Mild Cognitive Impairment (MCI): Predicting Conversion to Clinically Probable Alzheimer’s Disease with Fluoro-Deoxy-Glucose PET

  • J.-C. Baron
  • G. Chételat
  • B. Desgranges
  • F. Eustache
Conference paper
Part of the Research and Perspectives in Alzheimer’s Disease book series (ALZHEIMER)


Optimal implementation of disease-modifying treatment for sporadic Alzheimer’ s disease (AD) will require detection of patients at the pre-dementia stage. Resting-state mapping of brain glucose utilization with PET and 18F-fluorodeoxy-glucose (FDG) is sensitive to early changes in synaptic activity/density in neurodegenerative diseases such as AD. In this study, we assessed memory-impaired patients with mild cognitive impairment (MCI) and used voxel-based analysis to search for an FDG-PET profile associated with rapid conversion to AD.

We prospectively recruited 17 patients with neuropsychologically proven significant and isolated memory impairment fulfilling current criteria for amnestic MCI. We obtained resting-state 18FDG PET and followed each patient up for a fixed period of 18 months to assess conversion to AD based on NINDS-ADRDA criteria.

At the end of follow-up, seven patients had converted to AD (“converters”) and the remaining ten still fulfilled criteria for MCI (“non-converters”). Using SPM99, FDG uptake in the right temporo-parietal association cortex was significantly lower in converters relative to non-converters and discriminated the two groups without overlap. FDG uptake was also lower in the converters in the posterior cingulate cortex, but discrimination was less complete and high statistical significance was not maintained after controlling for MMSE score.

This study, using an objective and comprehensive voxel-based data analysis, suggests that FDG-PET may accurately identify rapid converters.


Mild Cognitive Impairment MMSE Score Mild Cognitive Impairment Patient Mild Cognitive Impairment Group Healthy Aged Control 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • J.-C. Baron
    • 1
  • G. Chételat
    • 2
  • B. Desgranges
    • 2
  • F. Eustache
    • 2
  1. 1.Dept. of NeurologyUniversity of CambridgeUK
  2. 2.INSERM E 218-University-CyceronCaenFrance

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