INTEGRATING INFORMATION FROM FDG - AND AMYLOID PET FOR DETECTING DIFFERENT TYPES OF DEMENTIA IN OLDER PERSONS. A CASE-SERIES STUDY
L. Ruffini, F. Lauretani, M. Scarlattei, A. Ticinesi, T. Meschi, C. Ghetti, G. Serreli, M. Maggio, P. Caffarra
J Prev Alz Dis 2016;3(3):127-132
A significant progress has been made in the understanding of the neurobiology of Alzheimer’s disease. The post-mortem studies are the gold standard for a correct histopathological diagnosis, contributing to clarify the correlation with cognitive, behavioral and extra-cognitive domains. However, the relationship between pathological staging and clinical involvement remains challenging.
Neuroimaging, including positron emission tomography (PET) and magnetic resonance, could help to bridge the gap by providing in vivo information about disease staging. In the last decade, advances in the sensitivity of neuroimaging techniques have been described, in order to accurately distinguish AD from other causes of dementia.
Fluorodeoxyglucose-traced PET (FDG-PET) is able to measure cerebral metabolic rates of glucose, a proxy for neuronal activity, theoretically allowing detection of AD. Many studies have shown that this technique could be used in early AD, where reduced metabolic activity correlates with disease progression and predicts histopathological diagnosis. More recently, molecular imaging has made possible to detect brain deposition of histopathology-confirmed neuritic β-amyloid plaques (Aβ) using PET. Although Aβ plaques are one of the defining pathological features of AD, elevated levels of Aβ can be detected with this technique also in older individuals without dementia. This raises doubts on the utility of Aβ PET to identify persons at high risk of developing AD.
In the present case-series, we sought to combine metabolic information (from FDG-PET) and amyloid plaque load (from Aβ PET) in order to correctly distinguish AD from other forms of dementia. By selecting patients with Aβ PET + / FDG-PET + and Aβ PET – / FDG-PET +, we propose an integrated algorithm of clinical and molecular imaging information to better define type of dementia in older persons.
L. Ruffini ; F. Lauretani ; M. Scarlattei ; A. Ticinesi ; T. Meschi ; C. Ghetti ; G. Serreli ; M. Maggio ; P. Caffarra (2016): Integrating Information from FDG - and Amyloid PET for Detecting Different Types of Dementia in Older Persons. A Case-Series Study. The Journal of Prevention of Alzheimer’s Disease (JPAD). http://dx.doi.org/10.14283/jpad.2016.101