Modeling the Relationships Between Functional Connectivity and Amyloid Deposition in Alzheimer's … (NCT04174287) | Clinical Trial Compass
UnknownPhase 2
Modeling the Relationships Between Functional Connectivity and Amyloid Deposition in Alzheimer's Disease
Taiwan300 participantsStarted 2019-03-28
Plain-language summary
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.
Who can participate
Age range55 Years – 80 Years
SexALL
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Inclusion criteria
✓. Age between 55-80 years.
✓. Patients population: Diagnosed as prodromal AD or mild AD dementia based on IWG-2 criteria.
✓. Normal control population: Cognitive unimpaired individual is defined as normal control in this study. Cognitive un-impaired normal control is defined as cognitive performance in the non-impaired range for that individual, defined as not mild cognitive impairment or demented. The normal control should have their clinical dementia rating score 0 AND Cognitive Ability Screening Instrument (CASI) scores rated \>50 percentile.
✓. Able to provide written informed consent with reliable caregiver in AD population. The participant should have reading ability OR 6/more years of formal education OR with working experiences.
Exclusion criteria
✕. Already receive outpatient clinic follow-ups with diseases that may affect the cognitive evaluation or presentation that include but not limited to Parkinsonism, Parkinson's disease dementia, epilepsy, schizophrenia, major depression, major psychiatric disorders, alcohol or drug abuse, major head trauma with consciousness loss.
✕. Severe progressive or unstable systemic disease that may interfere with the follow-up and test results. These included but not limited to cancer in the past 5 years, end stage renal or liver dysfunction, clinically significant myocardial infarction (New York Heart Association Functional Classification III-IV), Active disease that received admission in the past one year and unstable angina. Other diseases that were not listed but may interfere with the follow-up or test will be judged by the principle investigator.
What they're measuring
1
Amyloid Distribution Among Normal, Prodromal AD and AD Dementia Subjects Measured by Standardized Uptake Value Ratio (SUVR) as Assessed by 18F-AV45 amyloid PET Scan.