Electrical impedance tomography for imaging tissue electroporation

Electroporation is a method to introduce molecules, such as gene constructs or small drugs, into cells by temporarily permeating the cell membrane with electric pulses. In molecular medicine and biotechnology, tissue electroporation is performed with electrodes placed in the target area of the body. Currently, tissue electroporation, as with all other methods of molecular medicine, is performed without real-time control or near-term information regarding the extent and degree of electroporation. This paper expands the work from our previous study by implementing new ex vivo experimental data with "front-tracking" analysis for the image reconstruction algorithm. The experimental data is incorporated into numerical simulations of electroporation procedures and images are generated using the new reconstruction algorithm to demonstrate that electrical impedance tomography (EIT) can produce an image of the electroporated area. Combining EIT with electroporation could become an important biotechnological and medical technique to introduce therapeutic molecules into cells in tissue at predetermined areas of the body.     

Magnetic resonance driven electrical impedance tomography: a simulation study

Magnetic resonance electrical impedance tomography (MREIT) is a method for reconstructing a three-dimensional image of the conductivity distribution in a target volume using magnetic resonance (MR). In MREIT, currents are applied to the volume through surface electrodes and their effects on the MR induced magnetic fields are analyzed to produce the conductance image. However, current injection through surface electrodes poses technical problems such as the limitation on the safely applicable currents. In this paper, we present a new method called magnetic resonance driven electrical impedance tomography (MRDEIT), where the magnetic resonance in each voxel is used as the applied magnetic field source, and the resultant electromagnetic field is measured through surface electrodes or radio-frequency (RF) detectors placed near the surface. Because the applied magnetic field is at the RF frequency and eddy currents are the integral components in the method, a vector wave equation for the electric field is used as the basis of the analysis instead of a quasi-static approximation. Using computer simulations, it is shown that complex permittivity images can be reconstructed using MRDEIT, but that improvements in signal detection are necessary for detecting moderate complex permittivity changes.     

A feasibility study for electrical impedance tomography as a means to monitor tissue electroporation for molecular medicine

Molecular medicine involves the introduction of macromolecules, such as drugs or gene constructs, into specific cells of the body. Electroporation, which uses electric pulses to permeate cell membranes, is a method for achieving this. However, as with other molecular medicine procedures, it lacks a real-time mechanism to detect and control which cells have been affected. We propose and demonstrate, via computer simulation, that electrical impedance tomography has the potential for detecting and imaging electroporation of cells in tissue in real-time, thereby providing feedback for controlling electroporation.     

Magnetic resonance electrical impedance tomography (MREIT): simulation study of J-substitution algorithm

We developed a new image reconstruction algorithm for magnetic resonance electrical impedance tomography (MREIT). MREIT is a new EIT imaging technique integrated into magnetic resonance imaging (MRI) system. Based on the assumption that internal current density distribution is obtained using magnetic resonance imaging (MRI) technique, the new image reconstruction algorithm called J-substitution algorithm produces cross-sectional static images of resistivity (or conductivity) distributions. Computer simulations show that the spatial resolution of resistivity image is comparable to that of MRI. MREIT provides accurate high-resolution cross-sectional resistivity images making resistivity values of various human tissues available for many biomedical applications.     

Cryosurgical monitoring using bioimpedance measurements--a feasibility study for electrical impedance tomography

The effectiveness of cryosurgery in treating tumors is highly dependent on knowledge of freezing extent, and therefore relies heavily on real-time imaging techniques for monitoring. Electrical impedance tomography (EIT), which utilizes tissue impedance variation to construct an image, is very well suited to cryosurgery since frozen tissue impedance is much higher than that of unfrozen tissue. In this study, we explore cryosurgical monitoring as a previously uninvestigated application for EIT. The feasibility of bio-impedance measurements to detect ice front propagation is demonstrated by freezing planar tissue samples one-dimensionally while measuring impedance along a linear array. The experimental results compare favorably to a simple finite element model designed to provide an electrical field visualization tool.     

Noninvasive imaging of bioimpedance distribution by means of current reconstruction magnetic resonance electrical impedance tomography

We have developed a novel magnetic resonance electrical impedance tomography (MREIT) algorithm-current reconstruction MREIT algorithm-for noninvasive imaging of electrical impedance distribution of a biological system using only one component of magnetic flux density. The newly proposed algorithm uses the inverse of Biot-Savart Law to reconstruct the current density distribution, and then, uses a modified J-substitution algorithm to reconstruct the conductivity image. A series of computer simulations has been conducted to evaluate the performance of the proposed current reconstruction MREIT algorithm with simulation settings for breast cancer imaging applications, with consideration of measurement noise, current injection strength, size of simulated tumors, spatial resolution, and position dependency. The present simulation results are highly promising, demonstrating the high spatial resolution, high accuracy in conductivity reconstruction, and robustness against noise of the proposed algorithm for imaging electrical impedance of a biological system. The present MREIT method may have potential applications to breast cancer imaging and imaging of other organs.     

Ramp-preserving denoising for conductivity image reconstruction in magnetic resonance electrical impedance tomography

In magnetic resonance electrical impedance tomography, among several conductivity image reconstruction algorithms, the harmonic B(z) algorithm has been successfully applied to B(z) data from phantoms and animals. The algorithm is, however, sensitive to measurement noise in B(z) data. Especially, in in vivo animal and human experiments where injection current amplitudes are limited within a few milliampere at most, measured B(z) data tend to have a low SNR. In addition, magnetic resonance (MR) signal void in outer layers of bones and gas-filled organs, for example, produces salt-pepper noise in the MR phase and, consequently, B(z) images. The B(z) images typically present areas of sloped transitions, which can be assimilated to ramps. Conductivity contrasts change ramp slopes in B(z) images and it is critical to preserve positions of those ramps to correctly recover edges in conductivity images. In this paper, we propose a ramp-preserving denoising method utilizing a structure tensor. Using an eigenvalue analysis, we identified local regions of salt-pepper noise. Outside the identified local regions, we applied an anisotropic smoothing to reduce noise while preserving their ramp structures. Inside the local regions of salt-pepper noise, we used an isotropic smoothing. After validating the proposed denoising method through numerical simulations, we applied it to in vivo animal imaging experiments. Both numerical simulation and experimental results show significant improvements in the quality of reconstructed conductivity images.     

Harmonic decomposition in PDE-based denoising technique for magnetic resonance electrical impedance tomography

Recent progress in magnetic resonance electrical impedance tomography (MREIT) research via simulation and biological tissue phantom studies have shown that conductivity images with higher spatial resolution and accuracy are achievable. In order to apply MREIT to human subjects, one of the important remaining problems to be solved is to reduce the amount of the injection current such that it meets the electrical safety regulations. However, by limiting the amount of the injection current according to the safety regulations, the measured MR data such as the z-component of magnetic flux density Bz in MREIT tend to have low SNR and get usually degraded in their accuracy due to the nonideal data acquisition system of an MR scanner. Furthermore, numerical differentiations of the measured Bz required by the conductivity image reconstruction algorithms tend to further deteriorate the quality and accuracy of the reconstructed conductivity images. In this paper, we propose a denoising technique that incorporates a harmonic decomposition. The harmonic decomposition is especially suitable for MREIT due to the physical characteristics of Bz. It effectively removes systematic and random noises, while preserving important key features in the MR measurements, so that improved conductivity images can be obtained. The simulation and experimental results demonstrate that the proposed denoising technique is effective for MREIT, producing significantly improved quality of conductivity images. The denoising technique will be a valuable tool in MREIT to reduce the amount of the injection current when it is combined with an improved MREIT pulse sequence.     

Experimental characterization and numerical modeling of tissue electrical conductivity during pulsed electric fields for irreversible electroporation treatment planning

Irreversible electroporation is a new technique to kill cells in targeted tissue, such as tumors, through a nonthermal mechanism using electric pulses to irrecoverably disrupt the cell membrane. Treatment effects relate to the tissue electric field distribution, which can be predicted with numerical modeling for therapy planning. Pulse effects will change the cell and tissue properties through thermal and electroporation (EP)-based processes. This investigation characterizes these changes by measuring the electrical conductivity and temperature of ex vivo renal porcine tissue within a single pulse and for a 200 pulse protocol. These changes are incorporated into an equivalent circuit model for cells and tissue with a variable EP-based resistance, providing a potential method to estimate conductivity as a function of electric field and pulse length for other tissues. Finally, a numerical model using a human kidney volumetric mesh evaluated how treatment predictions vary when EP- and temperature-based electrical conductivity changes are incorporated. We conclude that significant changes in predicted outcomes will occur when the experimental results are applied to the numerical model, where the direction and degree of change varies with the electric field considered.     

Weighted least-squares criteria for electrical impedance tomography

Methods are developed for the design of electrical impedance tomographic reconstruction algorithms with specified properties. Assuming a starting model with constant conductivity or some other specified background distribution, an algorithm with the following properties is found. (1) The optimum constant for the starting model is determined automatically. (2) The weighted least-squares error between the predicted and measured power dissipation data is as small as possible. (3) The variance of the reconstructed conductivity from the starting model is minimized. (4) Potential distributions with the largest volume integral of gradient squared have the least influence on the reconstructed conductivity, and therefore distributions most likely to be corrupted by contact impedance effects are deemphasized. (5) Cells that dissipate the most power during the current injection tests tend to deviate least from the background value. For a starting model with nonconstant conductivity, the reconstruction algorithm has analogous properties.     

Temperature dependence of tissue impedivity in electrical impedance tomography of cryosurgery

The temperature-dependent impedivity of rat liver, transverse abdominal muscle and full skin was determined in vitro as a function of frequency across the temperature range 5 degrees C to 37 degrees C and from 100 Hz to 10 kHz. This study was motivated by an increasing interest in using electrical impedance tomography (EIT) for imaging of cryosurgery and a lack of applicable data in the hypothermic range. Using a controlled-temperature impedance analyzer, it was found that as the temperature is reduced the resulting increase in tissue impedivity is more pronounced at low frequencies and that the beta dispersion, resulting from cell membrane polarization, shifts to lower frequencies. With these new data a simple case study of EIT of liver cryosurgery was examined, using a finite-element model incorporating the Pennes bio-heat equation, to determine the impact of this behavior on imaging accuracy. Overestimation of the ice-front position was found to occur if the EIT system ignored the effects of the low-temperature zone surrounding the frozen tissue. This error decreases with increasing blood perfusion and with higher measurement frequencies.     

A direct reconstruction algorithm for electrical impedance tomography

A direct (noniterative) reconstruction algorithm for electrical impedance tomography in the two-dimensional (2-D), cross-sectional geometry is reviewed. New results of a reconstruction of a numerically simulated phantom chest are presented. The algorithm is based on the mathematical uniqueness proof by A. I. Nachman [1996] for the 2-D inverse conductivity problem. In this geometry, several of the clinical applications include monitoring heart and lung function, diagnosis of pulmonary embolus, diagnosis of pulmonary edema, monitoring for internal bleeding, and the early detection of breast cancer.     

On optimal current patterns for electrical impedance tomography

We develop a statistical criterion for optimal patterns in planar circular electrical impedance tomography. These patterns minimize the total variance of the estimation for the resistance or conductance matrix. It is shown that trigonometric patterns (Isaacson, 1986), originally derived from the concept of distinguishability, are a special case of our optimal statistical patterns. New optimal random patterns are introduced. Recovering the electrical properties of the measured body is greatly simplified when optimal patterns are used. The Neumann-to-Dirichlet map and the optimal patterns are derived for a homogeneous medium with an arbitrary distribution of the electrodes on the periphery. As a special case, optimal patterns are developed for a practical EIT system with a finite number of electrodes. For a general nonhomogeneous medium, with no a priori restriction, the optimal patterns for the resistance and conductance matrix are the same. However, for a homogeneous medium, the best current pattern is the worst voltage pattern and vice versa. We study the effect of the number and the width of the electrodes on the estimate of resistivity and conductivity in a homogeneous medium. We confirm experimentally that the optimal patterns produce minimum conductivity variance in a homogeneous medium. Our statistical model is able to discriminate between a homogenous agar phantom and one with a 2 mm air hole with error probability (p-value) 1/1000.     

Reconstruction of three-dimensional data for electrical impedance tomography

A two-dimensional reconstruction algorithm based on a modified version of the method of sensitivity regions is used to reconstruct data obtained from a three-dimensional finite element model. By using data obtained from off-drive-plane measurements an improved image of changes in resistivity on the drive plane is obtained.<>     

Optimal experiments in electrical impedance tomography

Electrical impedance tomography (EIT) is a noninvasive imaging technique which aims to image the impedance within a body from electrical measurements made on the surface. The reconstruction of impedance images is a ill-posed problem which is both extremely sensitive to noise and highly computationally intensive. The authors define an experimental measurement in EIT and calculate optimal experiments which maximize the distinguishability between the region to be imaged and a best-estimate conductivity distribution. These optimal experiments can be derived from measurements made on the boundary. The analysis clarifies the properties of different voltage measurement schemes. A reconstruction algorithm based on the use of optimal experiments is derived. It is shown to be many times faster than standard Newton-based reconstruction algorithms, and results from synthetic data indicate that the images that it produces are comparable.     

An image reconstruction algorithm for three-dimensional electrical impedance tomography

Electrical impedance tomography (EIT) has been studied by many authors and in most of this work it has been considered to be a two-dimensional problem. Many groups are now turning their attention to the full three-dimensional case in which the computational demands become much greater. It is interesting to look for ways to reduce this demand and in this paper we describe an implementation of an algorithm that is able to achieve this by precomputing many of the quantities needed in the image reconstruction. The algorithm is based on a method called NOSER introduced some years ago by Cheney et al. [3]. In this paper we have significantly extended the method by introducing a more realistic electrode model into the analysis. We have given explicit formulae for the quantities involved so that the reader can reproduce our results.     

Magnetic field effects in Alq3-based OLEDs investigated by electrical impedance spectroscopy

The effect of an external magnetic field on electrical impedance was measured on tris-(8-hydroxyquinoline) aluminum (Alq₃) based OLEDs at different temperatures. Magnetic field effects (MFEs) were responsible for significant changes on the real and imaginary components of the impedance, and for the intensification of the negative capacitance (NC) effect. The observed MFEs do not present a strong temperature dependence. Simulations via equivalent circuits and numerical solutions of Boltzmann transport equations in a drift-diffusion approximation and employing small sinusoidal signal analysis indicate that such effects are consistent with an enhancement of the carrier mobilities and a quenching of the recombination rates. Such changes lead to reduced resistance and more intense NC effects on the device. The results were interpreted in terms of the currently accepted OMAR models: electron-hole pair model, triplet-polaron reaction mechanism and bipolaron model.     

Measuring lung resistivity using electrical impedance tomography

We propose the use of electrical impedance tomography (EIT) imaging techniques in the measurement of lung resistivity for detection and monitoring of apnea and edema. In EIT, we inject currents into a subject using multiple electrodes and measure boundary voltages to reconstruct a cross-sectional image of internal resistivity distribution. We found that a simplified, therefore fast, version of the impedance imaging method can be used for detection and monitoring of apnea and edema. We have showed the feasibility of this method through computer simulations and human experiments. We speculate that the EIT imaging technique will be more reliable than the current impedance apnea monitoring method, since we are monitoring the change of internal lung resistivity. However, more study is required to verify that this method performs better in the presence of motion artifact than the conventional two-electrode impedance apnea monitoring method. Future work should include experiments which carefully simulate different kinds of motion artifacts.     

Increasing image resolution in electrical impedance tomography

An effective approach to increase the image resolution in static electrical impedance tomography is proposed, in which the image with local high resolution is reconstructed by fine meshing only the impedance abnormal element in the finite element model based on a genetic algorithm. Experimental results from a laboratory phantom are presented     

Using compound electrodes in electrical impedance tomography

A compound electrode composed of a large outer electrode to inject current and a small inner electrode to sense voltage was developed and used to measure voltages from a physical phantom. The measured voltages were smaller in amplitude than those from conventional electrodes, demonstrating that the compound electrode can minimize contact impedance voltage drop from the measured data. A finite-element model was used for the compound electrode and incorporated into the regularized Newton-Raphson reconstruction algorithm. A sensitivity study showed that the reconstructed resistivity distributions are less dependent on the unknown contact resistance values for a compound electrode than a conventional electrode and that the use of a compound electrode results in improved images for the reconstruction algorithm