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Description
FDG-PET has been proven so far to be a good modality for detecting functional brain changes in AD, for identifying changes in early AD, and in helping to differentiate AD from other causes of dementia. However, in recent years, novel MRI techniques, such as pCASL, showed to be promising in investigating brain metabolism and neurodegeneration.
In this work, a multiparametric approach is proposed to investigate the structure and the metabolism of the brain in a group of subjects with Mild Cognitive Impairment in order to verify whether Cerebral Blood Flow (CBF) measured by MRI can be used as a quantitative neuroimaging biomarker, alternative to FDG-PET, to differentiate disorders profiles and to assess quantitively the outcome in rehabilitative interventions.
A cohort of 78 subjects participated in the MRI study: 10 healthy elderly (HC, 8 females, F, mean age ± standard deviation = 73±4y) and 68 MCI subjects (32F, 76±5y). A half of the MCI subjects followed their natural lifestyle, while the other half underwent a multi-domain training for 7 months. The protocol provided to perform an MRI exam at T0 and a follow-up exam after 7 months (T7).
A Voxel Based Morphometry approach show to be able to detect CBF alterations of MCI subjects with respect to healthy controls at time zero and can pinpoint regional CBF increase after 7 months in the trained subjects. Moreover, an unsupervised clustering method proved to be effective in identifying four different structural neurodegeneration classes (on the basis of morphometry measurements derived from T1w structural imaging) which are associated also to different metabolic profiles as assessed by MRI-based CBF measurements.
This multiparametric approach shows to be promising in differentiating MCI subgroups and in monitoring MCI progress along time, as in the natural history of the disease as during pharmacological and non-pharmacological treatments.
