Skip to main content

Main menu

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI

User menu

  • Subscribe
  • My alerts
  • Log in
  • My Cart

Search

  • Advanced search
Journal of Nuclear Medicine
  • SNMMI
    • JNM
    • JNMT
    • SNMMI Journals
    • SNMMI
  • Subscribe
  • My alerts
  • Log in
  • My Cart
Journal of Nuclear Medicine

Advanced Search

  • Home
  • Content
    • Current
    • Ahead of print
    • Past Issues
    • JNM Supplement
    • SNMMI Annual Meeting Abstracts
    • Continuing Education
    • JNM Podcasts
  • Subscriptions
    • Subscribers
    • Institutional and Non-member
    • Rates
    • Journal Claims
    • Corporate & Special Sales
  • Authors
    • Submit to JNM
    • Information for Authors
    • Assignment of Copyright
    • AQARA requirements
  • Info
    • Reviewers
    • Permissions
    • Advertisers
  • About
    • About Us
    • Editorial Board
    • Contact Information
  • More
    • Alerts
    • Feedback
    • Help
    • SNMMI Journals
  • View or Listen to JNM Podcast
  • Visit JNM on Facebook
  • Join JNM on LinkedIn
  • Follow JNM on Twitter
  • Subscribe to our RSS feeds
OtherClinical Investigations

Prediction of Individual Clinical Outcome in MCI by Means of Genetic Assessment and 18F-FDG PET

Alexander Drzezga, Timo Grimmer, Matthias Riemenschneider, Nicola Lautenschlager, Hartwig Siebner, Panagiotis Alexopoulus, Satoshi Minoshima, Markus Schwaiger and Alexander Kurz
Journal of Nuclear Medicine October 2005, 46 (10) 1625-1632;
Alexander Drzezga
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Timo Grimmer
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Matthias Riemenschneider
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nicola Lautenschlager
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hartwig Siebner
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Panagiotis Alexopoulus
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Satoshi Minoshima
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Markus Schwaiger
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Alexander Kurz
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

Abstract

Patients with mild cognitive impairment (MCI) represent a risk population for progressing to dementia of the Alzheimer type (DAT). However, clinical criteria do not ensure reliable individual prognosis in these patients. The objective of this longitudinal, prospective study was to examine the value of 18F-FDG PET of cerebral glucose metabolism and of genetic susceptibility, as defined by an APOEε4–positive genotype, with regard to the early diagnosis of DAT in patients with MCI. Methods: In 30 patients with the diagnosis of MCI (16 female, 14 male; age, 70 ± 8 y), baseline and follow-up examinations (mean observation period, 16 mo) were performed. In all patients, the APOE genotype was assessed and cerebral glucose metabolism was evaluated at baseline using cranial 18F-FDG PET. Individual PET data were screened for findings suggestive of Alzheimer’s disease (AD), with the help of an automated computer program. After stereotactical normalization of the PET images, this program performs an observer-independent statistical comparison with an age-matched reference database (n = 22). Results: In 43% of all MCI subjects, a PET scan suggestive of AD pathology according to our predefined criteria was observed at baseline (PET+); 57% of all MCI patients were carriers of the APOE ε4 allele (e4+). In 40% of all patients, progression of symptoms within the observation period justified the clinical diagnosis of probable DAT at the time of follow-up reevaluation. Statistical evaluation revealed the best results for PET with regard to early diagnosis of DAT in MCI patients (sensitivity, 92%; specificity, 89%). Classification according to the APOE genotype was significantly less successful (sensitivity, 75%; specificity, 56%). However, a combination of both diagnostic tests allowed early diagnosis with either very high specificity (PET+ AND e4+: sensitivity, 67%; specificity, 100%) or very high sensitivity (PET+ OR e4+: sensitivity, 100%; specificity, 44%). Conclusion: 18F-FDG PET of cerebral glucose metabolism is a valuable diagnostic tool for the prediction of clinical outcome in individual MCI patients. Results are superior to the exclusive assessment of the APOE genotype. A combination of both functional imaging and genotyping may allow an early high-risk or low-risk stratification of patients with either very high sensitivity or very high specificity. This may be valuable, for example, for patient selection in scientific studies.

  • Alzheimer’s disease
  • mild cognitive impairment
  • PET
  • APOE genotype
  • predictive value

Footnotes

  • Received Apr. 6, 2005; revision accepted Jul. 11, 2005.

    For correspondence or reprints contact: Alexander Drzezga, MD, Nuklearmedizinische Klinik und Poliklinik, der Technischen Universität München, Klinikum rechts der Isar, Ismaninger Strasse 22, 81675 München, Germany

    E-mail: a.drzezga{at}lrz.tu-muenchen.de

View Full Text
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 46 (10)
Journal of Nuclear Medicine
Vol. 46, Issue 10
October 1, 2005
  • Table of Contents
  • About the Cover
  • Index by author
Print
Download PDF
Article Alerts
Sign In to Email Alerts with your Email Address
Email Article

Thank you for your interest in spreading the word on Journal of Nuclear Medicine.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Prediction of Individual Clinical Outcome in MCI by Means of Genetic Assessment and 18F-FDG PET
(Your Name) has sent you a message from Journal of Nuclear Medicine
(Your Name) thought you would like to see the Journal of Nuclear Medicine web site.
Citation Tools
Prediction of Individual Clinical Outcome in MCI by Means of Genetic Assessment and 18F-FDG PET
Alexander Drzezga, Timo Grimmer, Matthias Riemenschneider, Nicola Lautenschlager, Hartwig Siebner, Panagiotis Alexopoulus, Satoshi Minoshima, Markus Schwaiger, Alexander Kurz
Journal of Nuclear Medicine Oct 2005, 46 (10) 1625-1632;

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Prediction of Individual Clinical Outcome in MCI by Means of Genetic Assessment and 18F-FDG PET
Alexander Drzezga, Timo Grimmer, Matthias Riemenschneider, Nicola Lautenschlager, Hartwig Siebner, Panagiotis Alexopoulus, Satoshi Minoshima, Markus Schwaiger, Alexander Kurz
Journal of Nuclear Medicine Oct 2005, 46 (10) 1625-1632;
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

  • Article
    • Abstract
    • MATERIALS AND METHODS
    • RESULTS
    • DISCUSSION
    • CONCLUSION
    • Acknowledgments
    • Footnotes
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

Related Articles

  • THIS MONTH IN JNM
  • PubMed
  • Google Scholar

Cited By...

  • 18F-FDG PET Imaging in Neurodegenerative Dementing Disorders: Insights into Subtype Classification, Emerging Disease Categories, and Mixed Dementia with Copathologies
  • Predicting the Progression of Mild Cognitive Impairment Using Machine Learning: A Systematic, Quantitative and Critical Review
  • VGF in cerebrospinal fluid, when combined with conventional biomarkers, enhances prediction of conversion from mild cognitive impairment to Alzheimers Disease
  • Is Tau Imaging More Than Just Upside-Down 18F-FDG Imaging?
  • Diagnostic Value of 18F-FDG PET/CT Versus MRI in the Setting of Antibody-Specific Autoimmune Encephalitis
  • Inclusion criteria provide heterogeneity in baseline profiles of patients with mild cognitive impairment: comparison of two prospective cohort studies
  • Predictive value of APOE-{varepsilon}4 allele for progression from MCI to AD-type dementia: a meta-analysis
  • Magnetic resonance spectroscopy in the prediction of early conversion from amnestic mild cognitive impairment to dementia: a prospective cohort study
  • Tarot decks and PET scans: Predicting the future of MCI
  • Comparing predictors of conversion and decline in mild cognitive impairment
  • Comparison of 18F-FDG and PiB PET in Cognitive Impairment
  • Effect of APOE genotype on amyloid plaque load and gray matter volume in Alzheimer disease
  • Fluorodeoxyglucose-Positron-Emission Tomography, Single-Photon Emission Tomography, and Structural MR Imaging for Prediction of Rapid Conversion to Alzheimer Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis
  • Multicenter Standardized 18F-FDG PET Diagnosis of Mild Cognitive Impairment, Alzheimer's Disease, and Other Dementias
  • Positron emission tomography imaging in dementia
  • Maternal family history of Alzheimer's disease predisposes to reduced brain glucose metabolism
  • Role of Neuroimaging in Alzheimer's Disease, with Emphasis on Brain Perfusion SPECT
  • 18F-FDG PET Database of Longitudinally Confirmed Healthy Elderly Individuals Improves Detection of Mild Cognitive Impairment and Alzheimer's Disease
  • Google Scholar

More in this TOC Section

  • Cardiac Presynaptic Sympathetic Nervous Function Evaluated by Cardiac PET in Patients with Chronotropic Incompetence Without Heart Failure
  • Validation and Evaluation of a Vendor-Provided Head Motion Correction Algorithm on the uMI Panorama PET/CT System
  • An Investigation of Lesion Detection Accuracy for Artificial Intelligence–Based Denoising of Low-Dose 64Cu-DOTATATE PET Imaging in Patients with Neuroendocrine Neoplasms
Show more Clinical Investigations

Similar Articles

SNMMI

© 2025 SNMMI

Powered by HighWire