RESUMO
BACKGROUND: When Alzheimer's disease (AD) is occurring at an early onset before 65 years old, its clinical course is generally more aggressive than in the case of a late onset. We aim at identifying [[Formula: see text]F]florbetaben PET biomarkers sensitive to differences between early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD). We conducted [[Formula: see text]F]florbetaben PET/CT scans of 43 newly diagnosed AD subjects. We calculated 93 textural parameters for each of the 83 Hammers areas. We identified 41 independent principal components for each brain region, and we studied their Spearman correlation with the age of AD onset, by taking into account multiple comparison corrections. Finally, we calculated the probability that EOAD and LOAD patients have different amyloid-[Formula: see text] ([Formula: see text]) deposition by comparing the mean and the variance of the significant principal components obtained in the two groups with a 2-tailed Student's t-test. RESULTS: We found that four principal components exhibit a significant correlation at a 95% confidence level with the age of onset in the left lateral part of the anterior temporal lobe, the right anterior orbital gyrus of the frontal lobe, the right lateral orbital gyrus of the frontal lobe and the left anterior part of the superior temporal gyrus. The data are consistent with the hypothesis that EOAD patients have a significantly different [[Formula: see text]F]florbetaben uptake than LOAD patients in those four brain regions. CONCLUSIONS: Early-onset AD implies a very irregular pattern of [Formula: see text] deposition. The authors suggest that the identified textural features can be used as quantitative biomarkers for the diagnosis and characterization of EOAD patients.
RESUMO
BACKGROUND: The default-mode network (DMN) has been increasingly recognized as relevant to cognitive status. OBJECTIVES: To explore DMN changes in patients with relapsing-remitting (RR) multiple sclerosis (MS) and to relate these to the cognitive status. METHODS: Eighteen cognitively impaired (CI) and eighteen cognitively preserved (CP) RRMS patients and eighteen healthy controls (HCs), matched for age, sex and education, underwent neuropsychological evaluation and anatomical and resting-state functional MRI (rs-fMRI). DMN functional connectivity was evaluated from rs-fMRI data via independent component analysis. T2 lesion load (LL) was computed by a semi-automatic method and global and local atrophy was estimated by SIENAX and SPM8 voxel-based morphometry analyses from 3D-T1 images. RESULTS: When the whole group of RRMS patients was compared with HCs, DMN connectivity was significantly weaker in the anterior cingulate cortex, whereas it was significantly weaker in the core but stronger at the periphery of the posterior cingulate cortex. These findings were more evident in CP than CI patients. Observed DMN changes did not correlate with global atrophy or T2-LL, but were locally associated with regional grey matter loss. CONCLUSION: Relapsing-remitting multiple sclerosis patients show a consistent dysfunction of DMN at the level of the anterior node. DMN distribution changes in the posterior node may reflect a possible compensatory effect on cognitive performance.