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Early identification of MCI converting to AD: a FDG PET study

  • Marco Pagani
  • Flavio Nobili
  • Silvia Morbelli
  • Dario Arnaldi
  • Alessandro Giuliani
  • Johanna Öberg
  • Nicola Girtler
  • Andrea Brugnolo
  • Agnese Picco
  • Matteo Bauckneht
  • Roberta Piva
  • Andrea Chincarini
  • Gianmario Sambuceti
  • Cathrine Jonsson
  • Fabrizio De Carli
Original Article

Abstract

Purpose

Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer’s disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not.

Methods

FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy.

Results

The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients.

Conclusion

In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Keywords

Alzheimer’s disease Mild cognitive impairment Conversion to AD Positron emission tomography Support vector machine Volume of interest analysis 

Notes

Acknowledgments

The authors thank Ms. Katja Gasperini for helping with the English editing.

Compliance with ethical standards

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Conflicts of interest

None.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the principles of the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards

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Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Marco Pagani
    • 1
    • 2
  • Flavio Nobili
    • 3
  • Silvia Morbelli
    • 4
  • Dario Arnaldi
    • 3
  • Alessandro Giuliani
    • 5
  • Johanna Öberg
    • 6
  • Nicola Girtler
    • 3
    • 7
  • Andrea Brugnolo
    • 3
  • Agnese Picco
    • 3
  • Matteo Bauckneht
    • 4
  • Roberta Piva
    • 4
  • Andrea Chincarini
    • 8
  • Gianmario Sambuceti
    • 4
  • Cathrine Jonsson
    • 9
  • Fabrizio De Carli
    • 10
  1. 1.Institute of Cognitive Sciences and Technologies, CNRRomeItaly
  2. 2.Department of Nuclear MedicineKarolinska Hospital StockholmStockholmSweden
  3. 3.Clinical Neurology, Department of Neuroscience (DINOGMI)University of Genoa and IRCCS AOU San Martino-ISTGenoaItaly
  4. 4.Department of Nuclear Medicine, Department of Health Science (DISSAL)University of Genoa and IRCCS AOU San Martino-ISTGenoaItaly
  5. 5.Environment and Health DepartmentIstituto Superiore di SanitàRomeItaly
  6. 6.Department of Hospital PhysicsKarolinska HospitalStockholmSweden
  7. 7.Clinical PsychologyIRCCS AOU San Martino-ISTGenoaItaly
  8. 8.National Institute of Nuclear Physics (INFN), Genoa sectionGenoaItaly
  9. 9.Medical Radiation Physics and Nuclear Medicine, Imaging and PhysiologyKarolinska University HospitalStockholmSweden
  10. 10.Institute of Molecular Bioimaging and Physiology, CNR - Genoa UnitAOU San Martino-ISTGenoaItaly

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