Conventional magnetic resonance imaging (MRI) uses contrast that is weighted by the intrinsic tissue parameters T1, and T2. Contrast may also be generated in the rotating frame with the analogous time constants T1ρ or T2ρ. Traditionally T1ρ measurements have been used to investigate low frequency dipolar interactions in the kHz range. However, other biological processes, such as chemical exchange, also occur on this time scale. Recently it has been shown that these processes dominate R1ρ (1/T1ρ) relaxation at high field, and these interactions are of interest as high field imaging systems become increasingly common. We have developed quantitative spin-locking (SL) techniques to probe rotating frame relaxation on clinical and pre-clinical imaging systems. Experiments were performed with these techniques to generate T1ρ maps of pediatric epiphyseal cartilage and mouse brain. If the power of the SL field is varied, the measured T1ρ values will change in a phenomenon known as T1ρ dispersion. These dispersion profiles vary with tissue properties such as pH and metabolite concentration, and the data may be fit with a model to extract unique parameters such as chemical exchange. Novel methods were developed to generate exchange rate based contrast using the contrast features of T1ρ dispersion profiles. A number of exogenous and endogenous contrast agents were quantitatively compared to chemical exchange saturation contrast (CEST) imaging. CEST and SL techniques were evaluated for their complementary features to determine the experimental conditions where each may be most appropriately used. Diffusion processes were explored as an additional contributor to T1ρ dispersion. Various spherical phantoms of different size and material properties were measured with SL techniques to observe their effects on contrast. Methods were developed to separate the effects of diffusion and chemical exchange. The experiments reported here further elucidate the contributing factors to R1ρ relaxation in a variety of biologically relevant molecules and tissues. Finally, the methods resulting from these experiments are useful for generating novel contrast that is primarily dependent on exchange rates.

With cancer encompassing a range of disease states and phenotypes, assessing treatment efficacy early, accurately, and non-invasively is essential to optimize therapy planning on an individualized basis. This work discusses two types of cancer imaging techniques, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted MRI (DW-MRI), and the importance they have to several classes of drug treatment regimens. Additionally, this work optimizes and identifies errors in current protocols used in preclinical MRI studies of anti-cancer therapies. These optimized protocols were then used to assess the efficacy of a novel anti-cancer treatment early in the course of therapy. Finally, the relationship between two MR imaging biomarkers frequently used in monitoring cancer therapy were assessed and compared to histology.

The goal of this work is to develop and demonstrate a novel model of superparamagnetic iron oxide nanoparticle (SPION) magnetic properties based on physical first principles and experimental mathematical relationships. SPIONs exhibit magnetic properties that differ from the bulk properties of iron oxide due to scale affects unique to nanoparticles. The developed model is able to predict the magnetic properties of any type of SPION at a given temperature and applied field strength based solely on the particle size. By predicting SPION magnetization and induced magnetic field, the model is a useful engineering tool for nanomaterials design. Using the model, it is possible to predict the magnetic behavior of even complex SPION based nanomaterials, facilitating materials design rather than pure discovery using costly high throughput methods. Using this model, we have investigated the magnetic properties of a clustered system of SPIONs to potentially be used as a magnetic detection device and image contrast agent. Using the model, it is possible to predict the ideal particle size for these particular nanomaterials by optimizing key magnetic parameters with regards to a specific application.

The correlation between changes in mechanical properties and the onset of disease has led to an increased interest in assessing the elastic modulus of soft tissues as a biomarker for disease progression. In addition, soft tissue mechanical properties are desired for biomechanical modeling for surgical procedure planning and intraoperative guidance. Unfortunately, soft tissue modulus evaluation has proven inherently difficult due to tissue consistency and shape, and the approaches are highly variant. The work presented in this thesis focuses on the development, application, and interrogation of a novel soft tissue mechanical property evaluation technique, termed the Model-Gel-Tissue (MGT) assay, which utilizes a combination of a gel embedding process, direct mechanical testing, and computational modeling to analyze the elastic properties of a soft tissue sample. The goal was to develop a repeatable and adaptable evaluation technique that also allowed for irregularly shaped specimens and standardization of the implementation. This was accomplished by a rapid-embedding of the tissue in a gel with surfaces of known and uniform shape. The mechanical testing output is then utilized in a finite element model of the system developed from computed tomography (CT) scans of the specimen, in order to evaluate the mechanical properties of the embedded tissue. Preliminary testing of the MGT assay was implemented using fibrotic murine livers to assess the capability of the technique relative to traditional indentation testing. The assay was then used to investigate the correlation between microstructural collagen content and macroscopic tissue modulus in a murine model of breast cancer. Subsequently, the assay was used to investigate the propensity of modulus as an indicator of treatment resistance in a second murine model of breast cancer. Finally, extensive sensitivity tests were performed to qualify the fidelity of the system. The results of this work show that modulus assessment via the MGT assay correlates to traditional testing, as well as to tissue collagen content, and the concatenation of the work indicates that the MGT assay serves as a reliable and adaptable soft tissue modulus evaluation system.

This study demonstrated the relationship between brain connectivity and childrens reading abilities. For the behavioral part, the participants received proper reading interventions based on their responsiveness, and the standardized behavioral tests were administered throughout the process. For the imaging part, both T1-weighted images and diffusion weighted images were acquired. Nine cortical regions in each brain hemisphere were identified as regions of interest (ROI). The probabilistic streamlines connecting each pairing of the nine regions were calculated and used to estimate brain connectivity. The estimates were then used to correlate with childrens reading measures. Eight significant correlations were found, four of which were connections between the insular cortex and angular gyrus. The results are suggestive of a key role of connection between insular cortex and angular gyrus in mediating reading behavior. In spite of the limited sample size, the redundancy in the spread of group clusters is indicative of a relation between brain connectivity and childrens responsiveness to intervention.

The use of 18FDG-PET imaging to predict treatment response to IGF-1R/IR targeted therapy in mouse models of human lung cancer is presented in this thesis. In vitro cell studies were first conducted to establish sensitivity to treatment with OSI-906 and changes in glucose metabolism in responding cells. In vivo xenograft studies demonstrated that reduced 18FDG-PET correlated with PI3K pathway inhibition and was able to predict tumor response to OSI-906 prior to changes in tumor volume could be ascertained. The in vivo imaging results were validated with molecular correlates. Based upon these results 18FDG-PET imaging appears to serve as a rapid non-invasive marker of IGF-1R/IR inhibition and should be explored clinically as a predictive clinical biomarker in patients undergoing IGF-1R/IR-directed cancer therapy.

Both angiogenesis and inflammation are inescapable in vivo responses to any type of biomaterials implanted for regeneration. Continuous progress has been made in biomaterial design to facilitate tissue interactions with an implant by reducing inflammation and/or by inducing angiogenesis. However, it becomes increasingly clear that the physiological processes of angiogenesis and inflammation are interconnected through various molecular mechanisms. The role of implant-induced inflammation in the formation of new blood vessels into tissue surrounding the implant remains unclear. Therefore, we used a polyethylene glycol (PEG) cross-linked tyrosine derived polycarbonate hydrogel system as a model of implantable biomaterials. As opposed to the degradation rate, modulus and protein adsorption decreased as the cross-linking degree increased, due to hydrophilic repellent properties of PEG, indicating the unique and tunable hydrogel properties. The hydrogels were hybridized with pro- or anti-angiogenic (or inflammatory) peptides using collagen or fibrin gel and used for in vitro and in vivo biological studies. The results show a clear interconnectivity between angiogenic and inflammatory activities, indicating an inflammatory mechanism regulating follow-up angiogenic processes in hydrogels. This study suggests a new concept of biomaterial design that utilizes flexible inflammatory parameters to control angiogenesis for the eventual success of biomaterial implants.

Polymer properties can be altered by copolymerizing subunits with specific physicochemical characteristics. Vascular stent materials require biocompatibility, mechanical strength, and prevention of restenosis. Here we copolymerized poly(ε-caprolactone) (PCL), poly(ethylene glycol) (PEG), and carboxyl-PCL (cPCL) at varying molar ratios and characterized the resulting effects on physicochemical and mechanical properties. We then evaluated these polymers for their applicability as coronary stent materials using two primary human coronary artery cell types: smooth muscle cells (HCASMCs) and endothelial cells (HCAECs). Changes of their proliferation and phenotype were dependent upon intracellular reactive oxygen species (ROS) levels, and 4%PEG-96%PCL was identified as the most appropriate material for this application. On this substrate, HCASMCs maintained a contractile phenotype identified by arrested proliferation, moderate oxidative activity, up-regulated expression of smooth muscle myosin heavy chain (smMHC), and healthy spindle morphology. HCAECs on 4%PEG-96%PCL maintained a physiologically-relevant proliferation rate and a balanced redox state. Other test substrates promoted a pathological, synthetic phenotype in HCASMCs and/or hyperproliferation in HCAECs. The cellular responses related to the phenotypic change were modulated by Youngs modulus and surface charge of test substrates, indicating a structure-function relationship that can be exploited for intricate control over vascular cell functions.

The recent development of low-intensity, pulsed infrared light for neural activation has provided a new nerve stimulation modality that avoids the limitations of traditional electrical methods such as the necessity of contact, presence of a stimulation artifact and poor spatial precision. Infrared neural stimulation is, however, limited by a 2:1 ratio of damaging radiant exposures to stimulation threshold radiant exposures. For infrared neural stimulation to become more applicable and eventually suitable for implantation, the range of safe and effective radiant exposures as indicated by this ratio must be increased. In this study, we have shown that this ratio is increased to as much as 7:1 by combining the infrared pulse with a subthreshold depolarizing electrical stimulus. Our results indicate a nonlinear relationship between the subthreshold depolarizing electrical stimulus (expressed as percentage of electrical stimulation threshold) and the additional optical energy required to reach stimulation threshold (expressed as percentage of optical stimulation threshold). The results also show that the change in optical threshold decreases linearly as the delay between the electrical and optical pulses is increased. The primary benefit of infrared neural stimulation is spatial selectivity and we have shown that precision is maintained for this combined stimulation modality. Our findings are evaluated in the context of latent addition and "superexcitability" according to previously published results. The results of this study are expected to facilitate the development of applications for infrared neural stimulation, as well as target the efforts to uncover the mechanism by which infrared light activates neural tissue.

Achieving micron resolutions in magnetic resonance imaging is constrained first by limitations in available signal strength as voxel sizes decrease, and second, by acceptable acquisition times due to the large data sets required. The latter is problematic due to an increased sensitivity to patient bulk motion and physiological effects, and prevalence of distortion and blurring artifacts caused by susceptibility variation. Signal constraints can be mitigated using ultra-high field strengths, such as 7T, but face field dependent challenges such as increased B1 inhomogeneity and shorter T2* values. Scan times can be minimized using reduced field-of-view (FOV) imaging techniques that localize excitations to smaller regions of an object to achieve diminished imaging dimensions, but have largely been unexplored at 7T. To address this deficiency with the goal of improving human imaging resolutions, this thesis first implements and compares multiple reduced-FOV methods at 7T, assessing relative ability to localize excitation, suppress unwanted signal, minimize artifacts, and constrain power deposition. Inner-Volume Imaging (IVI) and Outer-Volume Suppression (OVS) methods optimized from this comparison are then synergistically combined with rapid parallel and echo planar imaging (EPI) techniques to obtain 160 to 500 μm2 in vivo images throughout the human brain in 3 to 12 minutes, accelerated 160 to 1400 fold for multi-slice and 3D scans, respectively. Compared to full-FOV scans, this approach demonstrates reduced geometric distortion and motion artifacts, with improved visibility of features at the high resolution. The parallel reduced-FOV method is similarly applied for diffusion tensor and cervical spine imaging prone to motion and susceptibility artifacts to obtain 1mm2 DTI images and 300 μm2 in the spine, with localized measurement of diffusion properties. Overall, the reduced-FOV approach provides reduction in scan times, artifact minimization, and achieves resolutions that exceed prior studies.