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Quantification of glial activation using positron emission tomography in neurodegenerative disease
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Fan-Z-2018-PhD-Thesis.pdf | Thesis | 9.16 MB | Adobe PDF | View/Open |
Title: | Quantification of glial activation using positron emission tomography in neurodegenerative disease |
Authors: | Fan, Zhen |
Item Type: | Thesis or dissertation |
Abstract: | Background: There is considerable evidence that neuroinflammation plays a significant role in neurodegenerative diseases, hence there is a need for glial activation measurements in Alzheimer’s disease (AD) with positron-emission tomography (PET). This thesis aims to 1) explore the quantification approach for novel glial activation tracers, 2) and develop new imaging techniques to evaluate biomarker interactions. Methods: [18F]GE180 and [11C]PBR28 for microglial activation were evaluated in 13 participants with AD and 13 with Mild Cognitive Impairment (MCI). [11C]BU99008 for astroglial activation was studied in 11 AD and MCI. Arterial input functions were acquired and full compartmental modelling, spectral analysis, graphic analysis, cluster analysis and standardized uptake value were evaluated. The VOI (Volume of interest) Prediction Tool (biomarker co-localization) and Individual Correlation Mapping (ICM) (biomarker correlation) were developed to assess biomarker interactions. Results: Based on Akaike Information Criterion, a two-tissue compartmental model demonstrated the best fit for [18F]GE180 and [11C]BU99008, while [11C]PBR28 fitted the two-tissue model with a vascular component. Impulse response function (IRF) generated by spectral analysis, have shown good consistency with compartmental modelling (R2>0.8, p<0.0001). [18F]GE180 revealed high plasma binding and low VT (AD=0.21 ±0.06 mL·cm-3, HC=0.17 ±0.05 mL·cm-3) in the brain. For amyloid-positive patients, I discovered 25% (p<0.01) and 19% (p<0.03) group-level increase in [11C]PBR28 and [11C]BU99008 VT, respectively. The interactive VOI of microglial activation, amyloid and tau has demonstrated a linear prediction model of individual annual cognitive decline (R2=0.86, p<0.0001). ICM demonstrated a positive correlation (R2=0.7, p<0.03) between the volume of biomarker interaction and the severity of the cognitive impairment on individual basis. Conclusion: This work explores the best quantification method for three new tracers and demonstrates elevation of glial activation in patients with neurodegenerative disease. The novel imaging techniques demonstrate an individualized association between biomarker interaction and cognitive performance, indicating the importance of biomarker interactions in AD. |
Content Version: | Open Access |
Issue Date: | Oct-2018 |
Date Awarded: | Jun-2019 |
URI: | http://hdl.handle.net/10044/1/89853 |
DOI: | https://doi.org/10.25560/89853 |
Copyright Statement: | Creative Commons Attribution NonCommercial NoDerivatives Licence |
Supervisor: | Gentleman, Steve Hinz, Rainer |
Sponsor/Funder: | Alzheimer’s Research UK GE Healthcare National Institute for Health Research (Great Britain) Imperial College Healthcare NHS Trust Medical Research Council (Great Britain) Dementia Platforms UK (DPUK) |
Department: | Department of Medicine |
Publisher: | Imperial College London |
Qualification Level: | Doctoral |
Qualification Name: | Doctor of Philosophy (PhD) |
Appears in Collections: | Medicine PhD theses |
This item is licensed under a Creative Commons License