Alzheimer's Disease Clinical Trial
Official title:
Modeling the Relationships Between Functional Connectivity and Amyloid Deposition in Alzheimer's Disease
Glucose is the main energy source of brain. Different neural degenerative diseases such as
Parkinson's disease or Alzheimer's disease have shown distinct brain glucose metabolic
patterns. FDG-PET is a established non-invasive method to measures cerebral glucose
metabolism and can be used to differentiate different types of neurodegenerative diseases
that anatomical imaging such as CT or MRI may not be able to differentiate. Among patients
whose Alzheimer's diseases have not been confirmed, the defects in brain glucose metabolism
can predict future amyloid plaque deposition. On the other hand, early amyloid plaque
deposition may predict the future occurrence of Alzheimer's disease as early as 15 years
before the onset. This research project is focusing on the sequential change of the two
biomarkers of brain glucose metabolism and amyloid plaque deposition and their correlation
with clinical symptoms in patients with Alzheimer's disease. The subjects in this project
will be including normal controls without cognitive impairment, patients with prodromal AD or
AD. The relationship between functional connectivity of FDG-PET and amyloid deposition in
different group of patients will be investigated. Further correlation with tau PET will be
also discussed.
In the imaging process part of this project, the standard tool, SPM (Spatial Parametric
Mapping) will be applied. As machine learning/deep learning methodology is gaining popularity
in medical imaging research community, collaboration with artificial intelligence core
laboratory at Linkou will be pursued to investigate hidden correlation between functional
connectivity, amyloid plaque, progress of clinical symptoms with time that previous
statistical methods may not be able to find.
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