Matching Items (20)
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- All Subjects: ethics
- Creators: Harrington Bioengineering Program
Description
Glioblastoma multiforme (GBM) is a malignant, aggressive and infiltrative cancer of the central nervous system with a median survival of 14.6 months with standard care. Diagnosis of GBM is made using medical imaging such as magnetic resonance imaging (MRI) or computed tomography (CT). Treatment is informed by medical images and includes chemotherapy, radiation therapy, and surgical removal if the tumor is surgically accessible. Treatment seldom results in a significant increase in longevity, partly due to the lack of precise information regarding tumor size and location. This lack of information arises from the physical limitations of MR and CT imaging coupled with the diffusive nature of glioblastoma tumors. GBM tumor cells can migrate far beyond the visible boundaries of the tumor and will result in a recurring tumor if not killed or removed. Since medical images are the only readily available information about the tumor, we aim to improve mathematical models of tumor growth to better estimate the missing information. Particularly, we investigate the effect of random variation in tumor cell behavior (anisotropy) using stochastic parameterizations of an established proliferation-diffusion model of tumor growth. To evaluate the performance of our mathematical model, we use MR images from an animal model consisting of Murine GL261 tumors implanted in immunocompetent mice, which provides consistency in tumor initiation and location, immune response, genetic variation, and treatment. Compared to non-stochastic simulations, stochastic simulations showed improved volume accuracy when proliferation variability was high, but diffusion variability was found to only marginally affect tumor volume estimates. Neither proliferation nor diffusion variability significantly affected the spatial distribution accuracy of the simulations. While certain cases of stochastic parameterizations improved volume accuracy, they failed to significantly improve simulation accuracy overall. Both the non-stochastic and stochastic simulations failed to achieve over 75% spatial distribution accuracy, suggesting that the underlying structure of the model fails to capture one or more biological processes that affect tumor growth. Two biological features that are candidates for further investigation are angiogenesis and anisotropy resulting from differences between white and gray matter. Time-dependent proliferation and diffusion terms could be introduced to model angiogenesis, and diffusion weighed imaging (DTI) could be used to differentiate between white and gray matter, which might allow for improved estimates brain anisotropy.
ContributorsAnderies, Barrett James (Author) / Kostelich, Eric (Thesis director) / Kuang, Yang (Committee member) / Stepien, Tracy (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Smart contrast agents allow for noninvasive study of specific events or tissue conditions inside of a patient's body using Magnetic Resonance Imaging (MRI). This research aims to develop and characterize novel smart contrast agents for MRI that respond to temperature changes in tissue microenvironments. Transmission Electron Microscopy, Nuclear Magnetic Resonance, and cell culture growth assays were used to characterize the physical, magnetic, and cytotoxic properties of candidate nanoprobes. The nanoprobes displayed thermosensitve MR properties with decreasing relaxivity with temperature. Future work will be focused on generating and characterizing photo-active analogues of the nanoprobes that could be used for both treatment of tissues and assessment of therapy.
ContributorsHussain, Khateeb Hyder (Author) / Kodibagkar, Vikram (Thesis director) / Stabenfeldt, Sarah (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
Description
Morphine is a commonly used analgesic in pain management. Opioid administration to a patient after surgery, such as spinal decompression surgery, can lead to adverse side effects. To demonstrate these adverse side effects could be decreased we created a model of how morphine and its metabolites are transported and excreted from the body. Using the of morphine and a standard compartment approach this thesis aimed at projecting pharmacokinetics trends of morphine overtime. A Matlab compartment model predicting the transport of morphine through the body can contribute to a better understanding of the concentrations at the systemic level, specifically with respect to a CSF, and what happens when you compare an intravenous injection to a local delivery. Other studies and models commonly utilized patient data over small periods of time2,3,5. An extended period of time will provide information into morphine’s time course after surgery. This model focuses on a compartmentalization of the major organs and the use of a simple Mechalis-Menten enzyme kinetics for the metabolites in the liver. Our results show a CSF concentration of about 1.086×〖10〗^(-12) nmol/L in 6 weeks and 1.0097×〖10〗^(-12) nmol/L in 12 weeks. The concentration profiles in this model are similar to what was expected. The implications of this suggest that patients who reported effects of morphine paste, a locally administered opioid, weeks after the surgery were due to other reasons. In creating a model we can determine important variables and dosage information. This information allows for a greater understanding of what is happening in the body and how to improve surgical outcomes. We propose this study has implications in general research in the pharmacokinetics and dynamics of pharmacology through the body.
ContributorsJacobs, Danielle Renee (Author) / Caplan, Michael (Thesis director) / Giers, Morgan (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
Glioblastoma Multiforme (GBM) is an aggressive and deadly form of brain cancer with a median survival time of about a year with treatment. Due to the aggressive nature of these tumors and the tendency of gliomas to follow white matter tracks in the brain, each tumor mass has a unique growth pattern. Consequently it is difficult for neurosurgeons to anticipate where the tumor will spread in the brain, making treatment planning difficult. Archival patient data including MRI scans depicting the progress of tumors have been helpful in developing a model to predict Glioblastoma proliferation, but limited scans per patient make the tumor growth rate difficult to determine. Furthermore, patient treatment between scan points can significantly compound the challenge of accurately predicting the tumor growth. A partnership with Barrow Neurological Institute has allowed murine studies to be conducted in order to closely observe tumor growth and potentially improve the current model to more closely resemble intermittent stages of GBM growth without treatment effects.
ContributorsSnyder, Lena Haley (Author) / Kostelich, Eric (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Harrington Bioengineering Program (Contributor)
Created2014-05
Description
In epilepsy, malformations that cause seizures often require surgery. The purpose of this research is to join forces with the Multi-Center Epilepsy Lesion Detection (MELD) project at University College London (UCL) in order to improve the process of detecting lesions in patients with drug-resistant epilepsy. This, in turn, will improve surgical outcomes via more structured surgical planning. It is a global effort, with more than 20 sites across 5 continents. The targeted populations for this study include patients whose epilepsy stems from Focal Cortical Dysplasia. Focal Cortical Dysplasia is an abnormality of cortical development, and causes most of the drug-resistant epilepsy. Currently, the creators of MELD have developed a set of protocols which wrap various
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
commands designed to streamline post-processing of MRI images. Using this partnership, the Applied Neuroscience and Technology Lab at PCH has been able to complete production of a post-processing pipeline which integrates locally sourced smoothing techniques to help identify lesions in patients with evidence of Focal Cortical Dysplasia. The end result is a system in which a patient with epilepsy may experience more successful post-surgical results due to the
combination of a lesion detection mechanism and the radiologist using their trained eye in the presurgical stages. As one of the main points of this work is the global aspect of it, Barrett thesis funding was dedicated for a trip to London in order to network with other MELD project collaborators. This was a successful trip for the project as a whole in addition to this particular thesis. The ability to troubleshoot problems with one another in a room full of subject matter
experts allowed for a high level of discussion and learning. Future work includes implementing machine learning approaches which consider all morphometry parameters simultaneously.
ContributorsHumphreys, Zachary William (Author) / Kodibagkar, Vikram (Thesis director) / Foldes, Stephen (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
At Arizona State University (ASU), there is a perceived lack of interdisciplinary symposiums for student presenters and a lack of understanding about the university's "#1 in Innovation" title awarded by U.S. News & World report. In addition, ASU focuses on advertising innovation in a few select fields, such as astronomy and space exploration. To address these issues, a team of Lincoln Undergraduate Scholars planned an Ethics & Innovation Symposium with the theme of "Defining Our Future" for April 11, 2018. I chose to conduct a post-event analysis of logistics, successes, and failures. This additional evaluation was meant to serve as a measure of the symposium's sustainability for future years. This thesis addresses the methods of event planning (incl. marketing, gathering student presenters, catering, room reservation), results, and analysis of outcomes specifically for the Ethics & Innovation Symposium. Overall, the thesis document will benefit anyone interested in planning some event at the university level. Additional reference documents are included in this report to provide help with creating a general checklist, developing marketing deliverables, and contacting university departments/organizations.
ContributorsJagadish, Ishitha (Author) / Coursen, Jerry (Thesis director) / Kenney, Sean (Committee member) / O'Neil, Erica (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Traumatic brain injury (TBI) is a major concern in public health due to its prevalence and effect. Every year, about 1.7 million TBIs are reported [7]. According to the According to the Centers for Disease Control and Prevention (CDC), 5.5% of all emergency department visits, hospitalizations, and deaths from 2002 to 2006 are due to TBI [8]. The brain's natural defense, the Blood Brain Barrier (BBB), prevents the entry of most substances into the brain through the blood stream, including medicines administered to treat TBI [11]. TBI may cause the breakdown of the BBB, and may result in increased permeability, providing an opportunity for NPs to enter the brain [3,4]. Dr. Stabenfeldt's lab has previously established that intravenously injected nanoparticles (NP) will accumulate near the injury site after focal brain injury [4]. The current project focuses on confirmation of the accumulation or extravasation of NPs after brain injury using 2-photon microscopy. Specifically, the project used controlled cortical impact injury induced mice models that were intravenously injected with 40nm NPs post-injury. The MATLAB code seeks to analyze the brain images through registration, segmentation, and intensity measurement and evaluate if fluorescent NPs will accumulate in the extravascular tissue of injured mice models. The code was developed with 2D bicubic interpolation, subpixel image registration, drawn dimension segmentation and fixed dimension segmentation, and dynamic image analysis. A statistical difference was found between the extravascular tissue of injured and uninjured mouse models. This statistical difference proves that the NPs do extravasate through the permeable cranial blood vessels in injured cranial tissue.
ContributorsIrwin, Jacob Aleksandr (Author) / Stabenfeldt, Sarah (Thesis director) / Bharadwaj, Vimala (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The International Dyslexia Association defines dyslexia as a learning disorder that is characterized by poor spelling, decoding, and word recognition abilities. There is still no known cause of dyslexia, although it is a very common disability that affects 1 in 10 people. Previous fMRI and MRI research in dyslexia has explored the neural correlations of hemispheric lateralization and phonemic awareness in dyslexia. The present study investigated the underlying neurobiology of five adults with dyslexia compared to age- and sex-matched control subjects using structural and functional magnetic resonance imaging. All subjects completed a large battery of behavioral tasks as part of a larger study and underwent functional and structural MRI acquisition. This data was collected and preprocessed at the University of Washington. Analyses focused on examining the neural correlates of hemispheric lateralization, letter reversal mistakes, reduced processing speed, and phonemic awareness. There were no significant findings of hemispheric differences between subjects with dyslexia and controls. The subject making the largest amount of letter reversal errors had deactivation in their cerebellum during the fMRI language task. Cerebellar white matter volume and surface area of the premotor cortex was the largest in the individual with the slowest reaction time to tapping. Phonemic decoding efficiency had a high correlation with neural activation in the primary motor cortex during the fMRI motor task (r=0.6). Findings from the present study suggest that brain regions utilized during motor control, such as the cerebellum, premotor cortex, and primary motor cortex, may have a larger role in dyslexia then previously considered. Future studies are needed to further distinguish the role of the cerebellum and other motor regions in relation to motor control and language processing deficits related to dyslexia.
ContributorsHoulihan, Chloe Carissa Prince (Author) / Rogalsky, Corianne (Thesis director) / Peter, Beate (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Memory augmentation will play a vital role in the development of our future. The predicted introduction of downloadable brains will be the first of many neurocognitive technologies that will alter our lives at both the societal and individual levels. These technologies can affect everything from educational institutions to the judicial system, meanwhile raising issues such as autonomy, human psychology, and selfhood. Because of its tremendous potential, memory augmentation and its implications should thoroughly be examined.
ContributorsKim, Jinkyu (Author) / McGregor, Joan (Thesis director) / Robert, Jason (Committee member) / Helms Tillery, Stephen (Committee member) / Barrett, The Honors College (Contributor) / Division of Educational Leadership and Innovation (Contributor) / Harrington Bioengineering Program (Contributor)
Created2013-05
Description
The development of computational systems known as brain-computer interfaces (BCIs) offers the possibility of allowing individuals disabled by neurological disorders such as Amyotrophic Lateral Sclerosis (ALS) and ischemic stroke the ability to perform relatively complex tasks such as communicating with others and walking. BCIs are closed-loop systems that record physiological signals from the brain and translate those signals into commands that control an external device such as a wheelchair or a robotic exoskeleton. Despite the potential for BCIs to vastly improve the lives of almost one billion people, one question arises: Just because we can use brain-computer interfaces, should we? The human brain is an embodiment of the mind, which is largely seen to determine a person's identity, so a number of ethical and philosophical concerns emerge over current and future uses of BCIs. These concerns include privacy, informed consent, autonomy, identity, enhancement, and justice. In this thesis, I focus on three of these issues: privacy, informed consent, and autonomy. The ultimate purpose of brain-computer interfaces is to provide patients with a greater degree of autonomy; thus, many of the ethical issues associated with BCIs are intertwined with autonomy. Currently, brain-computer interfaces exist mainly in the domain of medicine and medical research, but recently companies have started commercializing BCIs and providing them at affordable prices. These consumer-grade BCIs are primarily for non-medical purposes, and so they are beyond the scope of medicine. As BCIs become more widespread in the near future, it is crucial for interdisciplinary teams of ethicists, philosophers, engineers, and physicians to collaborate to address these ethical concerns now before BCIs become more commonplace.
ContributorsChu, Kevin Michael (Author) / Ankeny, Casey (Thesis director) / Robert, Jason (Committee member) / Frow, Emma (Committee member) / Harrington Bioengineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor) / School for the Future of Innovation in Society (Contributor) / Lincoln Center for Applied Ethics (Contributor)
Created2016-05