The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.
Effectiveness and Safety of 18F-FDG PET in the Evaluation of Dementia: A Review of the Recent Literature
Abstract
Imaging that can detect pathophysiologic change in the brain holds great promise for diagnostic assessment of patients with Alzheimer disease (AD) and dementia. Although a previous metaanalysis centering on literature from 1990 to 2000 showed a summary accuracy of 86% for (18)F-FDG PET for AD diagnosis, the clinical value was considered uncertain because of methodologic shortcomings. Review of the recent literature since 2000 demonstrates that the evidence for (18)F-FDG PET in assessment of dementia has increased with new studies that include autopsy confirmation, wide-diagnostic-spectrum recruitment in primary care settings, historical and prospective cohort studies, and multicenter data analyses. These data support the role of (18)F-FDG PET as an effective and useful adjunct to other diagnostic information in the assessment of patients with symptoms of dementia. Findings are in line with recently revised diagnostic criteria of AD that for the first time recognize the unique role of biomarker evidence in disease definition.
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Cites
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Metadata
- Authors
- Bohnen, N. I., Djang, D. S. W., Herholz, K., Anzai, Y., & Minoshima, S.
- Venue
- Journal of Nuclear Medicine
- Publisher
- Society of Nuclear Medicine
- Published
- 2011-12-15
- Volume
- 53
- Issue
- 1
- Pages
- 59-71
- ISSN
- 0161-5505 (ISSN-L)
- 2159-662X
- OpenAlex
- W2132680220
- Cited by
- 286
- References
- 96
- FWCI
- 15.17
- Type
- journal article
- Language
- en
- Open access
- closed
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- Bohnen, N. I., Djang, D. S. W., Herholz, K., Anzai, Y., & Minoshima, S. (2012). Effectiveness and Safety of 18F-FDG PET in the Evaluation of Dementia: A Review of the Recent Literature. Journal of Nuclear Medicine. https://doi.org/10.2967/jnumed.111.096578
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.