Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item Image Reconstruction for Hyperpolarized Carbon-13 Metabolic Magnetic Resonance Imaging with Iterative Methods(2024) Zhu, Minjie; Babadi, Behtash; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Magnetic resonance imaging (MRI) with hyperpolarized carbon-13 (13C) agents is an emerging in vivo medical imaging technique. 13C MRI gives a series of images that show the evolution of the injected substrate and its metabolic products in the imaging volume, which leads to various medical applications including monitoring tumor progression and post-treatment response in both animal models and clinical trials. This dissertation focuses on the application of novel iterative image reconstruction methods for 13C MRI that aim to improve image quality and temporal resolution.One of the challenges for the existing 13C MRI reconstruction method is the difficulty in quantification of lower intensity metabolites due to noise and overlapping peaks in the aliased spectrum. In the first part of the dissertation, a model-based iterative reconstruction method is proposed to overcome such difficulty. The proposed method utilizes prior knowledge of the properties of the metabolites in the imaging volume, including off-resonance frequency, T2* decay constants, and the image acquisition trajectory in spatial and frequency domain. Metabolic images are reconstructed through solving the linear equation between acquired signal and images with least square error estimation. The reconstruction results on in vivo imaging data sets demonstrate that the proposed method can separate two overlapped peaks in an aliased spectrum while the conventional method fails. Another challenge for 13C MRI is to reconstruct metabolic images from under-sampled acquisitions. Due to the short lifetime of the injected substrate and the physical limitation of the MRI scanner, only a few temporal frames can be acquired for 13C MRI with one injection. Under-sampling in the image acquisition can provide more frames, but certain reconstruction methods are required to remove the artifacts from direct reconstruction on the under-sampled data. In the second part of the dissertation, a customized low-rank plus sparse (L+S) reconstruction method is proposed to produce artifact-free images from under-sampled data. Digital phantom simulations are performed to evaluate the optimal reconstruction parameters. Simulation with digital phantom and in vivo mouse imaging on 2D and 3D dynamic imaging data demonstrate the effectiveness in acceleration without introducing image artifacts using the proposed reconstruction method. In the third part of the dissertation, we present a preclinical application of 13C MRI to study brain metabolism and identify the source of metabolic products based on the metabolic images derived. In vivo metabolic imaging with different flow-suppression levels was performed on rats in the brain region. Results show that metabolic product, lactate, has no significant dependence on the level of suppression while the substrate pyruvate is strongly dependent. This supports our hypothesis that lactate seen in metabolic images is generated in the brain. Additional high-resolution metabolic imaging was performed to show different signal distributions for pyruvate and lactate clearly. Our proposed L+S reconstruction method was applied to the dynamic image data to reduce the background noise. The derived dynamic images show distinct dynamics for pyruvate and lactate, further supporting our hypothesis.Item Direct Laser Writing-Enabled Microstructures with Tailored Reflectivity for Optical Coherence Tomography Phantoms(2023) Fitzgerald, Declan Morgan; Sochol, Ryan D; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As the continuous push to improve medical imaging techniques produces increasingly complex systems, so too must the phantoms critical to the accurate evaluation of these systems evolve. The inclusion of precise geometries is a well documented gap in optical coherence tomography (OCT) phantoms, a gap felt more severely as the technology improves. This thesis seeks to investigate the feasibility of utilizing new manufacturing techniques in the production of OCT phantoms with complex geometries while developing a phantom to determine the sensitivity of OCT systems. The new manufacturing methods include the replication of microstructures printed via direct laser writing into PMMA photoresist, the tailored smoothing of surface roughness inherent to direct laser writing, and the selective retention of surface roughness in certain regions. Each of these methods were implemented in the manufacture of an OCT sensitivity phantom and were found to be effective in each of their respective goals.The efficacy of the sensitivity phantom in evaluating the minimum reflectance still detectable by an OCT system shows promise. Effective reflectivity ranging from 0 to ~1 was accomplished within a single angled element and should provide a basis for determining the minimum reflectivity that results in a signal-to-noise ratio of 1. Further improvements must be made to the phantom footprint and manufacturing before the phantom’s reliability is certain.Item Development of Fluorescent Imaging Methods and Systems to Determine Photodynamic Potential and Inform Cancer Treatment Efficacy(2022) Gaitan, Brandon; Huang, Huang-Chiao; Chen, Yu; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Photodynamic therapy (PDT) is a treatment modality that has gained rapid popularity in both research and clinical settings over the past 20 years. PDT involves harmless red/near-infrared light excitation of non-toxic photosensitizers to generate reactive molecular species (RMS) that can induce tissue damage and/or cell death. In addition, the fluorescence signal generated from the photosensitizer can also be used for optical imaging. These effects have been harnessed for image-guided treatment of cancer and other diseases. As PDT gains popularity, it is crucial to understand and monitor different factors that could impact overall treatment efficacy. These factors include, but are not limited to, the RMS yield of photosensitizers, the distribution of photosensitizers in tissue, and the PDT activation depth in tissues. Our work focused on developing methodologies and devices to characterize and improve PDT treatment. In collaboration with the FDA, we developed a cell-free assay to rapidly and more quantitatively determine the potential phototoxicity of fluorescent probes through the measurement of singlet oxygen. We also developed a method to compare the maximal PDT activation depth of FDA-approved photosensitizers (BPD and PpIX) in the brain. We found that BPD can be activated 50% deeper into brain tissues compared to PpIX at the same radiant exposure. Next, we tested the ability of a 3D imaging system, Fluorescence Laminar Optical Tomography (FLOT), to image the distribution of photosensitizers in the rodent brain. We demonstrated that FLOT could accurately map the photosensitizer distribution up to 0.5 mm in tissues. Lastly, we developed an autofluorescent-based endoscopic imaging system to measure the metabolic impact of PDT on cancer and normal tissues, finding that PDT leads to significant changes in tissue metabolism immediately after treatment. In summary, we have developed a series of systems that can aid in PDT treatment optimization in three major ways:1) rapidly quantifying the singlet oxygen production of photosensitizers, 2) more accurately measuring a photosensitizers localization and activatable depth, and 3) developing the ability to measure a tissues response to PDT in real-time.Item TOWARD PHANTOM DEVELOPMENT FOR MEDICAL IMAGING USING DIRECT LASER WRITING(2020) Lamont, Andrew Carl; Sochol, Ryan D.; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)An important tool for the performance analysis and standardization of medical imaging technologies is the phantom, which offers specifically defined properties that mimic the structural and optical characteristics of a tissue of interest. The development of phantoms for high-resolution (i.e., micro-scale) three-dimensional (3D) imaging modalities can be challenging, however, as few manufacturing techniques can capture the architectural complexity of biological tissues at such scales. Direct Laser Writing (DLW) is an evolving additive manufacturing technique with nano-scale precision that can fabricate micro and nanostructures with unparalleled geometric complexity. This dissertation outlines the unique microfluidic-based DLW strategies that have been developed for novel micro-scale phantom production. First, I will outline the development and characterization of an in situ DLW strategy used to adhere printed components to the surfaces of a microchannel. I will then explain how we have leveraged this strategy for a proof-of-concept retinal cone outer segment phantom that is laden with light-scattering Titanium (IV) Dioxide nanoparticles. This phantom has valuable implications for the performance analysis of the emerging ophthalmological modality, adaptive optics-optical coherence tomography (AO-OCT). Next, I will describe the development and characterization of a microfluidic-based multi-material DLW strategy to fabricate single components from multiple materials with minimal registration error between the materials. Ultimately, we intend to use this method to develop multi-material platforms and phantoms, including high-aspect-ratio multi-material retinal cone phantoms for AO-OCT. Finally, to demonstrate the applicability of this method for applications beyond AO-OCT, I present a preliminary phantom production strategy for the light microscopy-based modality, whole slide imaging (WSI). Specifically, we assess the DLW and light microscopy performance of dyed photoresists and offer a preliminary multi-material demonstration, which are pivotal first steps toward the creation of a first-generation multi-material WSI phantom. This work provides valuable insights and strategies that leverage microfluidic-based DLW techniques to fabricate novel micro-scale phantoms. It is anticipated that these strategies will have a lasting impact, not only on the production of phantoms for medical imaging modalities, but also for the fabrication of advanced microfluidic and multi-material microstructures for fields such as meta-materials, micro-optics, lab-on-a-chip, and organ-on-a-chip.Item QUANTITATIVE STUDY OF LONGITUDINAL RELAXATION (T1) CONTRAST MECHANISMS IN BRAIN MRI(2017) Jiang, Xu; Anlage, Steven M.; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Longitudinal relaxation (T1) contrast in MRI is important for studying brain morphology and is widely used in clinical applications. Although MRI only detects signals from water hydrogen (1H) protons (WPs), T1 contrast is known to be influenced by other species of 1H protons, including those in macromolecules (MPs), such as lipids and proteins, through magnetization transfer (MT) between WPs and MPs. This complicates the use and quantification of T1 contrast for studying the underlying tissue composition and the physiology of the brain. MT contributes to T1 contrast to an extent that is generally dependent on MT kinetics, as well as the concentration and NMR spectral properties of MPs. However, the MP spectral properties and MT kinetics are both difficult to measure directly, as the signal from MPs is generally invisible to MRI. Therefore, to investigate MT kinetics and further quantify T1 contrast, we first developed a reliable way to indirectly measure the MP fraction and their exchange rate with WPs, with minimal dependence on the spectral properties of MPs. For this purpose, we used brief, high-power radiofrequency (RF) NMR excitation pulses to almost completely saturate the magnetization of MPs. Based on this, both MT kinetics and the contribution of MPs to T1 contrast through MT were studied. The thus obtained knowledge allowed us to subsequently infer the spectral properties of MPs by applying low-power, frequency-selective off-resonance RF pulses and measuring the offset-frequency dependent effect of MPs on the WP MRI signal. A two-pool exchange model was used in both cases to account for direct effects of the RF pulse on WP magnetization. Consistent with earlier works using MRI at low-field and post-mortem analysis of brain tissue, our novel measurement approach found that MPs constitute an up to 27% fraction of the total 1H protons in human brain white matter, and their spectrum follows a super-Lorentzian line with a T2 of 9.6±0.6 μs and a resonance frequency centered at -2.58±0.05 ppm, at 7 T. T1 contrast was found to be dominated by MP fraction, with iron only modestly contributing even in the iron-rich regions of brain.Item Accelerated Imaging Using Partial Fourier Compressed Sensing Reconstruction(2016) Chou, Chia-Chu; Babadi, Behtash; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Accelerated imaging is an active research area in medical imaging. The most intuitive way of image acceleration is to reconstruct images from only a subset of the whole raw data space, so that the acquisition time can be shortened. This concept has been formalized in recent years, and is known as Compressed Sensing (CS). In this dissertation, we developed a new image reconstruction method, Partial Fourier Compressed Sensing (PFCS), which combines the advantages of partial Fourier transform and compressed sensing techniques. Then, we explore its application on two imaging modalities. First, we apply PFCS to Electron Paramagnetic Resonance Imaging (EPRI) reconstruction for the purpose of imaging the cycling hypoxia phenomenon. We begin with validating PFCS with the prevailing medical acceleration techniques using CS. Then, we further explore its capability of imaging the oxygen distribution in the tumor tissue. Our results show that PFCS is able to accelerate the imaging process by at least 4 times with-out losing too much image resolution in comparison to conventional CS. Further, the ox-ygen map given by PFCS precisely captures the oxygen change inside the tumor tissue. In the second part, we apply PFCS to 3D diffusion tensor image (DTI) acquisition. We develop a new sampling strategy specified to diffusion weighted images and optimize the reconstruction cost function for PFCS. The results show that PFCS can reconstruct the accurate color FA map using only 30% of the k-space data. Moreover, PFCS can be further combined with Echo-Planar Imaging (EPI) to achieve an even faster acquisition speed. In summary, PFCS is shown to be a promising image acceleration method in medical imaging which can potentially benefit many clinical applications.Item Tensor Completion for Multidimensional Inverse Problems with Applications to Magnetic Resonance Relaxometry(2016) Hafftka, Ariel; Czaja, Wojciech; Applied Mathematics and Scientific Computation; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approximately low rank tensor from a small number of noisy linear measurements. New recovery guarantees, numerical algorithms, non-uniform sampling strategies, and parameter selection algorithms are developed. We derive a fixed point continuation algorithm for tensor completion and prove its convergence. A restricted isometry property (RIP) based tensor recovery guarantee is proved. Probabilistic recovery guarantees are obtained for sub-Gaussian measurement operators and for measurements obtained by non-uniform sampling from a Parseval tight frame. We show how tensor completion can be used to solve multidimensional inverse problems arising in NMR relaxometry. Algorithms are developed for regularization parameter selection, including accelerated k-fold cross-validation and generalized cross-validation. These methods are validated on experimental and simulated data. We also derive condition number estimates for nonnegative least squares problems. Tensor recovery promises to significantly accelerate N-dimensional NMR relaxometry and related experiments, enabling previously impractical experiments. Our methods could also be applied to other inverse problems arising in machine learning, image processing, signal processing, computer vision, and other fields.