Most functional MRI studies rely on fast Echo Planar Imaging, which is sensitive to magnetic susceptibility effects. These effects can lead to image-to-image signal instability, reducing the reliability of functional activation maps. Respiration is responsible for a significant component of image-to-image variance, but no widely effective method for correcting respiration-based susceptibility effects is available. We demonstrate a relationship between respiration-related susceptibility effects in the presence of parallel imaging acquisitions and apply our findings to analyze the behavior of IMPACT (IMage-based Physiological Artifact Correction Technique). Based on our findings regarding IMPACT, we propose COMPACT (Center of Mass-based Physiological Artifact Correction Technique), a new method which provides a reliable estimate of respiratory effects based on the motion of an image sets center of mass (centroid) through time.

Diffusion Tensor Imaging (DTI) has become the primary imaging modality for non-invasive characterization of the microstructure of living tissues, particularly of human white matter. Despite its success in various research areas and clinical applications, DTI is unable to describe adequately non-Gaussian diffusion. Fiber ORientation Estimated using Continuous Axially Symmetric Tensors (FORECAST), a new approach to High Angular Resolution Diffusion (HARD) analysis, is able to provide reliable estimates of the fiber radial diffusivity and orientation distribution within each voxel. In this study, several techniques were developed to enhance the FORECAST models reproducibility. The models dependence on various imaging parameters and analysis parameters was tested by Monte Carlo simulation. The optimal parameters for FORECAST analysis was determined based on the simulation results, and verified by in vivo human data.

In hepatic applications, radiofrequency ablation (RFA) produces ablation extents that are limited in size both as a result of local tissue properties as well as constraints in ablation device design and physics. Because RFA is a focal, nonconformal therapeutic modality, proper placement of the device is an important goal in producing successful treatment so that the resulting ablation extents overlap the detectable tumor as well as a suitably defined margin. This dissertation examines novel methods of treatment planning by using image-guided techniques to improve placement accuracy and computational modeling to predict ablation outcomes given suitable placements. A method is presented to search for needle placement that best satisfies a given therapeutic goal using outcomes predicted by finite element models of ablations. This search technique is applied to simulated scenarios requiring single as well as multiple ablations to study effects of nearby heat sinks on optimal placement. A phantom system is then constructed to conduct ablation experiments performed using a tracked RFA device. The phantom ablation results are compared against ablation extents predicted using computational models given the measured positional data from the tracked device. Metrics to quantify the model accuracy are introduced, and the effects of tracking inaccuracies are analyzed. Finally, the sensitivity of predicted ablations to needle placement inaccuracies is studied theoretically. Sensitivity analysis is conducted via a novel method that couples boundary element and finite element methods to obtain multiple simulations efficiently for different needle placements over a static mesh. This method is used with Monte Carlo simulations to generate a spatial map of the likelihood of ablation success given uncertainties in targeting accuracy. Using this technique, strategies to make treatment plans less sensitive to placement errors are studied. The results of this research demonstrate the feasibility of coupling image-guided techniques and computational modeling to produce predictive treatments plans for RFA that are robust to device placement uncertainties.

The collection of visual evidence of M13 bacteriophage displaying a nuclear localization heptapeptide localizing to the nuclei of breast cancer cells is described in this thesis. The bacteriophages displaying the heptapeptide were conjugated to a fluorochrome prior to incubation with live cells. After the incubation, the cells were fixed and cell nuclei were stained, and a fluorescent microscope was used to visualize and obtain photographs of the cells. Fluorochrome-labeled bacteriophages not displaying the heptapeptide showed no localization to cell nuclei, but fluorochrome-labeled bacteriophages displaying the heptapeptide exhibited peripheral nuclear binding. The second portion of this thesis describes an attempt to measure the amount of the metalloproteinase matrilysin produced by five cancer cell lines by analyzing supernantants taken at regular time points over a 96-hour interval. An ELISA using antibodies specific to matrilysin was performed initially, followed by an assay based on the cleavage activity of the matrilysin enzyme. The ELISA results indicated that the cell lines produced an undetectable level of matrilysin, while the activity assay indicated elevated production by all five of the cell lines. Diagnostic experiments were conducted to determine the cause of the substrate cleavage. It was determined that enzymes present in the samples other than metalloproteinases were cleaving the substrate. Efforts to isolate Cathepsin D, an aspartic protease which was not inhibited during the assays, detected its production by three of the five cell lines.

T cells occupy a central role in cell-mediated immunity and as such, deciphering the signaling events that govern T cell activity is critical in fully understanding the adaptive immune response. Current immunologic methodologies utilize either conventional cell culture techniques to analyze millions of cells over time, thereby averaging out rare signaling events, or technology that interrogates single cells at a single time point each, resulting in a loss of information regarding temporal signaling dynamics. To overcome these limitations, we have developed the multi-trap nanophysiometer, a novel, self-contained microfluidic platform fabricated of optically transparent, bio-inert PDMS designed to study signaling dynamics of multiple single T cells in parallel. This body of work describes the major accomplishments attained towards the development and validation of this platform. Cell viability analysis revealed that at flow rates of 100 nl/min, more than 70% of CD4+ T cells, held in place using only hydrodynamic forces, remained viable following 24 hours within the microfluidic environment. We then observed cytosolic calcium transients to demonstrate the ability to activate T cells within the multi-trap nanophysiometer using chemical, antibody, and cellular forms of stimulation. Applying this platform to study intercellular signaling events we were able to observe calcium transients in T cells in response to both contact- and non-contact-based interactions with dendritic cells. Further investigation revealed that in the absence of antigen, LPS-matured dendritic cells secrete chemical signals that induce calcium transients in naïve CD4+ T cells, but in such small concentrations that effects of these signals are not easily observed in normal cell culture conditions. Finally, utilizing the multi-trap nanophysiometer to study the immunological synapse between dendritic cells and T cells, we revealed the occurrence of bi-directional cytosolic dye transfer. This suggests that communication between dendritic cells and T cells during the immunological synapse may not be limited to cell surface interactions. Taken together, these results establish the multi-trap nanophysiometer as a powerful tool in the analysis of cell signaling dynamics.

The development of ultra-high field systems has benefited magnetic resonance imaging experiments due to the signal enhancement such systems provide. However, improvement in signal strength comes at the cost of increased artifacts caused by T2*, ´B0, and susceptability effects leading to image intensity loss, blurring, and geometrical distortion. As these effects are time and field dependent, techniques have been developed to speed up image acquisition. In particular, parallel imaging based methods have been developed that use the signal reception properties of a surface coil parallel array. Specifically, each coil has a distinct spatial sensitivity to the established image object intensity that provides additional acquired signal encoding. Techniques such as SENSE use knowledge of the coil sensitivities to remove aliasing artifacts that result when the image spatial frequencies are sparsely acquired. The reduction in data acquisition translates directly to a reduced scan time to diminish time-dependent artifacts or improve resolution, but at a loss in SNR due to data reduction and SENSE reconstruction errors. To date, parallel imaging approaches have been largely applied to human studies, with limited animal experiment application where they would also be of benefit. This thesis describes the development of a four channel parallel array and SENSE reconstruction program that enables parallel imaging studies to be performed on a Varian 9.4T small animal MR system.

Recent years have seen an explosive increase in the use of lasers for medical applications, particularly in the field of dermatology where they are commonly used to achieve aesthetic, surgical, and therapeutic clinical objectives. Effective cutaneous laser procedures are achieved by tailoring the operating parameters of the laser to the physical and optical properties of the skin. Ideal laser parameters are selected to optimize therapeutic efficacy while minimizing unwanted side effects and tissue damage. Laser-induced tissue injury is known to occur via oxidative, photothermal, photomechanical, and photochemical mechanisms. However, the specific cellular and molecular pathways that initiate and govern these mechanisms are poorly understood. The primary objective of this research was to develop skin models and in vivo molecular imaging techniques to investigate laser-skin interactions. In this work, human skin cells, skin equivalent models, and animal models were developed to assess cellular damage associated with aesthetic, ablative, and therapeutic laser procedures. Thermal damage was assessed using a reporter gene system in which the activation of a thermo-responsive gene (hsp70A1) acts like an on-off switch for the expression and production of light emitting reporter genes. The models were used in this study to: (1) evaluate sublethal cellular damage in aesthetic laser procedures, (2) assess collateral damage in laser surgical ablation procedures, and (3) develop a therapeutic laser preconditioning protocol to enhance cutaneous wound repair. The use of skin models in conjunction with a thermally responsive reporter is a useful strategy for assessing sublethal thermal damage and is a valuable tool for improving medical laser procedures.

Image to physical space registration is a very challenging problem in image guided surgical procedures for the liver due to deformation and paucity of prominent surface anatomical landmarks. Iterative closest point (ICP) algorithm, the surface registration method used for registering the intraoperative laser range scanner (LRS) data with the preoperative CT data in image guided liver surgery, requires a good starting pose to reduce the number of iterations. Currently anatomical landmarks such as vessel bifurcations are used for an initial registration. This paper presents a computational approach to obtain the initial alignment that would reduce contact with probes for registration during surgical procedures. A priori user information about the anatomical orientation of the liver is incorporated and used to orient the point clouds for segmented CT data and LRS liver data. Four points are computationally selected on the anatomical anterior surface of CT point cloud data and corresponding points are localized on the LRS data using the orientation information. These four points are then used to find the rigid transformation using the singular value decomposition method. Nine datasets were tested using the computational approach and the results were compared using the anatomical landmarks method as the "gold standard". Seven of the nine datasets converged to the same solution using both the methods. The computational method, being an approximated approach may increase the number of iterations to converge to the solution. However since the method does not require precise localization of anatomical landmarks, it could potentially reduce OR time.

In a complex visual scene, different objects with specific features are presented in combinations, which raises the question of how the visual system processes and represents structure in the huge amount of visual information that it receives every moment. Besides independent response rate modulation, which has been traditionally considered to be the primary coding mechanism in the visual system, correlated neural responses in the form of synchronized neural firing have been proposed as providing a versatile means of encoding. In this dissertation, the role of neural correlation in visual perception was explored by analyzing synchronized responses in cat primary visual cortex. We first tested the neural response to collinear and cocircular contours and found that the strength of synchrony between cells is not only affected by the receptive field properties but also determined by the effectiveness of the visual stimulus in driving cells. Synchrony was found to be more reliable for detecting cocircular contours than the independent firing rate, suggesting that contour integration through neural synchrony could start as early as in the lowest level of visual cortex. We then explored the relationship between spike timing synchronization and coherent frequency oscillation. Strong correlation between cross-correlation analysis and coherence analysis suggests synchrony and coherence are internally related, though these two estimates reflect neural connectivity from different perspectives. By systematically perturbing the timing accuracy in neural responses, we also discovered that the temporal structures of spike trains are important in maintaining neural correlation. We last studied how the synchronized neural response modulates with the change of spatial integrity in visual stimulation. We found that the general association between neural spike trains depends strongly on spatial integrity, with coherence in the gamma band showing greater sensitivity to the change of spatial structure than other frequency bands. Temporal integrity, and not spatial integrity, generates synchrony; spatial integrity however is critical in triggering subsequent gamma band synchronization.

USING DIFFUSION TENSOR IMAGING TO ASSESS WHITE MATTER INTEGRITY IN CHILDREN WITH MATH DIFFICULTIES CRAIG THOMAS LORANG Thesis under the direction of Professor Adam Anderson Dyscalculia is a learning disability that interferes with a persons ability to understand and manipulate numbers. This condition affects up to 6% of all children. Previous studies have shown cortical functional activation in the parietal lobe related to number processing, however no studies have investigated the relationship between white matter integrity and number processing. Thirty-three subjects (mean age: 9.6 years) were imaged using a 3 Tesla Philips Achieva MRI scanner. Anatomical and diffusion weighted datasets were pre-processed and registered to a common space. Fractional anisotropy maps were mapped into the common space. Group t-tests were performed on a voxel-by-voxel basis on the FA maps between control and math difficulty (MD) groups. Linear correlations were performed on a voxel-by-voxel basis between FA and Wide Range Achievement Test Third Edition (WRAT) performance in the math and reading subtests. Regions in the left parietal and occipital lobes were found to have FA values correlating with math performance. A frontal lobe region was found to correlate with both reading and math performance, suggesting these two complex operations share portions of white matter bundles. These findings suggest white matter disorganization in regions critical for number processing. Further investigation will be needed to determine if intervention can change the developmental trajectory of these white matter pathways.