Weiner M.
Associations Between Baseline Concentration of Alzheimer’s Disease Biochemical Markers
and MRI Regional Rates of Brain Tissue Loss in ADNI Data. Alzheimer’s Association 2009
International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
32) Risacher SL, Saykin AJ, Shen L, West JD, Kim S, McDonald BC. Volumetric, Cortical
Thickness and Grey Matter Density Changes on MRI over 12 Months: Relationship to
Conversion Status in the ADNI Cohort. Alzheimer’s Association 2009 International
Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
33) Belaroussi B, Bracoud L, Vincent F, Pachai C. Detection of Hippocampal Volume Changes
on Elderly Control, MCI and Alzheimer Patients from the ADNI Database: A One-Year
Follow Up. Alzheimer’s Association 2009 International Conference on Alzheimer’s Disease
(ICAD), July 11-16, 2009.
34) Thompson P, Hua X, Leow A, Morra JH, Apostolova LG, Lee S, Avedissian C, Madsen SK,
Green AE, Toga AW, Jack CR Jr, Shaw LM, Trojanowski JQ, Weiner MW. Brain Changes in
676 ADNI Subjects: Summary of 10 Studies Using Tensor-Based Morphometry and
Automated Hippocampal Mapping. Alzheimer’s Association 2009 International Conference
on Alzheimer’s Disease (ICAD), July 11-16, 2009.
35) Nikelski J, Evans A, Chertkow H. Assessment of Structural Differences in Normal Aging and
Alzheimer’s Disease: Quantitative and Qualitative Differences Using Subjects From the
Alzheimer’s Disease Neuroimaging Initiative (ADNI). Alzheimer’s Association 2009
International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
36) Ito K, Corrigan B, Zhao Q, French J, Miller R, Fullerton T. Disease Progression Analysis of
ADAS-Cog from ADNI Database in Normal Elderly, Mild Cognitive Impairment and
Alzheimer’s Disease Patients. Alzheimer’s Association 2009 International Conference on
Alzheimer’s Disease (ICAD), July 11-16, 2009.
37) Posner H, Cano S, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S,
Hobart J. The ADAS-Cog’s Performance as a Measure: Lessons from the ADNI Study – Part
1, Evaluation Using Traditional Psychometric Methods. Alzheimer’s Association 2009
International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
38) Hobart J, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zejicek J, Zeger S,
Cano S. The ADAS-Cog’s Performance as a Measure: Lessons from the ADNI Study – Part
3, Do the Scale Modifications Add Value? Alzheimer’s Association 2009 International
Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
39) Shaw LM. The ADNI Multicenter Study: CSF Biomarkers Data Report. Alzheimer’s
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40) Das SR, Pluta J, Avants BB, Soares HD, Yushkevich PA. A Preliminary Study of
Hippocampal Subfield Atrophy Using the ADNI Dataset. Alzheimer’s Association 2009
International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
41) Nestor SM, Borrie M, Smith M, Bartha R. A Direct Comparison of Ventricular Volumes
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42) Donohue M, Gamst A. Mining ADNI for a Predictive Model of Diagnostic Conversions
Using Classification and Regression Trees (CART). Alzheimer’s Association 2009
International Conference on Alzheimer’s Disease (ICAD), July 11-16, 2009.
43) Landau SM, Harvey D, Madison C, Foster NL, Reiman EM, Shaw LM, Trojanowski JQ,
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Alzheimer’s disease neuroimaging initiative. Alzheimer’s Association 2009 International
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44) Cano S, Posner H, Aisen P, Selnes O, Stern Y, Thomas R, Weiner M, Zajicek J, Zeger S,
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45) Soleda O. et al. Segmentation of Anatomical Structures in Brain MR Images Using Atlases in
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These slides and much more at
ADNI-INFO.ORG
All data at
www.loni.ucla.edu/ADNI/