Magnetic resonance electrical impedance tomography (MREIT) is a recently developed imaging technique that combines MRI and electrical impedance tomography (EIT). In MREIT, crosssectional electrical conductivity images are reconstructed from the internal magnetic field density data produced inside an electrically conducting object when an electrical current is injected into the object. In this work we present the results of electrical conductivity imaging experiments, and performance evaluations of MREIT in terms of noise characteristics and spatial resolution. The MREIT experiment was performed with a 3.0 Tesla MRI system on a phantom with an inhomogeneous conductivity distribution. We reconstructed the conductivity images in a 128 ؋ 128 matrix format by applying the harmonic B z algorithm to the z-component of the internal magnetic field density data. Since the harmonic B z algorithm uses only a single component of the internal magnetic field data, it was not necessary to rotate the object in the MRI scan. The root mean squared (RMS) errors of the reconstructed images were between 11% and 35% when the injection current was 24 mA. Information about electrical conductivity distribution inside biological tissues is useful for many purposes, such as modeling tissues to investigate action potential propagations, estimating therapeutic current distribution during electrical stimulation, and monitoring physiological functions (1-3). In combinatory studies of functional MRI (fMRI) with other brain mapping modalities, such as EEG and MEG brain mapping, information about conductivity distribution inside the brain is essential for the precise localization of activated regions (4,6). Electrical impedance tomography (EIT) is a conductivity imaging modality in which many surface electrodes are attached to an object to measure the electric potentials produced by injection currents. However, EIT has many drawbacks, including a limited amount of measured data, low sensitivity of the surface voltage to conductivity changes at the region far from the electrodes, and the ill-posedness of the corresponding inverse problem involved in image reconstruction. Recently, a combination of MRI and EIT (MREIT) was introduced as a new conductivity imaging modality (7-9). With MREIT, one can transform the ill-posed conductivity image reconstruction problem into a well-posed one by incorporating the internal data of magnetic flux density distributions measured by an MRI scanner. In previous MREIT experimental studies (10 -12), the biggest problems were object rotations inside the magnet to acquire the three components of the internal magnetic field data, and low SNR of reconstructed images. However, new MREIT reconstruction algorithms were recently introduced, along with phantom imaging results obtained without any object rotations (13)(14)(15).In this work we present some results of MREIT phantom imaging experiments performed with the harmonic B z algorithm and a 3.0 Tesla MRI system. After briefly introducing the fundamental principle of the...

Magnetic resonance electrical impedance tomography (MREIT) is a recently developed imaging technique that combines MRI and electrical impedance tomography (EIT). In MREIT, crosssectional electrical conductivity images are reconstructed from the internal magnetic field density data produced inside an electrically conducting subject when an electrical current is injected into the subject. In this work the results of an electrical conductivity imaging experiment are presented, along with some practical considerations regarding MREIT. The MREIT experiment was performed with a 0.3 Tesla MRI system on a phantom made of two compartments with different electrical conductivities. The current density inside the phantom was measured by the MR current density imaging (MRCDI) technique. The measured current density was then used for conductivity image reconstruction by the J-substitution algorithm. Information about electrical conductivity distribution inside biological tissues is useful for many purposes, such as locating the source of ECG and EEG signals, estimating therapeutic current distribution during electrical therapy, and monitoring physiological functions (1-3). Electrical impedance tomography (EIT) is a conductivity imaging modality in which many surface electrodes are attached to the subject to measure electric potentials produced by injection currents. The measured voltage data are used to reconstruct cross-sectional images of conductivity distributions. However, EIT has many drawbacks, including a limited amount of measured data, low sensitivity of the surface voltage to conductivity changes at the region far from the electrodes, and the ill-posedness of the corresponding inverse problem involved in image reconstruction. Most reconstruction algorithms in EIT produce conductivity images that have much poorer spatial resolution and accuracy in comparison with other medical imaging modalities. Recently, a combination of MRI and EIT (MREIT) was introduced as a new conductivity imaging modality (4 -9). Since MREIT utilizes high-spatial-resolution MR current density imaging (MRCDI) data, it does not suffer from the same problems as EIT. It has been reported that the MREIT image reconstruction algorithm, the so-called J-substitution algorithm, reconstructs conductivity images in a very stable manner, even with very noisy data (7,8).In this work we present some results of an MREIT phantom imaging experiment, along with some practical considerations. Among the many technical problems that must be solved before MREIT can be of practical use is the noise characteristic, which is a matter of great concern. Since the injection current must be limited to conform with safety guidelines for human imaging, the allowable current density within a human subject is sometimes very low. Therefore, in the current MREIT experiment we introduced certain modifications to account for the noise characteristic of MRCDI. MATERIALS AND METHODS MREIT With the J-Substitution AlgorithmWhen a current I is injected into an electrically conducting ...