ACT5 Electrical Impedance Tomography System.

OBJECTIVE: This article introduces the Adaptive Current Tomograph 5 (ACT5) Electrical Impedance Tomography (EIT) system. ACT5 is a 32 electrode applied-current multiple-source EIT system that can display real-time images of conductivity and susceptivity at 27 frames per second. The adaptive current sources in ACT5 can apply fully programmable current patterns with frequencies varying from 5 kHz to 500 kHz. The system also displays real-time ECG readings during the EIT imaging process. METHODS: The hardware and software design and specifications are presented, including the current source design, FPGA hardware, safety features, calibration, and shunt impedance measurement. RESULTS: Images of conductivity and susceptivity are presented from ACT5 data collected on tank phantoms and a human subject illustrating the system's ability to provide real-time images of pulsatile perfusion and ECG traces. SIGNIFICANCE: The portability, high signal-to-noise ratio, and flexibility of applied currents over a wide range of frequencies enable this instrument to be used to obtain useful human subject data with relative clinical ease.

Uterine bioimpedance combined with artificial intelligence as a means of cancer detection.

This study hypothesised that benign and tumour-bearing uterine tissue could be differentiated by their unique electrical bioimpedance patterns, with the aid of artificial intelligence. Twenty whole, ex-vivo uterine specimens were obtained at the time of hysterectomy. A total of 11 benign and 9 malignant specimens were studied. A uterine bioimpedance probe was designed to measure the tissue between the endometrial and serosal layers of the uterus. The impedance data was then analysed with multiple instance learning and principal component analysis, forms of artificial intelligence. Final pathology results for the specimens included uterine sarcoma, adenocarcinoma, carcinosarcoma, and high-grade serous carcinoma. The analysis correctly identified 78% (7/9) of the malignant specimens and 82% (9/11) of the benign specimens. The overall accuracy of our analysis was 80%. Our results demonstrate distinction between electrical impedance properties of malignant and benign uterine specimens. Bioimpedance and artificial intelligence may have potential implications in risk assessment of patients and may subsequently guide surgical decision-making regarding route of organ removal.

Efficient Simultaneous Reconstruction of Time-Varying Images and Electrode Contact Impedances in Electrical Impedance Tomography.

OBJECTIVE: In electrical impedance tomography (EIT), we apply patterns of currents on a set of electrodes at the external boundary of an object, measure the resulting potentials at the electrodes, and, given the aggregate dataset, reconstruct the complex conductivity and permittivity within the object. It is possible to maximize sensitivity to internal conductivity changes by simultaneously applying currents and measuring potentials on all electrodes but this approach also maximizes sensitivity to changes in impedance at the interface. METHODS: We have, therefore, developed algorithms to assess contact impedance changes at the interface as well as to efficiently and simultaneously reconstruct internal conductivity/permittivity changes within the body. We use simple linear algebraic manipulations, the generalized singular value decomposition, and a dual-mesh finite-element-based framework to reconstruct images in real time. We are also able to efficiently compute the linearized reconstruction for a wide range of regularization parameters and to compute both the generalized cross-validation parameter as well as the L-curve, objective approaches to determining the optimal regularization parameter, in a similarly efficient manner. RESULTS: Results are shown using data from a normal subject and from a clinical intensive care unit patient, both acquired with the GE GENESIS prototype EIT system, demonstrating significantly reduced boundary artifacts due to electrode drift and motion artifact.

Comparison of impedance measurements near the skin of newborns and adults.

Electrical impedance tomography (EIT) is a non-invasive imaging technology that has been extensively studied for monitoring lung function of neonatal and adult subjects, especially in neonatal intensive care unit (NICU) and intensive care unit (ICU) environments. The sources of the total impedance in these applications include internal organs, near-boundary tissues, electrode-skin impedance, electrodes and conducting wires. This total impedance must be considered for system design and setting voltage gain since it will contribute to the measured voltage. To adapt a single instrument for use on infants and adults, we studied the difference between the impedance near the skin in both classes of patients. We used a simultaneous multi-source EIT (SMS-EIT) system to make impedance measurements. Characteristic resistance was calculated for two different current patterns: one that is more sensitive to boundary region impedance and another that is more sensitive to interior changes. We present ratios of these resistances to assess the relative contribution of near-skin effects to the overall impedance. Twenty adult ICU subjects (10 male, 10 female, age: 49.05 ± 16.32 years (mean ± standard deviation)) and 45 neonates (23 male, 22 female, gestational age: 37.67 ± 2.11 weeks, postnatal age, 2.56 ± 2.67 d) were studied at Columbia University Medical Center. Impedance measurements at 10 kHz were collected for approximately one hour from each subject. The characteristic resistance ratio for each subject was computed and analyzed. The result shows the impedance at or near the skin of newborns is significantly higher than in adult subjects.

Adaptive techniques in electrical impedance tomography reconstruction.

We present an adaptive algorithm for solving the inverse problem in electrical impedance tomography. To strike a balance between the accuracy of the reconstructed images and the computational efficiency of the forward and inverse solvers, we propose to combine an adaptive mesh refinement technique with the adaptive Kaczmarz method. The iterative algorithm adaptively generates the optimal current patterns and a locally-refined mesh given the conductivity estimate and solves for the unknown conductivity distribution with the block Kaczmarz update step. Simulation and experimental results with numerical analysis demonstrate the accuracy and the efficiency of the proposed algorithm.

Real-time 3D electrical impedance imaging for ventilation and perfusion of the lung in lateral decubitus position.

We report a prototype Electrical Impedance Imaging System. It is able to detect the gravity-induced changes in the distributions of perfusion and ventilation in the lung between supine and lateral decubitus positions. Impedance data were collected on healthy volunteer subjects and 3D reconstructed images were produced in real-time, 20 frames per second on site, without using averaging or a contrast agent. Imaging data also can be reconstructed offline for further analysis.

Real-time 3D electrical impedance imaging for ventilation monitoring of the lung: Pilot study.

We report an Electrical Impedance Tomography device capable of detecting gravity-induced regional ventilation changes in real-time without averaging or using a contrast medium. Changes in lung ventilation are demonstrated in right and left lateral decubitus position and compared to those seen in an upright and supine normal subject.

Adaptive Kaczmarz method for image reconstruction in electrical impedance tomography.

We present an adaptive Kaczmarz method for solving the inverse problem in electrical impedance tomography and determining the conductivity distribution inside an object from electrical measurements made on the surface. To best characterize an unknown conductivity distribution and avoid inverting the Jacobian-related term J(T)J which could be expensive in terms of computation cost and memory in large-scale problems, we propose solving the inverse problem by applying the optimal current patterns for distinguishing the actual conductivity from the conductivity estimate between each iteration of the block Kaczmarz algorithm. With a novel subset scheme, the memory-efficient reconstruction algorithm which appropriately combines the optimal current pattern generation with the Kaczmarz method can produce more accurate and stable solutions adaptively as compared to traditional Kaczmarz- and Gauss-Newton-type methods. Choices of initial current pattern estimates are discussed in this paper. Several reconstruction image metrics are used to quantitatively evaluate the performance of the simulation results.

The development of biomedical engineering as experienced by one biomedical engineer.

This personal essay described the development of the field of Biomedical Engineering from its early days, from the perspective of one who lived through that development. It describes the making of a major invention using data that had been rejected by other scientists, the re-discovery of an obscure fact of physiology and its use in developing a major medical instrument, the development of a new medical imaging modality, and the near-death rescue of a research project. The essay concludes with comments about the development and present status of impedance imaging, and recent changes in the evolution of biomedical engineering as a field.

Methods for compensating for variable electrode contact in EIT.

Electrical impedance tomography (EIT) is an imaging modality that currently shows promise for the detection and characterization of breast cancer. A very significant problem in EIT imaging is the proper modeling of the interface between the body and the electrodes. We have found empirically that it is very difficult, in a clinical setting, to assure that all electrodes make satisfactory contact with the body. In addition, we have observed a capacitive effect at the skin/electrode boundary that is spatially heterogeneous. To compensate for these problems, we have developed a hybrid nonlinear-linear reconstruction algorithm using the complete electrode model in which we first estimate electrode surface impedances, by means of a Levenberg-Marquardt iterative optimization procedure with an analytically computed Jacobian matrix. We, subsequently, use a linearized algorithm to perform a 3-D reconstruction of perturbations in both contact impedances, and in the spatial distributions of conductivity and permittivity. Results show that, with this procedure, artifacts due to electrodes making poor contact can be greatly reduced. If the experimental apparatus physically applies voltages and measures currents, we show that it is preferable to compute the reconstruction with respect to the Dirichlet-to-Neumann map rather than the Neumann-to-Dirichlet map if there is a significant possibility that electrodes will be fully disconnected. Finally, we test our electrode compensation algorithms for a set of clinical data, showing that we can significantly improve the fit of our model to the measurements by allowing the electrode surface impedances to vary.

A two-layered forward model of tissue for electrical impedance tomography.

Electrical impedance tomography is being explored as a technique to detect breast cancer, exploiting the differences in admittivity between normal tissue and tumors. In this paper, the geometry is modeled as an infinite half space under a hand-held probe. A forward solution and a reconstruction algorithm for this geometry were developed previously by Mueller et al (1999 IEEE Trans. Biomed. Eng. 46 1379). In this paper, we present a different approach which uses the decomposition of the forward solution into its Fourier components to obtain the forward solution and the reconstructions. The two approaches are compared in terms of the forward solutions and the reconstructions of experimental tank data. We also introduce a two-layered model to incorporate the presence of the skin that surrounds the body area being imaged. We demonstrate an improvement in the reconstruction of a target in a layered medium using this layered model with finite difference simulated data. We then extend the application of our layered model to human subject data and estimate the skin and the tissue admittivities for data collected on the human abdomen using an ultrasound-like hand-held EIT probe. Lastly, we show that for this set of human subject data, the layered model yields an improvement in predicting the measured voltages of around 81% for the lowest temporal frequency (3 kHz) and around 61% for the highest temporal frequency (1 MHz) applied when compared to the homogeneous model.

Regional admittivity spectra with tomosynthesis images for breast cancer detection: preliminary patient study.

It has been known for some time that many tumors have a significantly different conductivity and permittivity from surrounding normal tissue. This high "contrast" in tissue electrical properties, occurring between a few kilohertz and several megahertz, may permit differentiating malignant from benign tissues. Here we show the ability of electrical impedance spectroscopy (EIS) to roughly localize and clearly distinguish cancers from normal tissues and benign lesions. Localization of these lesions is confirmed by simultaneous, in register digital breast tomosynthesis (DBT) mammography or 3-D mammograms.

A versatile high-permittivity phantom for EIT.

Phantoms are frequently used in medical imaging systems to test hardware, reconstruction algorithms, and the interpretation of data. This report describes and characterizes the use of powdered graphite as a means of adding a significant reactive component or permittivity to useful phantom media for electrical impedance imaging. The phantom materials produced have usable complex admittivity at the electrical impedance tomography (EIT) frequencies from a few kilohertz to 1 MHz, as measured by our EIT system (ACT4) and by a commercial bioimpedance analyzer (BIS 4000, Xitron). We have also studied a commercial ultrasound coupling gel, which is highly electrically conductive and semisolid but that permits objects to move within it. The mixture of agar-graphite and gel-graphite, increases in permittivity and conductivity are proportional to the graphite concentration. We also report the use of a porous polymer membrane to simulate skin. A thin layer of this membrane increased resistance and the characteristic frequency of the phantoms, providing a promising candidate to simulate the effect of skin and the layered structure of a breast or other anatomical structure. The graphite also provides a realistic level of "speckle" in ultrasound images of the phantom, which may be useful in developing dual-mode imaging systems with ultrasound and the EIT.

Robust linearized image reconstruction for multifrequency EIT of the breast.

Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.

An analytical layered forward model for breasts in electrical impedance tomography.

Electrical impedance tomography (EIT) can be used to determine the admittivity distribution within the breast from measurements made on its surface. It has been reported that the electrical impedance spectrum of normal breast tissue is significantly different from that of malignant tissue, making EIT a candidate technology for breast cancer detection. The inhomogeneous structure of breasts, with thin low-admittivity skin layers covering the relatively high-admittivity tissue inside, makes the breast imaging problem difficult. In addition, studies show that the electrical properties of skin vary considerably over frequency. This paper proposes a layered forward model which incorporates the presence of skin. Our layered model has three layers, thin low-admittivity top and bottom layers representing skin and a thicker high-admittivity middle layer representing breast tissue. We solve for the forward solution of the layered geometry and compare its behavior with the previously used homogeneous model. Next we develop an iterative method to estimate the skin and breast tissue admittivities from the measured data, and study the robustness and accuracy of the method for various simulated and experimental data. We then look at the reconstruction of a target embedded in a layered body when the homogeneous forward solution is replaced by the layered forward solution. Lastly, we demonstrate the improvement that the layered forward model produces over the homogeneous model when working with clinical data.

An Algorithm for Applying Multiple Currents Using Voltage Sources in Electrical Impedance Tomography.

A method to produce a desired current pattern in a multiple-source EIT system using voltage sources is presented. Application of current patterns to a body is known to be superior to the application of voltage patterns in terms of high spatial frequency noise suppression, resulting in high accuracy in conductivity and permittivity images. Since current sources are difficult and expensive to build, the use of voltage sources to apply the current pattern is desirable. An iterative algorithm presented in this paper generates the necessary voltage pattern that will produce the desired current pattern. The convergence of the algorithm is shown under the condition that the estimation error of the linear mapping matrix from voltage to current is small. Simulation results are presented to illustrate the convergence of the output current.

The complete electrode model for imaging and electrode contact compensation in electrical impedance tomography.

Electrical Impedance Tomography (EIT) is an imaging modality which currently shows promise for the detection and characterization of breast cancer. A very significant problem in EIT imaging is the proper modeling of the interface between the body and the electrodes. We have found empirically that it is very difficult, in a clinical setting, to assure that all electrodes make satisfactory contact with the body. In addition, we have observed a capacitive effect at skin/electrode boundary that is spatially heterogeneous. To compensate for these problems, we have developed a hybrid nonlinear-linear reconstruction algorithm in which we first estimate electrode surface impedances, using a Newton-type iterative optimization procedure with an analytically computed Jacobian matrix. We subsequently make use of a linearized algorithm to perform a three-dimensional reconstruction of perturbations in both contact impedances and in the spatial distributions of conductivity and permittivity. Results show that, using this procedure, artifacts due to electrodes making poor contact can be greatly reduced.

Regional admittivity spectra with tomosynthesis images for breast cancer detection.

Because the electrical properties of many breast tumors are different from those of surrounding, normal tissue, imaging these properties may provide useful diagnostic information. At the present time, X-ray mammography is the standard imaging modality used for breast cancer screening. The interpretation of EIT imaging is thus enhanced by its use together with x-ray mammography in the same geometry. This paper reports the ability of Electrical Impedance Spectroscopy (EIS) to localize and distinguish cancers from normal tissues. These findings are confirmed by simultaneous, co-registered 3-D mammograms or tomosynthesis images and are verified with biopsy reports.

Layered model for breasts in electrical impedance tomography.

We are presently using Electrical Impedance Tomography as a technique for breast cancer imaging, determining the admittivity distribution inside the breast. The admittivities we observed in compressed breasts in EIT were lower than those seen in earlier studies involving whole chest imaging. We attribute this to a thin low admittance skin layer which dominates in compressed breasts. To more accurately model breasts, we have developed a layered analytical forward model. Our layered model has three layers, thin low admittivity top and bottom layers representing skin and a thicker high admittivity middle layer representing breast tissue. In this paper we derive the forward solution for this layered geometry and compare it to the forward solution for the homogeneous case. We also demonstrate the improvement in reconstruction of a target embedded in a layered body when the homogeneous forward solution is replaced by the layered forward solution.

A method for analyzing electrical impedance spectroscopy data from breast cancer patients.

Research on freshly-excised malignant breast tissues and surrounding normal tissues in an in vitro impedance cell has shown that breast tumors have different conductivity and permittivity from normal or non-malignant tissues. This contrast may provide a basis for breast cancer detection using electrical impedance imaging. This paper describes a procedure for collecting electrical impedance spectroscopy data simultaneously and in register with tomosynthesis data from patients. We describe the methods used to analyze the data in order to determine if the electrodes are making contact with the breast of the patient. Canonical voltage patterns are applied and used to synthesize the data that would have resulted from constant voltage patterns applied to each of two parallel mammography plates. A type of Cole-Cole plot is generated and displayed from each of the currents measured on each of the electrodes for each of the frequencies (5, 10, 30, 100 and 300 kHz) of applied voltages. We illustrate the potential usefulness of these displays in distinguishing breast cancer from benign lesions with the Cole-Cole plots for two patients--one having cancer and one having a benign lesion--by comparing these graphs with electrical impedance spectra previously found by Jossinet and Schmitt in tissue samples taken from a variety of patients.