Imaging Electric Properties Of Biological Tissues By Magnetic Resonance Imaging Measurement

The electric properties (EPs) of biological tissue, i.e., the electric conductivity and permittivity, can provide important information in diagnosis of various diseases. The EPs distribution within human body has been the subject of research for over 30 years since the Electrical Impedance Tomography (EIT) was proposed. This dissertation reviews several important EPs imaging modalities, and provides theoretical and experimental studies on Magnetic Resonance Electrical Impedance Tomography (MREIT), which is popularly pursuit in recent 10 years. Using adaptive neuro-fuzzy inference system (ANFIS), a new ANFIS-MREIT algorithm has been developed, and only one component of the magnetic flux densities was utilized. Simulations were performed on sphere and realistic-geometry models to estimate head tissues conductivity with and without noise contamination, and electrodes excursion was also concerned to evaluate its effectiveness. Promising simulation results suggest the merits of ANFIS-MREIT in estimating the conductivity values of head volume conductor for piece-wise homogeneous head volume-conductor models.The first Magnetic Resonance Current Density Imaging (MRCDI) experiment was carried out in China. The feasibility of MRCDI as the tool of measurements for MREIT has been shown after a phantom experiment with a 1.5T MRI. The relative error of measured current density on a transverse plane was 10.62%, while noise induced by electronics and phantom rotation was observed to be the main cause of errors. Several effective ways to improve CDI result have been proposed according to the error analysis.Based on the measurement of the active transverse magnetic component of the applied RF field (known as B1-mapping), Magnetic Resonance Electric Properties Tomography (MREPT) has been newly developed to image EPs distributions within biological tissues. MREPT can be performed on a standard MRI system using a regular volume coil, and it differs from other noninvasive imaging techniques in that no electrode mounting is required and no external energy is introduced into the body during MRI scanning. MREPT can also help with specific absorption rate (SAR) calculation which is a major concern in high-field Magnetic Resonance Imaging (MRI) as well as in non-medical areas like wireless-telecommunications. We have proposed a novel MREPT algorithm, Dual-excitation algorithm, which uses two sets of measured B1 data, to noninvasively reconstruct the biological tissue's electric properties. The Finite Element Method (FEM) has been utilized in three-dimensional (3D) modeling and B1 field calculation. A series of computer simulations were conducted to evaluate the feasibility and performance of the proposed method on a 3D head model within a birdcage coil and a transverse electromagnetic (TEM) coil. Compared with other B1-mapping based reconstruction algorithms, our approach provides superior performance without the need for iterative computations. The present simulation results indicate good reconstruction of electric properties from B1 mapping.