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Description
The objective of this small animal pre-clinical research project was to study quantitatively the long-term micro- and macro- structural brain changes employing multiparametric MRI (Magnetic Resonance Imaging) techniques. Two separate projects make up the basis of this thesis. The first part focuses on obtaining prognostic information at early stages in

The objective of this small animal pre-clinical research project was to study quantitatively the long-term micro- and macro- structural brain changes employing multiparametric MRI (Magnetic Resonance Imaging) techniques. Two separate projects make up the basis of this thesis. The first part focuses on obtaining prognostic information at early stages in the case of Traumatic Brain Injury (TBI) in rat animal model using imaging data acquired at 24-hours and 7-days post injury. The obtained parametric T2 and diffusion values from DTI (Diffusion Tensor Imaging) showed significant deviations in the signal intensities from the control and were potentially useful as an early indicator of the severity of post-traumatic injury damage. DTI was especially critical in distinguishing between the cytotoxic and vasogenic edema and in identification of injury regions resolving to normal control values by day-7. These results indicate the potential of quantitative MRI as a clinical marker in predicting prognosis following TBI. The second part of this thesis focuses on studying the effect of novel therapeutic strategies employing dendritic cell (DC) based vaccinations in mice glioma model. The treatment cohorts included comparing a single dose of Azacytidine drug vs. mice getting three doses of drug per week. Another cohort was used as an untreated control group. The MRI results did not show any significant changes in between the two treated cohorts with no reduction in tumor volumes compared to the control group. The future studies would be focused on issues regarding the optimal dose for the application of DC vaccine. Together, the quantitative MRI plays an important role in the prognosis and diagnosis of the above mentioned pathologies, providing essential information about the anatomical location, micro-structural tissue environment, lesion volume and treatment response.
ContributorsAnnaldas, Bharat (Author) / Kodibagkar, Vikram (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Bhardwaj, Ratan (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive

Modern medical conditions, including cancer, traumatic brain injury, and cardiovascular disease, have elicited the need for cell therapies. The ability to non-invasively track cells in vivo in order to evaluate these therapies and explore cell dynamics is necessary. Magnetic Resonance Imaging provides a platform to track cells as a non-invasive modality with superior resolution and soft tissue contrast. A new methodology for cellular labeling and imaging uses Nile Red doped hexamethyldisiloxane (HMDSO) nanoemulsions as dual modality (Magnetic Resonance Imaging/Fluorescence), dual-functional (oximetry/ detection) nanoprobes. While Gadolinium chelates and super paramagnetic iron oxide-based particles have historically provided contrast enhancement in MRI, newer agents offer additional advantages. A technique using 1H MRI in conjunction with an oxygen reporter molecule is one tool capable of providing these benefits, and can be used in neural progenitor cell and cancer cell studies. Proton Imaging of Siloxanes to Map Tissue Oxygenation Levels (PISTOL) provides the ability to track the polydimethylsiloxane (PDMS) labeled cells utilizing the duality of the nanoemulsions. 1H MRI based labeling of neural stem cells and cancer cells was successfully demonstrated. Additionally, fluorescence labeling of the nanoprobes provided validation of the MRI data and could prove useful for quick in vivo verification and ex vivo validation for future studies.
ContributorsCusick, Alex (Author) / Kodibagkar, Vikram D. (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Kleim, Jeff (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Obtaining high-quality experimental designs to optimize statistical efficiency and data quality is quite challenging for functional magnetic resonance imaging (fMRI). The primary fMRI design issue is on the selection of the best sequence of stimuli based on a statistically meaningful optimality criterion. Some previous studies have provided some guidance and

Obtaining high-quality experimental designs to optimize statistical efficiency and data quality is quite challenging for functional magnetic resonance imaging (fMRI). The primary fMRI design issue is on the selection of the best sequence of stimuli based on a statistically meaningful optimality criterion. Some previous studies have provided some guidance and powerful computational tools for obtaining good fMRI designs. However, these results are mainly for basic experimental settings with simple statistical models. In this work, a type of modern fMRI experiments is considered, in which the design matrix of the statistical model depends not only on the selected design, but also on the experimental subject's probabilistic behavior during the experiment. The design matrix is thus uncertain at the design stage, making it diffcult to select good designs. By taking this uncertainty into account, a very efficient approach for obtaining high-quality fMRI designs is developed in this study. The proposed approach is built upon an analytical result, and an efficient computer algorithm. It is shown through case studies that the proposed approach can outperform an existing method in terms of computing time, and the quality of the obtained designs.
ContributorsZhou, Lin (Author) / Kao, Ming-Hung (Thesis advisor) / Reiser, Mark R. (Committee member) / Stufken, John (Committee member) / Welfert, Bruno (Committee member) / Arizona State University (Publisher)
Created2014
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Description
In this era of fast computational machines and new optimization algorithms, there have been great advances in Experimental Designs. We focus our research on design issues in generalized linear models (GLMs) and functional magnetic resonance imaging(fMRI). The first part of our research is on tackling the challenging problem of constructing

exact

In this era of fast computational machines and new optimization algorithms, there have been great advances in Experimental Designs. We focus our research on design issues in generalized linear models (GLMs) and functional magnetic resonance imaging(fMRI). The first part of our research is on tackling the challenging problem of constructing

exact designs for GLMs, that are robust against parameter, link and model

uncertainties by improving an existing algorithm and providing a new one, based on using a continuous particle swarm optimization (PSO) and spectral clustering. The proposed algorithm is sufficiently versatile to accomodate most popular design selection criteria, and we concentrate on providing robust designs for GLMs, using the D and A optimality criterion. The second part of our research is on providing an algorithm

that is a faster alternative to a recently proposed genetic algorithm (GA) to construct optimal designs for fMRI studies. Our algorithm is built upon a discrete version of the PSO.
ContributorsTemkit, M'Hamed (Author) / Kao, Jason (Thesis advisor) / Reiser, Mark R. (Committee member) / Barber, Jarrett (Committee member) / Montgomery, Douglas C. (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2014
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Description
Magnetic Resonance Imaging (MRI) is an efficient non-invasive imaging tool widely used in medical field to produce high quality images. The MRI signal is detected with specifically developed radio frequency (RF) systems or "coils". There are several key parameters to evaluate the performance of RF coils: signal-to-noise ratio (SNR), homogeneity,

Magnetic Resonance Imaging (MRI) is an efficient non-invasive imaging tool widely used in medical field to produce high quality images. The MRI signal is detected with specifically developed radio frequency (RF) systems or "coils". There are several key parameters to evaluate the performance of RF coils: signal-to-noise ratio (SNR), homogeneity, quality factor (Q factor), sensitivity, etc. The choice of coil size and configuration depends on the object to be imaged. While surface coils have better sensitivity, volume coils are often employed to image a larger region of interest (ROI) as they display better spatial homogeneity. For the cell labeling and imaging studies using the newly developed siloxane based nanoemulsions as 1H MR reporter probes, the first step is to determine the sensitivity of signal detection under controlled conditions in vitro. In this thesis, a novel designed 7 Tesla RF volume coil was designed and tested for detection of small quantities of siloxane probe as well as for imaging of labeled tumor spheroid. The procedure contains PCB circuit design, RF probe design, test and subsequent modification. In this report, both theory and design methodology will be discussed.
ContributorsWang, Haiqing (Author) / Kodibagkar, Vikram (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Sadleir, Rosalind (Committee member) / Arizona State University (Publisher)
Created2014
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Description
One of the most prominent biological challenges for the field of drug delivery is the blood-brain barrier. This physiological system blocks the entry of or actively removes almost all small molecules into the central nervous system (CNS), including many drugs that could be used to treat diseases in the CNS.

One of the most prominent biological challenges for the field of drug delivery is the blood-brain barrier. This physiological system blocks the entry of or actively removes almost all small molecules into the central nervous system (CNS), including many drugs that could be used to treat diseases in the CNS. Previous studies have shown that activation of the adenosine receptor signaling pathway through the use of agonists has been demonstrated to increase BBB permeability. For example, regadenoson is an adenosine A2A receptor agonist that has been shown to disrupt the BBB and allow for increased drug uptake in the CNS. The goal of this study was to verify this property of regadenoson. We hypothesized that co-administration of regadenoson with a non-brain penetrant macromolecule would facilitate its entry into the central nervous system. To test this hypothesis, healthy mice were administered regadenoson or saline concomitantly with a fluorescent dextran solution. The brain tissue was either homogenized to measure quantity of fluorescent molecule, or cryosectioned for imaging with confocal fluorescence microscopy. These experiments did not identify any significant difference in the amount of fluorescence detected in the brain after regadenoson treatment. These results contradict those of previous studies and highlight potential differences in injection methodology, time windows, and properties of brain impermeant molecules.
ContributorsWohlleb, Gregory Michael (Author) / Sirianni, Rachael (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
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Description
Contrast agents in medical imaging can help visualize structural details, distributions of particular cell types, or local environment characteristics. Multi-modal imaging techniques have become increasingly popular for their improved sensitivity, resolution, and ability to correlate structural and functional information. This study addresses the development of dual-modality (magnetic resonance/fluorescence) and dual-functional

Contrast agents in medical imaging can help visualize structural details, distributions of particular cell types, or local environment characteristics. Multi-modal imaging techniques have become increasingly popular for their improved sensitivity, resolution, and ability to correlate structural and functional information. This study addresses the development of dual-modality (magnetic resonance/fluorescence) and dual-functional (thermometry/detection) nanoprobes for enhanced tissue imaging.
ContributorsHemzacek, Katherine Leigh (Author) / Kodibagkar, Vikram (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2015-05
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Description
Several debilitating neurological disorders, such as Alzheimer's disease, stroke, and spinal cord injury, are characterized by the damage or loss of neuronal cell types in the central nervous system (CNS). Human neural progenitor cells (hNPCs) derived from human pluripotent stem cells (hPSCs) can proliferate extensively and differentiate into the various

Several debilitating neurological disorders, such as Alzheimer's disease, stroke, and spinal cord injury, are characterized by the damage or loss of neuronal cell types in the central nervous system (CNS). Human neural progenitor cells (hNPCs) derived from human pluripotent stem cells (hPSCs) can proliferate extensively and differentiate into the various neuronal subtypes and supporting cells that comprise the CNS. As such, hNPCs have tremendous potential for disease modeling, drug screening, and regenerative medicine applications. However, the use hNPCs for the study and treatment of neurological diseases requires the development of defined, robust, and scalable methods for their expansion and neuronal differentiation. To that end a rational design process was used to develop a vitronectin-derived peptide (VDP)-based substrate to support the growth and neuronal differentiation of hNPCs in conventional two-dimensional (2-D) culture and large-scale microcarrier (MC)-based suspension culture. Compared to hNPCs cultured on ECMP-based substrates, hNPCs grown on VDP-coated surfaces displayed similar morphologies, growth rates, and high expression levels of hNPC multipotency markers. Furthermore, VDP surfaces supported the directed differentiation of hNPCs to neurons at similar levels to cells differentiated on ECMP substrates. Here it has been demonstrated that VDP is a robust growth and differentiation matrix, as demonstrated by its ability to support the expansions and neuronal differentiation of hNPCs derived from three hESC (H9, HUES9, and HSF4) and one hiPSC (RiPSC) cell lines. Finally, it has been shown that VDP allows for the expansion or neuronal differentiation of hNPCs to quantities (>1010) necessary for drug screening or regenerative medicine purposes. In the future, the use of VDP as a defined culture substrate will significantly advance the clinical application of hNPCs and their derivatives as it will enable the large-scale expansion and neuronal differentiation of hNPCs in quantities necessary for disease modeling, drug screening, and regenerative medicine applications.
ContributorsVarun, Divya (Author) / Brafman, David (Thesis advisor) / Nikkhah, Mehdi (Committee member) / Stabenfeldt, Sarah (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Neurological disorders are difficult to treat with current drug delivery methods due to their inefficiency and the lack of knowledge of the mechanisms behind drug delivery across the blood brain barrier (BBB). Nanoparticles (NPs) are a promising drug delivery method due to their biocompatibility and ability to be modified by

Neurological disorders are difficult to treat with current drug delivery methods due to their inefficiency and the lack of knowledge of the mechanisms behind drug delivery across the blood brain barrier (BBB). Nanoparticles (NPs) are a promising drug delivery method due to their biocompatibility and ability to be modified by cell penetrating peptides, such as transactivating transciptor (TAT) peptide, which has been shown to increase efficiency of delivery. There are multiple proposed mechanisms of TAT-mediated delivery that also have size restrictions on the molecules that can undergo each BBB crossing mechanism. The effect of nanoparticle size on TAT-mediated delivery in vivo is an important aspect to research in order to better understand the delivery mechanisms and to create more efficient NPs. NPs called FluoSpheres are used because they come in defined diameters unlike polymeric NPs that have a broad distribution of diameters. Both modified and unmodified 100nm and 200nm NPs were able to bypass the BBB and were seen in the brain, spinal cord, liver, and spleen using confocal microscopy and a biodistribution study. Statistically significant differences in delivery rate of the different sized NPs or between TAT-modified and unmodified NPs were not found. Therefore in future work a larger range of diameter size will be evaluated. Also the unmodified NPs will be conjugated with scrambled peptide to ensure that both unmodified and TAT-modified NPs are prepared in identical fashion to better understand the role of size on TAT targeting. Although all the NPs were able to bypass the BBB, future work will hopefully provide a better representation of how NP size effects the rate of TAT-mediated delivery to the CNS.
ContributorsCeton, Ricki Ronea (Author) / Stabenfeldt, Sarah (Thesis director) / Sirianni, Rachael (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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Description
One of the premier technologies for studying human brain functions is the event-related functional magnetic resonance imaging (fMRI). The main design issue for such experiments is to find the optimal sequence for mental stimuli. This optimal design sequence allows for collecting informative data to make precise statistical inferences about the

One of the premier technologies for studying human brain functions is the event-related functional magnetic resonance imaging (fMRI). The main design issue for such experiments is to find the optimal sequence for mental stimuli. This optimal design sequence allows for collecting informative data to make precise statistical inferences about the inner workings of the brain. Unfortunately, this is not an easy task, especially when the error correlation of the response is unknown at the design stage. In the literature, the maximin approach was proposed to tackle this problem. However, this is an expensive and time-consuming method, especially when the correlated noise follows high-order autoregressive models. The main focus of this dissertation is to develop an efficient approach to reduce the amount of the computational resources needed to obtain A-optimal designs for event-related fMRI experiments. One proposed idea is to combine the Kriging approximation method, which is widely used in spatial statistics and computer experiments with a knowledge-based genetic algorithm. Through case studies, a demonstration is made to show that the new search method achieves similar design efficiencies as those attained by the traditional method, but the new method gives a significant reduction in computing time. Another useful strategy is also proposed to find such designs by considering only the boundary points of the parameter space of the correlation parameters. The usefulness of this strategy is also demonstrated via case studies. The first part of this dissertation focuses on finding optimal event-related designs for fMRI with simple trials when each stimulus consists of only one component (e.g., a picture). The study is then extended to the case of compound trials when stimuli of multiple components (e.g., a cue followed by a picture) are considered.
ContributorsAlrumayh, Amani (Author) / Kao, Ming-Hung (Thesis advisor) / Stufken, John (Committee member) / Reiser, Mark R. (Committee member) / Pan, Rong (Committee member) / Cheng, Dan (Committee member) / Arizona State University (Publisher)
Created2019