Multimodal MRI-based classification of Alzheimer’s disease

Vos, F. de (2021)

Doctoral Thesis

Alzheimer’s disease (AD) is a neurodegenerative disease characterized by memory loss and declined cognitive functioning. Brain changes in AD involve grey matter atrophy and changes in brain function. These different brain characteristics can respectively be visualized with structural and functional MRI scans. These MRI modalities have been used for AD classification, but studies typically only include a limited number of features. In this thesis we derived multiple types of features from each MRI modality, and combined those to discriminate AD patients and elderly controls. First, we showed that AD classification accuracy increases when combining multiple types of measures from a single MRI modality. This was shown for structural MRI scans in chapter 2, and for resting state fMRI scans in chapter 3. In chapter 4 we evaluated whether MRI based AD classification models can discriminate AD in a diverse clinical population as well. This worked to some extent, and it worked best using structural MRI scans. In chapter 5 we used baseline multimodal MRI scans from the same diverse clinical population to predict two-year follow-up cognitive decline. Decline was predicted above chance level for the MMSE, but not for six other neuropsychological tests.

• Alzheimer's disease
• Mild cognitive impairment
• Structural MRI
• Diffusion MRI
• Resting state functional MRI
• Multimodal MRI
• Classification
• Statistical learning

• All authors: Vos, F. de
• Supervisor: Rombouts, S.A.R.B.; Rooij, M.J. de
• Co-supervisor: Grond, J. van der
• Committee: Lelieveldt, B.P.F.; Batenburg, K.J.; Swieten, J.C. van; Tijms, B.M.
• Qualification: Doctor (dr.)
• Awarding Institution: Faculty of Medicine, Leiden University Medical Center (LUMC), Leiden University
• Date: 2021-12-09
• ISBN (print): 9789463327992
• Sponsorship: Alzheimer Nederland