Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease

Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in ident...

Full description

Saved in:
Bibliographic Details
Published inNeuroImage (Orlando, Fla.) Vol. 134; pp. 573 - 586
Main Authors Konukoglu, Ender, Coutu, Jean-Philippe, Salat, David H., Fischl, Bruce
Format Journal Article
LanguageEnglish
Published United States Elsevier Inc 01.07.2016
Elsevier Limited
Subjects
Aged
Aging
Alzheimer Disease - diagnostic imaging
Alzheimer Disease - pathology
Alzheimer's disease
Brain - diagnostic imaging
Brain - pathology
Cognitive ability
Cognitive Dysfunction - diagnostic imaging
Cognitive Dysfunction - pathology
Data processing
Diffusion Magnetic Resonance Imaging - methods
Diffusion tensor imaging
Female
Histopathology
Humans
Least-Squares Analysis
Magnetic resonance imaging
Male
Medical imaging
Multivariate Analysis
Neurodegenerative diseases
Neuroimaging
NMR
Nuclear magnetic resonance
Partial least squares
Pharmaceutical industry
Population studies
R&D
Research & development
Spatial variations
Statistical analysis
Statistics
Substantia alba
Variation
White Matter - diagnostic imaging
White Matter - pathology
Canada
United States > US
California
Multivariate analysis
Alzheimer's disease
Partial least squares
Diffusion tensor imaging
Online AccessGet full text

Cover

Abstract Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?” •Voxel-wise multivariate statistical method is proposed.•The method allows sophisticated multivariate hypotheses to be tested.•Results with diffusion imaging are demonstrated.•Method is applied to study effects of AD, MCI and aging.
AbstractList Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?”
Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer’s and Huntington’s diseases 1 , 2 . The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as Diffusion Tensor Imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer’s disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer’s disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer’s disease but with differing multivariate effects?”
Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?” •Voxel-wise multivariate statistical method is proposed.•The method allows sophisticated multivariate hypotheses to be tested.•Results with diffusion imaging are demonstrated.•Method is applied to study effects of AD, MCI and aging.
Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: "are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?" and "are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?"Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: "are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?" and "are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?"
Author Salat, David H.
Fischl, Bruce
Konukoglu, Ender
Coutu, Jean-Philippe
AuthorAffiliation a MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
c Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
d Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
e Computer Science and Artificial Intelligence Laboratory, MIT, USA
b Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
AuthorAffiliation_xml – name: c Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
– name: e Computer Science and Artificial Intelligence Laboratory, MIT, USA
– name: d Neuroimaging Research for Veterans Center, VA Boston Healthcare System, Boston, MA, USA
– name: a MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
– name: b Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
Author_xml – sequence: 1
  givenname: Ender
  surname: Konukoglu
  fullname: Konukoglu, Ender
  email: enderk@nmr.mgh.harvard.edu
  organization: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
– sequence: 2
  givenname: Jean-Philippe
  surname: Coutu
  fullname: Coutu, Jean-Philippe
  organization: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
– sequence: 3
  givenname: David H.
  surname: Salat
  fullname: Salat, David H.
  organization: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
– sequence: 4
  givenname: Bruce
  surname: Fischl
  fullname: Fischl, Bruce
  organization: MGH/MIT/HMS Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
BackLink https://www.ncbi.nlm.nih.gov/pubmed/27103138$$D View this record in MEDLINE/PubMed
BookMark eNqNkk1vEzEQhleoiLaBv4AscYBLgr0f9poDIlR8SUVc4Gx5d2eTCY6d2t6g8Fv4sXiTlkIu5GTLM-_zznjmMjuzzkKWEUZnjDL-cjWzMHiHa72AWZ5eZrSc0aJ-kF0wKquprER-Nt6rYlozJs-zyxBWlFLJyvpRdp4LRgtW1BfZr8-DibjVHnUEEqKOGCK22hBttdkFDMT1pMO-HwI6S0ZLtAuy0V6vIYIPJAUODxGTzIAOkYSbQXsIr8h8szEJF0dtdOTHEpPNWsekJAfXFAkELZmbn0vANfjnIfmFhIHH2cNemwBPbs9J9u39u69XH6fXXz58uppfT9tKijjtNBfAuhYkiKoqGi0a2fCyyUUheM_KUle9FBpyVrRV33W0L0UFgnLeSFpJXUyy1wfuZmjWkEA2em3Uxqdu_U45jerfiMWlWritKiXLZcET4MUtwLubAUJUawwtGKMtuCEoVtOaS8Hz-v-pQtY5L3jiTrJnR6krN_g0ln2WrIUo-Oj99O_i_1R9N-P77lrvQvDQqxbj_t9TL2gUo2pcKrVS90ulxqVStFR0D6iPAHceJ0jfHqSQxrdF8Cq0CLaFDj20UXUOT4G8OYK0Bu24pN9hdxriN7ldCK8
CitedBy_id crossref_primary_10_3389_fnhum_2024_1378896
crossref_primary_10_1016_j_clinbiochem_2019_07_008
crossref_primary_10_1371_journal_pone_0222977
crossref_primary_10_1016_j_msard_2021_103442
crossref_primary_10_3389_fneur_2020_00648
crossref_primary_10_1016_j_nicl_2018_10_026
crossref_primary_10_1109_JBHI_2019_2932565
crossref_primary_10_1002_dad2_12040
crossref_primary_10_1016_j_pscychresns_2022_111576
crossref_primary_10_3389_fneur_2023_1094313
crossref_primary_10_1371_journal_pone_0316544
crossref_primary_10_1159_000486565
crossref_primary_10_1016_j_cca_2017_04_019
crossref_primary_10_3389_fnagi_2019_00378
crossref_primary_10_1016_j_neurobiolaging_2017_04_024
crossref_primary_10_1002_jcp_28359
crossref_primary_10_1017_S0033291717001210
Cites_doi 10.1002/1522-2594(200008)44:2<259::AID-MRM13>3.0.CO;2-6
10.1016/j.neuroimage.2009.04.053
10.1016/j.neuroimage.2011.05.055
10.1016/j.neuroscience.2014.02.017
10.1016/j.neuroimage.2012.06.038
10.1002/hbm.22217
10.1016/j.neuroimage.2008.03.061
10.1016/j.neuroimage.2011.10.015
10.1016/j.neurobiolaging.2003.09.005
10.1002/hbm.20563
10.1016/j.neurobiolaging.2013.12.001
10.1212/WNL.34.7.939
10.1016/j.neuroimage.2004.07.020
10.1016/j.neuroimage.2010.09.073
10.1002/hbm.22030
10.1002/jmri.21049
10.1006/nimg.1996.0016
10.1212/WNL.57.2.216
10.1007/978-1-62703-059-5_23
10.1523/JNEUROSCI.1392-08.2008
10.1016/j.neurobiolaging.2008.03.013
10.1007/BF02289009
10.1002/mds.20979
10.1006/nimg.1995.1019
10.1016/j.neuroimage.2013.11.027
10.1136/jnnp.72.6.742
10.1016/j.neuroimage.2010.10.026
10.1159/000084560
10.1093/jnci/92.24.2029
10.3389/fneur.2011.00054
10.1016/j.neuroimage.2011.01.007
10.1002/hbm.1058
10.1016/j.neuroimage.2010.01.041
10.1016/j.jneumeth.2011.10.031
10.1016/j.neuroscience.2015.05.049
10.1016/j.neuroscience.2015.06.031
10.1016/j.neuroimage.2010.07.034
10.1016/j.neuroimage.2005.01.028
10.1002/nbm.782
10.1016/j.cub.2012.07.002
10.1016/j.neuroimage.2010.12.008
10.1016/j.neuroimage.2006.07.047
10.1002/hipo.20573
10.1016/j.neurobiolaging.2004.09.017
10.1016/j.neuroimage.2014.06.077
10.3233/JAD-150184
10.3233/JAD-131481
10.1002/nbm.786
10.1136/jnnp.69.4.528
10.1006/nimg.2002.1267
10.1117/12.2042237
10.1016/j.neuroimage.2003.07.005
10.1016/S0304-3940(02)00914-X
10.1016/j.neuroimage.2006.02.024
10.3233/JAD-122431
10.1212/WNL.43.11.2412-a
10.3233/JAD-2012-112111
10.1097/YCO.0b013e32835ed6e8
10.1016/j.neuroimage.2012.10.051
10.1002/nbm.785
10.1038/nprot.2007.45
ContentType Journal Article
Copyright 2016 Elsevier Inc.
Copyright © 2016 Elsevier Inc. All rights reserved.
Copyright Elsevier Limited Jul 1, 2016
Copyright_xml – notice: 2016 Elsevier Inc.
– notice: Copyright © 2016 Elsevier Inc. All rights reserved.
– notice: Copyright Elsevier Limited Jul 1, 2016
CorporateAuthor the Alzheimer's Disease Neuroimaging Initiative (ADNI)
Alzheimer's Disease Neuroimaging Initiative (ADNI)
CorporateAuthor_xml – name: the Alzheimer's Disease Neuroimaging Initiative (ADNI)
– name: Alzheimer's Disease Neuroimaging Initiative (ADNI)
DBID AAYXX
CITATION
CGR
CUY
CVF
ECM
EIF
NPM
3V.
7TK
7X7
7XB
88E
88G
8AO
8FD
8FE
8FH
8FI
8FJ
8FK
ABUWG
AFKRA
AZQEC
BBNVY
BENPR
BHPHI
CCPQU
DWQXO
FR3
FYUFA
GHDGH
GNUQQ
HCIFZ
K9.
LK8
M0S
M1P
M2M
M7P
P64
PHGZM
PHGZT
PJZUB
PKEHL
PPXIY
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
PSYQQ
Q9U
RC3
7X8
7QO
5PM
DOI 10.1016/j.neuroimage.2016.04.038
DatabaseName CrossRef
Medline
MEDLINE
MEDLINE (Ovid)
MEDLINE
MEDLINE
PubMed
ProQuest Central (Corporate)
Neurosciences Abstracts
Health & Medical Collection
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
Psychology Database (Alumni)
ProQuest Pharma Collection
Technology Research Database
ProQuest SciTech Collection
ProQuest Natural Science Collection
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest SciTech Premium Collection Natural Science Collection Biological Science Collection
ProQuest Central
Natural Science Collection
ProQuest One
ProQuest Central Korea
Engineering Research Database
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Central Student
SciTech Premium Collection
ProQuest Health & Medical Complete (Alumni)
ProQuest Biological Science Collection
ProQuest Health & Medical Collection
Medical Database
Psychology Database
Biological Science Database
Biotechnology and BioEngineering Abstracts
ProQuest Central Premium
ProQuest One Academic (New)
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic
ProQuest One Academic UKI Edition
ProQuest Central China
ProQuest One Psychology
ProQuest Central Basic
Genetics Abstracts
MEDLINE - Academic
Biotechnology Research Abstracts
PubMed Central (Full Participant titles)
DatabaseTitle CrossRef
MEDLINE
Medline Complete
MEDLINE with Full Text
PubMed
MEDLINE (Ovid)
ProQuest One Psychology
ProQuest Central Student
Technology Research Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
SciTech Premium Collection
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Natural Science Collection
ProQuest Pharma Collection
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Health & Medical Research Collection
Genetics Abstracts
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
Natural Science Collection
ProQuest Central Korea
Health & Medical Research Collection
Biological Science Collection
ProQuest Central (New)
ProQuest Medical Library (Alumni)
ProQuest Biological Science Collection
ProQuest Central Basic
ProQuest One Academic Eastern Edition
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Psychology Journals (Alumni)
Biological Science Database
ProQuest SciTech Collection
Neurosciences Abstracts
ProQuest Hospital Collection (Alumni)
Biotechnology and BioEngineering Abstracts
ProQuest Health & Medical Complete
ProQuest Medical Library
ProQuest Psychology Journals
ProQuest One Academic UKI Edition
Engineering Research Database
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
MEDLINE - Academic
Biotechnology Research Abstracts
DatabaseTitleList ProQuest One Psychology



MEDLINE
MEDLINE - Academic
Engineering Research Database
Database_xml – sequence: 1
  dbid: NPM
  name: PubMed
  url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 2
  dbid: EIF
  name: MEDLINE
  url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search
  sourceTypes: Index Database
– sequence: 3
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Medicine
Statistics
EISSN 1095-9572
EndPage 586
ExternalDocumentID PMC4912936
4102315591
27103138
10_1016_j_neuroimage_2016_04_038
S1053811916300787
Genre Journal Article
GeographicLocations Canada
United States--US
California
GeographicLocations_xml – name: Canada
– name: United States--US
– name: California
GrantInformation_xml – fundername: NINDS NIH HHS
  grantid: U01 NS086625
– fundername: NCCIH NIH HHS
  grantid: RC1 AT005728
– fundername: NINDS NIH HHS
  grantid: R01 NS083534
– fundername: NIA NIH HHS
  grantid: R01 AG022381
– fundername: NIBIB NIH HHS
  grantid: P41 EB015896
– fundername: NIA NIH HHS
  grantid: R01 AG050595
– fundername: NCRR NIH HHS
  grantid: S10 RR019254
– fundername: NINR NIH HHS
  grantid: R01 NR010827
– fundername: NIA NIH HHS
  grantid: U01 AG024904
– fundername: NIMH NIH HHS
  grantid: U01 MH093765
GroupedDBID ---
--K
--M
.1-
.FO
.~1
0R~
123
1B1
1RT
1~.
1~5
4.4
457
4G.
5RE
5VS
7-5
71M
7X7
88E
8AO
8FE
8FH
8FI
8FJ
8P~
9JM
AABNK
AAEDT
AAEDW
AAIKJ
AAKOC
AALRI
AAOAW
AAQFI
AATTM
AAXKI
AAXLA
AAXUO
AAYWO
ABBQC
ABCQJ
ABFNM
ABFRF
ABIVO
ABJNI
ABMAC
ABMZM
ABUWG
ACDAQ
ACGFO
ACGFS
ACIEU
ACPRK
ACRLP
ACVFH
ADBBV
ADCNI
ADEZE
ADFRT
AEBSH
AEFWE
AEIPS
AEKER
AENEX
AEUPX
AFJKZ
AFKRA
AFPUW
AFRHN
AFTJW
AFXIZ
AGCQF
AGHFR
AGUBO
AGWIK
AGYEJ
AHHHB
AHMBA
AIEXJ
AIIUN
AIKHN
AITUG
AJRQY
AJUYK
AKBMS
AKRWK
AKYEP
ALMA_UNASSIGNED_HOLDINGS
AMRAJ
ANKPU
ANZVX
APXCP
AXJTR
AZQEC
BBNVY
BENPR
BHPHI
BKOJK
BLXMC
BNPGV
BPHCQ
BVXVI
CCPQU
CS3
DM4
DU5
DWQXO
EBS
EFBJH
EFKBS
EJD
EO8
EO9
EP2
EP3
F5P
FDB
FIRID
FNPLU
FYGXN
FYUFA
G-Q
GBLVA
GNUQQ
GROUPED_DOAJ
HCIFZ
HMCUK
IHE
J1W
KOM
LG5
LK8
LX8
M1P
M29
M2M
M2V
M41
M7P
MO0
MOBAO
N9A
O-L
O9-
OAUVE
OVD
OZT
P-8
P-9
P2P
PC.
PHGZM
PHGZT
PJZUB
PPXIY
PQGLB
PQQKQ
PROAC
PSQYO
PSYQQ
PUEGO
Q38
ROL
RPZ
SAE
SCC
SDF
SDG
SDP
SES
SSH
SSN
SSZ
T5K
TEORI
UKHRP
UV1
YK3
Z5R
ZU3
~G-
3V.
AACTN
AADPK
AAIAV
ABLVK
ABYKQ
AFKWA
AJBFU
AJOXV
AMFUW
C45
EFLBG
HMQ
LCYCR
RIG
SNS
ZA5
29N
53G
AAFWJ
AAQXK
AAYXX
ABXDB
ACRPL
ADFGL
ADMUD
ADNMO
ADVLN
ADXHL
AFPKN
AGQPQ
AGRNS
AIGII
AKRLJ
ALIPV
ASPBG
AVWKF
AZFZN
CAG
CITATION
COF
FEDTE
FGOYB
G-2
HDW
HEI
HMK
HMO
HVGLF
HZ~
OK1
R2-
SEW
WUQ
XPP
ZMT
0SF
CGR
CUY
CVF
ECM
EIF
NPM
7TK
7XB
8FD
8FK
FR3
K9.
P64
PKEHL
PQEST
PQUKI
PRINS
Q9U
RC3
7X8
7QO
5PM
ID FETCH-LOGICAL-c597t-da67e1dce9e7553ba7b9b64b27376f144a5f97ae213c5fdd0f475e7066b9059a3
IEDL.DBID .~1
ISSN 1053-8119
1095-9572
IngestDate Thu Aug 21 18:29:41 EDT 2025
Mon Jul 21 11:40:33 EDT 2025
Fri Jul 11 02:16:52 EDT 2025
Wed Aug 13 07:23:44 EDT 2025
Wed Feb 19 02:42:46 EST 2025
Thu Apr 24 23:07:40 EDT 2025
Tue Jul 01 03:01:47 EDT 2025
Fri Feb 23 02:25:06 EST 2024
Tue Aug 26 20:08:39 EDT 2025
IsDoiOpenAccess false
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Keywords Multivariate analysis
Alzheimer's disease
Partial least squares
Diffusion tensor imaging
Language English
License Copyright © 2016 Elsevier Inc. All rights reserved.
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c597t-da67e1dce9e7553ba7b9b64b27376f144a5f97ae213c5fdd0f475e7066b9059a3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink https://www.sciencedirect.com/science/article/am/pii/S1053811916300787?via%3Dihub
PMID 27103138
PQID 1799877366
PQPubID 2031077
PageCount 14
ParticipantIDs pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912936
proquest_miscellaneous_1808697628
proquest_miscellaneous_1798263629
proquest_journals_1799877366
pubmed_primary_27103138
crossref_citationtrail_10_1016_j_neuroimage_2016_04_038
crossref_primary_10_1016_j_neuroimage_2016_04_038
elsevier_sciencedirect_doi_10_1016_j_neuroimage_2016_04_038
elsevier_clinicalkey_doi_10_1016_j_neuroimage_2016_04_038
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate 2016-07-01
PublicationDateYYYYMMDD 2016-07-01
PublicationDate_xml – month: 07
  year: 2016
  text: 2016-07-01
  day: 01
PublicationDecade 2010
PublicationPlace United States
PublicationPlace_xml – name: United States
– name: Amsterdam
PublicationTitle NeuroImage (Orlando, Fla.)
PublicationTitleAlternate Neuroimage
PublicationYear 2016
Publisher Elsevier Inc
Elsevier Limited
Publisher_xml – name: Elsevier Inc
– name: Elsevier Limited
References Smith (bb0235) 2007; 2
Sotak (bb0255) 2002; 15
Beaulieu (bb0035) 2002
Xie (bb0315) 2015; 47
Ouyang (bb0185) 2015; 301
Lu (bb0135) 2014; 39
Smith, Nichols (bb0225) 2009; 44
Takahashi (bb0280) 2002; 332
Shi, Liu, Zhou, Yu, Jiang (bb0220) 2009; 19
Smith (bb0230) 2006; 31
Williams (bb0310) 2013; 34
Jack (bb0105) 2008; 27
Song (bb0250) 2005; 26
Villain (bb0295) 2008; 28
Salat (bb0210) 2005; 26
Lee, Coutu, Wilkens, Yendiki, Rosas (bb0130) 2015
Morris (bb0155) 1993
Suk, Lee, Shen (bb0275) 2014; 101
Moseley (bb0160) 2002
Oishi, Akhter, Mielke, Ceritoglu, Zhang (bb0175) 2011
Amlien, Fjell (bb0015) 2014; 276
Krishnan, Williams, McIntosh, Abdi (bb0125) 2011; 56
Salat (bb0215) 2010; 31
Abdi (bb0010) 2012; 31
Pfefferbaum, Sullivan, Hedehus (bb0190) 2000
Wee (bb0300) 2011; 54
Rose (bb0200) 2000; 69
Abdi, Williams (bb0005) 2013; 930
Teipel (bb0285) 2007; 34
Naylor (bb0165) 2014; 35
Sui (bb0270) 2013; 66
Klawiter (bb0115) 2011; 55
McIntosh, Lobaugh (bb0140) 2004; 23
McKhann (bb0150) 1984; 34
Ouyang, X. et al. Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease. in (eds. Molthen, R. C. & Weaver, J. B.) 9038, (90380B–7) (SPIE, 2014).
Kincses (bb0110) 2013; 36
Chen (bb0050) 2009; 47
Barnes (bb0025) 2005; 19
Bartzokis (bb0030) 2004; 25
Damoiseaux (bb0065) 2009; 30
Chenevert (bb0055) 2000; 92
Good (bb0085) 2005
Wee (bb0305) 2012; 59
McIntosh, Bookstein, Haxby, Grady (bb0145) 1996; 3
Galton (bb0080) 2001; 57
Sachdev, Zhuang, Braidy, Wen (bb0205) 2013; 26
Song (bb0245) 2003; 20
Avants, Cook, Ungar, Gee, Grossman (bb0020) 2010; 50
Bozzali (bb0040) 2002; 72
Izenman (bb0100) 2008
Nichols, Holmes (bb0170) 2002; 15
Brown (bb0045) 2012; 22
Sui, Adali, Yu, Chen, Calhoun (bb0265) 2012; 204
Kovacevic, Abdi, Beaton, McIntosh (bb0120) 2013; 56
Tucker (bb0290) 1958; 23
Groves, Beckmann, Smith, Woolrich (bb0090) 2011; 54
Yendiki, Koldewyn, Kakunoori, Kanwisher, Fischl (bb0320) 2014; 88
Coutu, Chen, Rosas, Salat (bb0060) 2014; 35
Sui (bb0260) 2011; 57
Douaud (bb0070) 2011; 55
Friston, Frith, Frackowiak, Turner (bb0075) 1995; 2
Groves (bb0095) 2012; 63
Song (bb0240) 2002; 17
Rosas (bb0195) 2006; 21
Sui (10.1016/j.neuroimage.2016.04.038_bb0260) 2011; 57
Izenman (10.1016/j.neuroimage.2016.04.038_bb0100) 2008
McIntosh (10.1016/j.neuroimage.2016.04.038_bb0140) 2004; 23
Smith (10.1016/j.neuroimage.2016.04.038_bb0225) 2009; 44
Sotak (10.1016/j.neuroimage.2016.04.038_bb0255) 2002; 15
10.1016/j.neuroimage.2016.04.038_bb0180
Good (10.1016/j.neuroimage.2016.04.038_bb0085) 2005
Abdi (10.1016/j.neuroimage.2016.04.038_bb0010) 2012; 31
Pfefferbaum (10.1016/j.neuroimage.2016.04.038_bb0190) 2000
McKhann (10.1016/j.neuroimage.2016.04.038_bb0150) 1984; 34
Smith (10.1016/j.neuroimage.2016.04.038_bb0230) 2006; 31
Beaulieu (10.1016/j.neuroimage.2016.04.038_bb0035) 2002
Oishi (10.1016/j.neuroimage.2016.04.038_bb0175) 2011
Smith (10.1016/j.neuroimage.2016.04.038_bb0235) 2007; 2
Sui (10.1016/j.neuroimage.2016.04.038_bb0270) 2013; 66
Teipel (10.1016/j.neuroimage.2016.04.038_bb0285) 2007; 34
Song (10.1016/j.neuroimage.2016.04.038_bb0245) 2003; 20
Salat (10.1016/j.neuroimage.2016.04.038_bb0210) 2005; 26
Tucker (10.1016/j.neuroimage.2016.04.038_bb0290) 1958; 23
Brown (10.1016/j.neuroimage.2016.04.038_bb0045) 2012; 22
Chen (10.1016/j.neuroimage.2016.04.038_bb0050) 2009; 47
Song (10.1016/j.neuroimage.2016.04.038_bb0250) 2005; 26
Suk (10.1016/j.neuroimage.2016.04.038_bb0275) 2014; 101
Rose (10.1016/j.neuroimage.2016.04.038_bb0200) 2000; 69
Ouyang (10.1016/j.neuroimage.2016.04.038_bb0185) 2015; 301
Wee (10.1016/j.neuroimage.2016.04.038_bb0305) 2012; 59
Amlien (10.1016/j.neuroimage.2016.04.038_bb0015) 2014; 276
Douaud (10.1016/j.neuroimage.2016.04.038_bb0070) 2011; 55
Chenevert (10.1016/j.neuroimage.2016.04.038_bb0055) 2000; 92
Lee (10.1016/j.neuroimage.2016.04.038_bb0130) 2015
Moseley (10.1016/j.neuroimage.2016.04.038_bb0160) 2002
Sachdev (10.1016/j.neuroimage.2016.04.038_bb0205) 2013; 26
Klawiter (10.1016/j.neuroimage.2016.04.038_bb0115) 2011; 55
Naylor (10.1016/j.neuroimage.2016.04.038_bb0165) 2014; 35
Abdi (10.1016/j.neuroimage.2016.04.038_bb0005) 2013; 930
Avants (10.1016/j.neuroimage.2016.04.038_bb0020) 2010; 50
Lu (10.1016/j.neuroimage.2016.04.038_bb0135) 2014; 39
McIntosh (10.1016/j.neuroimage.2016.04.038_bb0145) 1996; 3
Xie (10.1016/j.neuroimage.2016.04.038_bb0315) 2015; 47
Groves (10.1016/j.neuroimage.2016.04.038_bb0090) 2011; 54
Jack (10.1016/j.neuroimage.2016.04.038_bb0105) 2008; 27
Sui (10.1016/j.neuroimage.2016.04.038_bb0265) 2012; 204
Krishnan (10.1016/j.neuroimage.2016.04.038_bb0125) 2011; 56
Coutu (10.1016/j.neuroimage.2016.04.038_bb0060) 2014; 35
Song (10.1016/j.neuroimage.2016.04.038_bb0240) 2002; 17
Groves (10.1016/j.neuroimage.2016.04.038_bb0095) 2012; 63
Villain (10.1016/j.neuroimage.2016.04.038_bb0295) 2008; 28
Nichols (10.1016/j.neuroimage.2016.04.038_bb0170) 2002; 15
Shi (10.1016/j.neuroimage.2016.04.038_bb0220) 2009; 19
Barnes (10.1016/j.neuroimage.2016.04.038_bb0025) 2005; 19
Kincses (10.1016/j.neuroimage.2016.04.038_bb0110) 2013; 36
Bartzokis (10.1016/j.neuroimage.2016.04.038_bb0030) 2004; 25
Friston (10.1016/j.neuroimage.2016.04.038_bb0075) 1995; 2
Kovacevic (10.1016/j.neuroimage.2016.04.038_bb0120) 2013; 56
Morris (10.1016/j.neuroimage.2016.04.038_bb0155) 1993
Rosas (10.1016/j.neuroimage.2016.04.038_bb0195) 2006; 21
Salat (10.1016/j.neuroimage.2016.04.038_bb0215) 2010; 31
Williams (10.1016/j.neuroimage.2016.04.038_bb0310) 2013; 34
Galton (10.1016/j.neuroimage.2016.04.038_bb0080) 2001; 57
Damoiseaux (10.1016/j.neuroimage.2016.04.038_bb0065) 2009; 30
Wee (10.1016/j.neuroimage.2016.04.038_bb0300) 2011; 54
Yendiki (10.1016/j.neuroimage.2016.04.038_bb0320) 2014; 88
Bozzali (10.1016/j.neuroimage.2016.04.038_bb0040) 2002; 72
Takahashi (10.1016/j.neuroimage.2016.04.038_bb0280) 2002; 332
24378085 - Neurobiol Aging. 2014 Jun;35(6):1412-21
19309039 - Hippocampus. 2009 Nov;19(11):1055-64
12377381 - Neurosci Lett. 2002 Oct 25;332(1):45-8
22019883 - Neuroimage. 2012 Feb 1;59(3):2045-56
18302232 - J Magn Reson Imaging. 2008 Apr;27(4):685-91
23493128 - Curr Opin Psychiatry. 2013 May;26(3):244-51
21640835 - Neuroimage. 2011 Aug 1;57(3):839-55
6610841 - Neurology. 1984 Jul;34(7):939-44
21904533 - Front Neurol. 2011 Aug 24;2:54
18501637 - Neuroimage. 2009 Jan 1;44(1):83-98
11121466 - J Natl Cancer Inst. 2000 Dec 20;92(24):2029-36
26116521 - Neuroscience. 2015 Aug 20;301:553-62
24583036 - Neuroscience. 2014 Sep 12;276:206-15
14642481 - Neuroimage. 2003 Nov;20(3):1714-22
22785390 - J Alzheimers Dis. 2012;31 Suppl 3:S189-201
16624579 - Neuroimage. 2006 Jul 15;31(4):1487-505
24269273 - Neuroimage. 2014 Mar;88:79-90
17166745 - Neuroimage. 2007 Feb 1;34(3):985-95
11747097 - Hum Brain Mapp. 2002 Jan;15(1):1-25
18455835 - Neurobiol Aging. 2010 Feb;31(2):244-56
15917106 - Neurobiol Aging. 2005 Aug-Sep;26(8):1215-27
15785035 - Dement Geriatr Cogn Disord. 2005;19(5-6):338-44
16755582 - Mov Disord. 2006 Sep;21(9):1317-25
18412132 - Hum Brain Mapp. 2009 Apr;30(4):1051-9
17406613 - Nat Protoc. 2007;2(3):499-503
23086857 - Methods Mol Biol. 2013;930:549-79
15862213 - Neuroimage. 2005 May 15;26(1):132-40
23408378 - Hum Brain Mapp. 2014 Mar;35(3):831-46
23542867 - J Alzheimers Dis. 2013;36(1):119-28
9345485 - Neuroimage. 1996 Jun;3(3 Pt 1):143-57
18550759 - J Neurosci. 2008 Jun 11;28(24):6174-81
15501095 - Neuroimage. 2004;23 Suppl 1:S250-63
12414282 - Neuroimage. 2002 Nov;17(3):1429-36
25042445 - Neuroimage. 2014 Nov 1;101:569-82
15212838 - Neurobiol Aging. 2004 Aug;25(7):843-51
24150110 - J Alzheimers Dis. 2014;39(2):261-9
12489102 - NMR Biomed. 2002 Nov-Dec;15(7-8):561-9
10918325 - Magn Reson Med. 2000 Aug;44(2):259-68
12023417 - J Neurol Neurosurg Psychiatry. 2002 Jun;72(6):742-6
22438182 - Hum Brain Mapp. 2013 Aug;34(8):1826-41
12489094 - NMR Biomed. 2002 Nov-Dec;15(7-8):435-55
9343599 - Neuroimage. 1995 Jun;2(2):166-72
21238597 - Neuroimage. 2011 Apr 15;55(4):1454-60
8232972 - Neurology. 1993 Nov;43(11):2412-4
22902750 - Curr Biol. 2012 Sep 25;22(18):1693-8
19393744 - Neuroimage. 2009 Aug 15;47(2):602-10
12489101 - NMR Biomed. 2002 Nov-Dec;15(7-8):553-60
26401572 - J Alzheimers Dis. 2015 ;47(2):509-22
26026680 - Neuroscience. 2015 Aug 20;301:79-89
20083207 - Neuroimage. 2010 Apr 15;50(3):1004-16
10990518 - J Neurol Neurosurg Psychiatry. 2000 Oct;69(4):528-30
22108139 - J Neurosci Methods. 2012 Feb 15;204(1):68-81
21182970 - Neuroimage. 2011 Apr 1;55(3):880-90
20970508 - Neuroimage. 2011 Feb 1;54(3):1812-22
20932919 - Neuroimage. 2011 Feb 1;54(3):2198-217
11468305 - Neurology. 2001 Jul 24;57(2):216-25
22750721 - Neuroimage. 2012 Oct 15;63(1):365-80
20656037 - Neuroimage. 2011 May 15;56(2):455-75
23108278 - Neuroimage. 2013 Feb 1;66:119-32
References_xml – volume: 31
  start-page: S189
  year: 2012
  end-page: S201
  ident: bb0010
  article-title: Analysis of regional cerebral blood flow data to discriminate among Alzheimer's disease, frontotemporal dementia, and elderly controls: a multi-block barycentric discriminant analysis (MUBADA) methodology
  publication-title: J. Alzheimers Dis.
– volume: 47
  start-page: 602
  year: 2009
  end-page: 610
  ident: bb0050
  article-title: Linking functional and structural brain images with multivariate network analyses: a novel application of the partial least square method
  publication-title: NeuroImage
– volume: 19
  start-page: 1055
  year: 2009
  end-page: 1064
  ident: bb0220
  article-title: Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: meta-analyses of MRI studies
  publication-title: Hippocampus
– volume: 57
  start-page: 839
  year: 2011
  end-page: 855
  ident: bb0260
  article-title: Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA
  publication-title: NeuroImage
– volume: 56
  start-page: 159
  year: 2013
  end-page: 170
  ident: bb0120
  publication-title: New Perspectives in Partial Least Squares and Related Methods
– volume: 3
  start-page: 143
  year: 1996
  end-page: 157
  ident: bb0145
  article-title: Spatial pattern analysis of functional brain images using partial least squares
  publication-title: NeuroImage
– volume: 15
  start-page: 1
  year: 2002
  end-page: 25
  ident: bb0170
  article-title: Nonparametric permutation tests for functional neuroimaging: a primer with examples
  publication-title: Hum. Brain Mapp.
– volume: 35
  start-page: 1412
  year: 2014
  end-page: 1421
  ident: bb0060
  article-title: Non-Gaussian water diffusion in aging white matter
  publication-title: Neurobiol. Aging
– volume: 23
  start-page: S250
  year: 2004
  end-page: S263
  ident: bb0140
  article-title: Partial least squares analysis of neuroimaging data: applications and advances
  publication-title: NeuroImage
– volume: 88
  start-page: 79
  year: 2014
  end-page: 90
  ident: bb0320
  article-title: Spurious group differences due to head motion in a diffusion MRI study
  publication-title: NeuroImage
– volume: 63
  start-page: 365
  year: 2012
  end-page: 380
  ident: bb0095
  article-title: Benefits of multi-modal fusion analysis on a large-scale dataset: life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure
  publication-title: NeuroImage
– volume: 35
  start-page: 831
  year: 2014
  end-page: 846
  ident: bb0165
  article-title: Voxelwise multivariate analysis of multimodality magnetic resonance imaging
  publication-title: Hum. Brain Mapp.
– volume: 31
  start-page: 1487
  year: 2006
  end-page: 1505
  ident: bb0230
  article-title: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data
  publication-title: NeuroImage
– volume: 2
  start-page: 499
  year: 2007
  end-page: 503
  ident: bb0235
  article-title: Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics
  publication-title: Nat. Protoc.
– volume: 26
  start-page: 244
  year: 2013
  end-page: 251
  ident: bb0205
  article-title: Is Alzheimer's a disease of the white matter?
  publication-title: Curr. Opin. Psychiatry
– year: 2015
  ident: bb0130
  article-title: Tract-based analysis of white matter degeneration in Alzheimer's disease
  publication-title: Neuroscience
– volume: 26
  start-page: 1215
  year: 2005
  end-page: 1227
  ident: bb0210
  article-title: Age-related alterations in white matter microstructure measured by diffusion tensor imaging
  publication-title: Neurobiol. Aging
– volume: 34
  start-page: 985
  year: 2007
  end-page: 995
  ident: bb0285
  article-title: Multivariate network analysis of fiber tract integrity in Alzheimer's disease
  publication-title: NeuroImage
– volume: 54
  start-page: 2198
  year: 2011
  end-page: 2217
  ident: bb0090
  article-title: Linked independent component analysis for multimodal data fusion
  publication-title: NeuroImage
– volume: 204
  start-page: 68
  year: 2012
  end-page: 81
  ident: bb0265
  article-title: A review of multivariate methods for multimodal fusion of brain imaging data
  publication-title: J. Neurosci. Methods
– volume: 301
  start-page: 553
  year: 2015
  end-page: 562
  ident: bb0185
  article-title: Simultaneous changes in gray matter volume and white matter fractional anisotropy in Alzheimer's disease revealed by multimodal CCA and joint ICA
  publication-title: Neuroscience
– year: 2002
  ident: bb0035
  article-title: The basis of anisotropic water diffusion in the nervous system—a technical review
  publication-title: NMR Biomed.
– volume: 34
  start-page: 1826
  year: 2013
  end-page: 1841
  ident: bb0310
  article-title: Interindividual variation in serum cholesterol is associated with regional white matter tissue integrity in older adults
  publication-title: Hum. Brain Mapp.
– volume: 332
  start-page: 45
  year: 2002
  end-page: 48
  ident: bb0280
  article-title: Selective reduction of diffusion anisotropy in white matter of Alzheimer disease brains measured by 3.0 tesla magnetic resonance imaging
  publication-title: Neurosci. Lett.
– volume: 26
  start-page: 132
  year: 2005
  end-page: 140
  ident: bb0250
  article-title: Demyelination increases radial diffusivity in corpus callosum of mouse brain
  publication-title: NeuroImage
– volume: 56
  start-page: 455
  year: 2011
  end-page: 475
  ident: bb0125
  article-title: Partial least squares (PLS) methods for neuroimaging: a tutorial and review
  publication-title: NeuroImage
– volume: 50
  start-page: 1004
  year: 2010
  end-page: 1016
  ident: bb0020
  article-title: Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis
  publication-title: NeuroImage
– volume: 72
  start-page: 742
  year: 2002
  end-page: 746
  ident: bb0040
  article-title: White matter damage in Alzheimer's disease assessed in vivo using diffusion tensor magnetic resonance imaging
  publication-title: J. Neurol. Neurosurg. Psychiatry
– volume: 47
  start-page: 509
  year: 2015
  end-page: 522
  ident: bb0315
  article-title: Identification of amnestic mild cognitive impairment using multi-modal brain features: a combined structural MRI and diffusion tensor imaging study
  publication-title: J. Alzheimers Dis.
– volume: 34
  start-page: 939
  year: 1984
  ident: bb0150
  article-title: Clinical diagnosis of Alzheimer's disease report of the NINCDS-ADRDA work group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease
  publication-title: Neurology
– volume: 930
  start-page: 549
  year: 2013
  end-page: 579
  ident: bb0005
  article-title: Partial least squares methods: partial least squares correlation and partial least square regression
  publication-title: Methods Mol. Biol.
– year: 2011
  ident: bb0175
  article-title: Multi-modal MRI analysis with disease-specific spatial filtering: initial testing to predict mild cognitive impairment patients who convert to Alzheimer's disease
  publication-title: Front. Neurol.
– volume: 17
  start-page: 1429
  year: 2002
  end-page: 1436
  ident: bb0240
  article-title: Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
  publication-title: NeuroImage
– year: 2002
  ident: bb0160
  article-title: Diffusion tensor imaging and aging—a review
  publication-title: NMR Biomed.
– volume: 54
  start-page: 1812
  year: 2011
  end-page: 1822
  ident: bb0300
  article-title: Enriched white matter connectivity networks for accurate identification of MCI patients
  publication-title: NeuroImage
– volume: 25
  start-page: 843
  year: 2004
  end-page: 851
  ident: bb0030
  article-title: Heterogeneous age-related breakdown of white matter structural integrity: implications for cortical ‘disconnection’ in aging and Alzheimer's disease
  publication-title: Neurobiol. Aging
– year: 2008
  ident: bb0100
  article-title: Modern Multivariate Statistical Techniques
– volume: 69
  start-page: 528
  year: 2000
  end-page: 530
  ident: bb0200
  article-title: Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging
  publication-title: J. Neurol. Neurosurg. Psychiatry
– volume: 31
  start-page: 244
  year: 2010
  end-page: 256
  ident: bb0215
  article-title: White matter pathology isolates the hippocampal formation in Alzheimer's disease
  publication-title: Neurobiol. Aging
– volume: 36
  start-page: 119
  year: 2013
  end-page: 128
  ident: bb0110
  article-title: The pattern of diffusion parameter changes in Alzheimer's disease, identified by means of linked independent component analysis
  publication-title: J. Alzheimers Dis.
– volume: 28
  start-page: 6174
  year: 2008
  end-page: 6181
  ident: bb0295
  article-title: Relationships between hippocampal atrophy, white matter disruption, and gray matter hypometabolism in Alzheimer's disease
  publication-title: J. Neurosci.
– volume: 30
  start-page: 1051
  year: 2009
  end-page: 1059
  ident: bb0065
  article-title: White matter tract integrity in aging and Alzheimer's disease
  publication-title: Hum. Brain Mapp.
– volume: 39
  start-page: 261
  year: 2014
  end-page: 269
  ident: bb0135
  article-title: Regional differences in white matter breakdown between frontotemporal dementia and early-onset Alzheimer's disease
  publication-title: J. Alzheimers Dis.
– volume: 15
  start-page: 561
  year: 2002
  end-page: 569
  ident: bb0255
  article-title: The role of diffusion tensor imaging in the evaluation of ischemic brain injury — a review
  publication-title: NMR Biomed.
– year: 1993
  ident: bb0155
  article-title: The clinical dementia rating (CDR): current version and scoring rules
  publication-title: Neurology
– volume: 101
  start-page: 569
  year: 2014
  end-page: 582
  ident: bb0275
  article-title: Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
  publication-title: NeuroImage
– volume: 2
  start-page: 166
  year: 1995
  end-page: 172
  ident: bb0075
  article-title: Characterizing dynamic brain responses with fMRI: a multivariate approach
  publication-title: NeuroImage
– volume: 55
  start-page: 880
  year: 2011
  end-page: 890
  ident: bb0070
  article-title: DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease
  publication-title: NeuroImage
– volume: 23
  start-page: 111
  year: 1958
  end-page: 136
  ident: bb0290
  article-title: An inter-battery method of factor analysis
  publication-title: Psychometrika
– volume: 22
  start-page: 1693
  year: 2012
  end-page: 1698
  ident: bb0045
  article-title: Neuroanatomical assessment of biological maturity
  publication-title: Curr. Biol.
– volume: 44
  start-page: 83
  year: 2009
  end-page: 98
  ident: bb0225
  article-title: Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference
  publication-title: NeuroImage
– volume: 66
  start-page: 119
  year: 2013
  end-page: 132
  ident: bb0270
  article-title: Three-way (N-way) fusion of brain imaging data based on mCCA
  publication-title: NeuroImage
– reference: Ouyang, X. et al. Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease. in (eds. Molthen, R. C. & Weaver, J. B.) 9038, (90380B–7) (SPIE, 2014).
– volume: 20
  start-page: 1714
  year: 2003
  end-page: 1722
  ident: bb0245
  article-title: Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia
  publication-title: NeuroImage
– volume: 276
  start-page: 206
  year: 2014
  end-page: 215
  ident: bb0015
  article-title: Diffusion tensor imaging of white matter degeneration in Alzheimer's disease and mild cognitive impairment
  publication-title: Neuroscience
– volume: 27
  start-page: 685
  year: 2008
  end-page: 691
  ident: bb0105
  article-title: The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods
  publication-title: J. Magn. Reson. Imaging
– volume: 55
  start-page: 1454
  year: 2011
  end-page: 1460
  ident: bb0115
  article-title: Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords
  publication-title: NeuroImage
– volume: 59
  start-page: 2045
  year: 2012
  end-page: 2056
  ident: bb0305
  article-title: Identification of MCI individuals using structural and functional connectivity networks
  publication-title: NeuroImage
– volume: 57
  start-page: 216
  year: 2001
  end-page: 225
  ident: bb0080
  article-title: Differing patterns of temporal atrophy in Alzheimer's disease and semantic dementia
  publication-title: Neurology
– volume: 19
  start-page: 338
  year: 2005
  end-page: 344
  ident: bb0025
  article-title: Does Alzheimer's disease affect hippocampal asymmetry? Evidence from a cross-sectional and longitudinal volumetric MRI study
  publication-title: Dement. Geriatr. Cogn. Disord.
– volume: 21
  start-page: 1317
  year: 2006
  end-page: 1325
  ident: bb0195
  article-title: Diffusion tensor imaging in presymptomatic and early Huntington's disease: selective white matter pathology and its relationship to clinical measures
  publication-title: Mov. Disord.
– year: 2005
  ident: bb0085
  article-title: Permutation, Parametric, and Bootstrap Tests of Hypotheses
– year: 2000
  ident: bb0190
  article-title: Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging
  publication-title: Magn. Reson. Med.
– volume: 92
  start-page: 2029
  year: 2000
  end-page: 2036
  ident: bb0055
  article-title: Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors
  publication-title: J. Natl. Cancer Inst.
– year: 2000
  ident: 10.1016/j.neuroimage.2016.04.038_bb0190
  article-title: Age-related decline in brain white matter anisotropy measured with spatially corrected echo-planar diffusion tensor imaging
  publication-title: Magn. Reson. Med.
  doi: 10.1002/1522-2594(200008)44:2<259::AID-MRM13>3.0.CO;2-6
– volume: 47
  start-page: 602
  year: 2009
  ident: 10.1016/j.neuroimage.2016.04.038_bb0050
  article-title: Linking functional and structural brain images with multivariate network analyses: a novel application of the partial least square method
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2009.04.053
– volume: 56
  start-page: 159
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0120
– volume: 57
  start-page: 839
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0260
  article-title: Discriminating schizophrenia and bipolar disorder by fusing fMRI and DTI in a multimodal CCA+ joint ICA model
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2011.05.055
– volume: 276
  start-page: 206
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0015
  article-title: Diffusion tensor imaging of white matter degeneration in Alzheimer's disease and mild cognitive impairment
  publication-title: Neuroscience
  doi: 10.1016/j.neuroscience.2014.02.017
– volume: 63
  start-page: 365
  year: 2012
  ident: 10.1016/j.neuroimage.2016.04.038_bb0095
  article-title: Benefits of multi-modal fusion analysis on a large-scale dataset: life-span patterns of inter-subject variability in cortical morphometry and white matter microstructure
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2012.06.038
– volume: 35
  start-page: 831
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0165
  article-title: Voxelwise multivariate analysis of multimodality magnetic resonance imaging
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.22217
– volume: 44
  start-page: 83
  year: 2009
  ident: 10.1016/j.neuroimage.2016.04.038_bb0225
  article-title: Threshold-free cluster enhancement: addressing problems of smoothing, threshold dependence and localisation in cluster inference
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2008.03.061
– volume: 59
  start-page: 2045
  year: 2012
  ident: 10.1016/j.neuroimage.2016.04.038_bb0305
  article-title: Identification of MCI individuals using structural and functional connectivity networks
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2011.10.015
– volume: 25
  start-page: 843
  year: 2004
  ident: 10.1016/j.neuroimage.2016.04.038_bb0030
  article-title: Heterogeneous age-related breakdown of white matter structural integrity: implications for cortical ‘disconnection’ in aging and Alzheimer's disease
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2003.09.005
– volume: 30
  start-page: 1051
  year: 2009
  ident: 10.1016/j.neuroimage.2016.04.038_bb0065
  article-title: White matter tract integrity in aging and Alzheimer's disease
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.20563
– volume: 35
  start-page: 1412
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0060
  article-title: Non-Gaussian water diffusion in aging white matter
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2013.12.001
– volume: 34
  start-page: 939
  year: 1984
  ident: 10.1016/j.neuroimage.2016.04.038_bb0150
  article-title: Clinical diagnosis of Alzheimer's disease report of the NINCDS-ADRDA work group* under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease
  publication-title: Neurology
  doi: 10.1212/WNL.34.7.939
– year: 2005
  ident: 10.1016/j.neuroimage.2016.04.038_bb0085
– volume: 23
  start-page: S250
  year: 2004
  ident: 10.1016/j.neuroimage.2016.04.038_bb0140
  article-title: Partial least squares analysis of neuroimaging data: applications and advances
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2004.07.020
– volume: 54
  start-page: 2198
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0090
  article-title: Linked independent component analysis for multimodal data fusion
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2010.09.073
– volume: 34
  start-page: 1826
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0310
  article-title: Interindividual variation in serum cholesterol is associated with regional white matter tissue integrity in older adults
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.22030
– volume: 27
  start-page: 685
  year: 2008
  ident: 10.1016/j.neuroimage.2016.04.038_bb0105
  article-title: The Alzheimer's disease neuroimaging initiative (ADNI): MRI methods
  publication-title: J. Magn. Reson. Imaging
  doi: 10.1002/jmri.21049
– volume: 3
  start-page: 143
  year: 1996
  ident: 10.1016/j.neuroimage.2016.04.038_bb0145
  article-title: Spatial pattern analysis of functional brain images using partial least squares
  publication-title: NeuroImage
  doi: 10.1006/nimg.1996.0016
– volume: 57
  start-page: 216
  year: 2001
  ident: 10.1016/j.neuroimage.2016.04.038_bb0080
  article-title: Differing patterns of temporal atrophy in Alzheimer's disease and semantic dementia
  publication-title: Neurology
  doi: 10.1212/WNL.57.2.216
– volume: 930
  start-page: 549
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0005
  article-title: Partial least squares methods: partial least squares correlation and partial least square regression
  publication-title: Methods Mol. Biol.
  doi: 10.1007/978-1-62703-059-5_23
– volume: 28
  start-page: 6174
  year: 2008
  ident: 10.1016/j.neuroimage.2016.04.038_bb0295
  article-title: Relationships between hippocampal atrophy, white matter disruption, and gray matter hypometabolism in Alzheimer's disease
  publication-title: J. Neurosci.
  doi: 10.1523/JNEUROSCI.1392-08.2008
– volume: 31
  start-page: 244
  year: 2010
  ident: 10.1016/j.neuroimage.2016.04.038_bb0215
  article-title: White matter pathology isolates the hippocampal formation in Alzheimer's disease
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2008.03.013
– volume: 23
  start-page: 111
  year: 1958
  ident: 10.1016/j.neuroimage.2016.04.038_bb0290
  article-title: An inter-battery method of factor analysis
  publication-title: Psychometrika
  doi: 10.1007/BF02289009
– volume: 21
  start-page: 1317
  year: 2006
  ident: 10.1016/j.neuroimage.2016.04.038_bb0195
  article-title: Diffusion tensor imaging in presymptomatic and early Huntington's disease: selective white matter pathology and its relationship to clinical measures
  publication-title: Mov. Disord.
  doi: 10.1002/mds.20979
– volume: 2
  start-page: 166
  year: 1995
  ident: 10.1016/j.neuroimage.2016.04.038_bb0075
  article-title: Characterizing dynamic brain responses with fMRI: a multivariate approach
  publication-title: NeuroImage
  doi: 10.1006/nimg.1995.1019
– volume: 88
  start-page: 79
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0320
  article-title: Spurious group differences due to head motion in a diffusion MRI study
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2013.11.027
– volume: 72
  start-page: 742
  year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0040
  article-title: White matter damage in Alzheimer's disease assessed in vivo using diffusion tensor magnetic resonance imaging
  publication-title: J. Neurol. Neurosurg. Psychiatry
  doi: 10.1136/jnnp.72.6.742
– volume: 54
  start-page: 1812
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0300
  article-title: Enriched white matter connectivity networks for accurate identification of MCI patients
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2010.10.026
– volume: 19
  start-page: 338
  year: 2005
  ident: 10.1016/j.neuroimage.2016.04.038_bb0025
  article-title: Does Alzheimer's disease affect hippocampal asymmetry? Evidence from a cross-sectional and longitudinal volumetric MRI study
  publication-title: Dement. Geriatr. Cogn. Disord.
  doi: 10.1159/000084560
– volume: 92
  start-page: 2029
  year: 2000
  ident: 10.1016/j.neuroimage.2016.04.038_bb0055
  article-title: Diffusion magnetic resonance imaging: an early surrogate marker of therapeutic efficacy in brain tumors
  publication-title: J. Natl. Cancer Inst.
  doi: 10.1093/jnci/92.24.2029
– year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0175
  article-title: Multi-modal MRI analysis with disease-specific spatial filtering: initial testing to predict mild cognitive impairment patients who convert to Alzheimer's disease
  publication-title: Front. Neurol.
  doi: 10.3389/fneur.2011.00054
– volume: 55
  start-page: 1454
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0115
  article-title: Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2011.01.007
– volume: 15
  start-page: 1
  year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0170
  article-title: Nonparametric permutation tests for functional neuroimaging: a primer with examples
  publication-title: Hum. Brain Mapp.
  doi: 10.1002/hbm.1058
– volume: 50
  start-page: 1004
  year: 2010
  ident: 10.1016/j.neuroimage.2016.04.038_bb0020
  article-title: Dementia induces correlated reductions in white matter integrity and cortical thickness: a multivariate neuroimaging study with sparse canonical correlation analysis
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2010.01.041
– volume: 204
  start-page: 68
  year: 2012
  ident: 10.1016/j.neuroimage.2016.04.038_bb0265
  article-title: A review of multivariate methods for multimodal fusion of brain imaging data
  publication-title: J. Neurosci. Methods
  doi: 10.1016/j.jneumeth.2011.10.031
– year: 2015
  ident: 10.1016/j.neuroimage.2016.04.038_bb0130
  article-title: Tract-based analysis of white matter degeneration in Alzheimer's disease
  publication-title: Neuroscience
  doi: 10.1016/j.neuroscience.2015.05.049
– volume: 301
  start-page: 553
  year: 2015
  ident: 10.1016/j.neuroimage.2016.04.038_bb0185
  article-title: Simultaneous changes in gray matter volume and white matter fractional anisotropy in Alzheimer's disease revealed by multimodal CCA and joint ICA
  publication-title: Neuroscience
  doi: 10.1016/j.neuroscience.2015.06.031
– volume: 56
  start-page: 455
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0125
  article-title: Partial least squares (PLS) methods for neuroimaging: a tutorial and review
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2010.07.034
– volume: 26
  start-page: 132
  year: 2005
  ident: 10.1016/j.neuroimage.2016.04.038_bb0250
  article-title: Demyelination increases radial diffusivity in corpus callosum of mouse brain
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2005.01.028
– year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0035
  article-title: The basis of anisotropic water diffusion in the nervous system—a technical review
  publication-title: NMR Biomed.
  doi: 10.1002/nbm.782
– volume: 22
  start-page: 1693
  year: 2012
  ident: 10.1016/j.neuroimage.2016.04.038_bb0045
  article-title: Neuroanatomical assessment of biological maturity
  publication-title: Curr. Biol.
  doi: 10.1016/j.cub.2012.07.002
– volume: 55
  start-page: 880
  year: 2011
  ident: 10.1016/j.neuroimage.2016.04.038_bb0070
  article-title: DTI measures in crossing-fibre areas: increased diffusion anisotropy reveals early white matter alteration in MCI and mild Alzheimer's disease
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2010.12.008
– volume: 34
  start-page: 985
  year: 2007
  ident: 10.1016/j.neuroimage.2016.04.038_bb0285
  article-title: Multivariate network analysis of fiber tract integrity in Alzheimer's disease
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2006.07.047
– volume: 19
  start-page: 1055
  year: 2009
  ident: 10.1016/j.neuroimage.2016.04.038_bb0220
  article-title: Hippocampal volume and asymmetry in mild cognitive impairment and Alzheimer's disease: meta-analyses of MRI studies
  publication-title: Hippocampus
  doi: 10.1002/hipo.20573
– volume: 26
  start-page: 1215
  year: 2005
  ident: 10.1016/j.neuroimage.2016.04.038_bb0210
  article-title: Age-related alterations in white matter microstructure measured by diffusion tensor imaging
  publication-title: Neurobiol. Aging
  doi: 10.1016/j.neurobiolaging.2004.09.017
– year: 2008
  ident: 10.1016/j.neuroimage.2016.04.038_bb0100
– volume: 101
  start-page: 569
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0275
  article-title: Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2014.06.077
– volume: 47
  start-page: 509
  year: 2015
  ident: 10.1016/j.neuroimage.2016.04.038_bb0315
  article-title: Identification of amnestic mild cognitive impairment using multi-modal brain features: a combined structural MRI and diffusion tensor imaging study
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-150184
– volume: 39
  start-page: 261
  year: 2014
  ident: 10.1016/j.neuroimage.2016.04.038_bb0135
  article-title: Regional differences in white matter breakdown between frontotemporal dementia and early-onset Alzheimer's disease
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-131481
– volume: 15
  start-page: 561
  year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0255
  article-title: The role of diffusion tensor imaging in the evaluation of ischemic brain injury — a review
  publication-title: NMR Biomed.
  doi: 10.1002/nbm.786
– volume: 69
  start-page: 528
  year: 2000
  ident: 10.1016/j.neuroimage.2016.04.038_bb0200
  article-title: Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging
  publication-title: J. Neurol. Neurosurg. Psychiatry
  doi: 10.1136/jnnp.69.4.528
– volume: 17
  start-page: 1429
  year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0240
  article-title: Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
  publication-title: NeuroImage
  doi: 10.1006/nimg.2002.1267
– ident: 10.1016/j.neuroimage.2016.04.038_bb0180
  doi: 10.1117/12.2042237
– volume: 20
  start-page: 1714
  year: 2003
  ident: 10.1016/j.neuroimage.2016.04.038_bb0245
  article-title: Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2003.07.005
– volume: 332
  start-page: 45
  year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0280
  article-title: Selective reduction of diffusion anisotropy in white matter of Alzheimer disease brains measured by 3.0 tesla magnetic resonance imaging
  publication-title: Neurosci. Lett.
  doi: 10.1016/S0304-3940(02)00914-X
– volume: 31
  start-page: 1487
  year: 2006
  ident: 10.1016/j.neuroimage.2016.04.038_bb0230
  article-title: Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2006.02.024
– volume: 36
  start-page: 119
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0110
  article-title: The pattern of diffusion parameter changes in Alzheimer's disease, identified by means of linked independent component analysis
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-122431
– year: 1993
  ident: 10.1016/j.neuroimage.2016.04.038_bb0155
  article-title: The clinical dementia rating (CDR): current version and scoring rules
  publication-title: Neurology
  doi: 10.1212/WNL.43.11.2412-a
– volume: 31
  start-page: S189
  issue: Suppl. 3
  year: 2012
  ident: 10.1016/j.neuroimage.2016.04.038_bb0010
  article-title: Analysis of regional cerebral blood flow data to discriminate among Alzheimer's disease, frontotemporal dementia, and elderly controls: a multi-block barycentric discriminant analysis (MUBADA) methodology
  publication-title: J. Alzheimers Dis.
  doi: 10.3233/JAD-2012-112111
– volume: 26
  start-page: 244
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0205
  article-title: Is Alzheimer's a disease of the white matter?
  publication-title: Curr. Opin. Psychiatry
  doi: 10.1097/YCO.0b013e32835ed6e8
– volume: 66
  start-page: 119
  year: 2013
  ident: 10.1016/j.neuroimage.2016.04.038_bb0270
  article-title: Three-way (N-way) fusion of brain imaging data based on mCCA+jICA and its application to discriminating schizophrenia
  publication-title: NeuroImage
  doi: 10.1016/j.neuroimage.2012.10.051
– year: 2002
  ident: 10.1016/j.neuroimage.2016.04.038_bb0160
  article-title: Diffusion tensor imaging and aging—a review
  publication-title: NMR Biomed.
  doi: 10.1002/nbm.785
– volume: 2
  start-page: 499
  year: 2007
  ident: 10.1016/j.neuroimage.2016.04.038_bb0235
  article-title: Acquisition and voxelwise analysis of multi-subject diffusion data with tract-based spatial statistics
  publication-title: Nat. Protoc.
  doi: 10.1038/nprot.2007.45
– reference: 9343599 - Neuroimage. 1995 Jun;2(2):166-72
– reference: 24378085 - Neurobiol Aging. 2014 Jun;35(6):1412-21
– reference: 18455835 - Neurobiol Aging. 2010 Feb;31(2):244-56
– reference: 11747097 - Hum Brain Mapp. 2002 Jan;15(1):1-25
– reference: 8232972 - Neurology. 1993 Nov;43(11):2412-4
– reference: 18550759 - J Neurosci. 2008 Jun 11;28(24):6174-81
– reference: 26401572 - J Alzheimers Dis. 2015 ;47(2):509-22
– reference: 24269273 - Neuroimage. 2014 Mar;88:79-90
– reference: 22019883 - Neuroimage. 2012 Feb 1;59(3):2045-56
– reference: 17406613 - Nat Protoc. 2007;2(3):499-503
– reference: 21182970 - Neuroimage. 2011 Apr 1;55(3):880-90
– reference: 19309039 - Hippocampus. 2009 Nov;19(11):1055-64
– reference: 19393744 - Neuroimage. 2009 Aug 15;47(2):602-10
– reference: 22785390 - J Alzheimers Dis. 2012;31 Suppl 3:S189-201
– reference: 12489102 - NMR Biomed. 2002 Nov-Dec;15(7-8):561-9
– reference: 25042445 - Neuroimage. 2014 Nov 1;101:569-82
– reference: 18302232 - J Magn Reson Imaging. 2008 Apr;27(4):685-91
– reference: 17166745 - Neuroimage. 2007 Feb 1;34(3):985-95
– reference: 26116521 - Neuroscience. 2015 Aug 20;301:553-62
– reference: 20970508 - Neuroimage. 2011 Feb 1;54(3):1812-22
– reference: 22438182 - Hum Brain Mapp. 2013 Aug;34(8):1826-41
– reference: 22750721 - Neuroimage. 2012 Oct 15;63(1):365-80
– reference: 23542867 - J Alzheimers Dis. 2013;36(1):119-28
– reference: 15785035 - Dement Geriatr Cogn Disord. 2005;19(5-6):338-44
– reference: 12489094 - NMR Biomed. 2002 Nov-Dec;15(7-8):435-55
– reference: 15212838 - Neurobiol Aging. 2004 Aug;25(7):843-51
– reference: 20083207 - Neuroimage. 2010 Apr 15;50(3):1004-16
– reference: 23086857 - Methods Mol Biol. 2013;930:549-79
– reference: 11121466 - J Natl Cancer Inst. 2000 Dec 20;92(24):2029-36
– reference: 12377381 - Neurosci Lett. 2002 Oct 25;332(1):45-8
– reference: 15501095 - Neuroimage. 2004;23 Suppl 1:S250-63
– reference: 20932919 - Neuroimage. 2011 Feb 1;54(3):2198-217
– reference: 18412132 - Hum Brain Mapp. 2009 Apr;30(4):1051-9
– reference: 22902750 - Curr Biol. 2012 Sep 25;22(18):1693-8
– reference: 26026680 - Neuroscience. 2015 Aug 20;301:79-89
– reference: 15917106 - Neurobiol Aging. 2005 Aug-Sep;26(8):1215-27
– reference: 16624579 - Neuroimage. 2006 Jul 15;31(4):1487-505
– reference: 23108278 - Neuroimage. 2013 Feb 1;66:119-32
– reference: 12414282 - Neuroimage. 2002 Nov;17(3):1429-36
– reference: 23493128 - Curr Opin Psychiatry. 2013 May;26(3):244-51
– reference: 24150110 - J Alzheimers Dis. 2014;39(2):261-9
– reference: 23408378 - Hum Brain Mapp. 2014 Mar;35(3):831-46
– reference: 6610841 - Neurology. 1984 Jul;34(7):939-44
– reference: 9345485 - Neuroimage. 1996 Jun;3(3 Pt 1):143-57
– reference: 18501637 - Neuroimage. 2009 Jan 1;44(1):83-98
– reference: 10918325 - Magn Reson Med. 2000 Aug;44(2):259-68
– reference: 11468305 - Neurology. 2001 Jul 24;57(2):216-25
– reference: 12489101 - NMR Biomed. 2002 Nov-Dec;15(7-8):553-60
– reference: 20656037 - Neuroimage. 2011 May 15;56(2):455-75
– reference: 15862213 - Neuroimage. 2005 May 15;26(1):132-40
– reference: 16755582 - Mov Disord. 2006 Sep;21(9):1317-25
– reference: 22108139 - J Neurosci Methods. 2012 Feb 15;204(1):68-81
– reference: 12023417 - J Neurol Neurosurg Psychiatry. 2002 Jun;72(6):742-6
– reference: 21640835 - Neuroimage. 2011 Aug 1;57(3):839-55
– reference: 21904533 - Front Neurol. 2011 Aug 24;2:54
– reference: 14642481 - Neuroimage. 2003 Nov;20(3):1714-22
– reference: 24583036 - Neuroscience. 2014 Sep 12;276:206-15
– reference: 10990518 - J Neurol Neurosurg Psychiatry. 2000 Oct;69(4):528-30
– reference: 21238597 - Neuroimage. 2011 Apr 15;55(4):1454-60
SSID ssj0009148
Score 2.3078153
Snippet Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human...
SourceID pubmedcentral
proquest
pubmed
crossref
elsevier
SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage 573
SubjectTerms Aged
Aging
Alzheimer Disease - diagnostic imaging
Alzheimer Disease - pathology
Alzheimer's disease
Brain - diagnostic imaging
Brain - pathology
Cognitive ability
Cognitive Dysfunction - diagnostic imaging
Cognitive Dysfunction - pathology
Data processing
Diffusion Magnetic Resonance Imaging - methods
Diffusion tensor imaging
Female
Histopathology
Humans
Least-Squares Analysis
Magnetic resonance imaging
Male
Medical imaging
Multivariate Analysis
Neurodegenerative diseases
Neuroimaging
NMR
Nuclear magnetic resonance
Partial least squares
Pharmaceutical industry
Population studies
R&D
Research & development
Spatial variations
Statistical analysis
Statistics
Substantia alba
Variation
White Matter - diagnostic imaging
White Matter - pathology
SummonAdditionalLinks – databaseName: Health & Medical Collection
  dbid: 7X7
  link: http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwjV3daxQxEA9aQfoiWr-uVhlB8Gnx9ivZ6IMcYilCfbJwbyHZTejJ3W7bvVPo3-If60yS3bMq5V4vGTZ7Mzv5TWbyG8beoFPEjT3Tia0qjQFKbRNZUYqdO1Pwhhpd0XnH6Vd-clZ8mZfzeODWx7LKwSd6R910NZ2RvyPmskqInPOPF5cJdY2i7GpsoXGX3SPqMirpEnOxJd1Ni3AVrsyTCifESp5Q3-X5Ihcr_GqpwIt7wlO6pfL_7elf-Pl3FeUf29LxQ_Yg4kmYBQN4xO7Y9oDdP40Z8wO2T2gykDE_Zr_8ddsfGB4jwoR-GEF5HblJoHNAPVM2dIgGtG7c2oD4wVdUN9MD1cn7H9AzLGFJnX-gv9zQLab3MNtmw2HdwU9KUcDKM3hCeCoZOSxamC2vz-1iZa_e9hBzRE_Y2fHnb59OktieIakxClknjebCpvj60oqyzI0WRhpeGAREgjsM1HTppNA2S_O6dE0zdYUorUCMYySCOp0_ZXtt19rnDEoMW2prmtRJXqQuQwwzxdjZOJOnmrtmwsSgFVVH7nJqobFUQ5Had7XVpyJ9qmmhUJ8Tlo6SF4G_YwcZOSheDfdT0aMq3GR2kP0wykYME7DJjtJHg52p6Et6tbX8CXs9DqMXoNSObm238XMwTkQwIm-ZU2H4iugzw8c8C6Y7_iWZoHYftABxw6jHCcRCfnOkXZx7NvJCEmTkh7cv_QXbp_cMhc5HbG99tbEvEc6tzSv_zf4GARFQSg
  priority: 102
  providerName: ProQuest
Title Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease
URI https://www.clinicalkey.com/#!/content/1-s2.0-S1053811916300787
https://dx.doi.org/10.1016/j.neuroimage.2016.04.038
https://www.ncbi.nlm.nih.gov/pubmed/27103138
https://www.proquest.com/docview/1799877366
https://www.proquest.com/docview/1798263629
https://www.proquest.com/docview/1808697628
https://pubmed.ncbi.nlm.nih.gov/PMC4912936
Volume 134
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3db9MwELemISFeEIyvwjYZCYmn0CZx7BieumlTAa1CwKS-WXZia5nadKwtSDzwl_DHcuc46QoIVeKlUROf4sTn-8jd_Y6QFyAUQbEnOrJ5rsFBKWwkcwyxc2cYL7HRFX7vOBvz0Tl7N8kmO-S4rYXBtMog-xuZ7qV1ONMPb7N_VVX9T2AZgLoBfwNRo4DvsIKdCeTyVz_WaR4yZk05XJZGODpk8zQ5Xh4zsprBzsUkL-5BT7FS5e8q6k8T9PdMyhuq6fQeuRtsSjpspn2f7Nh6j9w-C1HzB-Snr7L9Cl4xGJYUS4g8OjOQ6ABJQueOYquUFX47ozhV0GgUYcFnmC6zoJge70-AQJjSKTb8oYsvKyxeek2H6yA4Xc7pN4xM0JkH7qTNXZG3aVXT4fT7ha1m9vrlgobQ0ENyfnry-XgUha4MUQHOxzIqNRc2hieWVmRZarQw0nBmwA4S3IF_pjMnhbZJnBaZK8uBYyKzAkwbI8GW0-kjslvPa_uE0Ay8lcKaMnaSs9glYLoMwGU2zqSx5q7sEdEuhCoCZDl2zpiqNjftUq2XUOESqgFTsIQ9EneUVw1sxxY0sl1r1ZalgiBVoFu2oH3T0W6w75bU-y1rqSBCFgqh-nIhUs575Hl3GTY_RnR0becrPwbcQ7BB5D_G5OC1gtGZwG0eN9zavZJEYJcPnIDY4ONuAIKPb16pqwsPQs4kWor86X89-DNyB_816c_7ZHd5vbIHYOQtzaHfxfArJuKQ3Bq-fT8aw_HoZPzh4y8VHVtP
linkProvider Elsevier
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3db9MwELfGJsFeEIyvwgAjgXiKaL7sGIRQgU0dWyuENmlvnp3YWlGbbEvLBH8LfwN_I3ex0zJAU1_2WvsaJ2ff_c73RchzEIqg2CMVmCxTYKDkJhAZutiZ1QkrsNEV3ncMhqx_kHw6TA9XyK82FwbDKluZ2AjqosrxjvwVVi7LOI8Ze3dyGmDXKPSuti003LbYNd_PwWSr3-58BP6-iKLtrf0P_cB3FQhyAM_ToFCMm7DIjTA8TWOtuBaaJRr0OGcW7AuVWsGVicI4T21RdG3CU8NBNWsBWETF8L_XyFoCLwmCYO391vDzl0WZ3zBxyXdpHGRhKHzskIsoaypUjiYgJzCkjDUlVjEv5v8K8V_A-3fc5h-KcPsWuekRLO25LXebrJhyg1wfeB_9BllH_OrKP98hP5sE329gkAOmpXU7AvTKV0OhlaXYpWWG13YU1w3KlGJF8glG6tQUI_ObH0AWjekYew3R-nSGeVOvaW_hf6fTip6jU4ROmpqh1D0VjxUdlbQ3_nFsRhNz9rKm3it1lxxcCevukdWyKs0DQlMwlHKji9AKloQ2AtTUBWtdWx2HitmiQ3jLFZn7aunYtGMs27C4r3LBT4n8lN1EAj87JJxTnriKIUvQiJbxss2IBRkuQa0tQftmTutRk0NDS1JvtvtMeulVy8VZ65Bn82GQO-hMUqWpZs0csEwB_ohL5mRgMAPejeAx993WnX-SiGODEVwAv7Cp5xOw7vnFkXJ03NQ_TwSCVPbw8qU_JTf6-4M9ubcz3H1E1vGdXZj1Jlmdns3MYwCTU_3En2BKjq5aaPwGbFeO5Q
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV3NbhMxELZKkapeUCk_DRQwEojTqtk_ew1CKKJELaUVByrlZuxdWw1Kdttu0gqehSfh6ZhZezcUUJVLr7Enu8nYM994xt8Q8gKMIjj2SAUmyxQEKLkJRIYpdmZ1wgpsdIXnHYdHbO84-ThKRyvkV3sXBssqW5vYGOqiyvGMfAeZyzLOY8Z2rC-L-Lw7fHd6FmAHKcy0tu003BI5MN8vIXyr3-7vgq5fRtHww5f3e4HvMBDkAKRnQaEYN2GRG2F4msZacS00SzT4dM4sxBoqtYIrE4Vxntqi6NuEp4aDm9YCcImK4Xtvkds8TkPcY3zEF4S_YeKu4aVxkIWh8FVErras4aocT8FiYHEZa8hW8YbM_13jv9D37wrOP1zicIPc8ViWDtziu0tWTLlJ1g59tn6TrCOSdUTQ98jP5qrvBYTmgG5p3Y6AvPK8KLSyFPu1zPEAj-J7g1ulyE0-xZqdmmKNfvMBWKUJnWDXIVqfzfEG1Ws6WGTi6ayil5geodOGPZS6p-IGo-OSDiY_Tsx4as5f1dTnp-6T4xtR3AOyWlal2SI0hZApN7oIrWBJaCPAT32I27XVcaiYLXqEt1qRuedNx_YdE9kWyH2TC31K1KfsJxL02SNhJ3nquEOWkBGt4mV7NxasuQQHt4Tsm07W4yeHi5aU3m7XmfR2rJaLXdcjz7thsECYVlKlqebNHIhRAQiJa-ZkEDoD8o3gMQ_d0u3-kohjqxF8AX5lUXcTkAH96kg5PmmY0BOBcJU9uv7Vn5E1MBXy0_7RwWOyjj_Z1Vtvk9XZ-dw8AVQ500-b7UvJ15u2F78BEdmRtQ
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Multivariate+statistical+analysis+of+diffusion+imaging+parameters+using+partial+least+squares%3A+Application+to+white+matter+variations+in+Alzheimer%27s+disease&rft.jtitle=NeuroImage+%28Orlando%2C+Fla.%29&rft.au=Konukoglu%2C+Ender&rft.au=Coutu%2C+Jean-Philippe&rft.au=Salat%2C+David+H&rft.au=Fischl%2C+Bruce&rft.date=2016-07-01&rft.issn=1095-9572&rft.eissn=1095-9572&rft.volume=134&rft.spage=573&rft_id=info:doi/10.1016%2Fj.neuroimage.2016.04.038&rft.externalDBID=NO_FULL_TEXT
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1053-8119&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1053-8119&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1053-8119&client=summon