Search

Background and ObjectiveThis was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre–mild cognitive impairment [pre–MCI]).MethodsData were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism.ResultsA total of 105 participants (SCD = 49, pre–MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions.DiscussionFDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre–MCI. These results indicate that SCD and pre–MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.

Background and objectives: Amyloid-related imaging abnormalities suggestive of vasogenic edema or sulcal effusion (ARIA-E) are the most common adverse events complicating Alzheimer's disease (AD) immunotherapy with anti-amyloid-beta (Aβ) monoclonal antibodies (mAbs). ARIA-E can also occur spontaneously in cerebral amyloid angiopathy-related inflammation (CAA-ri), a rare autoimmune encephalopathy associated with increased cerebrospinal fluid (CSF) levels of anti-Aβ autoantibodies. Although the pathophysiological mechanisms of ARIA-E remain to be fully elucidated, experimental evidence from ex-vivo studies suggest that gantenerumab and aducanumab enable microglial activation. However, the in vivo evidence for a direct association between neuroinflammation and ARIA-E in patients with high CSF anti-Aβ (auto)antibody levels has never been demonstrated. Methods: Spatial distribution and temporal variations of microglial activation associated with ARIA-E and CSF anti-Aβ autoantibody levels at (sub)acute presentation and after corticosteroid therapy, in a longitudinal case series of patients with CAA-ri, an increasingly recognized spontaneous model of the iatrogenic ARIA-E in AD immunotherapy. Multimodal and multiparametric magnetic resonance imaging (MRI) for CAA and ARIA-E quantification, as measured with validated MRI scoring systems; CSF testing for anti-Aβ autoantibodies and AD biomarkers; 11C-PK11195 positron emission tomography (PET) for activated microglia. Results: At (sub)acute presentation, we found focal peaks of microglial activation having a greater spatial co-localization with ARIA-E compared to chronic age-related white matter change (ARWMC) imaging abnormalities. The severity of ARIA-E and the magnitude of the associated microglial activation was greater in patients having AD and severe CAA concomitant disease, compared to patients having CAA only. CSF anti-Aβ autoantibodies at presentation were high in all patients and markedly decreased at post-treatment follow-up, in parallel with clinical resolution of acute symptoms, reduced ARIA-E severity, and reduced microglial activation. Discussion: Our findings extend the current notion of ARIA-E by providing the first in vivo 11C-PK11195-PET evidence for an association between microglial activation and the magnitude and severity of ARIA-E in patients with increased CSF concentration of anti-Aβ autoantibodies and comorbid AD and CAA disease..Our results highlight CSF testing for anti-Aβ autoantibodies as a promising diagnostic, prognostic, and therapy response biomarker to help guide future treatment and management decisions in real clinical practice and clinical trials.

Purpose: The aim of this study was to investigate the role of 18F-FDG PET/CT in predicting pathological prognostic factors, including tumor type and International Federation of Gynecology and Obstetrics (FIGO) score, in gestational trophoblastic disease (GTD). Methods: Retrospective monocentric study including 24 consecutive patients who underwent to 18F-FDG PET/CT from May 2005 to March 2021 for GTD staging purpose. The following semiquantitative PET parameters were measured from the primary tumor and used for the analysis: maximum standardized uptake value (SUVmax), SUVmean, metabolic tumor volume (MTV) and total lesion glycolisis (TLG). Statistical analysis included Spearman correlation coefficient to evaluate the correlations between imaging parameters and tumor type (nonmolar trophoblastic vs postmolar trophoblastic tumors) and risk groups (high vs low, defined according to the FIGO score), whereas area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess the predictive value of the PET parameters. Mann-Whitney U test was used to further describe the parameter's potential in differentiating the populations. Results: SUVmax and SUVmean resulted fair (AUC, 0.783; 95% confidence interval [CI], 0.56-0.95) and good (AUC, 0.811; 95% CI, 0.59-0.97) predictors of tumor type, respectively, showing a low (ρ = 0.489, adjusted P = 0.030) and moderate (ρ = 0.538, adjusted P = 0.027) correlation. According to FIGO score, TLG was instead a fair predictor (AUC, 0.770; 95% CI, 0.50-0.99) for patient risk stratification. Conclusions: 18F-FDG PET parameters have a role in predicting GTD pathological prognostic factors, with SUVmax and SUVmean being predictive for tumor type and TLG for risk stratification.