Abstract
MRI bears great potential for advancing our knowledge of the early pathological substrates
of Alzheimer’s disease and can add valuable information for the disease diagnosis and
understanding. Biologically characterizing MRI-derived features will provide us with
non-invasive in vivo information about the pathophysiological processes that interact with
early Aβ deposition and promote pathogenesis of AD from its preclinical asymptomatic
stages. The overall aim of this thesis was therefore to characterize the value of MRI-derived
phenotypes in preclinical AD research. To this end, the following questions were addressed:
1. How can we address the methodological challenges of performing large neuroimaging
multicenter studies with preclinical AD cohorts?
2. What are the structural and functional brain endophenotypes that are altered in
relationship with early AD proteinopathies measured in CSF?
3. What is the impact of vascular factors in AD, and how can this be measured using MRI
features?
4. What are the genetic pathways that determine distinct imaging features?
In Chapter 2, I present the EPAD cohort through its characterization based on pathological
markers of Alzheimer’s disease, and present our semi-automatic multimodal and multisite
pipeline to curate, preprocess and quality control the EPAD MRI dataset, and compute
image-derived phenotypes. In Chapter 3, I present alterations of brain functional
and structural properties in the preclinical stages of AD, as measured by multimodal
quantitative MRI techniques. Chapter 4 investigates the relevance of MRI for the
understanding of possible alternative early pathological mechanisms, specifically focusing
on the role of semi-quantitative and quantitative vascular markers and their association
with AD pathology. Chapter 5 aims at providing evidence of the genetic bases and associated
polygenic pathways promoting distinct imaging biomarkers alterations in preclinical AD.
This thesis is concluded with a general discussion in Chapter 6.
Original language | English |
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Qualification | PhD |
Awarding Institution |
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Supervisors/Advisors |
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Award date | 23 Feb 2024 |
DOIs | |
Publication status | Published - 23 Feb 2024 |
Keywords
- MRI
- brain connectivity
- Alzheimer's disease
- preclinical stages