Magnetic Resonance Imaging has become an increasingly reliable source of medical imaging to obtain high quality detailed images of the human anatomy. Application specific coil or an array of coils when placed closely to the anatomy produces high quality image due to the improved spatial signal to noise ratio. Elastic RF coils have been shown to conform to the shape of the patient’s body and drastically reduce the gap between coil and anatomy. First, a major challenge faced by these elastic RF coils is the changing impedance condition as the coil takes a different shape for every individual. Next, an area that could benefit from the improved image quality and patient comfort that comes from flexible RF coil design is endorectal prostate imaging. Demonstrated in the first part of this dissertation is a modular solution to compensate the impedance mismatch. Standalone Wireless Impedance Matching (SWIM) system is an automatic impedance mismatch compensation system that can function independently of the MR scanner. The matching network consists of a capacitor array with RF switches to electronically cycle through different input impedance conditions. The SWIM system can automatically calibrate an RF coil in 3s with a reflection coefficient of less than -15dB resulting in improved Signal-to-noise ratio (SNR) of the sample image by 12% - 24%, based on sample size, when compared to a loaded coil without retuning. For the second part, we propose a novel elastic and inflatable RF coil integrated with the SWIM system for endorectal prostate imaging at 9.4T. A silicone polymer substrate filled with liquid metal alloy is designed and fabricated with a cavity to create ii inflation. This inflatable RF coil is combined with the SWIM system to automatically tune and match after inflating the RF coil for individual levels of inflation. The imaging results have shown a ~10%, ~19%, and ~25 % increase in SNR due to inflation of RF coil at different ROIs in the acquired image. Overall, the methods proposed and discussed in this thesis are a step towards a new generation of RF coil systems for both existing applications and upcoming ones.

Electromagnetic fields (EMFs) generated by biologically active neural tissue are critical in the diagnosis and treatment of neurological diseases. Biological EMFs are characterized by electromagnetic properties such as electrical conductivity, permittivity and magnetic susceptibility. The electrical conductivity of active tissue has been shown to serve as a biomarker for the direct detection of neural activity, and the diagnosis, staging and prognosis of disease states such as cancer. Magnetic resonance electrical impedance tomography (MREIT) was developed to map the cross-sectional conductivity distribution of electrically conductive objects using externally applied electrical currents. Simulation and in vitro studies of invertebrate neural tissue complexes demonstrated the correlation of membrane conductivity variations with neural activation levels using the MREIT technique, therefore laying the foundation for functional MREIT (fMREIT) to detect neural activity, and future in vivo fMREIT studies.



The development of fMREIT for the direct detection of neural activity using conductivity contrast in in vivo settings has been the focus of the research work presented here. An in vivo animal model was developed to detect neural activity initiated changes in neuronal membrane conductivities under external electrical current stimulation. Neural activity was induced in somatosensory areas I (SAI) and II (SAII) by applying electrical currents between the second and fourth digits of the rodent forepaw. The in vivo animal model involved the use of forepaw stimulation to evoke somatosensory neural activations along with hippocampal fMREIT imaging currents contemporaneously applied under magnetic field strengths of 7 Tesla. Three distinct types of fMREIT current waveforms were applied as imaging currents under two inhalants – air and carbogen. Active regions in the somatosensory cortex showed significant apparent conductivity changes as variations in fMREIT phase (φ_d and ∇^2 φ_d) signals represented by fMREIT activation maps (F-tests, p <0.05). Consistent changes in the standard deviation of φ_d and ∇^2 φ_d in cortical voxels contralateral to forepaw stimulation were observed across imaging sessions. These preliminary findings show that fMREIT may have the potential to detect conductivity changes correlated with neural activity.

Transcranial electrical stimulation (tES) is a non-invasive brain stimulation therapy that has shown potential in improving motor, physiological and cognitive functions in healthy and diseased population. Typical tES procedures involve application of weak current (< 2 mA) to the brain via a pair of large electrodes placed on the scalp. While the therapeutic benefits of tES are promising, the efficacy of tES treatments is limited by the knowledge of how current travels in the brain. It has been assumed that the current density and electric fields are the largest, and thus have the most effect, in brain structures nearby the electrodes. Recent studies using finite element modeling (FEM) have suggested that current patterns in the brain are diffuse and not concentrated in any particular brain structure. Although current flow modeling is useful means of informing tES target optimization, few studies have validated tES FEM models against experimental measurements. MREIT-CDI can be used to recover magnetic flux density caused by current flow in a conducting object. This dissertation reports the first comparisons between experimental data from in-vivo human MREIT-CDI during tES and results from tES FEM using head models derived from the same subjects. First, tES FEM pipelines were verified by confirming FEM predictions agreed with analytic results at the mesh sizes used and that a sufficiently large head extent was modeled to approximate results on human subjects. Second, models were used to predict magnetic flux density, and predicted and MREIT-CDI results were compared to validate and refine modeling outcomes. Finally, models were used to investigate inter-subject variability and biological side effects reported by tES subjects. The study demonstrated good agreements in patterns between magnetic flux distributions from experimental and simulation data. However, the discrepancy in scales between simulation and experimental data suggested that tissue conductivities typically used in tES FEM might be incorrect, and thus performing in-vivo conductivity measurements in humans is desirable. Overall, in-vivo MREIT-CDI in human heads has been established as a validation tool for tES predictions and to study the underlying mechanisms of tES therapies.

A tumor is a heterogeneous combination of proliferating tumor cells, infiltrating immune cells and stromal components along with a variety of associated host tissue cells, collectively termed the tumor microenvironment (TME). The constituents of the TME and their interaction with the host organ shape and define the properties of tumors and contribute towards the acquisition of hallmark traits such as hypoxia. Hypoxia imparts resistance to cancer from chemotherapy and radiotherapy due to the decreased production of reactive oxygen species and also promotes angiogenesis, malignant progression and metastasis. It also provides a powerful physiological stimulus that can be exploited as a tumor-specific condition, allowing for the rational design of anticancer hypoxia-activated pro-drugs (HAP). Accurate evaluation of tumor oxygenation in response to therapeutics interventions at various stages of growth should provide a better understanding of tumor response to therapy, potentially allowing therapy to be tailored to individual characteristics. The primary goal of this research was to investigate the utility of prospective identification of hypoxic tumors, by two different Magnetic Resonance Imaging (MRI) based oximetry approaches, in successful treatment with hypoxia activated therapy. In the present study, I report the utility of these two techniques 1) PISTOL (Proton Imaging of Siloxanes to map Tissue Oxygenation Levels) and 2) use of a hypoxia binding T1 contrast agent GdDO3NI in reporting the modulations of hypoxia pre and post hypoxia activated therapies in pre-clinical models of cancer. I have performed these studies in non-small cell lung cancer (NSCLC) and epidermoid carcinoma (NCI-H1975 and A431 cell lines, respectively) as well as in patient derived xenograft models of NSCLC. Both the oximetry techniques have the potential to differentiate between normoxic and hypoxic regions of the tumor and reveal both baseline heterogeneity and differential response to therapeutic intervention. The response of the tumor models to therapeutic interventions indicates that, in conjunction with pO2, other factors such as tumor perfusion (essential for delivering HAPs) and relative expression of nitroreductases (essential for activating HAPs) may play an important role. The long term goal of the proposed research is the clinical translation of both the MRI techniques and aiding the design and development of personalized therapy (e.g. patient stratification for novel hypoxia activated pro-drugs) particularly for cancer.

Among electrical properties of living tissues, the differentiation of tissues or organs provided by electrical conductivity is superior. The pathological condition of living tissues is inferred from the spatial distribution of conductivity. Magnetic Resonance Electrical Impedance Tomography (MREIT) is a relatively new non-invasive conductivity imaging technique. The majority of conductivity reconstruction algorithms are suitable for isotropic conductivity distributions. However, tissues such as cardiac muscle and white matter in the brain are highly anisotropic. Until recently, the conductivity distributions of anisotropic samples were solved using isotropic conductivity reconstruction algorithms. First and second spatial derivatives of conductivity (∇σ and ∇2σ ) are integrated to obtain the conductivity distribution. Existing algorithms estimate a scalar conductivity instead of a tensor in anisotropic samples.

Accurate determination of the spatial distribution of a conductivity tensor in an anisotropic sample necessitates the development of anisotropic conductivity tensor image reconstruction techniques. Therefore, experimental studies investigating the effect of ∇2σ on degree of anisotropy is necessary. The purpose of the thesis is to compare the influence of ∇2σ on the degree of anisotropy under two different orthogonal current injection pairs.

The anisotropic property of tissues such as white matter is investigated by constructing stable TX-151 gel layer phantoms with varying degrees of anisotropy. MREIT and Diffusion Magnetic Resonance Imaging (DWI) experiments were conducted to probe the conductivity and diffusion properties of phantoms. MREIT involved current injection synchronized to a spin-echo pulse sequence. Similarities and differences in the divergence of the vector field of ∇σ (∇2σ) among anisotropic samples subjected to two different current injection pairs were studied. DWI of anisotropic phantoms involved the application of diffusion-weighted magnetic field gradients with a spin-echo pulse sequence. Eigenvalues and eigenvectors of diffusion tensors were compared to characterize diffusion properties of anisotropic phantoms.

The orientation of current injection electrode pair and degree of anisotropy influence the spatial distribution of ∇2σ. Anisotropy in conductivity is preserved in ∇2σ subjected to non-symmetric electric fields. Non-symmetry in electric field is observed in current injections parallel and perpendicular to the orientation of gel layers. The principal eigenvalue and eigenvector in the phantom with maximum anisotropy display diffusion anisotropy.