sup 18^F-FDG PET Database of Longitudinally Confirmed Healthy Elderly Individuals Improves Detection of Mild Cognitive Impairment and Alzheimer's Disease

sup 18^F-FDG PET Database of Longitudinally Confirmed Healthy Elderly Individuals Improves Detection of Mild Cognitive Impairment and Alzheimer's Disease

The normative reference sample is crucial for the diagnosis of Alzheimer's disease (AD) with automated ^sup 18^F-FDG PET analysis. We tested whether an ^sup 18^F-FDG PET database of longitudinally confirmed healthy elderly individuals ("normals," or NLs) would improve diagnosis of AD...

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Veröffentlicht in:The Journal of nuclear medicine (1978) 2007-07, Vol.48 (7), p.1129
Hauptverfasser: Mosconi, Lisa, Wai Hon Tsui, Pupi, Alberto, De Santi, Susan
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Accuracy
Alzheimer's disease
Clinical outcomes
Patients
Ratings & rankings
Studies
Testing
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container_issue 7
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container_title The Journal of nuclear medicine (1978)
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creator Mosconi, Lisa
Wai Hon Tsui
Pupi, Alberto
De Santi, Susan
description The normative reference sample is crucial for the diagnosis of Alzheimer's disease (AD) with automated ^sup 18^F-FDG PET analysis. We tested whether an ^sup 18^F-FDG PET database of longitudinally confirmed healthy elderly individuals ("normals," or NLs) would improve diagnosis of AD and mild cognitive impairment (MCI). Methods: Two ^sup 18^F-FDG PET databases of 55 NLs with 4-y clinical follow-up examinations were created: one of NLs who remained NL, and the other including a fraction of NLs who declined to MCI at follow-up. Each ^sup 18^F-FDG PET scan of 19 NLs, 37 MCI patients, and 33 AD patients was z scored using automated voxel-based comparison to both databases and examined for AD-related abnormalities. Results: Our database of longitudinally confirmed NLs yielded 1.4- to 2-fold higher z scores than did the mixed database in detecting ^sup 18^F-FDG PET abnormalities in both the MCI and the AD groups. ^sup 18^F-FDG PET diagnosis using the longitudinal NL database identified 100% NLs, 100% MCI patients, and 100% AD patients, which was significantly more accurate for MCI patients than with the mixed database (100% NLs, 68% MCI patients, and 94% AD patients identified). Conclusion: Our longitudinally confirmed NL database constitutes reliable ^sup 18^F-FDG PET normative values for MCI and AD. [PUBLICATION ABSTRACT]
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We tested whether an ^sup 18^F-FDG PET database of longitudinally confirmed healthy elderly individuals ("normals," or NLs) would improve diagnosis of AD and mild cognitive impairment (MCI). Methods: Two ^sup 18^F-FDG PET databases of 55 NLs with 4-y clinical follow-up examinations were created: one of NLs who remained NL, and the other including a fraction of NLs who declined to MCI at follow-up. Each ^sup 18^F-FDG PET scan of 19 NLs, 37 MCI patients, and 33 AD patients was z scored using automated voxel-based comparison to both databases and examined for AD-related abnormalities. Results: Our database of longitudinally confirmed NLs yielded 1.4- to 2-fold higher z scores than did the mixed database in detecting ^sup 18^F-FDG PET abnormalities in both the MCI and the AD groups. ^sup 18^F-FDG PET diagnosis using the longitudinal NL database identified 100% NLs, 100% MCI patients, and 100% AD patients, which was significantly more accurate for MCI patients than with the mixed database (100% NLs, 68% MCI patients, and 94% AD patients identified). Conclusion: Our longitudinally confirmed NL database constitutes reliable ^sup 18^F-FDG PET normative values for MCI and AD. 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Results: Our database of longitudinally confirmed NLs yielded 1.4- to 2-fold higher z scores than did the mixed database in detecting ^sup 18^F-FDG PET abnormalities in both the MCI and the AD groups. ^sup 18^F-FDG PET diagnosis using the longitudinal NL database identified 100% NLs, 100% MCI patients, and 100% AD patients, which was significantly more accurate for MCI patients than with the mixed database (100% NLs, 68% MCI patients, and 94% AD patients identified). Conclusion: Our longitudinally confirmed NL database constitutes reliable ^sup 18^F-FDG PET normative values for MCI and AD. 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We tested whether an ^sup 18^F-FDG PET database of longitudinally confirmed healthy elderly individuals ("normals," or NLs) would improve diagnosis of AD and mild cognitive impairment (MCI). Methods: Two ^sup 18^F-FDG PET databases of 55 NLs with 4-y clinical follow-up examinations were created: one of NLs who remained NL, and the other including a fraction of NLs who declined to MCI at follow-up. Each ^sup 18^F-FDG PET scan of 19 NLs, 37 MCI patients, and 33 AD patients was z scored using automated voxel-based comparison to both databases and examined for AD-related abnormalities. Results: Our database of longitudinally confirmed NLs yielded 1.4- to 2-fold higher z scores than did the mixed database in detecting ^sup 18^F-FDG PET abnormalities in both the MCI and the AD groups. ^sup 18^F-FDG PET diagnosis using the longitudinal NL database identified 100% NLs, 100% MCI patients, and 100% AD patients, which was significantly more accurate for MCI patients than with the mixed database (100% NLs, 68% MCI patients, and 94% AD patients identified). Conclusion: Our longitudinally confirmed NL database constitutes reliable ^sup 18^F-FDG PET normative values for MCI and AD. [PUBLICATION ABSTRACT]</abstract><cop>New York</cop><pub>Society of Nuclear Medicine</pub></addata></record>
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source EZB-FREE-00999 freely available EZB journals
subjects Accuracy
Alzheimer's disease
Clinical outcomes
Patients
Ratings & rankings
Studies
Testing
title sup 18^F-FDG PET Database of Longitudinally Confirmed Healthy Elderly Individuals Improves Detection of Mild Cognitive Impairment and Alzheimer's Disease
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