Date of Award
Winter 12-11-2023
Degree Name
Doctor of Philosophy (PhD)
Degree Type
Dissertation
Abstract
Among a series of contrasts of MRI, diffusion MRI (dMRI) is different from conventional MRI by its ability to capture information about the random movement of water molecules and their interaction with local tissue microstructures. This capability holds the potential to reveal intricate subvoxel microstructural information linked to pathological changes, offering potential imaging biomarkers. A higher-order diffusion analysis model helps to yield more accurate and specific parameters but requires more extensive parameter tuning and higher image quality. In this study, we firstly fine-tuned the previously developed diffusion basis spectrum imaging (DBSI) method to strike a balance between efficiency and accuracy when dealing with various b-table designs, signal-to-noise ratios (SNR), and organ-of-interest (Chapter 2). The dMRI data, usually obtained through echoplanar imaging (EPI), frequently encounter challenges related to misalignment of the image caused by the motion of the subject. This is- sue is particularly pronounced in placenta imaging, where fetal movements are unpredictable and uncontrollable. To address this issue, we devised a tailored registration pipeline capable of mitigating both intra-volume and inter-volume misalignment (Chapter 3). Furthermore, we noticed the absence of detailed segmentation methods within placenta re- gion, as most of the previous study used the average value from either the entire placenta or several manually labelled regions. We developed an automatic separation method con- sidering dMRI and T2* MRI features that divides placenta into subregions. The improved more specific compartment-wise quantification revealed new insights in longitudinal changes in placenta (Chapter 4). In the DBSI placenta application, we carefully performed ex vivo validation and simulation validation before in-vivo application. The method imaged the spatial distribution of the placental immune cells and revealed significantly greater immune cell infiltration in the in- flammation placentas throughout gestation, demonstrating its potential to serve as a clinical tool to monitor the placenta immune status of pregnancy longitudinally without ionizing radiation (Chapter 5). Finally, although DBSI was initially developed and validated in brain studies, we recently recognized its potential for enhancement, inspired by an in vivo observation of increasing cell ADC along progress of Alzheimer’s disease (AD). We targeted microglia as a potential marker and hypothesized that DBSI can quantify the proliferation and activation of microglia with Monte-Carlo simulated reference signal from real microglia model (Chapter 6).
Language
English (en)
Chair
Yong Wang