Electrical spectral imaging using magnetic resonance methods

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The low-frequency electrical properties of biological tissue provide sensitive and valuable indications of cell density, membrane properties, electrolyte concentrations and mobilities and the presence or absence of disease, particularly at frequencies between 1 kHz and 1 MHz. Measurements of variations in these properties between these frequencies provide a unique view of tissue state. Imaging of electrical properties, combined with electrical spectroscopy, would allow subtle examination of both spatial and time-dependent tissue characteristics that are important in the diagnosis and therapy of brain cancers. Unfortunately, relatively few reports of tissue electrical properties are in this frequency range, because they involve invasive and often error-prone procedures. Several Magnetic Resonance Imaging (MRI)-based, non-invasive methods of imaging electrical property distributions have recently been developed. However, these methods can only be used at high frequencies (>100 MHz) or very low frequencies (<100 Hz). For example, the technique of Diffusion Tensor Magnetic Resonance Electrical Impedance Tomography (DT-MREIT) combines MR diffusion tensor and MR phase images to produce reconstruction of full anisotropic conductivity tensor images at very low frequencies. However, present DT-MREIT techniques are restricted to measurement frequencies of around 10 Hz. We now propose transforming MREIT methods to capture spectral effects over the frequency range from 10 Hz to 500 kHz. The new technique, multifrequency MREIT (MF-MREIT) will be validated using computational models, cell and tissue phantoms and in-vivo using a rat model of brain cancer. The specific focus of the project will be measuring and characterizing low-frequency electrical properties of cancer cell cultures and tumors grown from these cells in rat brains. It is anticipated that these measurements will lead to better understanding of tumor properties and aid in planning new electrical therapies that are increasingly being used to successfully treat brain tumors. The technique will have further application in diverse areas, including characterization of tissue responses to tumor treating fields, irreversible electroporation therapy, and measurement of tissue properties for construction of accurate computational models used in planning neuromodulation treatments.