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The Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias

IRCCS San Raffaele · 2021
ClinicalTrials.gov · Datasets · License: Public Domain · 2021
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alzheimer-diseasehealthy-subjectsmild-cognitive-impairmentpositron-emission-tomography
The study aims to use advanced brainwave recordings of electroencephalogram (EEG) to understand early signs of Alzheimer's disease (AD) in people with mild memory problems, known as amnestic Mild Cognitive Impairment (MCI). The goals of the study are to: 1. Find early markers of Alzheimer by analyzing EEG recordings, the researchers hope to identify patterns that indicate the presence of Alzheimer's disease. They will compare these patterns with other brain scans, like Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) scans, and look at different biological markers in the participants' spinal fluid and genetic data. 2. Predict the risk of Alzheimer's disease. The study will try to find EEG patterns that can predict whether someone with MCI will develop full-blown Alzheimer's disease. The aim is to create a system that combines EEG data with other brain scans and genetic information to better understand the risk of disease progression. 3. Track changes over time: The research will also monitor changes in brain activity and structure over time to understand how Alzheimer's disease progresses. In addition to studying people with MCI, the researchers will also look at EEG patterns in people with mild Alzheimer's disease (MILD AD), frontotemporal dementia (FTD), and Lewy-body dementia (LBD) to see how these patterns differ across various brain conditions. This could help improve the accuracy of diagnosing these diseases and understanding their link to genetic factors.
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