Purpose: To develop software that enables the rapid implementation of custom MRI spectrometers using commercially-available software defined radios (SDRs). Methods: The gr-MRI software package comprises a set of Python scripts, flowgraphs, and signal generation and recording blocks for GNU Radio, an open-source SDR software package that is widely used in communications research. gr-MRI Implements basic event sequencing functionality, and tools for system calibrations, multi-radio synchronization, and MR signal processing and image reconstruction. It includes four pulse sequences: a single-pulse sequence to record free induction signals, a gradient recalled echo imaging sequence, a spin echo imaging sequence, and a spin echo inversion recovery imaging sequence. The gr-MRI sequences were used to perform phantom imaging scans with a 0.5 Tesla tabletop MRI scanner and two commercially-available SDRs. One SDR was used for RF excitation and reception, and the other for gradient pulse generation. The total SDR hardware cost was approximately $2000. The frequency of radio desynchronization events and the frequency with which the software recovered from those events was also measured, and the SDRâs ability to generate frequency-swept RF waveforms was validated and compared to the scannerâs spectrometer. Results: Gradient echo and spin echo images geometrically matched those acquired using the scannerâs spectrometer, with no unexpected distortions. Inversion recovery images exhibited expected behavior as a function of inversion time. Desynchronization events were more likely to occur at the very beginning of an imaging scan, but were nearly eliminated if the user invokes the sequence for a short period before beginning data recording. The SDR was able to produce a 500 kHz bandwidth frequency-swept pulse with high fidelity, while the scannerâs spectrometer produced a waveform with large frequency spike errors. Conclusion: The developed gr-MRI software can be used to develop high-fidelity, low-cost custom MRI spectrometers using commercially-available SDRs.

The inability to identify the parathyroid glands is a significant challenge during endocrine procedures. Successful parathyroid and thyroid surgeries require careful resection of diseased tissue and preservation of normal tissues, but this is not always the reality. Inaccurate localization of parathyroid glands during these procedures may permanently prevent patients from achieving normal calcium levels after surgery. Current parathyroid detection methods cannot convey real-time information and are limited to localization of only diseased glands. There is, therefore, a large unmet need in endocrine surgery for a technique to find diseased and normal parathyroid glands during surgery. Previous studies have observed an intrinsic near-infrared (NIR) fluorescence signal in the parathyroid gland that is higher than the fluorescence of surrounding neck tissues. The goal of this dissertation is to develop NIR fluorescence spectroscopy and imaging into a reliable, real-time tool for parathyroid detection regardless of disease state. The clinical utility of NIR fluorescence spectroscopy was established over a diverse patient population. Studies show 97% accuracy in NIR fluorescence detection of the parathyroid glands with minimal effects from patient factors. Parathyroid imaging was achieved to replace point measurements acquired from spectroscopy with spatial images to show gland location. A novel Overlay Tissue Imaging System (OTIS) was developed to project fluorescence information directly on the patient in the surgeonâs line of sight. This imaging approach could replace traditional display monitors and reduce errors in image perception. Finally, the mechanism of the NIR fluorescence signal in the parathyroid was investigated. The endogenous NIR fluorophore in the parathyroid gland has an emission peak at a wavelength that has been thought to be devoid of autofluorescence. Studies revealed the biochemical behavior and location of the fluorophore. Ultimately this combination of studies lowers the barrier for clinical translation of the technology. Widespread adoption of NIR fluorescence detection of the parathyroid glands will greatly improve patient care by reducing harmful surgical complications.

<p> Anterior cruciate ligament (ACL) injuries are one of most common musculoskeletal injuries and negatively affect mobility and quality of life. ACL rupture requires reconstruction to repair ligament at an estimated cost of $1.5 billion/year. Current surgical solutions invariably involve either donor site morbidity with the use of autografts or the risk of disease transmission and immune rejection with the use of allografts. Successful reconstruction requires the presence of an intact interface between ligament and bone, a transitional tissue called the enthesis. The enthesis is critical for the safe and effective transfer of force from the stiff bone to the more compliant ligament by providing a gradual transition of mechanical and biochemical properties to prevent the formation of stress concentrations. A tissue engineered ligament containing mature entheses is a promising alternative to autografts and allografts, especially since this interface does not normally regenerate. Toward this end, this dissertation sought to improve engineered fibrin-based bone-to-bone ligaments previously developed by our lab and to demonstrate their utility in understanding physiological processes through three specific aims: 1) optimize the environment for <i> in vitro</i> ligament function, 2) induce the formation of a fibrocartilaginous interface, and 3) demonstrate the utility of engineered ligaments as a physiological model.</p><p> In Aim 1, the <i>in vitro</i> culture environment was investigated for engineered ligaments formed using human ACL fibroblasts. Using a DOE approach, we identified significant effects and interactions of soluble factors on the maximal tensile load (MTL) and collagen content of engineered human ACL. The DOE model was used to predict a maximal growth media which significantly improved the MTL and collagen content of engineered ligaments and can be combined with increases in the initial construct volume for 77% further improvement in MTL. In addition to the improvements in tissue function, these data suggest that a DOE approach can more efficiently optimize <i>in vitro</i> parameters including the dosage and timing of chemical and mechanical stimuli as well as any interactions.</p><p> Aim 2 presented two strategies to improve of the engineered enthesis. First, the local release of bone morphogenetic protein (BMP)-4 at the enthesis of engineered ligaments demonstrated improved interface strength as well as the transition of cells at the enthesis towards an unmineralized fibrocartilage phenotype. Second, engineered ligaments formed in a modular fashion improved the mechanical function and the morphology of the engineered enthesis including the development of cell and soft tissue integration into the mineral phase, a tidemark between mineralized and unmineralized tissue, and the presence of a dense band of extracellular matrix (ECM) at the soft tissue-mineral interface. Importantly, this is the first demonstration of the <i>in vitro</i> formation of a functional interface between engineered ligament and mineral in a complete bone-to-bone ligament unit.</p><p> Aim 3 demonstrated the use of our engineered ligament model as a physiological tool. During the estrogen surge in the menstrual cycle, there is an associated increase in the incidence of ACL ruptures as well as knee laxity. Using physiological levels of estrogen mimicking the estrogen surge <i>in vitro</i>, we determined that estrogen decreases the activity of the collagen crosslinker lysyl oxidase (LOX) with a subsequent decrease in tissue stiffness providing insight into why women have greater incidences of ACL rupture. We also examined the role of the exercise-induced biochemical environment on connective tissue using our <i>in vitro</i> model. Engineered ligaments cultured with serum obtained from human donors after exercise had significantly better mechanical strength and collagen content than those treated with serum obtained at rest. In 2D culture, we determined that this effect was likely a result of greater mTOR and ERK signaling.</p><p> In summary, the work in this dissertation has made great strides in developing a more mature engineered bone-to-bone ligament. We have optimized a growth factor environment for their <i>in vitro</i> culture and created the most advanced engineered enthesis to date. We have also used these engineered tissues as a platform to mechanistically study the influence of hormones on connective tissue. With further advances in our understanding of the <i> in vivo</i> development of ligaments and their entheses, our bone-to-bone engineered ligaments can be improved making them more suited for clinical applications and for probing physiologically processes in a more controlled environment.</p>

Resting state functional magnetic resonance imaging (rsfMRI) has been widely used for measuring functional connectivity between cortical regions. However, there have been minimal reports of rsfMRI in white matter, presumably because of the sparse vasculature in white matter relative to gray, and the consistent failure to observe significant hemodynamic responses from tasks within white matter. In this study, we aimed to investigate and assess the nature of temporal variations in rsfMRI signals from human and monkey brains in white matter. Previous studies have reported that the correlations of time course signals in a resting state between voxels are anisotropic in white matter. We therefore constructed functional correlation tensors (FCTs) that quantify the functional relationships between neighboring voxels and their anisotropy in normal brains at rest, and compared these to underlying structural features. Furthermore, we elucidated the underlying biophysical mechanisms that account for their origins by assessing whether MRI signal fluctuations in white and gray matter vary for different baseline levels of neural activity. We found FCTs were capable of visualizing long range white matter tracts as well as short range sub-cortical fibers imaged at rest, suggesting temporal resting state signals may reflect intrinsic synchronizations of neural activity in white matter. Moreover, our monkey studies revealed that fractional power of rsfMRI signals are modulated similarly in regions of SI cortex, gray and white matter as neural baseline activity is varied. Our results imply that neural activity is encoded in white matter, and that that BOLD signal fluctuations in white matter may be detected in a resting state.

Given the prevalence of malaria in underdeveloped countries, specialized solutions must be developed for its diagnosis. The most common diagnostic throughout these regions is a lateral flow assay. While generally useful, these have a higher limit of detection than standard malaria diagnostics in the developed world. To help bridge this gap we are developing a system to concentrate malaria biomarkers on a lateral flow strip in order to lower its effective limit of detection. By using functionalized ferromagnetic micro-particles in a patient sample we can concentrate biomarkers and then transfer them to a surface leaving behind the bulk fluid. One of the first steps towards this is to understand parameters affecting particle transfer from an idealized fluid and across an air gap to a surface below. We were able to transfer various bead across distances of over 3mm for samples over 300?g when holding the sample orthogonal to the surface and over 200?g when holding the sample at a 45° angle to the surface. Bubble exchange between the seems to be the limiting factor driving bead transfer and occurs more readily in 45° samples allowing bead transfer to occur in an unimpeded fashion leading to more easily discernable trends within these samples.

<p>Prostate and breast cancers are two of the most common types of cancer in the United States, and those cancers metastasize to bone in more than two thirds of patients. Recent evidence suggests that thermal therapy is effective at treating metastatic bone cancer. For example, thermal therapy enables targeted drug delivery to bone, ablation of cancer cells in bone marrow, and palliation of bone pain. Thermal therapy of bone metastases would be greatly improved if it were possible to image the temperature of the tissue surrounding the disease, which is usually red bone marrow (RBM). Unfortunately, current thermal imaging techniques are inaccurate in RBM.</p><p>This dissertation shows that many of the difficulties with thermal imaging of RBM can be overcome using a magnetic resonance phenomenon called an intermolecular multiple quantum coherence (iMQC). Herein, iMQCs are detected with a magnetic resonance imaging (MRI) pulse sequence called multi-spin-echo HOMOGENIZED with off resonance transfer (MSE-HOT). Compared to traditional methods, MSE-HOT provided ten-fold more accurate images of temperature change. Furthermore, MSE-HOT was translated to a human MRI scanner, which enabled imaging of RBM temperature during heating with a clinical focused ultrasound applicator. In summary, this dissertation develops a MRI technique that enables thermal imaging of RBM during thermal therapy of bone metastases.</p> / Dissertation

Proteomics allows us to see post-translational modifications and expression patterns that we cannot see with genomics and transcriptomics alone. By itself, proteomics has limited sensitivity to detect genetic variation (e.g. single-nucleotide polymorphisms and insertion/deletion mutations), but we can improve that with access to genomic data: an approach known as proteogenomics. As in many of the -omics fields, reproducibility of proteogenomic results is a problem. Since 2005, the web application âGalaxyâ has been available to improve the transparency and reproducibility of -omic analyses. However, a Galaxy server is not easy to set up, and to work around that, investigators have sometimes distributed their customizations as virtual machines (VMs). In recent years, a more efficient approach for software isolation - âcontainersâ - has become popular. A proteogenomics âflavorâ of Galaxy â Omicron â was created to simplify reproduction of proteogenomic workflows. An easy way for anyone to launch Omicron on Amazon Web Services, paired with a scalable compute cluster, was also created. Using Omicron, results from a 2014 Nature paper were partially reproduced. Due to changes in online reference data and possibly due to different tool versions, it was not possible to perfectly reproduce the previous results. However, other investigators could easily reproduce the Omicron results without digging through methods and supplemental data. Then they could easily apply the same workflow to their own data.

Colorectal Cancer (CRC) remains a leading cause of cancer-related mortality in the United States. A key therapeutic dilemma in the treatment of CRC is whether patients with stage II and stage III disease require adjuvant chemotherapy after surgical resection. Attempts to improve identification of patients at increased risk of recurrence have yielded many predictive models based on gene expression data, but none are FDA approved and none are used in standard clinical practice. To improve recurrence prediction, we utilize an ensemble learning approach to predict recurrence status at 3 years after diagnosis. Multiple views of a microarray dataset were generated then used to train a diverse pool of base learners using 10x 10-fold cross-validation. Stacked generalization was used to train an ensemble model. Our results demonstrate that molecular data predicts recurrence significantly better than basic clinical data. We also demonstrate that the performance of the multiple-view multiple learner (MVML) supervised learning framework exceeds or matches that of the best base learners across all performance metrics.

<p>In this work, I investigate the mechanical response of the liver to increasing pressure in the portal vein using ultrasonic approaches. In advancing liver disease, portal venous pressure increases lead to severe clinical problems and death. Monitoring these pressure increases can predict patient outcomes and guide treatment. Current methods for measurement of portal venous pressure are invasive, expensive, and therefore are rarely repeated. Ultrasonic methods show promise because they are noninvasive, but traditional ultrasound images and doppler measurements do not yield accurate repeatable measures of hepatic pressure. However, increases in portal venous pressure have been associated with higher estimates of liver stiffness using ultrasound-based shear wave speed estimation algorithms. These quantitative estimates of shear wave speed may provide a mechanism for noninvasive hepatic pressure characterization, but they cannot currently be distinguished from the increases in shear wave speed estimates that are also observed in patients with normal portal venous pressures with advancing liver diseases. Thus, a better understanding of the mechanisms by which hepatic pressure modulates estimates of liver stiffness could provide information needed to distinguish increasing hepatic pressure from advancing brosis stage. This work is devoted to identifying and characterizing the underlying mechanism behind the observed increases in hepatic shear wave speed with pressurization.</p><p>Two experiments were designed in order to dene the mechanical properties of liver tissue that underlie the observed increase in shear wave speeds with increasing portal venous pressure. First, the behavior of the liver was shown to be nonlinear (or strain-dependent) by comparing stiness estimates in livers that were free to expand and constrained from expansion at increasing hepatic pressures. Shear wave speeds were observed to increase only in the unconstrained case in which the liver was observed to qualitatively deform. Second, the deformation of the liver was quantied using a clinical scanner and 3-D transducer to generate estimates of axial strain during pressurization. Axial strain was found to increase with elevation in portal venous pressure. This axial expansion of the liver also corresponded to increases in shear wave speed estimates with portal venous pressure.</p><p>The techniques developed herein were used to elucidate mechanical properties of the pressurized liver by concurrent ultrasound-based quantication of hepatic deformation and stiffness. This work shows that increasing shear wave speed estimates with hepatic pressurization are associated with increases in hepatic axial strain measurements. These results provide the basis for quantifying the relationship between pressurization and hepatic strain, laying the foundation for hyperelastic material modeling of the liver. Such nonlinear mechanical models can provide the basis for noninvasive characterization of hepatic pressure using stiffness metrics in the future.</p> / Dissertation

Thesis under the direction of Dr. Jeremy L. Warner The practice of oncology increasingly relies on genetic information from tumors to determine diagnosis, prognosis and therapy. These tumor molecular profiling reports are generated by clinical laboratories specializing in molecular diagnostics; however, there is no consensus on what the reports should contain, how they should be structured, or how best to transmit and present them to oncologists. This thesis outlines a framework for the data elements, file structure, transmission requirements, clinical information technology requirements and secondary use cases for molecular profiling. This framework is used as a guide to describe the implementation of tumor molecular profile reports into clinical workflows. The experience of implementing automated structured molecular profile reports from a third party laboratory into an electronic health record is described. Using file structures and data elements from the framework, molecular profile genetic data and sample metadata can be accurately parsed, restructured and aggregated for secondary uses. A system of parsing this data into a database and the use cases this database satisfies is described. This framework helps to inform clinical and translational uses of tumor molecular profiling.