Development and evaluation of a novel framework for subcortical gray matter segmentation using quantitative magnetic susceptibility and R2* mapping
Quantitative susceptibility mapping (QSM) and effective relaxation rate (R∗2) mapping are promising magnetic resonance imaging (MRI) techniques to study iron content in the human brain in vivo. The ability to quantify iron content in subcortical gray matter (SGM) is important to better understand its role in neurodegenerative diseases as well as during normal brain aging. However, accurate determination of tissue magnetic susceptibility and R∗2 in brain structures, such as SGM, may be challenging due to potential segmentation inaccuracies, specifically when performed automatically. The present thesis introduces a robust framework to automatically segment and characterize SGM using quantitative susceptibility maps and exemplarily applies it to investigate iron-related susceptibility and R∗2 changes in patients with multiple sclerosis (MS) in comparison to controls.