Matching Items (55)
Description
Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, causing nearly 25% of deaths in the United States. Despite the efforts to create in vitro models for the study and treatment of CVDs, these are still limited in their recapitulation of the heart tissue. Thus, the engineering of accurate cardiac models is imperative to gain more understanding and improve the outcome of CVDs. This Ph.D. dissertation focuses on the development and characterization of isogenic cardiac organoids derived from human induced pluripotent stem cells (hiPSCs). Additionally, the integration of chemical and biological cues for enriching their microenvironment and promoting their maturation state and function were studied. First, hiPSC-derived cardiac cells were utilized for the fabrication of multicellular spherical microtissues, namely isogenic cardiac organoids. The cellular composition and culture time of the engineered tissues were optimized to induce cellular aggregation and the formation of cell-cell interactions. Also, ribbon-like gold nanoparticles, namely gold nanoribbons (AuNRs), were synthesized, characterized, and biofunctionalized for their integration into the isogenic cardiac organoids. In-depth biological evaluation of the organoids showed enhanced cardiac maturation markers. Furthermore, a supplement-free cell culture regime was designed and evaluated for fabricating isogenic cardiac organoids. Mechanistic, cellular, and molecular-level studies demonstrated that the presence of hiPSC-derived cardiac fibroblasts (hiPSC-CFs) significantly improves the morphology and gene expression profile of the organoids. Electrophysiological-relevant features of the organoids, such as conduction velocity (CV), were further investigated utilizing a microelectrode array (MEA) platform. It was shown that MEA offers a simple, yet powerful approach to assessing electrophysiological responses of the tissues, where a trend in decreased CV was found due to the presence of hiPSC-CFs. Overall, this dissertation has a broad impact casting light on the development strategy and biological mechanisms that govern the formation and function of isogenic cardiac organoids. Moreover, this study presents two unique approaches to promote maturation of stem cell-derived cardiac organoids: 1) through the integration of novel biofunctionalized nanomaterials, and 2) through a cell culture regime, leading to enhanced function of the organoids. The proposed micro-engineered organoids have broad applications as physiologically relevant tissues for drug discovery, CVDs modeling, and regenerative medicine.
ContributorsPatino, Alejandra (Author) / Nikkhah, Medhi (Thesis advisor) / Blain-Christen, Jennifer (Committee member) / Kodibagkar, Vikram (Committee member) / Vernon, Brent (Committee member) / Zhu, Wuqiang (Committee member) / Arizona State University (Publisher)
Created2023
Description
Cardiovascular diseases (CVDs), including myocardial infarction (MI), are the major cause of death globally. Considerable research has been devoted in recent years to developing in vitro cardiac tissue models utilizing human induced pluripotent stem cells (hiPSCs) for regenerative medicine, disease modeling, and drug discovery applications. Notably, electroconductive hydrogel scaffolds have shown great promise in the development of functional hiPSC-derived cardiac tissues for both in vitro and in vivo cardiac research. However, the underlying mechanism(s) by which these nanoparticles contribute to the function and fate of stem cell-derived cardiac tissues have not been fully investigated. To address these knowledge gaps, this Ph.D. dissertation focuses on the mechanistic analysis of the impact of nanoengineered electroconductive hydrogel scaffolds on 2D and 3D hiPSC-derived cardiac tissues. Specifically, within the first phase of the project, hydrogel scaffolds were nanoengineered using either electroconductive or non-conductive nanoparticles to dissect the role of electroconductivity features of gold nanorods (GNRs) in the functionality of isogenic 2D hiPSC-derived cardiac patches. Extensive biological and electrophysiological assessments revealed that, while biophysical cues from the presence of nanoparticles could potentially play a role in cardiac tissue development, electroconductivity cues played a major role in enhancing the functional maturation of hiPSC-derived cardiac tissues in 2D cell-seeded cardiac patches. This dissertation further describes the application of GNRs in developing a biomimetic 3D electroconductive Heart-on-a-chip (eHOC) model. The 3D eHOC model was then leveraged to comprehensively investigate the cellular and molecular responses of isogenic human cardiac tissues to the electroconductive microenvironment through single-cell RNA sequencing (scRNAseq), an aspect not addressed in previous studies. The enhanced functional maturation of the 3D eHOC was demonstrated through extensive tissue-level and molecular-level assays. It was revealed that the GNR-based electroconductive microenvironment contributes to cardiac tissue development through the enrichment of calcium handling and cardiac contractile pathways.Overall, these findings offer additional insights into the role of electroconductive hydrogel scaffolds in regulating the functionalities of hiPSC-derived cardiac tissues. Furthermore, the proposed 3D eHOC platform could also serve as a more physiologically representative model of the in vivo microenvironment for in vitro applications, such as drug testing and disease modeling studies.
ContributorsEsmaeili, Hamid (Author) / Nikkhah, Mehdi (Thesis advisor) / Migrino, Raymond (Committee member) / Zhu, Wuqiang (Committee member) / Vernon, Brent (Committee member) / Weaver, Jessica (Committee member) / Arizona State University (Publisher)
Created2024
Description
Since their invention in the 19th century, polymers have played an essential role, yet their full potential in biomedicine remains largely untapped. Biocompatible polymers, known for their flexibility, accessibility, and modifiability, hold promise in creating complex biomimetic structures for bioscaffolds and biosensors. 3D printing, an emerging manufacturing technique, enables on-demand production of intricate structures, offering significant potential for personalized medicine and advanced biomedical engineering. This thesis focuses on designing and developing polymer-based bioscaffolds and biosensors using 3D printing. Chapter 1 provides an all-round introduction to common 3D printing techniques and polymeric biomaterials, especially biodegradable polymers. In Chapter 2, a gill-mimicking thermoelectric generator (TEG) was created to harvest body temperature and monitor bio-signals without external power. The out-of-plane geometry is obtained with fused deposition modeling (FDM), which is crucial for effective contact with various curved surfaces. Further improvements in biocompatibility enable the material to be implanted in vivo. Chapter 3 discusses UV-facilitated DIW printing for pelvic organ prolapse (POP) tissue scaffolds, featuring crosslink strategies for native tissue-like mechanical behavior. The double network comprises thiol-ene UV-initiated chemical bonds and alkaline-induced crystal regions as physical crosslink nodes. The crosslink density affects the degradation rate of the scaffold, enabling a slow degradation behavior beneficial to the recovery of the injured tissue. Chapter 4 presents a novel artificial artery design with varying moduli and natural polymers for bypass surgeries. The inner and outer layers of the conduit were stretched successively under different strains, endowing the vessel with varying moduli. Natural polymers were utilized to achieve low cytotoxicity and promote adequate cell adhesion. Additionally, the gelation behavior and the ink composition suitable for extrusion with a DIW platform were thoroughly studied. Image analysis, finite element analysis, and machine learning were employed to substantiate the findings regarding mechanical properties, extrusion quality, and printing fidelity in Chapters 3 and 4. This combination of computer-assisted analysis with experimental results enhances the robustness of the studies. Lastly, Chapter 5 provides an outlook and perspectives on the applications of biocompatible polymeric materials manufactured by 3D printing in the field of health applications.
ContributorsZhu, Yuxiang (Author) / Li, Xiangjia (Thesis advisor) / Vernon, Brent (Committee member) / Bhate, Dhruv (Committee member) / Guo, Shenghan (Committee member) / Song, Kenan (Committee member) / Arizona State University (Publisher)
Created2024
Description
Cardiovascular diseases are the number one cause of death worldwide. Cardiac biomarkers can provide objective and quantitative information to facilitate early diagnosis and guide treatment of cardiovascular diseases. Even though a variety of methods have been developed for cardiac biomarker detection, a point-of-care testing (POCT) for cardiac biomarkers with high sensitivity, specificity and precision is still missing. To fulfil this unmet need, novel digital biosensing methods based on optical imaging and nanomaterials are developed in this dissertation for high-sensitivity POCT of cardiac biomarkers.First, a high-sensitivity and POC-compatible optical imaging-based digital immunoassay is developed for rapid detection of low-abundance biomarkers. This technology was established on a model analyte IL-6 and can be adapted to various other protein targets. The digital immunoassay was also utilized as the reference method for evaluating the digital nanobiosensors developed afterwards.
Second, a microfluidic digital nanobiosensor (MDNB) is developed for POC-compatible detection of heart failure biomarker NT-proBNP from 7 µL of whole blood. Using the MDNB, detection in a clinically relevant concentration range was achieved with a 10-minute assay time. With a high potential utility in outpatient and possibly even home settings, the MDNB could become a POC device for decentralized detection of NT-proBNP to assist heart failure patient management.
Lastly, the development of a digital immunogold-linked apta-sorbent assay (DILASA) for rapid high-sensitivity detection of heart attack biomarker cardiac troponin is introduced. Reliable detection of 10 ng/L cTnT in human plasma was achieved with a 15-minute assay time using DILASA. It is expected that with further optimization and development, DILASA will be a promising candidate approach for realizing a high-sensitivity POCT of cTnT.
ContributorsChen, Chao (Author) / Wang, Shaopeng (Thesis advisor) / Snozek, Christine (Committee member) / Pizziconi, Vincent (Committee member) / Vernon, Brent (Committee member) / Weaver, Jessica (Committee member) / Arizona State University (Publisher)
Created2024
Description
Minimally invasive endovascular embolization procedures decrease surgery time, speed up recovery, and provide the possibility for more comprehensive treatment of aneurysms, arteriovenous malformations (AVMs), and hypervascular tumors. Liquid embolic agents (LEAs) are preferred over mechanical embolic agents, such as coils, because they achieve homogeneous filling of aneurysms and more complex angioarchitectures. The gold standard of commercially available LEAs is dissolved in dimethyl sulfoxide (DMSO), which has been associated with vasospasm and angiotoxicity. The aim of this study was to investigate amino acid substitution in an enzyme-degradable side group of an N-isopropylacrylamide (NIPAAm) copolymer for the development of a LEA that would be delivered in water and degrade at the rate that tissue is regenerated. NIPAAm copolymers have a lower critical solution temperature (LCST) due to their amphiphilic nature. This property enables them to be delivered as liquids through a microcatheter below their LCST and to solidify in situ above the LCST, which would result in the successful selective occlusion of blood vessels. Therefore, in this work, a series of poly(NIPAAm-co-peptide) copolymers with hydrophobic side groups containing the Ala-Pro-Gly-Leu collagenase substrate peptide sequence were synthesized as in situ forming, injectable copolymers.. The Gly-Leu peptide bond in these polypeptides is cleaved by collagenase, converting the side group into the more hydrophilic Gly-Ala-Pro-Gly-COOH (GAPG-COOH), thus increasing the LCST of the hydrogel after enzyme degradation. Enzyme degradation property and moderate mechanical stability convinces the use of these copolymers as liquid embolic agents.
ContributorsRosas Gomez, Karime Jocelyn (Author) / Vernon, Brent (Thesis advisor) / Weaver, Jessica (Committee member) / Pal, Amrita (Committee member) / Arizona State University (Publisher)
Created2019
Description
Achieving effective drug concentrations within the central nervous system (CNS) remains one of the greatest challenges for the treatment of brain tumors. The presence of the blood-brain barrier and blood-spinal cord barrier severely restricts the blood-to-CNS entry of nearly all systemically administered therapeutics, often leading to the development of peripheral toxicities before a treatment benefit is observed. To circumvent systemic barriers, intrathecal (IT) injection of therapeutics directly into the cerebrospinal fluid (CSF) surrounding the brain and spinal cord has been used as an alternative administration route; however, its widespread translation to the clinic has been hindered by poor drug pharmacokinetics (PK), including rapid clearance, inadequate distribution, as well as toxicity. One strategy to overcome the limitations of free drug PK and improve drug efficacy is to encapsulate drug within nanoparticles (NP), which solubilize hydrophobic molecules for sustained release in physiological environments. In this thesis, we will develop NP delivery strategies for brain tumor therapy in two model systems: glioblastoma (GBM), the most common and deadly malignant primary brain tumor, and medulloblastoma, the most common pediatric brain tumor. In the first research chapter, we developed 120 nm poly(lactic acid-co-glycolic acid) NPs encapsulating the chemotherapy, camptothecin, for intravenous delivery to GBM. NP encapsulation of camptothecin was shown to reduce the drug’s toxicity and enable effective delivery to orthotopic GBM. To build off the success of intravenous NP, the second research chapter explored the utility of 100 nm PEGylated NPs for use with IT administration. Using in vivo imaging and ex vivo tissue slices, we found the NPs were rapidly transported by the convective forces of the CSF along the entire neuraxis and were retained for over 3 weeks. Based on their wide spread delivery and prolonged circulation, we examine the ability of the NPs to localize with tumor lesions in a leptomeningeal metastasis (LM) model of medulloblastoma. NPs administered to LM bearing mice were shown to penetrate into LM mets seeded within the meninges around the brain. These data show the potential to translate our success with intravenous NPs for GBM to improve IT chemotherapy delivery to LM.
ContributorsHouseholder, Kyle Thomas (Author) / Sirianni, Rachael W. (Thesis advisor) / Stabenfeldt, Sarah (Committee member) / Vernon, Brent (Committee member) / Caplan, Michael (Committee member) / Wechsler-Reya, Robert (Committee member) / Arizona State University (Publisher)
Created2018
Description
Rapid intraoperative diagnosis of brain tumors is of great importance for planning treatment and guiding the surgeon about the extent of resection. Currently, the standard for the preliminary intraoperative tissue analysis is frozen section biopsy that has major limitations such as tissue freezing and cutting artifacts, sampling errors, lack of immediate interaction between the pathologist and the surgeon, and time consuming.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
Handheld, portable confocal laser endomicroscopy (CLE) is being explored in neurosurgery for its ability to image histopathological features of tissue at cellular resolution in real time during brain tumor surgery. Over the course of examination of the surgical tumor resection, hundreds to thousands of images may be collected. The high number of images requires significant time and storage load for subsequent reviewing, which motivated several research groups to employ deep convolutional neural networks (DCNNs) to improve its utility during surgery. DCNNs have proven to be useful in natural and medical image analysis tasks such as classification, object detection, and image segmentation.
This thesis proposes using DCNNs for analyzing CLE images of brain tumors. Particularly, it explores the practicality of DCNNs in three main tasks. First, off-the shelf DCNNs were used to classify images into diagnostic and non-diagnostic. Further experiments showed that both ensemble modeling and transfer learning improved the classifier’s accuracy in evaluating the diagnostic quality of new images at test stage. Second, a weakly-supervised learning pipeline was developed for localizing key features of diagnostic CLE images from gliomas. Third, image style transfer was used to improve the diagnostic quality of CLE images from glioma tumors by transforming the histology patterns in CLE images of fluorescein sodium-stained tissue into the ones in conventional hematoxylin and eosin-stained tissue slides.
These studies suggest that DCNNs are opted for analysis of CLE images. They may assist surgeons in sorting out the non-diagnostic images, highlighting the key regions and enhancing their appearance through pattern transformation in real time. With recent advances in deep learning such as generative adversarial networks and semi-supervised learning, new research directions need to be followed to discover more promises of DCNNs in CLE image analysis.
ContributorsIzady Yazdanabadi, Mohammadhassan (Author) / Preul, Mark (Thesis advisor) / Yang, Yezhou (Thesis advisor) / Nakaji, Peter (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2019
Description
According to the World Health Organization, cancer is one of the leading causes of death around the world. Although early diagnostics using biomarkers and improved treatments with targeted therapy have reduced the rate of cancer related mortalities, there remain many unknowns regarding the contributions of the tumor microenvironment to cancer progression and therapeutic resistance. The tumor microenvironment plays a significant role by manipulating the progression of cancer cells through biochemical and biophysical signals from the surrounding stromal cells along with the extracellular matrix. As such, there is a critical need to understand how the tumor microenvironment influences the molecular mechanisms underlying cancer metastasis to facilitate the discovery of better therapies. This thesis described the development of microfluidic technologies to study the interplay of cancer cells with their surrounding microenvironment. The microfluidic model was used to assess how exposure to chemoattractant, epidermal growth factor (EGF), impacted 3D breast cancer cell invasion and enhanced cell motility speed was noted in the presence of EGF validating physiological cell behavior. Additionally, breast cancer and patient-derived cancer-associated fibroblast (CAF) cells were co-cultured to study cell-cell crosstalk and how it affected cancer invasion. GPNMB was identified as a novel gene of interest and it was shown that CAFs enhanced breast cancer invasion by up-regulating the expression of GPNMB on breast cancer cells resulting in increased migration speed. Lastly, this thesis described the design, biological validation, and use of this microfluidic platform as a new in vitro 3D organotypic model to study mechanisms of glioma stem cell (GSC) invasion in the context of a vascular niche. It was confirmed that CXCL12-CXCR4 signaling is involved in promoting GSC invasion in a 3D vascular microenvironment, while also demonstrating the effectiveness of the microfluidic as a drug screening assay. Taken together, the broader impacts of the microfluidic model developed in this dissertation include, a possible alternative platform to animal testing that is focused on mimicking human physiology, a potential ex vivo platform using patient-derived cells for studying the interplay of cancer cells with its surrounding microenvironment, and development of future therapeutic strategies tailored toward disrupting key molecular pathways involved in regulatory mechanisms of cancer invasion.
ContributorsTruong, Danh, Ph.D (Author) / Nikkhah, Mehdi (Thesis advisor) / LaBaer, Joshua (Committee member) / Smith, Barbara (Committee member) / Mouneimne, Ghassan (Committee member) / Vernon, Brent (Committee member) / Arizona State University (Publisher)
Created2018
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 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.
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
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 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.
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