Using cingulum bundle microstructural models metrics to better understand the early posterior cingulate hypometabolism in the framework of Alzheimer's Disease

Details

Supervisors

Macq, Benoît ; Dricot, Laurence

Faculty

Ecole polytechnique de Louvain

Degree label

Master [120] : ingénieur civil biomédical, à finalité spécialisée

Abstract

The increase in the number of elderly people in our society has led to a higher occurrence of aging-related illnesses such as Alzheimer’s disease. A novel approach has yielded the identification of fresh biomarkers that hold potential for enhancing diagnoses, personalized treatment, clinical management, and drug development. Utilizing diffusion magnetic resonance imaging, a non-invasive imaging technique devoid of invasive procedures or radiation, it becomes possible to assess the microstructural attributes of brain tissues by examining the diffusion of water molecules across biological barriers. This process of linking the diffusion magnetic resonance signal to tissue microstructural characteristics through mathematical models is termed "microstructure imaging." This Master's thesis seeks to explore the hypometabolism within the posterior cingulate in the context of Alzheimer's disease using the accumulation of biomarkers and microstructural metrics originating from models such as Diffusion Tensor Imaging (DTI), Neurite Orientation Dispersion and Density Imaging (NODDI), Distribution of 3D Anisotropic MicrOstructural eNvironments in Diffusion compartment imaging (DIAMOND), and Microstructure Fingerprinting (MF).