Bollack, Ariane;
(2024)
Capturing Alzheimer's Disease Progression through PET imaging.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Alzheimer’s disease (AD) is one of the major challenges to healthcare and society. With an ageing population, the number of individuals affected by AD will increase, causing substantial emotional and economic burdens to patients and their families. Longitudinal studies using positron emission tomography (PET) can help monitor the evolution of AD by tracking spatiotemporal changes in amyloid and tau burden, the two primary pathological hallmarks of AD. This is especially valuable in the earliest stages of the disease beginning a decade or more before clinically observable symptoms. The use of longitudinal PET studies is however hampered by uncertainties in measuring amyloid and tau changes with sufficient precision and accuracy. The overarching aim of this PhD is to provide more accurate and precise markers of AD evolution, improving clinical trial design and aiding disease monitoring. Therefore, the work presented here addresses two main questions: how to improve PET quantification methodology; and how to translate research innovations into clinical practice. To address the former, technical and biological sources of variability in longitudinal PET are first characterised before providing recommendations on how to mitigate them. Novel, data-driven amyloid metrics conceived to improve PET quantification are then evaluated. Last, a framework for designing longitudinal PET processing and analysis pipelines and evaluating their performance is detailed. To help translate research progress into clinical settings, the notion of reliable amyloid accumulation beyond measurement variability is investigated, and optimal levels of amyloid burden predictive of future accumulation are assessed. Finally, this thesis outlines contributions to the technical evaluation of a PET quantification software for submission to regulatory bodies, and to the proposal supporting a tracer-independent amyloid metric to be endorsed as a biomarker in Europe. Overall, this work suggests tools to enhance precision in PET measurements leading to a deeper understanding of the AD’s onset and progression.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Capturing Alzheimer's Disease Progression through PET imaging |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2024. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10190026 |
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