968 resultados para Biomedical engineering.


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A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

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A number of studies in the areas of Biomedical Engineering and Health Sciences have employed machine learning tools to develop methods capable of identifying patterns in different sets of data. Despite its extinction in many countries of the developed world, Hansen’s disease is still a disease that affects a huge part of the population in countries such as India and Brazil. In this context, this research proposes to develop a method that makes it possible to understand in the future how Hansen’s disease affects facial muscles. By using surface electromyography, a system was adapted so as to capture the signals from the largest possible number of facial muscles. We have first looked upon the literature to learn about the way researchers around the globe have been working with diseases that affect the peripheral neural system and how electromyography has acted to contribute to the understanding of these diseases. From these data, a protocol was proposed to collect facial surface electromyographic (sEMG) signals so that these signals presented a high signal to noise ratio. After collecting the signals, we looked for a method that would enable the visualization of this information in a way to make it possible to guarantee that the method used presented satisfactory results. After identifying the method's efficiency, we tried to understand which information could be extracted from the electromyographic signal representing the collected data. Once studies demonstrating which information could contribute to a better understanding of this pathology were not to be found in literature, parameters of amplitude, frequency and entropy were extracted from the signal and a feature selection was made in order to look for the features that better distinguish a healthy individual from a pathological one. After, we tried to identify the classifier that best discriminates distinct individuals from different groups, and also the set of parameters of this classifier that would bring the best outcome. It was identified that the protocol proposed in this study and the adaptation with disposable electrodes available in market proved their effectiveness and capability of being used in different studies whose intention is to collect data from facial electromyography. The feature selection algorithm also showed that not all of the features extracted from the signal are significant for data classification, with some more relevant than others. The classifier Support Vector Machine (SVM) proved itself efficient when the adequate Kernel function was used with the muscle from which information was to be extracted. Each investigated muscle presented different results when the classifier used linear, radial and polynomial kernel functions. Even though we have focused on Hansen’s disease, the method applied here can be used to study facial electromyography in other pathologies.

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We have harnessed two reactions catalyzed by the enzyme sortase A and applied them to generate new methods for the purification and site-selective modification of recombinant protein therapeutics.

We utilized native peptide ligation —a well-known function of sortase A— to attach a small molecule drug specifically to the carboxy-terminus of a recombinant protein. By combining this reaction with the unique phase behavior of elastin-like polypeptides, we developed a protocol that produces homogenously-labeled protein-small molecule conjugates using only centrifugation. The same reaction can be used to produce unmodified therapeutic proteins simply by substituting a single reactant. The isolated proteins or protein-small molecule conjugates do not have any exogenous purification tags, eliminating the potential influence of these tags on bioactivity. Because both unmodified and modified proteins are produced by a general process that is the same for any protein of interest and does not require any chromatography, the time, effort, and cost associated with protein purification and modification is greatly reduced.

We also developed an innovative and unique method that attaches a tunable number of drug molecules to any recombinant protein of interest in a site-specific manner. Although the ability of sortase A to carry out native peptide ligation is widely used, we demonstrated that Sortase A is also capable of attaching small molecules to proteins through an isopeptide bond at lysine side chains within a unique amino acid sequence. This reaction —isopeptide ligation— is a new site-specific conjugation method that is orthogonal to all available protein-small conjugation technologies and is the first site-specific conjugation method that attaches the payload to lysine residues. We show that isopeptide ligation can be applied broadly to peptides, proteins, and antibodies using a variety of small molecule cargoes to efficiently generate stable conjugates. We thoroughly assessed the site-selectivity of this reaction using a variety of analytical methods and showed that in many cases the reaction is site-specific for lysines in flexible, disordered regions of the substrate proteins. Finally, we showed that isopeptide ligation can be used to create clinically-relevant antibody-drug conjugates that have potent cytotoxicity towards cancerous cells

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A new modality for preventing HIV transmission is emerging in the form of topical microbicides. Some clinical trials have shown some promising results of these methods of protection while other trials have failed to show efficacy. Due to the relatively novel nature of microbicide drug transport, a rigorous, deterministic analysis of that transport can help improve the design of microbicide vehicles and understand results from clinical trials. This type of analysis can aid microbicide product design by helping understand and organize the determinants of drug transport and the potential efficacies of candidate microbicide products.

Microbicide drug transport is modeled as a diffusion process with convection and reaction effects in appropriate compartments. This is applied here to vaginal gels and rings and a rectal enema, all delivering the microbicide drug Tenofovir. Although the focus here is on Tenofovir, the methods established in this dissertation can readily be adapted to other drugs, given knowledge of their physical and chemical properties, such as the diffusion coefficient, partition coefficient, and reaction kinetics. Other dosage forms such as tablets and fiber meshes can also be modeled using the perspective and methods developed here.

The analyses here include convective details of intravaginal flows by both ambient fluid and spreading gels with different rheological properties and applied volumes. These are input to the overall conservation equations for drug mass transport in different compartments. The results are Tenofovir concentration distributions in time and space for a variety of microbicide products and conditions. The Tenofovir concentrations in the vaginal and rectal mucosal stroma are converted, via a coupled reaction equation, to concentrations of Tenofovir diphosphate, which is the active form of the drug that functions as a reverse transcriptase inhibitor against HIV. Key model outputs are related to concentrations measured in experimental pharmacokinetic (PK) studies, e.g. concentrations in biopsies and blood. A new measure of microbicide prophylactic functionality, the Percent Protected, is calculated. This is the time dependent volume of the entire stroma (and thus fraction of host cells therein) in which Tenofovir diphosphate concentrations equal or exceed a target prophylactic value, e.g. an EC50.

Results show the prophylactic potentials of the studied microbicide vehicles against HIV infections. Key design parameters for each are addressed in application of the models. For a vaginal gel, fast spreading at small volume is more effective than slower spreading at high volume. Vaginal rings are shown to be most effective if inserted and retained as close to the fornix as possible. Because of the long half-life of Tenofovir diphosphate, temporary removal of the vaginal ring (after achieving steady state) for up to 24h does not appreciably diminish Percent Protected. However, full steady state (for the entire stromal volume) is not achieved until several days after ring insertion. Delivery of Tenofovir to the rectal mucosa by an enema is dominated by surface area of coated mucosa and whether the interiors of rectal crypts are filled with the enema fluid. For the enema 100% Percent Protected is achieved much more rapidly than for vaginal products, primarily because of the much thinner epithelial layer of the mucosa. For example, 100% Percent Protected can be achieved with a one minute enema application, and 15 minute wait time.

Results of these models have good agreement with experimental pharmacokinetic data, in animals and clinical trials. They also improve upon traditional, empirical PK modeling, and this is illustrated here. Our deterministic approach can inform design of sampling in clinical trials by indicating time periods during which significant changes in drug concentrations occur in different compartments. More fundamentally, the work here helps delineate the determinants of microbicide drug delivery. This information can be the key to improved, rational design of microbicide products and their dosage regimens.

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The goal of my Ph.D. thesis is to enhance the visualization of the peripheral retina using wide-field optical coherence tomography (OCT) in a clinical setting.

OCT has gain widespread adoption in clinical ophthalmology due to its ability to visualize the diseases of the macula and central retina in three-dimensions, however, clinical OCT has a limited field-of-view of 300. There has been increasing interest to obtain high-resolution images outside of this narrow field-of-view, because three-dimensional imaging of the peripheral retina may prove to be important in the early detection of neurodegenerative diseases, such as Alzheimer's and dementia, and the monitoring of known ocular diseases, such as diabetic retinopathy, retinal vein occlusions, and choroid masses.

Before attempting to build a wide-field OCT system, we need to better understand the peripheral optics of the human eye. Shack-Hartmann wavefront sensors are commonly used tools for measuring the optical imperfections of the eye, but their acquisition speed is limited by their underlying camera hardware. The first aim of my thesis research is to create a fast method of ocular wavefront sensing such that we can measure the wavefront aberrations at numerous points across a wide visual field. In order to address aim one, we will develop a sparse Zernike reconstruction technique (SPARZER) that will enable Shack-Hartmann wavefront sensors to use as little as 1/10th of the data that would normally be required for an accurate wavefront reading. If less data needs to be acquired, then we can increase the speed at which wavefronts can be recorded.

For my second aim, we will create a sophisticated optical model that reproduces the measured aberrations of the human eye. If we know how the average eye's optics distort light, then we can engineer ophthalmic imaging systems that preemptively cancel inherent ocular aberrations. This invention will help the retinal imaging community to design systems that are capable of acquiring high resolution images across a wide visual field. The proposed model eye is also of interest to the field of vision science as it aids in the study of how anatomy affects visual performance in the peripheral retina.

Using the optical model from aim two, we will design and reduce to practice a clinical OCT system that is capable of imaging a large (800) field-of-view with enhanced visualization of the peripheral retina. A key aspect of this third and final aim is to make the imaging system compatible with standard clinical practices. To this end, we will incorporate sensorless adaptive optics in order to correct the inter- and intra- patient variability in ophthalmic aberrations. Sensorless adaptive optics will improve both the brightness (signal) and clarity (resolution) of features in the peripheral retina without affecting the size of the imaging system.

The proposed work should not only be a noteworthy contribution to the ophthalmic and engineering communities, but it should strengthen our existing collaborations with the Duke Eye Center by advancing their capability to diagnose pathologies of the peripheral retinal.

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Magnetic resonance imaging is a research and clinical tool that has been applied in a wide variety of sciences. One area of magnetic resonance imaging that has exhibited terrific promise and growth in the past decade is magnetic susceptibility imaging. Imaging tissue susceptibility provides insight into the microstructural organization and chemical properties of biological tissues, but this image contrast is not well understood. The purpose of this work is to develop effective approaches to image, assess, and model the mechanisms that generate both isotropic and anisotropic magnetic susceptibility contrast in biological tissues, including myocardium and central nervous system white matter.

This document contains the first report of MRI-measured susceptibility anisotropy in myocardium. Intact mouse heart specimens were scanned using MRI at 9.4 T to ascertain both the magnetic susceptibility and myofiber orientation of the tissue. The susceptibility anisotropy of myocardium was observed and measured by relating the apparent tissue susceptibility as a function of the myofiber angle with respect to the applied magnetic field. A multi-filament model of myocardial tissue revealed that the diamagnetically anisotropy α-helix peptide bonds in myofilament proteins are capable of producing bulk susceptibility anisotropy on a scale measurable by MRI, and are potentially the chief sources of the experimentally observed anisotropy.

The growing use of paramagnetic contrast agents in magnetic susceptibility imaging motivated a series of investigations regarding the effect of these exogenous agents on susceptibility imaging in the brain, heart, and kidney. In each of these organs, gadolinium increases susceptibility contrast and anisotropy, though the enhancements depend on the tissue type, compartmentalization of contrast agent, and complex multi-pool relaxation. In the brain, the introduction of paramagnetic contrast agents actually makes white matter tissue regions appear more diamagnetic relative to the reference susceptibility. Gadolinium-enhanced MRI yields tensor-valued susceptibility images with eigenvectors that more accurately reflect the underlying tissue orientation.

Despite the boost gadolinium provides, tensor-valued susceptibility image reconstruction is prone to image artifacts. A novel algorithm was developed to mitigate these artifacts by incorporating orientation-dependent tissue relaxation information into susceptibility tensor estimation. The technique was verified using a numerical phantom simulation, and improves susceptibility-based tractography in the brain, kidney, and heart. This work represents the first successful application of susceptibility-based tractography to a whole, intact heart.

The knowledge and tools developed throughout the course of this research were then applied to studying mouse models of Alzheimer’s disease in vivo, and studying hypertrophic human myocardium specimens ex vivo. Though a preliminary study using contrast-enhanced quantitative susceptibility mapping has revealed diamagnetic amyloid plaques associated with Alzheimer’s disease in the mouse brain ex vivo, non-contrast susceptibility imaging was unable to precisely identify these plaques in vivo. Susceptibility tensor imaging of human myocardium specimens at 9.4 T shows that susceptibility anisotropy is larger and mean susceptibility is more diamagnetic in hypertrophic tissue than in normal tissue. These findings support the hypothesis that myofilament proteins are a source of susceptibility contrast and anisotropy in myocardium. This collection of preclinical studies provides new tools and context for analyzing tissue structure, chemistry, and health in a variety of organs throughout the body.

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Gene regulation is a complex and tightly controlled process that defines cell function in physiological and abnormal states. Programmable gene repression technologies enable loss-of-function studies for dissecting gene regulation mechanisms and represent an exciting avenue for gene therapy. Established and recently developed methods now exist to modulate gene sequence, epigenetic marks, transcriptional activity, and post-transcriptional processes, providing unprecedented genetic control over cell phenotype. Our objective was to apply and develop targeted repression technologies for regenerative medicine, genomics, and gene therapy applications. We used RNA interference to control cell cycle regulation in myogenic differentiation and enhance the proliferative capacity of tissue engineered cartilage constructs. These studies demonstrate how modulation of a single gene can be used to guide cell differentiation for regenerative medicine strategies. RNA-guided gene regulation with the CRISPR/Cas9 system has rapidly expanded the targeted repression repertoire from silencing single protein-coding genes to modulation of genes, promoters, and other distal regulatory elements. In order to facilitate its adaptation for basic research and translational applications, we demonstrated the high degree of specificity for gene targeting, gene silencing, and chromatin modification possible with Cas9 repressors. The specificity and effectiveness of RNA-guided transcriptional repressors for silencing endogenous genes are promising characteristics for mechanistic studies of gene regulation and cell phenotype. Furthermore, our results support the use of Cas9-based repressors as a platform for novel gene therapy strategies. We developed an in vivo AAV-based gene repression system for silencing endogenous genes in a mouse model. Together, these studies demonstrate the utility of gene repression tools for guiding cell phenotype and the potential of the RNA-guided CRISPR/Cas9 platform for applications such as causal studies of gene regulatory mechanisms and gene therapy.

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Cancer comprises a collection of diseases, all of which begin with abnormal tissue growth from various stimuli, including (but not limited to): heredity, genetic mutation, exposure to harmful substances, radiation as well as poor dieting and lack of exercise. The early detection of cancer is vital to providing life-saving, therapeutic intervention. However, current methods for detection (e.g., tissue biopsy, endoscopy and medical imaging) often suffer from low patient compliance and an elevated risk of complications in elderly patients. As such, many are looking to “liquid biopsies” for clues into presence and status of cancer due to its minimal invasiveness and ability to provide rich information about the native tumor. In such liquid biopsies, peripheral blood is drawn from patients and is screened for key biomarkers, chiefly circulating tumor cells (CTCs). Capturing, enumerating and analyzing the genetic and metabolomic characteristics of these CTCs may hold the key for guiding doctors to better understand the source of cancer at an earlier stage for more efficacious disease management.

The isolation of CTCs from whole blood, however, remains a significant challenge due to their (i) low abundance, (ii) lack of a universal surface marker and (iii) epithelial-mesenchymal transition that down-regulates common surface markers (e.g., EpCAM), reducing their likelihood of detection via positive selection assays. These factors potentiate the need for an improved cell isolation strategy that can collect CTCs via both positive and negative selection modalities as to avoid the reliance on a single marker, or set of markers, for more accurate enumeration and diagnosis.

The technologies proposed herein offer a unique set of strategies to focus, sort and template cells in three independent microfluidic modules. The first module exploits ultrasonic standing waves and a class of elastomeric particles for the rapid and discriminate sequestration of cells. This type of cell handling holds promise not only in sorting, but also in the isolation of soluble markers from biofluids. The second module contains components to focus (i.e., arrange) cells via forces from acoustic standing waves and separate cells in a high throughput fashion via free-flow magnetophoresis. The third module uses a printed array of micromagnets to capture magnetically labeled cells into well-defined compartments, enabling on-chip staining and single cell analysis. These technologies can operate in standalone formats, or can be adapted to operate with established analytical technologies, such as flow cytometry. A key advantage of these innovations is their ability to process erythrocyte-lysed blood in a rapid (and thus high throughput) fashion. They can process fluids at a variety of concentrations and flow rates, target cells with various immunophenotypes and sort cells via positive (and potentially negative) selection. These technologies are chip-based, fabricated using standard clean room equipment, towards a disposable clinical tool. With further optimization in design and performance, these technologies might aid in the early detection, and potentially treatment, of cancer and various other physical ailments.

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Optical coherence tomography (OCT) is a noninvasive three-dimensional interferometric imaging technique capable of achieving micrometer scale resolution. It is now a standard of care in ophthalmology, where it is used to improve the accuracy of early diagnosis, to better understand the source of pathophysiology, and to monitor disease progression and response to therapy. In particular, retinal imaging has been the most prevalent clinical application of OCT, but researchers and companies alike are developing OCT systems for cardiology, dermatology, dentistry, and many other medical and industrial applications.

Adaptive optics (AO) is a technique used to reduce monochromatic aberrations in optical instruments. It is used in astronomical telescopes, laser communications, high-power lasers, retinal imaging, optical fabrication and microscopy to improve system performance. Scanning laser ophthalmoscopy (SLO) is a noninvasive confocal imaging technique that produces high contrast two-dimensional retinal images. AO is combined with SLO (AOSLO) to compensate for the wavefront distortions caused by the optics of the eye, providing the ability to visualize the living retina with cellular resolution. AOSLO has shown great promise to advance the understanding of the etiology of retinal diseases on a cellular level.

Broadly, we endeavor to enhance the vision outcome of ophthalmic patients through improved diagnostics and personalized therapy. Toward this end, the objective of the work presented herein was the development of advanced techniques for increasing the imaging speed, reducing the form factor, and broadening the versatility of OCT and AOSLO. Despite our focus on applications in ophthalmology, the techniques developed could be applied to other medical and industrial applications. In this dissertation, a technique to quadruple the imaging speed of OCT was developed. This technique was demonstrated by imaging the retinas of healthy human subjects. A handheld, dual depth OCT system was developed. This system enabled sequential imaging of the anterior segment and retina of human eyes. Finally, handheld SLO/OCT systems were developed, culminating in the design of a handheld AOSLO system. This system has the potential to provide cellular level imaging of the human retina, resolving even the most densely packed foveal cones.

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Burn injuries in the United States account for over one million hospital admissions per year, with treatment estimated at four billion dollars. Of severe burn patients, 30-90% will develop hypertrophic scars (HSc). Current burn therapies rely upon the use of bioengineered skin equivalents (BSEs), which assist in wound healing but do not prevent HSc. HSc contraction occurs of 6-18 months and results in the formation of a fixed, inelastic skin deformity, with 60% of cases occurring across a joint. HSc contraction is characterized by abnormally high presence of contractile myofibroblasts which normally apoptose at the completion of the proliferative phase of wound healing. Additionally, clinical observation suggests that the likelihood of HSc is increased in injuries with a prolonged immune response. Given the pathogenesis of HSc, we hypothesize that BSEs should be designed with two key anti-scarring characterizes: (1) 3D architecture and surface chemistry to mitigate the inflammatory microenvironment and decrease myofibroblast transition; and (2) using materials which persist in the wound bed throughout the remodeling phase of repair. We employed electrospinning and 3D printing to generate scaffolds with well-controlled degradation rate, surface coatings, and 3D architecture to explore our hypothesis through four aims.

In the first aim, we evaluate the impact of elastomeric, randomly-oriented biostable polyurethane (PU) scaffold on HSc-related outcomes. In unwounded skin, native collagen is arranged randomly, elastin fibers are abundant, and myofibroblasts are absent. Conversely, in scar contractures, collagen is arranged in linear arrays and elastin fibers are few, while myofibroblast density is high. Randomly oriented collagen fibers native to the uninjured dermis encourage random cell alignment through contact guidance and do not transmit as much force as aligned collagen fibers. However, the linear ECM serves as a system for mechanotransduction between cells in a feed-forward mechanism, which perpetuates ECM remodeling and myofibroblast contraction. The electrospinning process allowed us to create scaffolds with randomly-oriented fibers that promote random collagen deposition and decrease myofibroblast formation. Compared to an in vitro HSc contraction model, fibroblast-seeded PU scaffolds significantly decreased matrix and myofibroblast formation. In a murine HSc model, collagen coated PU (ccPU) scaffolds significantly reduced HSc contraction as compared to untreated control wounds and wounds treated with the clinical standard of care. The data from this study suggest that electrospun ccPU scaffolds meet the requirements to mitigate HSc contraction including: reduction of in vitro HSc related outcomes, diminished scar stiffness, and reduced scar contraction. While clinical dogma suggests treating severe burn patients with rapidly biodegrading skin equivalents, these data suggest that a more long-term scaffold may possess merit in reducing HSc.

In the second aim, we further investigate the impact of scaffold longevity on HSc contraction by studying a degradable, elastomeric, randomly oriented, electrospun micro-fibrous scaffold fabricated from the copolymer poly(l-lactide-co-ε-caprolactone) (PLCL). PLCL scaffolds displayed appropriate elastomeric and tensile characteristics for implantation beneath a human skin graft. In vitro analysis using normal human dermal fibroblasts (NHDF) demonstrated that PLCL scaffolds decreased myofibroblast formation as compared to an in vitro HSc contraction model. Using our murine HSc contraction model, we found that HSc contraction was significantly greater in animals treated with standard of care, Integra, as compared to those treated with collagen coated-PLCL (ccPLCL) scaffolds at d 56 following implantation. Finally, wounds treated with ccPLCL were significantly less stiff than control wounds at d 56 in vivo. Together, these data further solidify our hypothesis that scaffolds which persist throughout the remodeling phase of repair represent a clinically translatable method to prevent HSc contraction.

In the third aim, we attempt to optimize cell-scaffold interactions by employing an anti-inflammatory coating on electrospun PLCL scaffolds. The anti-inflammatory sub-epidermal glycosaminoglycan, hyaluronic acid (HA) was used as a coating material for PLCL scaffolds to encourage a regenerative healing phenotype. To minimize local inflammation, an anti-TNFα monoclonal antibody (mAB) was conjugated to the HA backbone prior to PLCL coating. ELISA analysis confirmed mAB activity following conjugation to HA (HA+mAB), and following adsorption of HA+mAB to the PLCL backbone [(HA+mAB)PLCL]. Alican blue staining demonstrated thorough HA coating of PLCL scaffolds using pressure-driven adsorption. In vitro studies demonstrated that treatment with (HA+mAB)PLCL prevented downstream inflammatory events in mouse macrophages treated with soluble TNFα. In vivo studies using our murine HSc contraction model suggested positive impact of HA coating, which was partiall impeded by the inclusion of the TNFα mAB. Further characterization of the inflammatory microenvironment of our murine model is required prior to conclusions regarding the potential for anti-TNFα therapeutics for HSc. Together, our data demonstrate the development of a complex anti-inflammatory coating for PLCL scaffolds, and the potential impact of altering the ECM coating material on HSc contraction.

In the fourth aim, we investigate how scaffold design, specifically pore dimensions, can influence myofibroblast interactions and subsequent formation of OB-cadherin positive adherens junctions in vitro. We collaborated with Wake Forest University to produce 3D printed (3DP) scaffolds with well-controlled pore sizes we hypothesized that decreasing pore size would mitigate intra-cellular communication via OB-cadherin-positive adherens junctions. PU was 3D printed via pressure extrusion in basket-weave design with feature diameter of ~70 µm and pore sizes of 50, 100, or 150 µm. Tensile elastic moduli of 3DP scaffolds were similar to Integra; however, flexural moduli of 3DP were significantly greater than Integra. 3DP scaffolds demonstrated ~50% porosity. 24 h and 5 d western blot data demonstrated significant increases in OB-cadherin expression in 100 µm pores relative to 50 µm pores, suggesting that pore size may play a role in regulating cell-cell communication. To analyze the impact of pore size in these scaffolds on scarring in vivo, scaffolds were implanted beneath skin graft in a murine HSc model. While flexural stiffness resulted in graft necrosis by d 14, cellular and blood vessel integration into scaffolds was evident, suggesting potential for this design if employed in a less stiff material. In this study, we demonstrate for the first time that pore size alone impacts OB-cadherin protein expression in vitro, suggesting that pore size may play a role on adherens junction formation affiliated with the fibroblast-to-myofibroblast transition. Overall, this work introduces a new bioengineered scaffold design to both study the mechanism behind HSc and prevent the clinical burden of this contractile disease.

Together, these studies inform the field of critical design parameters in scaffold design for the prevention of HSc contraction. We propose that scaffold 3D architectural design, surface chemistry, and longevity can be employed as key design parameters during the development of next generation, low-cost scaffolds to mitigate post-burn hypertrophic scar contraction. The lessening of post-burn scarring and scar contraction would improve clinical practice by reducing medical expenditures, increasing patient survival, and dramatically improving quality of life for millions of patients worldwide.

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Advancements in retinal imaging technologies have drastically improved the quality of eye care in the past couple decades. Scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT) are two examples of critical imaging modalities for the diagnosis of retinal pathologies. However current-generation SLO and OCT systems have limitations in diagnostic capability due to the following factors: the use of bulky tabletop systems, monochromatic imaging, and resolution degradation due to ocular aberrations and diffraction.

Bulky tabletop SLO and OCT systems are incapable of imaging patients that are supine, under anesthesia, or otherwise unable to maintain the required posture and fixation. Monochromatic SLO and OCT imaging prevents the identification of various color-specific diagnostic markers visible with color fundus photography like those of neovascular age-related macular degeneration. Resolution degradation due to ocular aberrations and diffraction has prevented the imaging of photoreceptors close to the fovea without the use of adaptive optics (AO), which require bulky and expensive components that limit the potential for widespread clinical use.

In this dissertation, techniques for extending the diagnostic capability of SLO and OCT systems are developed. These techniques include design strategies for miniaturizing and combining SLO and OCT to permit multi-modal, lightweight handheld probes to extend high quality retinal imaging to pediatric eye care. In addition, a method for extending true color retinal imaging to SLO to enable high-contrast, depth-resolved, high-fidelity color fundus imaging is demonstrated using a supercontinuum light source. Finally, the development and combination of SLO with a super-resolution confocal microscopy technique known as optical photon reassignment (OPRA) is demonstrated to enable high-resolution imaging of retinal photoreceptors without the use of adaptive optics.

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Purpose: The purpose of this work was to investigate the breast dose saving potential of a breast positioning technique (BP) for thoracic CT examinations with organ-based tube current modulation (OTCM).

Methods: The study included 13 female patient models (XCAT, age range: 27-65 y.o., weight range: 52 to 105.8 kg). Each model was modified to simulate three breast sizes in standard supine geometry. The modeled breasts were further deformed, emulating a BP that would constrain the breasts within 120° anterior tube current (mA) reduction zone. The tube current value of the CT examination was modeled using an attenuation-based program, which reduces the radiation dose to 20% in the anterior region with a corresponding increase to the posterior region. A validated Monte Carlo program was used to estimate organ doses with a typical clinical system (SOMATOM Definition Flash, Siemens Healthcare). The simulated organ doses and organ doses normalized by CTDIvol were compared between attenuation-based tube current modulation (ATCM), OTCM, and OTCM with BP (OTCMBP).

Results: On average, compared to ATCM, OTCM reduced the breast dose by 19.3±4.5%, whereas OTCMBP reduced breast dose by 36.6±6.9% (an additional 21.3±7.3%). The dose saving of OTCMBP was more significant for larger breasts (on average 32, 38, and 44% reduction for 0.5, 1.5, and 2.5 kg breasts, respectively). Compared to ATCM, OTCMBP also reduced thymus and heart dose by 12.1 ± 6.3% and 13.1 ± 5.4%, respectively.

Conclusions: In thoracic CT examinations, OTCM with a breast positioning technique can markedly reduce unnecessary exposure to the radiosensitive organs in the anterior chest wall, specifically breast tissue. The breast dose reduction is more notable for women with larger breasts.

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Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.

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Scatter in medical imaging is typically cast off as image-related noise that detracts from meaningful diagnosis. It is therefore typically rejected or removed from medical images. However, it has been found that every material, including cancerous tissue, has a unique X-ray coherent scatter signature that can be used to identify the material or tissue. Such scatter-based tissue-identification provides the advantage of locating and identifying particular materials over conventional anatomical imaging through X-ray radiography. A coded aperture X-ray coherent scatter spectral imaging system has been developed in our group to classify different tissue types based on their unique scatter signatures. Previous experiments using our prototype have demonstrated that the depth-resolved coherent scatter spectral imaging system (CACSSI) can discriminate healthy and cancerous tissue present in the path of a non-destructive x-ray beam. A key to the successful optimization of CACSSI as a clinical imaging method is to obtain anatomically accurate phantoms of the human body. This thesis describes the development and fabrication of 3D printed anatomical scatter phantoms of the breast and lung.

The purpose of this work is to accurately model different breast geometries using a tissue equivalent phantom, and to classify these tissues in a coherent x-ray scatter imaging system. Tissue-equivalent anatomical phantoms were designed to assess the capability of the CACSSI system to classify different types of breast tissue (adipose, fibroglandular, malignant). These phantoms were 3D printed based on DICOM data obtained from CT scans of prone breasts. The phantoms were tested through comparison of measured scatter signatures with those of adipose and fibroglandular tissue from literature. Tumors in the phantom were modeled using a variety of biological tissue including actual surgically excised benign and malignant tissue specimens. Lung based phantoms have also been printed for future testing. Our imaging system has been able to define the location and composition of the various materials in the phantom. These phantoms were used to characterize the CACSSI system in terms of beam width and imaging technique. The result of this work showed accurate modeling and characterization of the phantoms through comparison of the tissue-equivalent form factors to those from literature. The physical construction of the phantoms, based on actual patient anatomy, was validated using mammography and computed tomography to visually compare the clinical images to those of actual patient anatomy.

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Computational fluid dynamic (CFD) studies of blood flow in cerebrovascular aneurysms have potential to improve patient treatment planning by enabling clinicians and engineers to model patient-specific geometries and compute predictors and risks prior to neurovascular intervention. However, the use of patient-specific computational models in clinical settings is unfeasible due to their complexity, computationally intensive and time-consuming nature. An important factor contributing to this challenge is the choice of outlet boundary conditions, which often involves a trade-off between physiological accuracy, patient-specificity, simplicity and speed. In this study, we analyze how resistance and impedance outlet boundary conditions affect blood flow velocities, wall shear stresses and pressure distributions in a patient-specific model of a cerebrovascular aneurysm. We also use geometrical manipulation techniques to obtain a model of the patient’s vasculature prior to aneurysm development, and study how forces and stresses may have been involved in the initiation of aneurysm growth. Our CFD results show that the nature of the prescribed outlet boundary conditions is not as important as the relative distributions of blood flow through each outlet branch. As long as the appropriate parameters are chosen to keep these flow distributions consistent with physiology, resistance boundary conditions, which are simpler, easier to use and more practical than their impedance counterparts, are sufficient to study aneurysm pathophysiology, since they predict very similar wall shear stresses, time-averaged wall shear stresses, time-averaged pressures, and blood flow patterns and velocities. The only situations where the use of impedance boundary conditions should be prioritized is if pressure waveforms are being analyzed, or if local pressure distributions are being evaluated at specific time points, especially at peak systole, where the use of resistance boundary conditions leads to unnaturally large pressure pulses. In addition, we show that in this specific patient, the region of the blood vessel where the neck of the aneurysm developed was subject to abnormally high wall shear stresses, and that regions surrounding blebs on the aneurysmal surface were subject to low, oscillatory wall shear stresses. Computational models using resistance outlet boundary conditions may be suitable to study patient-specific aneurysm progression in a clinical setting, although several other challenges must be addressed before these tools can be applied clinically.