Early detection of breast lesions with malignant potential plays an important role in patient prognosis and survival. While X-ray mammography is the current clinical standard for screening and detection, traditional techniques such as palpation in the physical exam still play an important diagnostic role, and additional alternative means are actively being sought for the identification of suspicious lesions. This work has been focused on the development of a novel method termed modality-independent elastography (MIE) for the purpose of quantitatively extracting the material properties of tissue. This is quite relevant in the context of breast cancer, as solid tumors are typically stiffer than the surrounding unremarkable normal tissue. MIE performs an iterative non-rigid, model-constrained image registration analysis of a tissue under differing states of mechanical loading to produce a spatial mapping of elastic modulus values, which can be then used to characterize and/or localize a lesion. Simulation and phantom experiments were performed for two- and three-dimensional systems with a variety of image data acquired from CT, MR, and digital photography. Additional work produced a clinically compatible proof-of-concept system that is suitable for undergoing further refinement in preparation for initial human trials. Preliminary results have been encouraging and hold promise for the use of MIE in detection and characterization of abnormal stiffness within the breast.

The goal of this work was to develop methods to overcome the practical difficulties of 3T human myocardial imaging and to determine reliable reference values for transverse relaxation in normal human myocardium. Nine healthy volunteers were investigated with three multi-echo, turbo spin-echo (TSE) methods. Each method involved tradeoffs between acquired phase encoding lines per image and the number of echo-image sample points obtained along the T2 decay curve. Three multi-echo turbo field-echo (TFE) methods were also tested. The TFE methods highlighted differences between achievable bandwidth per pixel and echo time constraints versus the number of sample points obtained along the T2* decay curve. Measured transverse relaxation values in pixel maps and regions of interest, quality of monoexponential curve fits, and signal-to-noise ratio (SNR) were assessed among methods to determine accuracy and repeatability. Measured T2 and T2* values were consistent in reported means and in SNR across all scan methods. T2 for the ventricular septum was 59.5 ± 7.9 ms (N=9) across all TSE methods. The 4-echo method gave the best curve fits. T2* for the ventricular septum was 31.6 ± 6.1 ms (N = 9) with the 4-echo method yielding the highest quality curve fits. Significant differences between measured endo- and epicardial transverse relaxation due to myocardial perfusion were not observed. These results indicate that the 4- echo methods are best for optimal T2 and T2* sampling in the mid-ventricular septum.

Modern neuroscience seeks to understand the human brain and determine how stimulus features are directly mapped to neuronal representations that govern emergent properties like perception and behavior. One prominent proposal for population-based encoding of information is synchronization in the firing of two or more cells. Although synchrony has tremendous potential as a coding mechanism, understanding its relevance is difficult since the techniques to measure and analyze synchrony are relatively new. The work presented here combines simultaneous recordings from dozens of neurons with a novel method for identification of cellular assemblies defined by synchrony to investigate the dynamic associations among small populations during natural stimulation. We found that synchronous activity was able to discriminate changes in structural integrity and overcome the ambiguity of firing rate to identify contour structure reliably and consistently. The time course of synchrony suggests that it is directly related to spatial stimulus properties. Using a large natural image sequence with a variety of visual features to optimize stimulation of the entire recorded population, we showed that synchronous activity was correlated with the receptive field properties of proximity, orientation, and continuity. We used these properties to create a contour index, which quantitatively described how well an assembly's configuration matched a contour structure. Synchrony was well-correlated with this measure, which indicates that cooperation may be selective for local contrast structure arranged in continuous, well-defined contours. Synchronous activity is particularly sensitive to structural content in natural images, which is preserved in the phase regularities in the image and not the power spectrum. We found that synchrony measured between assemblies representing different contours was severely reduced. Responses were sparse for each assembly across the image set and well as across all assemblies for each condition. Our results demonstrate that synchrony has the potential to encode image properties not apparent from changes in firing rate. As a fundamental mechanism of sensory cognition, synchrony may act as a sparse code to help facilitate the detection of contour information for integration and processing in higher visual areas.

Recent advances in breast cancer imaging have generated new ways to characterize the disease, and many of these novel analysis techniques require the registration of breast surfaces during a non-rigid deformation. In this paper, a semi-automated method to register breast surfaces before and after a non-rigid deformation is presented. This method involves solving the Laplace or diffusion equations over the undeformed and deformed breast surfaces, yielding potential fields and isocontours that are used to establish surface correspondence. The proposed partial differential equation (PDE)-based registration method is compared to a thin-plate spline (TPS) interpolation of surface displacements tracked by fiducial markers. These registration methods are tested on a realistic finite element simulation of a breast compression, a breast phantom, and on a clinical data set. The results indicate that the TPS registration technique is the most accurate; however, if fiducial information is not available, the PDE-based registration methods may be viable alternatives. The PDE-based and TPS registration methods have the potential to be used by analyses requiring the non-rigid registration of breast surfaces before and after compression, and both have been used in Modality-Independent Elastography (MIE) to determine the boundary conditions needed for elasticity imaging.

This dissertation covers research regarding the use of computational models during brain tumor resection therapies. Systematic studies have shown that the brain tissue shifts during tumor resection therapies and that current image-guided systems do not account for this shift. Compensating for intraoperative brain shift using computational models has been used with promising results. For computational models to be clinically useful in tumor resection guidance, these models should meet the real-time constraints of neurosurgery and they should also provide images that mirror their intraoperative counterparts. The primary goal behind this research involves developing one such computational framework. More specifically, this framework involves combining a computational model with a linear inverse model to predict intraoperative brain shift. The framework reported in this dissertation relies on relatively inexpensive small scale computer clusters and can compute image updates on a time scale that is compatible with the surgical removal of tumor. In-vivo validation shows that the framework presented in this dissertation increases the efficiency and accuracy of image-guided systems. Results obtained have also been presented as graphical images for qualitative assessment. In summary this research constitutes a significant step towards using computational models for neuronavigation.

Most magnetic resonance imaging techniques offer tissue contrast but provide limited information regarding the variation of the magnetic resonance signal that exists on a smaller scale. The magnetic resonance signal arising from a heterogeneous tissue, such as spinal cord white matter, is the sum of signals from each tissue compartment within the imaging voxel. Analysis of this signal can better characterize the micro-anatomical heterogeneity tissue, white matter in particular. Many questions remain with regard to the compartmental contributions for the various types of magnetic resonance imaging (MRI) contrast. This project utilizes a variety of in vitro studies as well as simulations to better characterize the contribution of different water compartments to conventional MRI methods. Such an understanding of the complex combination of the various relaxation and exchange properties is important in developing an anatomical basis for interpreting magnetization transfer and T2 weighted images, particularly with respect to myelination.

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.