Manning, Emily Ndakola; (2018) Automated subcortical brain segmentation using multispectral MRI for improved AD diagnosis and disease tracking. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

This thesis is a detailed investigation into subcortical changes in Alzheimer's disease (AD). Hippocampal volumes, shapes and diffusion metrics were investigated in different disease stages and presentations, and the ability of these metrics for disease group classification investigated. A new method for automated thalamic segmentation using multimodal imaging was developed and applied to two different datasets. Hippocampal volumes were found to be disproportionately affected by the apolipoprotein (APOE) e4 allele. Hippocampal volumes were also found to be reduced in subjects with the posterior cortical atrophy variant of AD. These changes were localized in the hippocampal tail region and hippocampal shape metrics were found to be superior to hippocampal volumes in differentiating these subjects from controls. The manual thalamic segmentation protocol developed was found to have good reliability, and a template library of thalamic segmentations was generated for use in automated pipelines. The manual segmentation protocol used both T1-weighted and diffusion magnetic resonance imaging (MRI) scans for improved segmentation accuracy. The template library was used for automatic segmentation of the thalamus and leave-one-out cross-validation revealed good segmentation reliability, better than that reported by the most widely used automated thalamic segmentation techniques. The thalami from subjects from the Alzheimer's disease neuroimaging initiative (ADNI)-GO/2 datasets, which includes control subjects, subjects with subjective memory complaints, with early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD, were segmented using the automated thalamic pipeline. Subjects with AD and mild cognitive impairment (MCI) were found to have lower thalamic volumes, as well as lower hippocampal volumes suggesting early thalamic involvement. Differences in diffusion metrics were found and some diffusion metrics were associated with subsequently higher atrophy rates. The inclusion of hippocampal and thalamic diffusion metrics, in addition to volumes were found to improve disease group classification. In summary, the work in this thesis extends existing knowledge about how the hippocampi and thalami are affected in Alzheimer's disease.

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