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

Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and... This Article Free to Access Figures Only Full Text Full Text (PDF) Supplemental Online Table All Versions of this Article: ajnr.A1809v1 31/2/347 most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via CrossRef Google Scholar Articles by Walhovd, K.B. PubMed PubMed Citation Articles by Walhovd, K.B. Hotlight (NEW!) What's Hotlight? American Journal of Neuroradiology 31:347-354, February 2010 © 2010 American Society of Neuroradiology BRAIN Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease K.B. Walhovd a ,b , A.M. Fjell a ,b , J. Brewer c ,d , L.K. McEvoy d , C. Fennema-Notestine e , D.J. Hagler, Jr d , R.G. Jennings d , D. Karow d , A.M. Dale c ,d and the Alzheimer's Disease Neuroimaging Initiative a From Department of Psychology (K.B.W., A.M.F.), CSHC, University of Oslo, Oslo, Norway b Department of Neuropsychology (K.B.W., A.M.F.), Ulleval University Hospital, Oslo, Norway c Departments of Neuroscience (J.B., A.M.D.) d Radiology (J.B., L.K.M., C.F.-N., D.J.H., R.G.J., D.K., A.M.D.) e Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, California. Please address correspondence to Kristine B. Walhovd, MD,Department of Psychology, CSHC, University of Oslo, POB 1094 Blindern, 0317 Oslo, Norway; e-mail: k.b.walhovd@psykologi.uio.no 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, 18 F 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 Home Subscribe Author Instructions Submit Online Search the AJNR Archives Feedback Help Copyright © 2010 by the American Society of Neuroradiology. Print ISSN: 0195-6108 Online ISSN: 1936-959X http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png American Journal of Neuroradiology American Journal of Neuroradiology

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

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Publisher
American Journal of Neuroradiology
Copyright
Copyright © 2010 by the American Society of Neuroradiology.
ISSN
0195-6108
eISSN
1936-959X
DOI
10.3174/ajnr.A1809
Publisher site
See Article on Publisher Site

Abstract

This Article Free to Access Figures Only Full Text Full Text (PDF) Supplemental Online Table All Versions of this Article: ajnr.A1809v1 31/2/347 most recent Alert me when this article is cited Alert me if a correction is posted Citation Map Services Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via CrossRef Google Scholar Articles by Walhovd, K.B. PubMed PubMed Citation Articles by Walhovd, K.B. Hotlight (NEW!) What's Hotlight? American Journal of Neuroradiology 31:347-354, February 2010 © 2010 American Society of Neuroradiology BRAIN Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease K.B. Walhovd a ,b , A.M. Fjell a ,b , J. Brewer c ,d , L.K. McEvoy d , C. Fennema-Notestine e , D.J. Hagler, Jr d , R.G. Jennings d , D. Karow d , A.M. Dale c ,d and the Alzheimer's Disease Neuroimaging Initiative a From Department of Psychology (K.B.W., A.M.F.), CSHC, University of Oslo, Oslo, Norway b Department of Neuropsychology (K.B.W., A.M.F.), Ulleval University Hospital, Oslo, Norway c Departments of Neuroscience (J.B., A.M.D.) d Radiology (J.B., L.K.M., C.F.-N., D.J.H., R.G.J., D.K., A.M.D.) e Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, California. Please address correspondence to Kristine B. Walhovd, MD,Department of Psychology, CSHC, University of Oslo, POB 1094 Blindern, 0317 Oslo, Norway; e-mail: k.b.walhovd@psykologi.uio.no 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, 18 F 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 Home Subscribe Author Instructions Submit Online Search the AJNR Archives Feedback Help Copyright © 2010 by the American Society of Neuroradiology. Print ISSN: 0195-6108 Online ISSN: 1936-959X

Journal

American Journal of NeuroradiologyAmerican Journal of Neuroradiology

Published: Feb 1, 2010

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