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Research ArticleBrainE
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Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease

K.B. Walhovd, A.M. Fjell, J. Brewer, L.K. McEvoy, C. Fennema-Notestine, D.J. Hagler, R.G. Jennings, D. Karow, A.M. Dale and the Alzheimer's Disease Neuroimaging Initiative
American Journal of Neuroradiology February 2010, 31 (2) 347-354; DOI: https://doi.org/10.3174/ajnr.A1809
K.B. Walhovd
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A.M. Fjell
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J. Brewer
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L.K. McEvoy
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C. Fennema-Notestine
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D.J. Hagler Jr
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R.G. Jennings
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D. Karow
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A.M. Dale
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Abstract

BACKGROUND AND PURPOSE: Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline.

MATERIALS AND METHODS: ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Aβ42, t-tau, p-tau, and ratios of t-tau/Aβ42 and p-tau/Aβ42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI.

RESULTS: Hippocampal volume, retrosplenial thickness, and t-tau/Aβ42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume.

CONCLUSIONS: All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.

Abbreviations

Aβ42
β amyloid 1–42
AD
Alzheimer disease
ADNI
Alzheimer's Disease Neuroimaging Initiative
AUC
area under the curve
B
B coefficient for each predictor in the regression equation
CDR-SB
Clinical Dementia Rating sum of boxes
Corr. Class.
correlation classification
CSHC
Center for the Study of Human Cognition
FDA
US Food and Drug Administration
18F-FDG
[18F] fluorodeoxyglucose
FDG-PET
fluorodeoxyglucose–positron-emission tomography
inf.
inferior
lat.
lateral
LM-del
delayed Logical Memory from the Wechsler Memory Scale Logical Memory II
M
mean
MCI
mild cognitive impairment
med. orb. front.
medial orbital frontal
mid
middle
MMSE
Mini-Mental State Examination
MRI
MR imaging
NIH
National Institutes of Health
NC
healthy control
orb. front.
orbital frontal
p-tau
phosphorylated tau protein 181
parahippoc.
parahippocampus
PET
positron-emission tomography
t-tau
tau protein
ROC
receiver operating characteristics
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American Journal of Neuroradiology: 31 (2)
American Journal of Neuroradiology
Vol. 31, Issue 2
1 Feb 2010
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K.B. Walhovd, A.M. Fjell, J. Brewer, L.K. McEvoy, C. Fennema-Notestine, D.J. Hagler, R.G. Jennings, D. Karow, A.M. Dale, the Alzheimer's Disease Neuroimaging Initiative
Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease
American Journal of Neuroradiology Feb 2010, 31 (2) 347-354; DOI: 10.3174/ajnr.A1809

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Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease
K.B. Walhovd, A.M. Fjell, J. Brewer, L.K. McEvoy, C. Fennema-Notestine, D.J. Hagler, R.G. Jennings, D. Karow, A.M. Dale, the Alzheimer's Disease Neuroimaging Initiative
American Journal of Neuroradiology Feb 2010, 31 (2) 347-354; DOI: 10.3174/ajnr.A1809
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