This Masters Thesis project had as its objectives: (1) to optimize algorithms for solvent-accessible surface area (SASA) approximation to develop an environment free energy knowledge-based potential; and, (2) to assess the knowledge-based environment free energy potentials for de novo protein structure prediction. This project achieved its goals by developing, implementing, optimizing, and evaluating four different algorithms for approximating the SASA of a given protein model and generating knowledge-based potentials for de novo protein structure prediction. The algorithms are entitled Neighbor Count, Neighbor Vector, Artificial Neural Network, and Overlapping Spheres.

Lasers have taken on an ever-expanding role in the medical field for diagnostic and therapeutic applications. Commonly, damage from laser procedures has been quantified on the tissue level. As a result, relatively little knowledge has been gathered about the cellular level of sub-lethal damage. In reality, damaged cells undergo a complex reformation of their underlying biochemistry when pathways are activated and suppressed in response to heat damage. We used a cell culture system and a molecular biology approach to study laser induced sub-lethal cellular damage. Our approach incorporated three key components to interrogate the character and function of HSP70, which is one of the most well know mediators of thermal stress in cells. First a bioluminescent transgene system was used wherein the luciferase reporter gene is expressed upon activation of the Hsp70 promoter and light is emitted. The changes in bioluminescence correlated to the level of thermal stress within the cells. We showed that exposing cells to a mild thermal insult prior to more severe heat shock significantly increased cell survival. Using a 'knockout' cell line that has the Hsp70 gene deleted, we showed that the efficacy of this preconditioning treatment was greatly reduced in the absence of HSP70 protein. However, some thermotolerance was still present. Consequently, a gene expression analysis was carried out to determine the other genes that are involved in the cellular response to thermal stress. The methods used in this research allowed us a unique window into the molecular workings of the cell on a fundamental level that may eventually translate to clinical applications involving thermal responses.

Diffusion weighted magnetic resonance imaging (DW-MRI) is an imaging technique that provides a measure of local tissue microstructure based on the water molecular diffusion. Although this imaging method has been successfully used in investigating brain white matter for normal and various dysfunctional states, major limitations of this technique have recently been identified. In diffusion tensor MRI (DT-MRI), image noise produces both noise and bias in the estimated tensor, and leads to errors in estimated axonal fiber pathways. Moreover the single-tensor model is inappropriate in regions with non-parallel fiber structure. Several high angular resolution diffusion imaging (HARDI) methods have been proposed as alternative tools for resolving multiple fiber structures within a single voxel. At low SNR, however, fiber orientation from HARDI becomes unreliable. Also none of the HARDI methods can provide estimates of the intrinsic diffusion properties of any of the fibers. Addressing limitations of this technique, we suggest improved imaging methods for brain white matter in conventional and ultra high field imaging environments. This study provides experimental and theoretical results about the uncertainty in fiber orientation using DT-MRI. It proposes methods for the estimation of intrinsic diffusion properties as well as reliable fiber orientation distribution (FOD) functions using HARDI with simulations and in vivo experiments. These methods are then applied to ultra high field strength experiments using a field inhomogeneity correction for image distortions. In summary, the results of this study provide improved diffusion imaging methods for human and/or non-human primates.

This thesis is concerned with the quantification of cardiac longitudinal relaxation (T1) at 3.0 T. Normal and hyperoxic T1 are quantified in the myocardium and left ventricular blood pool of healthy volunteers using the Modified Look-Locker Inversion recovery (MOLLI) technique. Change in mean myocardial T1 with hyperoxia at 3.0 T is compared to similar results at lower field strengths. Three alternative T1 quantification techniques based on the original MOLLI sequence are presented and evaluated along with the original MOLLI sequence for accuracy and consistency in measuring T1 values expected in the myocardium and blood at 3.0 T. Additionally, a theoretical model predicting the reduction in myocardial T1 with an intravascular contrast agent is examined for applicability to oxygen as a contrast agent. The results of this theoretical model are compared to experimental results obtained in this study.

Hepatic fibrosis is a progressive disease in which progression is correlated to liver mechanical properties. This correlation may be used to assess the state of the disease, and hence methods to determine the elastic modulus of the liver are of considerable interest. In order to assess the diseased state of the liver accurately, controlled experiments to establish baseline modulus values for healthy livers as well as diseased livers must be conducted. The focus of this work is the development of a protocol for mechanical testing combined with finite element modeling to allow for the evaluation of normal and fibrotic murine livers using multiple testing methods. The developed system employs a portion of liver tissue suspended in a cylindrical gel for CT imaging and mechanical testing. A finite element model is built from the CT images, and boundary conditions are imposed in order to simulate the testing conditions of the gels. The resulting model surface stress is compared to that obtained during mechanical testing which subsequently allows for direct evaluation of the liver modulus. Though the sample sizes for this initial work were small, the preliminary results indicate that the livers can be identified within the gel, and the fibrotic livers can be identified as having a higher modulus than the control livers, thus implying that the developed gel-tissue assay system could be used for controlled evaluation of soft-tissue moduli.

Endoscopic orbital procedures are hindered by both the difficulty in differentiating between orbital structures and the loss of orbital landmarks during these procedures. These difficulties are due to the orbital fat that obstructs direct vision of the orbital structures. Image guidance can address these problems because real time image and physical space tracking information can be provided to the surgeons during the orbital procedure to help in the delivery of therapy to the orbit. Image guidance requires an image-space to physical-space registration and tracking in physical-space with a localizer. To effectively use a magnetic localizer for transorbital guidance, the error metrics must be characterized so that expected guidance errors can be determined. After characterizing the magnetic tracker, the registration of the physical-space to image-space needs to be addressed. Since the target in this research is the optic nerve, a structure which can be anywhere in the retroorbital pyramid, a new form of fiducial placement is created. In this method the retroorbital pyramid was sampled and a fiducial placement which minimized TRE throughout the possible location of the optic nerve head was determined. After characterizing the magnetic localizer and determining an optimal fiducial placement for the task of optic nerve drug delivery, the performance of the system had to be tested. An experimental protocol which allowed performance quantification in an application mimicking manner was developed. Performance metrics from that protocol were gathered on a number of surgeons.

Diffusion tensor imaging (DTI) is a magnetic resonance imaging (MRI) technique that provides information about the organization and structural integrity of tissue. It has become an increasingly popular tool for investigation of white matter tissue in the brain emph{in vivo}, with clinical applications ranging from myelin-related diseases, such as multiple sclerosis and Krabbe disease, to psychiatric disorders, such as schizophrenia and bipolar disorder. In studies comparing DTI data between groups, whole-brain, voxel-wise analyses are commonly performed. However, there is not enough information in the scalar images typically used for image co-registration to accurately align specific fiber pathways within large white matter structures. This misalignment potentially results in decreased sensitivity to detecting subtle changes within specific tracts and makes interpretation of results more difficult in studies of disorders where it is suspected that changes in white matter diffusion properties are pathway-specific. In an effort to overcome this limitation, several tract-based analysis methods that utilize fiber tractography to isolate specific tracts of interest have recently been proposed. However, the majority of these methods have been developed for particular white matter pathways and are not easily translated to other tracts, or compare the average of diffusion parameters over the entire tract, overlooking localized changes within the tracts. Proposed here is a new tract-based method that utilizes the image co-registration necessary for a voxel-wise analysis to automatically isolate white matter tracts-of-interest in each subject with fiber tractography and parameterize them so that spatially localized statistical comparisons between groups can be made. It was applied to studies of schizophrenia and Williams syndrome, and the results were compared to voxel-based analyses of these studies. Our results suggest that the new tract-based analysis method performs better than the voxel-based method in regions where image co-registration performs poorly and in regions where image co-registration appears to perform well but actually fails to align smaller tracts within larger white matter structures. This new tract-based analysis method, used in combination with a voxel-wise analysis, may be able to improve the interpretation of results from group comparisons of diffusion tensor imaging data.

The processes of tumor growth and treatment response are associated with the upregulation of numerous proteins [1, 2], yet current clinical imaging methods of cancer characterization monitor only gross morphology [3, 4]. This study combines in vivo diffusion weighted magnetic resonance imaging (MRI) with matrix-assisted laser desorption ionization (MALDI) analysis of healthy and tumorous ex vivo specimens in order to examine the proteomic influences on the apparent diffusion coefficient provided by MRI. Spatial co-registration of MALDI and ADC datasets enables examination of the statistical correlations between the two metrics [5] in the hopes of elucidating the proteomic signatures that give rise to particular ADC values. <p> ADC and MALDI data were acquired for two rats, one control and one in which a C6 glioma model of brain cancer was implanted. Principal component analysis was conducted to determine the degree of spatial correlation between the ADC and protein measurements. It was found that ADC and MALDI data correlated significantly (p-value of 0.05) in 44.0% of 114 regions of interest (ROIs) in the two rats. Protein profiles were identified which correlated with statistically similar ADCs in selected ROIs for each rat. The results of this study are consistent with the theory that protein expression in both healthy and tumorous rat brain tissue is a molecular-level source of contrast in diffusion-weighted MRI.

The failure of synthetic vascular grafts due to de-endothelialization of the lumen as a result of exposure to fluid-induced shear stress prevents the widespread use of such grafts as small-diameter vessel replacements. Physical surface modification, an approach that seeks to alter the topography of the luminal surface, has been investigated as a method of reducing de-endothelialization under physiological stresses. Based on prior experimental evidence supporting this approach, computation fluid dynamics was used to investigate the impact of selected channel geometry parameters (wall angle, channel width, depth, and radius of curvature) on fluid flow and the resulting wall shear stress. Optimization of these parameters was performed in order to determine if micro-topographical modification of the lumen wall could alter fluid flow in a manner such that favorable conditions for both endothelial cell retention and stimulation are produced. It was found that a 50% decrease in the wall angle, width, and depth causes a decrease in maximum wall shear stress of around 8%, 8%, and 15%, respectively. Additionally, increasing the radius of curvature at the top and bottom edges by 50% results in a 10% decrease in maximum wall shear stress. These results indicate that it may be possible to tune the lumen micro-topography in order to provide a desired range of stresses, and subsequently reduce thrombogenicity by enhancing endothelial cell retention and function.

The emerging field of molecular imaging (MI) aims to noninvasively, quantitatively and repetitively monitor biological processes in vivo to detect disease, probe its basis, and study relevant biochemical pathways at the molecular level. Since molecular targets undergo alterations prior to morphological or physical transformations, MI should aid in early detection and improved diagnosis of disease, resulting in improved clinical outcomes and enhanced long-term patient survival. In addition, the capability to monitor lesion physiology in vivo may facilitate therapeutic efficacy monitoring, speed drug discovery, and potentially lead to patient-specific treatment regimens. Optical MI, particularly in the near infrared (NIR) wavelength region, is an inexpensive technique that provides relatively high sensitivity without the use of ionizing radiation. Fluorescence imaging is rapid, allowing for dynamic, real-time monitoring of agent biodistribution and clearance profiles and is commonly performed concurrently on multiple animals in a relatively high-throughput manner. The ultimate success of optical MI depends on the development, characterization and optimization of probes as well as superior instrumentation to accurately detect, localize and quantify these unique MI compounds. The overall objectives of this dissertation were directed at quantitative in vitro and in vivo characterization of two novel MI agents developed in our laboratory: a peripheral benzodiazepine receptor (PBR)-targeted NIR MI agent (NIR-conPK11195) and a potential optical analogue to the 2-[18F]fluoro-2deoxy-D-glucose (18FDG) positron emission tomography agent (NIR-glucosamine). Specific Aims I and II demonstrate the utility of NIR-conPK11195 for breast cancer screening and monitoring as well as for studying breast cancer metastases to the brain, respectively. The dose-dependent and PBR-specific cellular uptake of NIR-conPK11195 can be quantified in live-cell competition assays, visualized by fluorescence microscopy, and monitored in vivo. In Specific Aim III, NIR-glucosamine appears to preferentially label tumor tissue in vivo, but with a potential size and/or vascularity requirement for appreciable tumor-specific contrast. Furthermore, several observations suggest that NIR-glucosamine does not follow the GLUT/hexokinase pathway and may label tumors in a non-specific manner.