Imaging the future brain: Neuroimaging markers for dementia predicition

The overall aim of this thesis is to investigate the role of magnetic resonance imaging
in identifying individuals at high risk of dementia, to assess how neuroimaging can
enhance the performance of dementia prediction models, and to explore strategies
for the implementation of such models in clinical practice.
Chapter 2 focusses on the role of white matter characteristics, as measured on MRI,
in predicting neurodegeneration within the population-based Rotterdam Study. In
Chapter 2.1, I investigate distinct white matter signatures using multimodal brain
MRI. We subsequently assess the underlying risk profiles of the signatures and their
risk of dementia, stroke, and mortality. Chapter 2.2 compares the predictive value of
multiple diffusion imaging measures for dementia and cognitive decline.
Chapter 3 revolves around volumetric measurements of grey matter and which areas
have an important role in dementia prediction. In Chapter 3.1, I investigate which
subcortical grey matter structures are independently associated with risk of dementia
across multiple cohorts, consisting of individuals with subjective cognitive decline or
mild cognitive impairment. Chapter 3.2 presents a replication study assessing the
prognostic value of a novel cortical thickness signature for dementia, comparing its predictive performance with other grey matter measures, including hippocampal
volume and cortical thickness of the whole brain.
Chapter 4 sheds light on the development and potential implementation of a
dementia prediction model in clinical practice. In Chapter 4.1, I investigate the
attitude of the public towards dementia risk prediction models. Chapter 4.2 focusses
on the development and validation of a prediction model for dementia.