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Research ArticleBrain
Open Access

FLAIR and Diffusion MRI Signals Are Independent Predictors of White Matter Hyperintensities

P. Maillard, O. Carmichael, D. Harvey, E. Fletcher, B. Reed, D. Mungas and C. DeCarli
American Journal of Neuroradiology January 2013, 34 (1) 54-61; DOI: https://doi.org/10.3174/ajnr.A3146
P. Maillard
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
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O. Carmichael
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
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D. Harvey
cDivision of Biostatistics (D.H., B.R., D.M., C.D.), Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California.
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E. Fletcher
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
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B. Reed
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
cDivision of Biostatistics (D.H., B.R., D.M., C.D.), Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California.
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D. Mungas
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
cDivision of Biostatistics (D.H., B.R., D.M., C.D.), Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California.
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C. DeCarli
aFrom the Imaging of Dementia and Aging Laboratory (P.M., O.C., E.F., B.R., D.M., C.D.)
bDepartment of Neurology and Center for Neuroscience (P.M., O.C., E.F., B.R., D.M., C.D.), University of California, Davis, Davis, California
cDivision of Biostatistics (D.H., B.R., D.M., C.D.), Department of Public Health Sciences, School of Medicine, University of California, Davis, Davis, California.
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Abstract

BACKGROUND AND PURPOSE: WMH, associated with cognitive decline and cardiovascular risk factors, may represent only the extreme end of a more widespread continuous WM injury process that progresses during aging and is poorly understood. We investigated the ability of FLAIR and DTI to characterize the longitudinal course of WMH development.

MATERIALS AND METHODS: One hundred nineteen participants (mean age, 74.5 ± 7.4), including cognitively healthy elders and subjects diagnosed with Alzheimer disease and mild cognitive impairment, received a comprehensive clinical evaluation and brain MR imaging, including FLAIR and DTI on 2 dates. The risk for each baseline normal-appearing WM voxel to convert into WMH was modeled as a function of baseline FA (model M1) and both baseline FA and standardized FLAIR (M2). Sensitivity, specificity, accuracy, and AUC for predicting conversion to WMH were compared between models.

RESULTS: Independent of clinical diagnosis, lower baseline FA (P < .001, both models) and higher baseline FLAIR intensity (P < .001, M2) were independently associated with increased risk for conversion from normal WM to WMH. M1 exhibited higher sensitivity but lower specificity, accuracy, and AUC compared with M2.

CONCLUSIONS: These findings provide further evidence that WMH result from a continuous process of WM degeneration with time. Stepwise decreases in WM integrity as measured by both DTI and FLAIR were independently associated with stepwise increases in WMH risk, emphasizing that these modalities may provide complementary information for understanding the time course of aging-associated WM degeneration.

ABBREVIATIONS:

AD
Alzheimer disease
AUC
area under the receiver operating characteristic analysis curve
CN
cognitively healthy
FA
fractional anisotropy
M1
first logistic regression model
M2
second logistic regression model
MCI
mild cognitive impairment
MDT
minimal deformation template
nFA
baseline normalized FA
nFL
baseline normalized FLAIR
OR
odds ratio
WMH
white matter hyperintensities
  • © 2013 by American Journal of Neuroradiology

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American Journal of Neuroradiology: 34 (1)
American Journal of Neuroradiology
Vol. 34, Issue 1
1 Jan 2013
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Cite this article
P. Maillard, O. Carmichael, D. Harvey, E. Fletcher, B. Reed, D. Mungas, C. DeCarli
FLAIR and Diffusion MRI Signals Are Independent Predictors of White Matter Hyperintensities
American Journal of Neuroradiology Jan 2013, 34 (1) 54-61; DOI: 10.3174/ajnr.A3146

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FLAIR and Diffusion MRI Signals Are Independent Predictors of White Matter Hyperintensities
P. Maillard, O. Carmichael, D. Harvey, E. Fletcher, B. Reed, D. Mungas, C. DeCarli
American Journal of Neuroradiology Jan 2013, 34 (1) 54-61; DOI: 10.3174/ajnr.A3146
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