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
Research ArticleClinical Investigation

Early-Phase 18F-Florbetapir and 18F-Flutemetamol Images as Proxies of Brain Metabolism in a Memory Clinic Setting

Cecilia Boccalini, Débora Elisa Peretti, Federica Ribaldi, Max Scheffler, Sara Stampacchia, Szymon Tomczyk, Cristelle Rodriguez, Marie-Louise Montandon, Sven Haller, Panteleimon Giannakopoulos, Giovanni B. Frisoni, Daniela Perani and Valentina Garibotto
Journal of Nuclear Medicine February 2023, 64 (2) 266-273; DOI: https://doi.org/10.2967/jnumed.122.264256
Cecilia Boccalini
1Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland;
2Vita-Salute San Raffaele University, Milan, Italy;
3In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Débora Elisa Peretti
1Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Federica Ribaldi
4Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland;
5Memory Clinic, Geneva University Hospitals, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Max Scheffler
6Division of Radiology, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sara Stampacchia
1Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Szymon Tomczyk
4Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Cristelle Rodriguez
7Division of Institutional Measures, Medical Direction, University Hospitals of Geneva, Geneva, Switzerland;
8Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Marie-Louise Montandon
8Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland;
9Department of Rehabilitation and Geriatrics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sven Haller
10CIMC–Centre d’Imagerie Médicale de Cornavin, Geneva, Switzerland;
11Faculty of Medicine of University of Geneva, Geneva, Switzerland;
12Division of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden;
13Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Panteleimon Giannakopoulos
7Division of Institutional Measures, Medical Direction, University Hospitals of Geneva, Geneva, Switzerland;
8Department of Psychiatry, Faculty of Medicine, University of Geneva, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Giovanni B. Frisoni
4Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland;
5Memory Clinic, Geneva University Hospitals, Geneva, Switzerland;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Daniela Perani
2Vita-Salute San Raffaele University, Milan, Italy;
3In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy;
14Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Valentina Garibotto
1Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland;
15Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland; and
16CIBM Center for Biomedical Imaging, Geneva, Switzerland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Supplemental
  • Info & Metrics
  • PDF
Loading

Article Figures & Data

Figures

  • Tables
  • Additional Files
  • Figure
    • Download figure
    • Open in new tab
    • Download powerpoint
  • FIGURE 1.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 1.

    Correlation between eFBP/eFMM and 18F-FDG PET SUVR. Scatterplots showing association between eFBP/eFMM SUVR (y-axis) in AAL regions and their respective 18F-FDG SUVR (x-axis). Results are presented for whole sample and separately for subgroups divided according to Aβ status. Lines resulting from linear regression are shown in blue. R and P values are given in the upper left corner. FBP = florbetapir; FMM = flutemetamol; eFBP = early FBP; eFMM = early FMM; Aβ− = amyloid negative; Aβ+ = amyloid positive.

  • FIGURE 2.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 2.

    Hypometabolic and hypoperfusion patterns at the single-subject level. (A) Patterns of 18F-FDG PET hypometabolism and eFBP/eFMM hypoperfusion in single individuals. Hypometabolism maps, hypoperfusion maps, and their overlap were imposed on standard Montreal Neurological Institute template. These maps were obtained from binarization of single-subject 18F-FDG PET SPM T-maps and eFBP/eFMM SPM T-maps (P < 0.05 uncorrected, k > 100). The Dice similarity index is reported to the right of the brain template of each subject. (B) Clinical groups ordered according to degree of similarity between brain hypometabolism and hypoperfusion, as measured by Dice similarity index average. Lower-to-higher values of Dice indicate increasing degree of overlap. DEM = dementia; eFBP = early florbetapir; eFMM = early flutemetamol; Aβ+ = amyloid positive; Aβ− = amyloid negative; AD = Alzheimer disease; MCI = mild cognitive impairment.

  • FIGURE 3.
    • Download figure
    • Open in new tab
    • Download powerpoint
    FIGURE 3.

    Discriminative performance of eFBP/eFMM and 18F-FDG PET SUVR. ROC curves showing diagnostic performance of 18F-FDG PET and eFBP/eFMM SUVR in AD composite meta-ROI for distinguishing AD patients from HC. AUCs for eFBP/eFMM and 18F-FDG PET are shown in blue and green, respectively. Results of De Long test comparing 2 AUCs (eFBP/eFMM vs. 18F-FDG PET) are given in bottom box. A+ = Aβ-positive; N+ = neurodegeneration-positive; AUC = area under the curve; FBP = florbetapir; FMM = flutemetamol; AD = Alzheimer disease; HC = healthy controls.

Tables

  • Figures
  • Additional Files
    • View popup
    TABLE 1.

    Demographic Characteristics of Subjects

    CharacteristicWhole sampleFBP groupFMM groupP*
    n1669472
    Age73.18 ± 6.3574.27 ± 5.54871.76 ± 7.0680.012
    Sex0.425
     Female985840
     Male683632
    MMSE25.92 ± 4.0026.12 ± 3.85725.66 ± 4.2020.471
    Aβ status0.980
     Negative703931
     Positive935241
    Clinical groups according to Aβ status
     Aβ+ AD dementia18135
     Aβ− dementia321
     Aβ+ MCI523122
     Aβ− MCI21911
     Aβ+ CU301119
     Aβ− CU (HC)422814
    • ↵* From t test comparing data from eFBP and eFMM subgroups.

    • MMSE = Mini-Mental State Examination; FBP = florbetapir; FMM = flutemetamol; n = number; Aβ− = amyloid negative; Aβ+ = amyloid positive; AD = Alzheimer disease; MCI = mild cognitive impairment; CU = cognitively unimpaired; HC = healthy controls.

    • Qualitative data are number; continuous data are mean ± SD.

    • View popup
    TABLE 2.

    Contingency Table Reporting Frequency of Different Hypometabolism and Hypoperfusion Patterns in Whole Sample

    Hypoperfusion pattern
    Hypometabolism patternAD-likeFTD-likeDLB-likeLimbic-likeUnclassifiedNormalTotal
    AD-like301042239
    FTD-like09010010
    DLB-like0030003
    Limbic-like000140014
    Unclassified000124126
    Normal200012932
    Total32112192832124
    • AD = Alzheimer disease; FTD = frontotemporal dementia; DLB = dementia with Lewy bodies.

    • View popup
    TABLE 3.

    Distribution of Hypometabolism Patterns and Their Voxel-by-Voxel Concordance with Hypoperfusion Maps in Clinical Groups

    18F-FDG hypometabolism patternDementiaMCICUWhole group
    Sample (n = 21)Dice*% visual matchSample (n = 73)Dice*% visual matchSample (n = 30)Dice*% visual matchSample (n = 124)Dice% visual match
    AD-like10 (all Aβ+)0.632 ± 0.1599025 (all Aβ+)0.459 ± 0.178684 (all Aβ+)0.611 ± 0.13510039 (all Aβ+)0.516 ± 0.18577
    FTD-like5 (3 Aβ+,   2 Aβ−)0.483 ± 0.201805 (3 Aβ+,  2 Aβ−)0.531 ± 0.128100010 (6 Aβ+,  4 Aβ−)0.507 ± 0.16190
    DLB-like03 (2 Aβ+,  1 Aβ−)0.467 ± 0.23610003 (2 Aβ+,  1 Aβ−)0.467 ± 0.236100
    Limbic-like013 (9 Aβ+,  4 Aβ−)0.504 ± 0.0781001 (all Aβ+)0.52110014 (10 Aβ+,  4 Aβ−)0.504 ± 0.075100
    Unclassified6 (5 Aβ+,   1 Aβ−)0.621 ± 0.0718313 (8 Aβ+,  5 Aβ−)0.498 ± 0.2051007 (all Aβ+)0.381 ± 0.2938626 (20 Aβ+,  6 Aβ−)0.499 ± 0.21792
    Normal014 (6 Aβ+,  8 Aβ−)86†18 (all Aβ+)94†32 (24 Aβ+,  8 Aβ−)90†
    • ↵* Average ± SD.

    • ↵† Percentage of patients consistently negative on 18F-FDG and early-phase scans.

    • FTD = frontotemporal dementia; DLB = dementia with Lewy bodies; MCI = mild cognitive impairment; CU = cognitively unimpaired; AD = Alzheimer disease.

Additional Files

  • Figures
  • Tables
  • Supplemental Data

    Files in this Data Supplement:

    • Supplemental Data
PreviousNext
Back to top

In this issue

Journal of Nuclear Medicine: 64 (2)
Journal of Nuclear Medicine
Vol. 64, Issue 2
February 1, 2023
  • Table of Contents
  • Table of Contents (PDF)
  • About the Cover
  • Index by author
  • Complete Issue (PDF)
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.
Early-Phase 18F-Florbetapir and 18F-Flutemetamol Images as Proxies of Brain Metabolism in a Memory Clinic Setting
(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
Early-Phase 18F-Florbetapir and 18F-Flutemetamol Images as Proxies of Brain Metabolism in a Memory Clinic Setting
Cecilia Boccalini, Débora Elisa Peretti, Federica Ribaldi, Max Scheffler, Sara Stampacchia, Szymon Tomczyk, Cristelle Rodriguez, Marie-Louise Montandon, Sven Haller, Panteleimon Giannakopoulos, Giovanni B. Frisoni, Daniela Perani, Valentina Garibotto
Journal of Nuclear Medicine Feb 2023, 64 (2) 266-273; DOI: 10.2967/jnumed.122.264256

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Share
Early-Phase 18F-Florbetapir and 18F-Flutemetamol Images as Proxies of Brain Metabolism in a Memory Clinic Setting
Cecilia Boccalini, Débora Elisa Peretti, Federica Ribaldi, Max Scheffler, Sara Stampacchia, Szymon Tomczyk, Cristelle Rodriguez, Marie-Louise Montandon, Sven Haller, Panteleimon Giannakopoulos, Giovanni B. Frisoni, Daniela Perani, Valentina Garibotto
Journal of Nuclear Medicine Feb 2023, 64 (2) 266-273; DOI: 10.2967/jnumed.122.264256
Twitter logo Facebook logo LinkedIn logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Bookmark this article

Jump to section

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

Related Articles

  • PubMed
  • Google Scholar

Cited By...

  • PET-derived amyloid patterns in gray and white matter across the Alzheimers disease: A high-model-order ICA
  • Google Scholar

More in this TOC Section

  • First-in-Human Study of 18F-Labeled PET Tracer for Glutamate AMPA Receptor [18F]K-40: A Derivative of [11C]K-2
  • Detection of HER2-Low Lesions Using HER2-Targeted PET Imaging in Patients with Metastatic Breast Cancer: A Paired HER2 PET and Tumor Biopsy Analysis
  • [11C]Carfentanil PET Whole-Body Imaging of μ-Opioid Receptors: A First in-Human Study
Show more Clinical Investigation

Similar Articles

Keywords

  • neurodegeneration
  • early-phase amyloid PET
  • 18F-FDG PET
  • individual maps
SNMMI

© 2025 SNMMI

Powered by HighWire