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Ann N Y Acad Sci. 2007 Feb;1097:114-45.

Imaging and CSF studies in the preclinical diagnosis of Alzheimer's disease.

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  • 1Center for Brain Health, NYU School of Medicine, Department of Psychiatry, 560 First Ave., New York 10016, USA. mony.deleon@med.nyu.edu

Abstract

It is widely believed that the path to early and effective treatment for Alzheimer's disease (AD) requires the development of early diagnostic markers that are both sensitive and specific. To this aim, using longitudinal study designs, we and others have examined magnetic resonance imaging (MRI), 2-fluoro-2-deoxy-d-glucose-positron emission tomography (FDG/PET), and cerebrospinal fluid (CSF) biomarkers in cognitively normal elderly (NL) subjects and in patients with mild cognitive impairment (MCI). Such investigations have led to the often replicated findings that structural evidence of hippocampal atrophy as determined by MRI, as well as metabolic evidence from FDG-PET scan of hippocampal damage, predicts the conversion from MCI to AD. In this article we present a growing body of evidence of even earlier diagnosis. Brain pathology can be detected in NL subjects and used to predict future transition to MCI. This prediction is enabled by examinations revealing reduced glucose metabolism in the hippocampal formation (hippocampus and entorhinal cortex [EC]) as well as by the rate of medial temporal lobe atrophy as determined by MRI. However, neither regional atrophy nor glucose metabolism reductions are specific for AD. These measures provide secondary not primary evidence for AD. Consequently, we will also summarize recent efforts to improve the diagnostic specificity by combining imaging with CSF biomarkers and most recently by evaluating amyloid imaging using PET. We conclude that the combined use of conventional imaging, that is MRI or FDG-PET, with selected CSF biomarkers incrementally contributes to the early and specific diagnosis of AD. Moreover, selected combinations of imaging and CSF biomarkers measures are of importance in monitoring the course of AD and thus relevant to evaluating clinical trials.

PMID:
17413016
[PubMed - indexed for MEDLINE]
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