The purpose of this thesis was to assess the utility and potential of amyloid PET imaging beyond its current implementation. To this end, a broad range of methodological opportunities were investigated, including the use of regional information available from amyloid PET images for both visual assessment and quantification, and the value of dynamic image acquisition in preclinical AD populations. First, knowledge gaps limiting the current use of amyloid PET imaging in the clinical trial settings and clinical routine were identified and put into context of the rationale and design of the AMYPAD PNHS and DPMS studies. Then, approaches for optimizing guidelines for the visual assessment of amyloid burden were investigated. Next, the spatial-temporal ordering of amyloid pathology as measured with PET imaging and the value of regional quantitation for characterizing disease stage and predicating disease progression was explored. Finally, the value of regional amyloid assessment and dynamic PET acquisition within the context of clinical trial design was assessed. In short, the main findings presented in this thesis are: 1. Considering the recent developments in the scientific/clinical trial settings, identifying the optimal use of amyloid PET imaging in an early population should be the current and future focus of research, aimed at improving subject selection and risk prediction models for secondary and primary prevention efforts. The PNHS study will focus on the possible advantages of implementing fully quantitative and regional instead of semi-quantitative and global amyloid PET assessments. In contrast, the main knowledge gaps in the clinical routine is a systematic assessment of clinical utility of amyloid PET. The DPMS study aims to fill this evidence gap with a randomized-controlled trial design and the baseline demographics of the final cohort support high generalizability of the study outcomes. 2. Visual assessment of parametric amyloid PET images derived from dynamic acquisition results in a higher agreement between readers and improved reliability of the final read classification in a cognitively unimpaired population. Yet, visual assessment by experienced readers of standard static images is able to detect early (sparse) amyloid pathology and grade its extent by documenting regional positivity. 3. Regional quantification can be used to identify a spatial-temporal ordering of amyloid burden. This information facilitates the development of a system to characterize disease stage based on amyloid PET and enables investigating the effect of early amyloid pathology on other early AD-related biomarkers, such as white matter microstructure as measured with diffusion tensor imaging. 4. Implementation of dynamic PET imaging and regional quantification reduces sample size requirements to measure treatment effect in anti-amyloid secondary and primary prevention trials. In addition, information on amyloid accumulation in early-stage regions improves the prediction of cognitive change in initially cognitively unimpaired individuals.
|Qualification||Doctor of Philosophy|
|Award date||30 Jun 2021|
|Place of Publication||s.l.|
|Publication status||Published - 1 Jul 2021|