Although defibrillation has been in clinical use for more than 50 years, the complete current flow distribution inside the body during a defibrillation procedure has never been directly measured. This is due to the lack of appropriate imaging technology to noninvasively monitor the current flow inside the body. The current density imaging (CDI) technique, using a magnetic resonance (MR) imager, provides a new approach to this problem [Scott et al. (1991)]. CDI measures the local magnetic field generated by the current and calculates the current density by computing its curl. In this study, CDI was used to measure current density at all points within a postmortem pig torso during an electrical current application through defibrillation electrodes. Furthermore, current flow information was visualized along the chest wall and within the chest cavity using streamline analysis. As expected, some of the highest current densities were observed in the chest wall. However, current density distribution varied significantly from one region to another, possibly reflecting underlying heterogeneous tissue conductivity and anisotropy. Moreover, the current flow analysis revealed many complex and unexpected current flow patterns that have never been observed before. This study has, for the first time, noninvasively measured the volume current measurement inside the pig torso.

Abstract-The origin of electrical burns under gel-type surface electrodes is a controversial topic that is not well understood. To investigate the phenomenon, we have developed an excised porcine skin-gel model, and used low-frequency current density imaging (LFCDI) to determine the current density (CD) distribution through the skin before and after burns were induced by application of electrical current (200 Hz, 70% duty cycle, 20-35 mA monophasic square waveform applied to the electrodes for 30-135 min). The regions of increased CD correlate well with the gross morphological changes (burns) observed. The measurement is sensitive enough to show regions of high current densities in the pre-burn skin, that correlate with areas were burn welts were produced, thus predicting areas where burns are likely to occur. Statistics performed on 28 skin patches revealed a charge dependency of the burn areas and a relatively uniform distribution. The results do not support a thermal origin of the burns but rather electro-chemical mechanisms. We found a statistically significant difference between burn area coverage during anodic and cathodic experiments.

We present a quantitative validation study to assess the accuracy of low-frequency conductivity imaging methods, based on a testing current measured using Current Density Imaging (CDI). We tested the proposed procedure to study the influence of tissue anisotropy on the accuracy of conductivity reconstruction methods, using a finite element model of anisotropic brain tissue. Simulations were carried out for three different levels of tissue anisotropy to compare the results obtained by our recently developed anisotropic conductivity method with those obtained by our well-established conductivity method that assumes isotropic conductivity. The validation results clearly show that the conductivity imaging method which takes into account tissue anisotropy yields significantly superior accuracy.

This paper presents the first experiment of imaging anisotropic impedance using a novel technique called Diffusion Tensor Current Density Impedance Imaging (DTCD-II). A biological anisotropic tissue phantom was constructed and an experimental implementation of the new method was performed. The results show that DT-CD-II is an effective way of non-invasively measuring anisotropic conductivity in biological media. The cross-property factor between the diffusion tensor and the conductivity tensor has been carefully determined from the experimental data, and shown to be spatially inhomogeneous. The results show that this novel imaging approach has the potential to provide valuable new information on tissue properties.

Radio frequency current density imaging (RF-CDI) is an imaging technique that measures current density distribution at the Larmor frequency utilizing magnetic resonance imaging (MRI). The multi-slice RF-CDI sequence has extended the ability of RF-CDI to image multiple slices and thus has enhanced its capacity for biomedical applications. In this paper, the influence of MRI random noise on the sensitivity of multi-slice RF-CDI measurement is studied. The formula of current noise is derived, which is verified by both simulation and phantom experiments. A 3-D finite-difference time-domain (FDTD) model is employed to compute the electromagnetic fields in the simulation. T. P. DeMonte is with Field