Fischell Department of Bioengineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/6628
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Item SPECTRAL X-RAY SCATTERING METHOD FOR IN VIVO ESTIMATION OF AMYLOID BURDEN(2020) Dahal, Eshan; Badano, Aldo; Chen, Yu; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Amyloid-beta plaque deposition in the brain is one of the hallmark features of Alzheimer's disease (AD). Current estimation methods of amyloid burden depend on post-mortem histological analysis or resource-intensive contrast-enhanced imaging techniques. This dissertation focuses on developing a label-free, fast and non-invasive method based on spectral small-angle x-ray scattering (sSAXS) to estimate brain amyloid burden in vivo in small animals. Small-angle x-ray scattering (SAXS) is a well-established technique for identifying molecular structures based on their scattering features. However, SAXS is limited to the study of thin biological samples in the mm scale relying on low-energy monochromatic x rays. I built a prototype sSAXS system to tackle the sample thickness limit of traditional SAXS and explore in vivo applications with higher x-ray energies. This was achieved by integrating a polychromatic x-ray source with a 2D spectroscopic detector for simultaneously and efficiently collecting SAXS data in angle- and energy dispersive modes. A method based on sSAXS was introduced, and its capability was first demonstrated by identifying embedded targets in up to 5-cm-thick phantoms with an x-ray energy range between 30 and 45 keV. Wild-type and 5XFAD mice (AD animal model) were used to demonstrate the ability of the method to estimate amyloid burden in specific areas of the brain without using contrast agents. The mouse head was irradiated at selected locations using a two-pinhole collimated beam of polychromatic x rays for 300 s. The findings correlated well with the histological (gold standard) results. This work presents a promising new method based on sSAXS to estimate amyloid burden in the brain of small animals and possibly in humans.Item Feasibility of in vivo SAXS imaging for detection of Alzheimer's disease(2017) Choi, Mina; Chen, Yu; Badano, Aldo; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Small-angle x-ray scattering (SAXS) imaging has been proposed as a technique to characterize and selectively image structures based on electron density structure which allows for discriminating materials based on their scatter cross sections. This dissertation explores the feasibility of SAXS imaging for the detection of Alzheimer's disease (AD) amyloid plaques. The inherent scatter cross sections of amyloid plaque serve as biomarkers in vivo without the need of injected molecular tags. SAXS imaging can also assist in a better understanding of how these biomarkers play a role in Alzheimer’s disease which in turn can lead to the development of more effective disease-modifying therapies. I implement simulations of x-ray transport using Monte Carlo methods for SAXS imaging enabling accurate calculation of radiation dose and image quality in SAXS-computed tomography (CT). I describe SAXS imaging phantoms with tissue-mimicking material and embedded scatter targets as a way of demonstrating the characteristics of SAXS imaging. I also performed a comprehensive study of scattering cross sections of brain tissue from measurements of ex-vivo sections of a wild-type mouse brain and reported generalized cross sections of gray matter, white matter, and corpus callosum obtained and registered by planar SAXS imaging. Finally, I demonstrate the ability of SAXS imaging to locate an amyloid fibril pellet within a brain section. This work contributes to novel application of SAXS imaging for Alzheimer's disease detection and studies its feasibility as an imaging tool for AD biomarkers.Item Of Mice and Math: A Systems Biology Model for Alzheimer's disease(2011) Kyrtsos, Christina Rose; Baras, John S; Lee, Hey-Kyoung; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder in the US, affecting over 1 in 8 people over the age of 65. There are several well-known pathological changes in the brains of AD patients, namely: the presence of diffuse beta amyloid plaques derived from the amyloid precursor protein (APP), hyper-phosphorylated tau protein, neuroinflammation and mitochondrial dysfunction. Recent studies have shown that cholesterol levels in both the plasma and the brain may play a role in disease pathogenesis, however, this exact role is not well understood. Additional proteins of interest have also been identified (ApoE, LRP-1, IL-1) as possible contributors to AD pathogenesis. To help understand these roles better, a systems biology mathematical model was developed. Basic principles from graph theory and control analysis were used to study the effect of altered cholesterol, ApoE, LRP and APP on the system as a whole. Negative feedback regulation and the rate of cholesterol transfer between astrocytes and neurons were identified as key modulators in the level of beta amyloid. Experiments were run concurrently to test whether decreasing plasma and brain cholesterol levels with simvastatin altered the expression levels of beta amyloid, ApoE, and LRP-1, to ascertain the edge directions in the network model and to better understand whether statin treatment served as a viable treatment option for AD patients. The work completed herein represents the first attempt to create a systems-level mathematical model to study AD that looks at intercellular interactions, as well as interactions between metabolic and inflammatory pathways.