Coding Strategies and Implementations of Compressive Sensing

<p>This dissertation studies the coding strategies of computational imaging to overcome the limitation of conventional sensing techniques. The information capacity of conventional sensing is limited by the physical properties of optics, such as aperture size, detector pixels, quantum efficiency, and sampling rate. These parameters determine the spatial, depth, spectral, temporal, and polarization sensitivity of each imager. To increase sensitivity in any dimension can significantly compromise the others. </p><p>This research implements various coding strategies subject to optical multidimensional imaging and acoustic sensing in order to extend their sensing abilities. The proposed coding strategies combine hardware modification and signal processing to exploiting bandwidth and sensitivity from conventional sensors. We discuss the hardware architecture, compression strategies, sensing process modeling, and reconstruction algorithm of each sensing system. </p><p>Optical multidimensional imaging measures three or more dimensional information of the optical signal. Traditional multidimensional imagers acquire extra dimensional information at the cost of degrading temporal or spatial resolution. Compressive multidimensional imaging multiplexes the transverse spatial, spectral, temporal, and polarization information on a two-dimensional (2D) detector. The corresponding spectral, temporal and polarization coding strategies adapt optics, electronic devices, and designed modulation techniques for multiplex measurement. This computational imaging technique provides multispectral, temporal super-resolution, and polarization imaging abilities with minimal loss in spatial resolution and noise level while maintaining or gaining higher temporal resolution. The experimental results prove that the appropriate coding strategies may improve hundreds times more sensing capacity. </p><p>Human auditory system has the astonishing ability in localizing, tracking, and filtering the selected sound sources or information from a noisy environment. Using engineering efforts to accomplish the same task usually requires multiple detectors, advanced computational algorithms, or artificial intelligence systems. Compressive acoustic sensing incorporates acoustic metamaterials in compressive sensing theory to emulate the abilities of sound localization and selective attention. This research investigates and optimizes the sensing capacity and the spatial sensitivity of the acoustic sensor. The well-modeled acoustic sensor allows localizing multiple speakers in both stationary and dynamic auditory scene; and distinguishing mixed conversations from independent sources with high audio recognition rate.</p>

Engineering Highly-functional, Self-regenerative Skeletal Muscle Tissues with Enhanced Vascularization and Survival in Vivo

<p>Tissue engineering of biomimetic skeletal muscle may lead to development of new therapies for myogenic repair and generation of improved in vitro models for studies of muscle function, regeneration, and disease. For the optimal therapeutic and in vitro results, engineered muscle should recreate the force-generating and regenerative capacities of native muscle, enabled respectively by its two main cellular constituents, the mature myofibers and satellite cells (SCs). Still, after 20 years of research, engineered muscle tissues fall short of mimicking contractile function and self-repair capacity of native skeletal muscle. To overcome this limitation, we set the thesis goals to: 1) generate a highly functional, self-regenerative engineered skeletal muscle and 2) explore mechanisms governing its formation and regeneration in vitro and survival and vascularization in vivo.</p><p>By studying myogenic progenitors isolated from neonatal rats, we first discovered advantages of using an adherent cell fraction for engineering of skeletal muscles with robust structure and function and the formation of a SC pool. Specifically, when synergized with dynamic culture conditions, the use of adherent cells yielded muscle constructs capable of replicating the contractile output of native neonatal muscle, generating >40 mN/mm2 of specific force. Moreover, tissue structure and cellular heterogeneity of engineered muscle constructs closely resembled those of native muscle, consisting of aligned, striated myofibers embedded in a matrix of basal lamina proteins and SCs that resided in native-like niches. Importantly, we identified rapid formation of myofibers early during engineered muscle culture as a critical condition leading to SC homing and conversion to a quiescent, non-proliferative state. The SCs retained natural regenerative capacity and activated, proliferated, and differentiated to rebuild damaged myofibers and recover contractile function within 10 days after the muscle was injured by cardiotoxin (CTX). The resulting regenerative response was directly dependent on the abundance of SCs in the engineered muscle that we varied by expanding starting cell population under different levels of basic fibroblast growth factor (bFGF), an inhibitor of myogenic differentiation. Using a dorsal skinfold window chamber model in nude mice, we further demonstrated that within 2 weeks after implantation, initially avascular engineered muscle underwent robust vascularization and perfusion and exhibited improved structure and contractile function beyond what was achievable in vitro. </p><p>To enhance translational value of our approach, we transitioned to use of adult rat myogenic cells, but found that despite similar function to that of neonatal constructs, adult-derived muscle lacked regenerative capacity. Using a novel platform for live monitoring of calcium transients during construct culture, we rapidly screened for potential enhancers of regeneration to establish that many known pro-regenerative soluble factors were ineffective in stimulating in vitro engineered muscle recovery from CTX injury. This led us to introduce bone marrow-derived macrophages (BMDMs), an established non-myogenic contributor to muscle repair, to the adult-derived constructs and to demonstrate remarkable recovery of force generation (>80%) and muscle mass (>70%) following CTX injury. Mechanistically, while similar patterns of early SC activation and proliferation upon injury were observed in engineered muscles with and without BMDMs, a significant decrease in injury-induced apoptosis occurred only in the presence of BMDMs. The importance of preventing apoptosis was further demonstrated by showing that application of caspase inhibitor (Q-VD-OPh) yielded myofiber regrowth and functional recovery post-injury. Gene expression analysis suggested muscle-secreted tumor necrosis factor-�� (TNF��) as a potential inducer of apoptosis as common for muscle degeneration in diseases and aging in vivo. Finally, we showed that BMDM incorporation in engineered muscle enhanced its growth, angiogenesis, and function following implantation in the dorsal window chambers in nude mice.</p><p>In summary, this thesis describes novel strategies to engineer highly contractile and regenerative skeletal muscle tissues starting from neonatal or adult rat myogenic cells. We find that age-dependent differences of myogenic cells distinctly affect the self-repair capacity but not contractile function of engineered muscle. Adult, but not neonatal, myogenic progenitors appear to require co-culture with other cells, such as bone marrow-derived macrophages, to allow robust muscle regeneration in vitro and rapid vascularization in vivo. Regarding the established roles of immune system cells in the repair of various muscle and non-muscle tissues, we expect that our work will stimulate the future applications of immune cells as pro-regenerative or anti-inflammatory constituents of engineered tissue grafts. Furthermore, we expect that rodent studies in this thesis will inspire successful engineering of biomimetic human muscle tissues for use in regenerative therapy and drug discovery applications.</p>

Experiences of Internalized and Enacted Stigma among Women with Obstetric Fistula in Tanzania

<p>Background: Obstetric fistula is the development of a necrosis between the bladder and the vagina and/or the bladder and the rectum as a result of prolonged obstructed labor, resulting in urinary or fecal incontinence. In Tanzania surgical repair for obstetric fistula is provided freely by the government but it is estimated that there are over 25,000 women living with an untreated fistula. These women experience high degrees of psycho-social stresses exacerbated by the stigma surrounding their condition. There is a dire need to explore stigma within this population in order to better understand its impact, as stigma affects both treatment seeking behavior as well as long term recovery of those who access surgical repair.</p><p>Study Aims: This study aims to understand the experiences of stigma among women with obstetric fistulas by examining both internalized and enacted stigma, and by identifying pertinent correlates of internalized stigma.</p><p>Methods: This mixed-methods study utilized both quantitative and qualitative data collected in two related studies at a single hospital in Moshi, Tanzania. All study participants were women receiving surgical repair for an obstetric fistula. In the quantitative portion, cross-sectional survey data were collected from 52 patients. The primary outcome was fistula-related stigma, measured using an adaptation of the HASI-P stigma scale, which included constructs of both internalized and enacted stigma. In the qualitative portion, 45 patients participated in a semi-structured in-depth interview, which explored topics such as stressors caused by the fistula, coping mechanisms, and available support. The transcripts were analyzed using analytic memos and an iterative process of thematic coding using the framework of content analysis. </p><p>Results: Expressions of internalized stigma were common in the sample, with a median score of 2.1 on a scale of 0 ��� 3. Internalized was significantly correlated with negative religious coping, social participation, impact of incontinence and enacted stigma. Qualitative analysis was consistent and demonstrated widespread themes of shame and embarrassment. Experiences of enacted stigma were not as common (median score of 0), although some items, like those pertaining to mockery and blame, were endorsed by up to 25% of the study sample. Themes of anticipated stigma (isolation and non-disclosure due to the possibility of stigmatization) were also evident in the qualitative sample and may explain the low enacted stigma scores observed. </p><p>Conclusion: In this sample of women receiving surgical repair for an obstetric fistula, stigma was evident, with internalized stigma resulting in psychological impacts for patients. Experiences of both anticipated and enacted stigma were also observed. There is a need to explore interventions that would decrease stigma while also increasing support for these women, as stigma may be a barrier towards accessing surgical repair and reintegration following surgery. </p><p>Keywords: Tanzania, obstetric fistula, stigma, maternal health</p>

Advanced Techniques for Image Quality Assessment of Modern X-ray Computed Tomography Systems

<p>X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination. </p><p>A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.</p><p>Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.</p><p>The work in this dissertation used the ���task-based��� definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an ���observer��� to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer���s performance in completing the task at hand (e.g., detection sensitivity/specificity).</p><p>First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection��� FPB vs Advanced Modeled Iterative Reconstruction��� ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.</p><p>Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.</p><p>Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included na��ve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.</p><p>The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.</p><p>To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.</p><p>The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called ���Clustured Lumpy Background��� texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.</p><p>The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion���s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called ���hybrid��� images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.</p><p>Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.</p><p>The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose. </p><p>In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.</p>

Defining the Role of the Histone Methyltransferase, PR-Set7, in Maintaining the Genome Integrity of Drosophila Melanogaster

<p>The complete and faithful duplication of the genome is essential to ensure normal cell division and organismal development. Eukaryotic DNA replication is initiated at multiple sites termed origins of replication that are activated at different time through S phase. The replication timing program is regulated by the S-phase checkpoint, which signals and repairs replicative stress. Eukaryotic DNA is packaged with histones into chromatin, thus DNA-templated processes including replication are modulated by the local chromatin environment such as post-translational modifications (PTMs) of histones.</p><p>One such epigenetic mark, methylation of lysine 20 on histone H4 (H4K20), has been linked to chromatin compaction, transcription, DNA repair and DNA replication. H4K20 can be mono-, di- and tri-methylated. Monomethylation of H4K20 (H4K20me1) is mediated by the cell cycle-regulated histone methyltransferase PR-Set7 and subsequent di-/tri- methylation is catalyzed by Suv4-20. Prior studies have shown that PR-Set7 depletion in mammalian cells results in defective S phase progression and the accumulation of DNA damage, which may be partially attributed to defects in origin selection and activation. Meanwhile, overexpression of mammalian PR-Set7 recruits components of pre-Replication Complex (pre-RC) onto chromatin and licenses replication origins for re-replication. However, these studies were limited to only a handful of mammalian origins, and it remains unclear how PR-Set7 impacts the replication program on a genomic scale. Finally, the methylation substrates of PR-Set7 include both histone (H4K20) and non-histone targets, therefore it is necessary to directly test the role of H4K20 methylation in PR-Set7 regulated phenotypes. </p><p>I employed genetic, cytological, and genomic approaches to better understand the role of H4K20 methylation in regulating DNA replication and genome stability in Drosophila melanogaster cells. Depletion of Drosophila PR-Set7 by RNAi in cultured Kc167 cells led to an ATR-dependent cell cycle arrest with near 4N DNA content and the accumulation of DNA damage, indicating a defect in completing S phase. The cells were arrested at the second S phase following PR-Set7 downregulation, suggesting that it was an epigenetic effect that coupled to the dilution of histone modification over multiple cell cycles. To directly test the role of H4K20 methylation in regulating genome integrity, I collaborated with the Duronio Lab and observed spontaneous DNA damage on the imaginal wing discs of third instar mutant larvae that had an alanine substitution on H4K20 (H4K20A) thus unable to be methylated, confirming that H4K20 is a bona fide target of PR-Set7 in maintaining genome integrity. </p><p>One possible source of DNA damage due to loss of PR-Set7 is reduced origin activity. I used BrdU-seq to profile the genome-wide origin activation pattern. However, I found that deregulation of H4K20 methylation states by manipulating the H4K20 methyltransferases PR-Set7 and Suv4-20 had no impact on origin activation throughout the genome. I then mapped the genomic distribution of DNA damage upon PR-Set7 depletion. Surprisingly, ChIP-seq of the DNA damage marker ��-H2A.v located the DNA damage to late replicating euchromatic regions of the Drosophila genome, and the strength of ��-H2A.v signal was uniformly distributed and spanned the entire late replication domain, implying stochastic replication fork collapse within late replicating regions. Together these data suggest that PR-Set7-mediated monomethylation of H4K20 is critical for maintaining the genomic integrity of late replicating domains, presumably via stabilization of late replicating forks.</p><p>In addition to investigating the function of H4K20me, I also used immunofluorescence to characterize the cell cycle regulated chromatin loading of Mcm2-7 complex, the DNA helicase that licenses replication origins, using H4K20me1 level as a proxy for cell cycle stages. In parallel with chromatin spindown data by Powell et al. (Powell et al. 2015), we showed a continuous loading of Mcm2-7 during G1 and a progressive removal from chromatin through S phase.</p>