TY - JOUR
T1 - Effectiveness of regional DTI measures in distinguishing Alzheimer's disease, MCI, and normal aging
AU - Nir, Talia M.
AU - Jahanshad, Neda
AU - Villalon-Reina, Julio E.
AU - Toga, Arthur W.
AU - Jack, Clifford R.
AU - Weiner, Michael W.
AU - Thompson, Paul M.
N1 - Funding Information:
Data collection and sharing for this project was funded by ADNI (NIH Grant U01 AG024904 ). ADNI is funded by the National Institute on Aging , the National Institute of Biomedical Imaging and Bioengineering , and through generous contributions from the following: Abbott ; Alzheimer's Association ; Alzheimer's Drug Discovery Foundation ; Amorfix Life Sciences Ltd. ; AstraZeneca ; Bayer HealthCare ; BioClinica, Inc. ; Biogen Idec Inc. ; Bristol-Myers Squibb Company ; Eisai Inc. ; Elan Pharmaceuticals Inc. ; Eli Lilly and Company ; F. Hoffmann-La Roche Ltd. and its affiliated company Genentech, Inc. ; GE Healthcare ; Innogenetics, N.V. ; IXICO Ltd. ; Janssen Alzheimer Immunotherapy Research & Development, LLC. ; Johnson & Johnson Pharmaceutical Research & Development LLC. ; Medpace, Inc. ; Merck & Co., Inc. ; Meso Scale Diagnostics, LLC. ; Novartis Pharmaceuticals Corporation ; Pfizer Inc. ; Servier ; Synarc Inc. ; and Takeda Pharmaceutical Company . The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514 . Algorithm development for this study was also funded by the NIA , NIBIB , the National Library of Medicine , and the National Center for Research Resources ( AG016570 , EB01651 , LM05639 , RR019771 to PT). Investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in the analysis or writing of this report. For a complete listing of ADNI investigators, please see: http://adni.loni.ucla.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf . Appendix A
PY - 2013
Y1 - 2013
N2 - The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.
AB - The Alzheimer's Disease Neuroimaging Initiative (ADNI) recently added diffusion tensor imaging (DTI), among several other new imaging modalities, in an effort to identify sensitive biomarkers of Alzheimer's disease (AD). While anatomical MRI is the main structural neuroimaging method used in most AD studies and clinical trials, DTI is sensitive to microscopic white matter (WM) changes not detectable with standard MRI, offering additional markers of neurodegeneration. Prior DTI studies of AD report lower fractional anisotropy (FA), and increased mean, axial, and radial diffusivity (MD, AxD, RD) throughout WM. Here we assessed which DTI measures may best identify differences among AD, mild cognitive impairment (MCI), and cognitively healthy elderly control (NC) groups, in region of interest (ROI) and voxel-based analyses of 155 ADNI participants (mean age: 73.5 ± 7.4; 90 M/65 F; 44 NC, 88 MCI, 23 AD). Both VBA and ROI analyses revealed widespread group differences in FA and all diffusivity measures. DTI maps were strongly correlated with widely-used clinical ratings (MMSE, CDR-sob, and ADAS-cog). When effect sizes were ranked, FA analyses were least sensitive for picking up group differences. Diffusivity measures could detect more subtle MCI differences, where FA could not. ROIs showing strongest group differentiation (lowest p-values) included tracts that pass through the temporal lobe, and posterior brain regions. The left hippocampal component of the cingulum showed consistently high effect sizes for distinguishing groups, across all diffusivity and anisotropy measures, and in correlations with cognitive scores.
KW - Alzheimer's disease
KW - Biomarkers
KW - Clinical scores
KW - DTI
KW - MCI
KW - White matter
UR - http://www.scopus.com/inward/record.url?scp=84883878305&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883878305&partnerID=8YFLogxK
U2 - 10.1016/j.nicl.2013.07.006
DO - 10.1016/j.nicl.2013.07.006
M3 - Article
C2 - 24179862
AN - SCOPUS:84883878305
SN - 2213-1582
VL - 3
SP - 180
EP - 195
JO - NeuroImage: Clinical
JF - NeuroImage: Clinical
ER -