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- Creators: Barrett, The Honors College
- Creators: Harrington Bioengineering Program
- Resource Type: Text
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
Background: Noninvasive MRI methods that can accurately detect subtle brain changes are highly desirable when studying disease-modifying interventions. Texture analysis is a novel imaging technique which utilizes the extraction of a large number of image features with high specificity and predictive power. In this investigation, we use texture analysis to assess and classify age-related changes in the right and left hippocampal regions, the areas known to show some of the earliest change in Alzheimer's disease (AD). Apolipoprotein E (APOE)'s e4 allele confers an increased risk for AD, so studying differences in APOE e4 carriers may help to ascertain subtle brain changes before there has been an obvious change in behavior. We examined texture analysis measures that predict age-related changes, which reflect atrophy in a group of cognitively normal individuals. We hypothesized that the APOE e4 carriers would exhibit significant age-related differences in texture features compared to non-carriers, so that the predictive texture features hold promise for early assessment of AD. Methods: 120 normal adults between the ages of 32 and 90 were recruited for this neuroimaging study from a larger parent study at Mayo Clinic Arizona studying longitudinal cognitive functioning (Caselli et al., 2009). As part of the parent study, the participants were genotyped for APOE genetic polymorphisms and received comprehensive cognitive testing every two years, on average. Neuroimaging was done at Barrow Neurological Institute and a 3D T1-weighted magnetic resonance image was obtained during scanning that allowed for subsequent texture analysis processing. Voxel-based features of the appearance, structure, and arrangement of these regions of interest were extracted utilizing the Mayo Clinic Python Texture Analysis Pipeline (pyTAP). Algorithms applied in feature extraction included Grey-Level Co-Occurrence Matrix (GLCM), Gabor Filter Banks (GFB), Local Binary Patterns (LBP), Discrete Orthogonal Stockwell Transform (DOST), and Laplacian-of-Gaussian Histograms (LoGH). Principal component (PC) analysis was used to reduce the dimensionality of the algorithmically selected features to 13 PCs. A stepwise forward regression model was used to determine the effect of APOE status (APOE e4 carriers vs. noncarriers), and the texture feature principal components on age (as a continuous variable). After identification of 5 significant predictors of age in the model, the individual feature coefficients of those principal components were examined to determine which features contributed most significantly to the prediction of an aging brain. Results: 70 texture features were extracted for the two regions of interest in each participant's scan. The texture features were coded as 70 initial components andwere rotated to generate 13 principal components (PC) that contributed 75% of the variance in the dataset by scree plot analysis. The forward stepwise regression model used in this exploratory study significantly predicted age, accounting for approximately 40% of the variance in the data. The regression model revealed 5 significant regressors (2 right PC's, APOE status, and 2 left PC by APOE interactions). Finally, the specific texture features that contributed to each significant PCs were identified. Conclusion: Analysis of image texture features resulted in a statistical model that was able to detect subtle changes in brain integrity associated with age in a group of participants who are cognitively normal, but have an increased risk of developing AD based on the presence of the APOE e4 phenotype. This is an important finding, given that detecting subtle changes in regions vulnerable to the effects of AD in patients could allow certain texture features to serve as noninvasive, sensitive biomarkers predictive of AD. Even with only a small number of patients, the ability for us to determine sensitive imaging biomarkers could facilitate great improvement in speed of detection and effectiveness of AD interventions..
ContributorsSilva, Annelise Michelle (Author) / Baxter, Leslie (Thesis director) / McBeath, Michael (Committee member) / Presson, Clark (Committee member) / School of Life Sciences (Contributor) / Department of Psychology (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
One major issue that surgeons face during closed body cavity surgery is fogging of the lens surfaces. The cloudy and opaque lens surface caused by water vapor present in closed body cavities forces the surgeon to repeatedly remove the endoscope, wipe it, and reinsert it back into the patient. This presents several risks such as increased surgery time, greater scarring, and an increased chance of infection. In order to address this issue, the development of the Thin Fluid Film Device (TFFD™) VitreOx™ aims to render the lens surface hydrophilic, whereas it is typically hydrophobic. By creating a hydrophilic polymeric nanomesh, the 3-D water droplets can be trapped to lie flatter, thus resulting in a flatter 2-D sheeting effect. The light can no longer be refracted at different angles off of the 3-dimensional water beads, thus eliminating the opacity of the lens surface.
Two animal trials were performed involving a rat and two pigs in order to prove the efficacy of VitreOx™ in addition to being compared with competitor, Covidien Clearify. A laparoscopy was performed on each animal, and the length of time that the endoscope took to fog was measured post product application. The results of the optimized animal clinical trials involving two Yucatan pigs showed that the scope treated with Covidien’s Clearify began fogging within 8 minutes and continued to do so for the remained of the surgery, as opposed to the scope with VitreOx™ which remained fog free for the full 90-minute procedure. The results proved the efficacy of our product.
The second part of the thesis aimed to optimize HemoClear™, the blood evacuating TFFD™. This was done by testing a higher concentration of 6 mg/mL fibrinogen as compared to previous work. After conducting an experiment designed to mimic closed-body cavity surgery it was determined that the HemoClear™ eliminated fog 67% of the time and evacuated blood with a success of 83%. Future work aims to continue testing at this concentration with variances in mixing and application technique.
Two animal trials were performed involving a rat and two pigs in order to prove the efficacy of VitreOx™ in addition to being compared with competitor, Covidien Clearify. A laparoscopy was performed on each animal, and the length of time that the endoscope took to fog was measured post product application. The results of the optimized animal clinical trials involving two Yucatan pigs showed that the scope treated with Covidien’s Clearify began fogging within 8 minutes and continued to do so for the remained of the surgery, as opposed to the scope with VitreOx™ which remained fog free for the full 90-minute procedure. The results proved the efficacy of our product.
The second part of the thesis aimed to optimize HemoClear™, the blood evacuating TFFD™. This was done by testing a higher concentration of 6 mg/mL fibrinogen as compared to previous work. After conducting an experiment designed to mimic closed-body cavity surgery it was determined that the HemoClear™ eliminated fog 67% of the time and evacuated blood with a success of 83%. Future work aims to continue testing at this concentration with variances in mixing and application technique.
ContributorsSinha, Saloni Agarwal (Author) / Culbertson, Robert (Thesis director) / Herbots, Nicole (Committee member) / Watson, Clarizza (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2015-05
Description
Spasticity is a neurological disorder in which a target group of muscles remain in a contracted state. In addition to interfering with the function of these muscles, spasticity causes chronic pain and discomfort. Often found in patients with cerebral palsy, multiple sclerosis, or stroke history, spasticity affects an estimated twelve million people worldwide. Not only does spasticity cause discomfort and loss of function, but the condition can lead to contractures, or permanent shortenings of the muscle and connective tissue, if left untreated. Current treatments for spasticity are primarily different forms of muscle relaxant pharmaceuticals. Almost all of these drugs, however, carry unwanted side effects, including total muscle weakness, liver toxicity, and possible dependence. Additionally, kinesiotherapy, conducted by physical therapists at rehabilitation clinics, is often prescribed to people suffering from spasticity. Since kinesiotherapy requires frequent practice to be effective, proper treatment requires constant professional care and clinic appointments, discouraging patient compliance. Consequently, a medical device that could automate relief for spasticity outside of a clinic is desired in the market. While a number of different dynamic splints for hand spasticity are currently on the market, research has shown that these devices, which simply brace the hand in an extended position, do not work through any mechanism to decrease spastic tension over time. Two methods of temporarily reducing spasticity that have been observed in clinical studies are cryotherapy, or the decrease of temperature on a target area, and electrotherapy, which is the delivery of regulated electrical pulses to a target area. It is possible that either of these mechanisms could be incorporated into a medical device aimed toward spastic relief. In fact, electrotherapy is used in a current market device called the SaeboStim, which is advertised to help stroke recovery and spastic reduction. The purpose of this paper is to evaluate the viability of a potential spastic relief device that utilizes cryotherapy to a current and closest competitor, the SaeboStim. The effectiveness of each device in relieving spasticity is reviewed. The two devices are also compared on their ability to address primary customer needs, such as convenience, ease of use, durability, and price. Overall, it is concluded that the cryotherapy device more effectively relieves hand spasticity in users, although the SaeboStim's smaller size and better convenience gives it market appeal, and reveals some of the shortcomings in the preliminary design of the cryotherapy device.
ContributorsWiedeman, Christopher Blaise (Author) / Kleim, Jeffrey (Thesis director) / Buneo, Christopher (Committee member) / W.P. Carey School of Business (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The reconstruction of piecewise smooth functions from non-uniform Fourier data arises in sensing applications such as magnetic resonance imaging (MRI). This thesis presents a new polynomial based resampling method (PRM) for 1-dimensional problems which uses edge information to recover the Fourier transform at its integer coefficients, thereby enabling the use of the inverse fast Fourier transform algorithm. By minimizing the error of the PRM approximation at the sampled Fourier modes, the PRM can also be used to improve on initial edge location estimates. Numerical examples show that using the PRM to improve on initial edge location estimates and then taking of the PRM approximation of the integer frequency Fourier coefficients is a viable way to reconstruct the underlying function in one dimension. In particular, the PRM is shown to converge more quickly and to be more robust than current resampling techniques used in MRI, and is particularly amenable to highly irregular sampling patterns.
ContributorsGutierrez, Alexander Jay (Author) / Platte, Rodrigo (Thesis director) / Gelb, Anne (Committee member) / Viswanathan, Adityavikram (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-05
Description
The objective of the research presented here was to validate the use of kinetic models for the analysis of the dynamic behavior of a contrast agent in tumor tissue and evaluate the utility of such models in determining kinetic properties - in particular perfusion and molecular binding uptake associated with tissue hypoxia - of the imaged tissue, from concentration data acquired with dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) procedure. Data from two separate DCE-MRI experiments, performed in the past, using a standard contrast agent and a hypoxia-binding agent respectively, were analyzed. The results of the analysis demonstrated that the models used may provide novel characterization of the tumor tissue properties. Future research will work to further characterize the physical significance of the estimated parameters, particularly to provide quantitative oxygenation data for the imaged tissue.
ContributorsMartin, Jonathan Michael (Author) / Kodibagkar, Vikram (Thesis director) / Rege, Kaushal (Committee member) / Barrett, The Honors College (Contributor) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2013-12
Description
In applications such as Magnetic Resonance Imaging (MRI), data are acquired as Fourier samples. Since the underlying images are only piecewise smooth, standard recon- struction techniques will yield the Gibbs phenomenon, which can lead to misdiagnosis. Although filtering will reduce the oscillations at jump locations, it can often have the adverse effect of blurring at these critical junctures, which can also lead to misdiagno- sis. Incorporating prior information into reconstruction methods can help reconstruct a sharper solution. For example, compressed sensing (CS) algorithms exploit the expected sparsity of some features of the image. In this thesis, we develop a method to exploit the sparsity in the edges of the underlying image. We design a convex optimization problem that exploits this sparsity to provide an approximation of the underlying image. Our method successfully reduces the Gibbs phenomenon with only minimal "blurring" at the discontinuities. In addition, we see a high rate of convergence in smooth regions.
ContributorsWasserman, Gabriel Kanter (Author) / Gelb, Anne (Thesis director) / Cochran, Doug (Committee member) / Archibald, Rick (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-05
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
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
As the rates of anxiety in adults rapidly swell, new and creative treatment methods become increasingly relevant. Individuals with an anxiety disorder may experience challenging symptoms that interfere with daily activities and impede academic and social success. The purpose of this project is to design and engineer a portable heart rate monitor that communicates with an iOS mobile application for use by individuals suffering from anxiety or panic disorders. The proposed device captures the innovation of combining biosensor feedback with new, creative therapy methods on a convenient iOS application. The device is implemented as an Arduino Uno which translates radial pulse information onto an LCD screen from a wristband. Additionally, the iOS portion uses a slow expanding and collapsing animation to guide the user through a calming breathing exercise while displaying their pulse in beats per minute. The user's awareness or his or her ability to control one's own physiological state supports and facilitates an additional form of innovative therapy. The current design of the iOS app uses a random-number generator between 40 to 125 to imitate a realistic heart rate. If the value is less than 60 or greater than 105, the number is printed in red; otherwise the heart rate is displayed in green. Future versions of this device incorporate bluetooth capabilities and potentially additional synchronous methods of therapy. The information presented in this research provides an excellent example of the integrations of new mobile technology and healthcare.
ContributorsTadayon, Ramesh (Author) / Muthuswamy, Jit (Thesis director) / Towe, Bruce (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05