1,721,758 research outputs found
Metodologie Statistiche per l'Analisi delle Immagini Mediche: la Neuroanatomia Computazionale
No full textNon-invasive brain stimulation in dementia: a complex network story
No full textNon-invasive brain stimulation (NIBS) is emerging as a promising rehabilitation tool for a number of neurodegenerative diseases. However, the therapeutic mechanisms of NIBS are not completely understood. In this review, we will summarize NIBS results in the context of brain imaging studies of functional connectivity and metabolites to gain insight into the possible mechanisms underlying recovery. We will briefly discuss how the clinical manifestations of common neurodegenerative disorders may be related with aberrant connectivity within large-scale neural networks. We will then focus on recent studies combining resting-state functional magnetic resonance imaging with NIBS to delineate how stimulation of different brain regions induce complex network modifications, both at the local and distal level. Moreover, we will review studies combining magnetic resonance spectroscopy and NIBS to investigate how microscale changes are related to modifications of large-scale networks. Finally, we will re-examine previous NIBS studies in dementia in light of this network perspective. A better understanding of NIBS impact on the functionality of large-scale brain networks may be useful to design beneficial treatments for neurodegenerative disorders
EMBARK study
No full textPhase 3b Open-Label, Multicenter, Safety Study of BIIB037 (aducanumab) in Subjects with Alzheimer’s disease Who Had Previously Participated in the Aducanumab Studies 221AD103, 221AD301, 221AD302 and 221AD205.
Data EDC pdf files End Of study / IRT site audit file / WCG dat
Brain networks stimulation in dementia: insights from functional imaging
No full textPurpose of review: Noninvasive brain stimulation (NIBS) is increasingly used in the field of dementia as a therapeutic option; however, evidence of clinical efficacy is limited, and the mechanism of action remains unknown. This review summarizes how functional imaging could contribute to the design of targeted and effective NIBS interventions for dementia. Recent findings: Resting-state functional magnetic resonance imaging (fMRI) has largely contributed to understanding brain dysfunction in dementia by identifying disease-specific networks. Resting-state fMRI might inform on a number of factors critical for the conduction of effective NIBS trials, such as definition of stimulation paradigms and choice of the stimulation target. In addition, fMRI may contribute to the understanding of the mechanisms of action of NIBS, and provide a tool to monitor treatment efficacy. Summary: Functional imaging is a promising approach for the development of hypothesis-driven, targeted stimulation approaches in the field of dementia
AMYPAD Diagnostic and Patient Management Study (DPMS)
No full textThe AMYPAD Diagnostic and Patient Management Study (DPMS) has selected and is following-up a memory clinic population suspected of possible Alzheimer's disease (AD), focusing on those with subjective cognitive decline (SCD), mild cognitive impairment (MCI) and dementia where Alzheimer's disease is in the differential diagnosis, to determine the usefulness of β-amyloid imaging with regards to diagnostic confidence, decision trees, change in diagnosis, and alterations between planned and actual patient management plans
Insights into single-timepoint ASL hemodynamics: what visual assessment and spatial coefficient of variation can tell
No full textPurpose: Arterial spin labeling (ASL) represents a noninvasive perfusion biomarker, and, in the study of nonvascular disease, the use of the single-timepoint ASL technique is recommended. However, the obtained cerebral blood flow (CBF) maps may be highly influenced by delayed arterial transit time (ATT). Our aim was to assess the complexity of hemodynamic information of single-timepoint CBF maps using a new visual scale and comparing it with an ATT proxy, the "coefficient of spatial variation" (sCoV). Material and methods: Individual CBF maps were estimated in a memory clinic population (mild cognitive impairment, dementia and cognitively unimpaired controls) and classified into four levels of delayed perfusion based on a visual rating scale. Calculated measures included global/regional sCoVs and common CBF statistics, as mean, median and standard deviation. One-way ANOVA was performed to compare these measures across the four groups of delayed perfusion. Spearman correlation was used to study the association of global sCoV with clinical data and CBF statistics. Results: One hundred and forty-four participants (72 ± 7 years, 53% women) were included in the study. The proportion of maps with none, mild, moderate, and severe delayed perfusion was 15, 20, 37, and 28%, respectively. SCoV demonstrated a significant increase (p < 0.05) across the four groups, except when comparing none vs mild delayed perfusion groups (pBonf > 0.05). Global sCoV values, as an ATT proxy, ranged from 67 ± 4% (none) to 121 ± 24% (severe delayed) and were significantly associated with age and CBF statistics (p < 0.05). Conclusion: The impact of ATT delay in single-time CBF maps requires the use of a visual scale or sCoV in clinical or research settings
White matter lesions in the elderly: effect on brain plasticity and reserve
No full textThe effect of white matter lesions (WMLs) on the brain of elderly individuals is unclear. Most debate has focused on the clinical effect of WMLs on cognitive impairment. Large cross-sectional and longitudinal clinic- and population-based studies suggest that the effect of WMLs on global cognitive performance is relatively small, only individuals with the most severe degrees of WMLs having clinically relevant effects. Here, we review recent data suggesting that WMLs might affect brain function through impairment of brain plasticity and reserve. The clinical effect consists in inability of the brain to respond to interventions such as psychotropic drug medications or rehabilitative interventions
Probabilistic disease progression modeling to characterize diagnostic uncertainty: application to staging and prediction in Alzheimer's disease
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