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Description
Aortic pathologies such as coarctation, dissection, and aneurysm represent a

particularly emergent class of cardiovascular diseases and account for significant cardiovascular morbidity and mortality worldwide. Computational simulations of aortic flows are growing increasingly important as tools for gaining understanding of these pathologies and for planning their surgical repair. In vitro experiments

Aortic pathologies such as coarctation, dissection, and aneurysm represent a

particularly emergent class of cardiovascular diseases and account for significant cardiovascular morbidity and mortality worldwide. Computational simulations of aortic flows are growing increasingly important as tools for gaining understanding of these pathologies and for planning their surgical repair. In vitro experiments are required to validate these simulations against real world data, and a pulsatile flow pump system can provide physiologic flow conditions characteristic of the aorta.

This dissertation presents improved experimental techniques for in vitro aortic blood flow and the increasingly larger parts of the human cardiovascular system. Specifically, this work develops new flow management and measurement techniques for cardiovascular flow experiments with the aim to improve clinical evaluation and treatment planning of aortic diseases.

The hypothesis of this research is that transient flow driven by a step change in volume flux in a piston-based pulsatile flow pump system behaves differently from transient flow driven by a step change in pressure gradient, the development time being substantially reduced in the former. Due to this difference in behavior, the response to a piston-driven pump can be predicted in order to establish inlet velocity and flow waveforms at a downstream phantom model.

The main objectives of this dissertation were: 1) to design, construct, and validate a piston-based flow pump system for aortic flow experiments, 2) to characterize temporal and spatial development of start-up flows driven by a piston pump that produces a step change from zero flow to a constant volume flux in realistic (finite) tube geometries for physiologic Reynolds numbers, and 3) to develop a method to predict downstream velocity and flow waveforms at the inlet of an aortic phantom model and determine the input waveform needed to achieve the intended waveform at the test section. Application of these newly improved flow management tools and measurement techniques were then demonstrated through in vitro experiments in patient-specific coarctation of aorta flow phantom models manufactured in-house and compared to computational simulations to inform and execute future experiments and simulations.
ContributorsChaudhury, Rafeed Ahmed (Author) / Frakes, David (Thesis advisor) / Adrian, Ronald J (Thesis advisor) / Vernon, Brent (Committee member) / Pizziconi, Vincent (Committee member) / Caplan, Michael (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Tracking microscale targets in soft tissue using implantable probes is important in clinical applications such as neurosurgery, chemotherapy and in neurophysiological application such as brain monitoring. In most of these applications, such tracking is done with visual feedback involving some imaging modality that helps localization of the targets through images

Tracking microscale targets in soft tissue using implantable probes is important in clinical applications such as neurosurgery, chemotherapy and in neurophysiological application such as brain monitoring. In most of these applications, such tracking is done with visual feedback involving some imaging modality that helps localization of the targets through images that are co-registered with stereotaxic coordinates. However, there are applications in brain monitoring where precision targeting of microscale targets such as single neurons need to be done in the absence of such visual feedback. In all of the above mentioned applications, it is important to understand the dynamics of mechanical stress and strain induced by the movement of implantable, often microscale probes in soft viscoelastic tissue. Propagation of such stresses and strains induce inaccuracies in positioning if they are not adequately compensated. The aim of this research is to quantitatively assess (a) the lateral propagation of stress and (b) the spatio-temporal distribution of strain induced by the movement of microscale probes in soft viscoelastic tissue. Using agarose hydrogel and a silicone derivative as two different bench-top models of brain tissue, we measured stress propagation during movement of microscale probes using a sensitive load cell. We further used a solution of microscale beads and the silicone derivative to quantitatively map the strain fields using video microscopy. The above measurements were done under two different types of microelectrode movement – first, a unidirectional movement and second, a bidirectional (inch-worm like) movement both of 30 μm step-size with 3min inter-movement interval. Results indicate movements of microscale probes can induce significant stresses as far as 500 μm laterally from the location of the probe. Strain fields indicate significantly high levels of displacements (in the order of 100 μm) within 100 μm laterally from the surface of the probes. The above measurements will allow us to build precise mechanical models of soft tissue and compensators that will enhance the accuracy of tracking microscale targets in soft tissue.
ContributorsTalebianmoghaddam, Shahrzad (Author) / Muthuswamy, Jitendran (Thesis advisor) / Towe, Bruce (Committee member) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Cerebral aneurysms are pathological balloonings of blood vessels in the brain, commonly found in the arterial network at the base of the brain. Cerebral aneurysm rupture can lead to a dangerous medical condition, subarachnoid hemorrhage, that is associated with high rates of morbidity and mortality. Effective evaluation and management of

Cerebral aneurysms are pathological balloonings of blood vessels in the brain, commonly found in the arterial network at the base of the brain. Cerebral aneurysm rupture can lead to a dangerous medical condition, subarachnoid hemorrhage, that is associated with high rates of morbidity and mortality. Effective evaluation and management of cerebral aneurysms is therefore essential to public health. The goal of treating an aneurysm is to isolate the aneurysm from its surrounding circulation, thereby preventing further growth and rupture. Endovascular treatment for cerebral aneurysms has gained popularity over traditional surgical techniques due to its minimally invasive nature and shorter associated recovery time. The hemodynamic modifications that the treatment effects can promote thrombus formation within the aneurysm leading to eventual isolation. However, different treatment devices can effect very different hemodynamic outcomes in aneurysms with different geometries.

Currently, cerebral aneurysm risk evaluation and treatment planning in clinical practice is largely based on geometric features of the aneurysm including the dome size, dome-to-neck ratio, and parent vessel geometry. Hemodynamics, on the other hand, although known to be deeply involved in cerebral aneurysm initiation and progression, are considered to a lesser degree. Previous work in the field of biofluid mechanics has demonstrated that geometry is a driving factor behind aneurysmal hemodynamics.

The goal of this research is to develop a more combined geometric/hemodynamic basis for informing clinical decisions. Geometric main effects were analyzed to quantify contributions made by geometric factors that describe cerebral aneurysms (i.e., dome size, dome-to-neck ratio, and inflow angle) to clinically relevant hemodynamic responses (i.e., wall shear stress, root mean square velocity magnitude and cross-neck flow). Computational templates of idealized bifurcation and sidewall aneurysms were created to satisfy a two-level full factorial design, and examined using computational fluid dynamics. A subset of the computational bifurcation templates was also translated into physical models for experimental validation using particle image velocimetry. The effects of geometry on treatment were analyzed by virtually treating the aneurysm templates with endovascular devices. The statistical relationships between geometry, treatment, and flow that emerged have the potential to play a valuable role in clinical practice.
ContributorsNair, Priya (Author) / Frakes, David (Thesis advisor) / Vernon, Brent (Committee member) / Chong, Brian (Committee member) / Pizziconi, Vincent (Committee member) / Adrian, Ronald (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors

Magnetic resonance spectroscopic imaging (MRSI) is a valuable technique for assessing the in vivo spatial profiles of metabolites like N-acetylaspartate (NAA), creatine, choline, and lactate. Changes in metabolite concentrations can help identify tissue heterogeneity, providing prognostic and diagnostic information to the clinician. The increased uptake of glucose by solid tumors as compared to normal tissues and its conversion to lactate can be exploited for tumor diagnostics, anti-cancer therapy, and in the detection of metastasis. Lactate levels in cancer cells are suggestive of altered metabolism, tumor recurrence, and poor outcome. A dedicated technique like MRSI could contribute to an improved assessment of metabolic abnormalities in the clinical setting, and introduce the possibility of employing non-invasive lactate imaging as a powerful prognostic marker.

However, the long acquisition time in MRSI is a deterrent to its inclusion in clinical protocols due to associated costs, patient discomfort (especially in pediatric patients under anesthesia), and higher susceptibility to motion artifacts. Acceleration strategies like compressed sensing (CS) permit faithful reconstructions even when the k-space is undersampled well below the Nyquist limit. CS is apt for MRSI as spectroscopic data are inherently sparse in multiple dimensions of space and frequency in an appropriate transform domain, for e.g. the wavelet domain. The objective of this research was three-fold: firstly on the preclinical front, to prospectively speed-up spectrally-edited MRSI using CS for rapid mapping of lactate and capture associated changes in response to therapy. Secondly, to retrospectively evaluate CS-MRSI in pediatric patients scanned for various brain-related concerns. Thirdly, to implement prospective CS-MRSI acquisitions on a clinical magnetic resonance imaging (MRI) scanner for fast spectroscopic imaging studies. Both phantom and in vivo results demonstrated a reduction in the scan time by up to 80%, with the accelerated CS-MRSI reconstructions maintaining high spectral fidelity and statistically insignificant errors as compared to the fully sampled reference dataset. Optimization of CS parameters involved identifying an optimal sampling mask for CS-MRSI at each acceleration factor. It is envisioned that time-efficient MRSI realized with optimized CS acceleration would facilitate the clinical acceptance of routine MRSI exams for a quantitative mapping of important biomarkers.
ContributorsVidya Shankar, Rohini (Author) / Kodibagkar, Vikram D (Thesis advisor) / Pipe, James (Committee member) / Chang, John (Committee member) / Sadleir, Rosalind (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Traumatic brain injury (TBI) is a significant public health concern in the U.S., where approximately 1.7 million Americans sustain a TBI annually, an estimated 52,000 of which lead to death. Almost half (43%) of all TBI patients report experiencing long-term cognitive and/or motor dysfunction. These long-term deficits are largely due

Traumatic brain injury (TBI) is a significant public health concern in the U.S., where approximately 1.7 million Americans sustain a TBI annually, an estimated 52,000 of which lead to death. Almost half (43%) of all TBI patients report experiencing long-term cognitive and/or motor dysfunction. These long-term deficits are largely due to the expansive biochemical injury that underlies the mechanical injury traditionally associated with TBI. Despite this, there are currently no clinically available therapies that directly address these underlying pathologies. Preclinical studies have looked at stem cell transplantation as a means to mitigate the effects of the biochemical injury with moderate success; however, transplants suffer very low retention and engraftment rates (2-4%). Therefore, transplants need better tools to dynamically respond to the injury microenvironment.

One approach to develop new tools for stem cell transplants may be to look towards the endogenous repair response for inspiration. Specifically, activated cell types surrounding the injury secrete the chemokine stromal cell-derived factor-1α (SDF-1α), which has been shown to play a critical role in recruiting endogenous neural progenitor/stem cells (NPSCs) to the site of injury. Therefore, it was hypothesized that improving NPSC response to SDF-1α may be a viable mechanism for improving NPSC transplant retention and migration into the surrounding host tissue. To this end, work presented here has 1. identified critical extracellular signals that mediate the NPSC response to SDF-1α, 2. incorporated these findings into the development of a transplantation platform that increases NPSC responsiveness to SDF-1α and 3. observed increased NPSC responsiveness to local exogenous SDF-1α signaling following transplantation within our novel system. Future work will include studies investigating NSPC response to endogenous, injury-induced SDF-1α and the application of this work to understanding differences between stem cell sources and their implications in cell therapies.
ContributorsAddington, Caroline (Author) / Stabenfeldt, Sarah E (Thesis advisor) / Kleim, Jeffrey A (Committee member) / Caplan, Michael R (Committee member) / Lifshitz, Jonathan (Committee member) / Massia, Stephen P (Committee member) / Arizona State University (Publisher)
Created2015
Description
Through decades of clinical progress, cochlear implants have brought the world of speech and language to thousands of profoundly deaf patients. However, the technology has many possible areas for improvement, including providing information of non-linguistic cues, also called indexical properties of speech. The field of sensory substitution, providing information relating

Through decades of clinical progress, cochlear implants have brought the world of speech and language to thousands of profoundly deaf patients. However, the technology has many possible areas for improvement, including providing information of non-linguistic cues, also called indexical properties of speech. The field of sensory substitution, providing information relating one sense to another, offers a potential avenue to further assist those with cochlear implants, in addition to the promise they hold for those without existing aids. A user study with a vibrotactile device is evaluated to exhibit the effectiveness of this approach in an auditory gender discrimination task. Additionally, preliminary computational work is included that demonstrates advantages and limitations encountered when expanding the complexity of future implementations.
ContributorsButts, Austin McRae (Author) / Helms Tillery, Stephen (Thesis advisor) / Berisha, Visar (Committee member) / Buneo, Christopher (Committee member) / McDaniel, Troy (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and

Cigarette smoking remains a major global public health issue. This is partially due to the chronic and relapsing nature of tobacco use, which contributes to the approximately 90% quit attempt failure rate. The recent rise in mobile technologies has led to an increased ability to frequently measure smoking behaviors and related constructs over time, i.e., obtain intensive longitudinal data (ILD). Dynamical systems modeling and system identification methods from engineering offer a means to leverage ILD in order to better model dynamic smoking behaviors. In this dissertation, two sets of dynamical systems models are estimated using ILD from a smoking cessation clinical trial: one set describes cessation as a craving-mediated process; a second set was reverse-engineered and describes a psychological self-regulation process in which smoking activity regulates craving levels. The estimated expressions suggest that self-regulation more accurately describes cessation behavior change, and that the psychological self-regulator resembles a proportional-with-filter controller. In contrast to current clinical practice, adaptive smoking cessation interventions seek to personalize cessation treatment over time. An intervention of this nature generally reflects a control system with feedback and feedforward components, suggesting its design could benefit from a control systems engineering perspective. An adaptive intervention is designed in this dissertation in the form of a Hybrid Model Predictive Control (HMPC) decision algorithm. This algorithm assigns counseling, bupropion, and nicotine lozenges each day to promote tracking of target smoking and craving levels. Demonstrated through a diverse series of simulations, this HMPC-based intervention can aid a successful cessation attempt. Objective function weights and three-degree-of-freedom tuning parameters can be sensibly selected to achieve intervention performance goals despite strict clinical and operational constraints. Such tuning largely affects the rate at which peak bupropion and lozenge dosages are assigned; total post-quit smoking levels, craving offset, and other performance metrics are consequently affected. Overall, the interconnected nature of the smoking and craving controlled variables facilitate the controller's robust decision-making capabilities, even despite the presence of noise or plant-model mismatch. Altogether, this dissertation lays the conceptual and computational groundwork for future efforts to utilize engineering concepts to further study smoking behaviors and to optimize smoking cessation interventions.
ContributorsTimms, Kevin Patrick (Author) / Rivera, Daniel E (Thesis advisor) / Frakes, David (Committee member) / Nielsen, David R (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The advent of medical imaging has enabled significant advances in pre-procedural planning, allowing cardiovascular anatomy to be visualized noninvasively before a procedure. However, absolute scale and tactile information are not conveyed in traditional pre-procedural planning based on images alone. This information deficit fails to completely prepare clinicians for complex heart

The advent of medical imaging has enabled significant advances in pre-procedural planning, allowing cardiovascular anatomy to be visualized noninvasively before a procedure. However, absolute scale and tactile information are not conveyed in traditional pre-procedural planning based on images alone. This information deficit fails to completely prepare clinicians for complex heart repair, where surgeons must consider the varied presentations of cardiac morphology and malformations. Three-dimensional (3D) visualization and 3D printing provide a mechanism to construct patient-specific, scale models of cardiovascular anatomy that surgeons and interventionalists can examine prior to a procedure. In addition, the same patient-specific models provide a valuable resource for educating future medical professionals. Instead of looking at idealized images on a computer screen or pages from medical textbooks, medical students can review a life-like model of patient anatomy.



In cases where surgical repair is insufficient to return the heart to normal function, a patient may proceed to advanced heart failure, and a heart transplant may be required. Unfortunately, a finite number of available donor hearts are available. A mechanical circulatory support (MCS) device can be used to bridge the time between heart failure and reception of a donor heart. These MCS devices are typically constructed for the adult population. Accordingly, the size associated to the device is a limiting factor for small adults or pediatric patients who often have smaller thoracic measurements. While current eligibility criteria are based on correlative measurements, the aforementioned 3D visualization capabilities can be leveraged to accomplish patient-specific fit analysis.

The main objectives of the work presented in this dissertation were 1) to develop and evaluate an optimized process for 3D printing cardiovascular anatomy for surgical planning and medical education and 2) to develop and evaluate computational tools to assess MCS device fit in specific patients. The evaluations for objectives 1 and 2 were completed with a collection of qualitative and quantitative validations. These validations include case studies to illustrate meaningful, qualitative results as well as quantitative results from surgical outcomes. The latter results present the first quantitative supporting evidence, beyond anecdotal case studies, regarding the efficacy of 3D printing for pre-procedural planning; this data is suitable as pilot data for clinical trials. The products of this work were used to plan 200 cardiovascular procedures (including 79 cardiothoracic surgeries at Phoenix Children's Hospital), via 3D printed heart models and assess MCS device fit in 29 patients across 6 countries.
ContributorsRyan, Justin Robert (Author) / Frakes, David (Thesis advisor) / Collins, Daniel (Committee member) / LaBelle, Jeffrey (Committee member) / Pizziconi, Vincent (Committee member) / Pophal, Stephen (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Parkinson's disease (PD) is a neurodegenerative disorder that produces a characteristic set of neuromotor deficits that sometimes includes reduced amplitude and velocity of movement. Several studies have shown that people with PD improved their motor performance when presented with external cues. Other work has demonstrated that high velocity

Parkinson's disease (PD) is a neurodegenerative disorder that produces a characteristic set of neuromotor deficits that sometimes includes reduced amplitude and velocity of movement. Several studies have shown that people with PD improved their motor performance when presented with external cues. Other work has demonstrated that high velocity and large amplitude exercises can increase the amplitude and velocity of movement in simple carryover tasks in the upper and lower extremities. Although the cause for these effects is not known, improvements due to cueing suggest that part of the neuromotor deficit in PD is in the integration of sensory feedback to produce motor commands. Previous studies have documented some somatosensory deficits, but only limited information is available regarding the nature and magnitude of sensorimotor deficits in the shoulder of people with PD. The goals of this research were to characterize the sensorimotor impairment in the shoulder joint of people with PD and to investigate the use of visual feedback and large amplitude/high velocity exercises to target PD-related motor deficits. Two systems were designed and developed to use visual feedback to assess the ability of participants to accurately adjust limb placement or limb movement velocity and to encourage improvements in performance of these tasks. Each system was tested on participants with PD, age-matched control subjects and young control subjects to characterize and compare limb placement and velocity control capabilities. Results demonstrated that participants with PD were less accurate at placing their limbs than age-matched or young control subjects, but that their performance improved over the course of the test session such that by the end, the participants with PD performed as well as controls. For the limb velocity feedback task, participants with PD and age-matched control subjects were less accurate than young control subjects, but at the end of the session, participants with PD and age-matched control subjects were as accurate as the young control subjects. This study demonstrates that people with PD were able to improve their movement patterns based on visual feedback of performance and suggests that this feedback paradigm may be useful in exercise programs for people with PD.
ContributorsSmith, Catherine (Author) / Abbas, James J (Thesis advisor) / Ingalls, Todd (Thesis advisor) / Krishnamurthi, Narayanan (Committee member) / Buneo, Christopher (Committee member) / Rikakis, Thanassis (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Gait and balance disorders are the second leading cause of falls in the elderly. Investigating the changes in static and dynamic balance due to aging may provide a better understanding of the effects of aging on postural control system. Static and dynamic balance were evaluated in a total of 21

Gait and balance disorders are the second leading cause of falls in the elderly. Investigating the changes in static and dynamic balance due to aging may provide a better understanding of the effects of aging on postural control system. Static and dynamic balance were evaluated in a total of 21 young (21-35 years) and 22 elderly (50-75 years) healthy subjects while they performed three different tasks: quiet standing, dynamic weight shifts, and over ground walking. During the quiet standing task, the subjects stood with their eyes open and eyes closed. When performing dynamic weight shifts task, subjects shifted their Center of Pressure (CoP) from the center target to outward targets and vice versa while following real-time feedback of their CoP. For over ground walking tasks, subjects performed Timed Up and Go test, tandem walking, and regular walking at their self-selected speed. Various quantitative balance and gait measures were obtained to evaluate the above respective balance and walking tasks. Total excursion, sway area, and mean frequency of CoP during quiet standing were found to be the most reliable and showed significant increase with age and absence of visual input. During dynamic shifts, elderly subjects exhibited higher initiation time, initiation path length, movement time, movement path length, and inaccuracy indicating deterioration in performance. Furthermore, the elderly walked with a shorter stride length, increased stride variability, with a greater turn and turn-to-sit duration. Significant correlations were also observed between measures derived from the different balance and gait tasks. Thus, it can be concluded that aging deteriorates the postural control system affecting static and dynamic balance and some of the alterations in CoP and gait measures may be considered as protective mechanisms to prevent loss of balance.
ContributorsBalasubramanian, Shruthi (Author) / Krishnamurthi, Narayanan (Thesis advisor) / Abbas, James (Thesis advisor) / Buneo, Christopher (Committee member) / Arizona State University (Publisher)
Created2014