Ignite Creation Date:
2025-12-24 @ 6:50 PM
Ignite Modification Date:
2025-12-28 @ 2:53 PM
Study NCT ID:
NCT06826157
Status:
ENROLLING_BY_INVITATION
Last Update Posted:
2025-02-17
First Post:
2024-12-04
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
The Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias
Sponsor:
IRCCS San Raffaele
Organization:
Study Overview
Official Title:
Assessing the Role of Advanced Electroencephalographic Data as Marker of Pathology and Prognosis in Primary Dementias
Status:
ENROLLING_BY_INVITATION
Status Verified Date:
2025-02
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
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.
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.
Detailed Description:
The main aim of the project is to examine resting-state high definition EEG cortical sources of participants diagnosed with amnestic MCI with the goal of:
\- exploring EEG-markers of Alzheimer's disease pathology and their relationships with both conventional and non-conventional brain MRI data. Researchers will explore these relationships after grouping participants according to their cerebrospinal fluid (CSF) biomarkers profile.
Researchers will explain further relationships through brain Positron Tomography Emission with fluorodeoxyglucose (PET-FDG) data performed during clinical diagnostic work-up and with Apolipoprotein E (APOE) gene profile.
* prospectively identifying EEG-markers predictive of clinical conversion to full-blown AD dementia and defining an algorithm for risk stratification by combining them with brain MRI, brain FDG-PET and genetic data;
* assessing the longitudinal changes of electrophysiological and MRI signals throughout the AD neuropathology progression;
The secondary aim of the project is to assess the accuracy of the Alzheimer-related EEG signal patterns identified in the MCI group. This will be done by comparing the EEG data with the APOE genetic information in a group of patients diagnosed with mild dementia due to Alzheimer's disease, frontotemporal dementia and Lewy-Body dementia
\- exploring EEG-markers of Alzheimer's disease pathology and their relationships with both conventional and non-conventional brain MRI data. Researchers will explore these relationships after grouping participants according to their cerebrospinal fluid (CSF) biomarkers profile.
Researchers will explain further relationships through brain Positron Tomography Emission with fluorodeoxyglucose (PET-FDG) data performed during clinical diagnostic work-up and with Apolipoprotein E (APOE) gene profile.
* prospectively identifying EEG-markers predictive of clinical conversion to full-blown AD dementia and defining an algorithm for risk stratification by combining them with brain MRI, brain FDG-PET and genetic data;
* assessing the longitudinal changes of electrophysiological and MRI signals throughout the AD neuropathology progression;
The secondary aim of the project is to assess the accuracy of the Alzheimer-related EEG signal patterns identified in the MCI group. This will be done by comparing the EEG data with the APOE genetic information in a group of patients diagnosed with mild dementia due to Alzheimer's disease, frontotemporal dementia and Lewy-Body dementia
Study Oversight
Has Oversight DMC:
True
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: