Application Of Electrical Impedance Tomography Research Articles

Linearly constrained minimum variance spatial filtering for localization of conductivity changes in electrical impedance tomography.

We localize dynamic electrical conductivity changes and reconstruct their time evolution introducing the spatial filtering technique to electrical impedance tomography (EIT). More precisely, we use the unit-noise-gain constrained variation of the distortionless-response linearly constrained minimum variance spatial filter. We address the effects of interference and the use of zero gain constraints. The approach is successfully tested in simulated and real tank phantoms. We compute the position error and resolution to compare the localization performance of the proposed method with the one-step Gauss-Newton reconstruction with Laplacian prior. We also study the effects of sensor position errors. Our results show that EIT spatial filtering is useful for localizing conductivity changes of relatively small size and for estimating their time-courses. Some potential dynamic EIT applications such as acute ischemic stroke detection and neuronal activity localization may benefit from the higher resolution of spatial filters as compared to conventional tomographic reconstruction algorithms.

Estimation of conductivity changes in a region of interest with electrical impedance tomography

This paper proposes a novel approach to reconstruct changesin a target conductivity from electrical impedance tomography measurements.As in the conventional difference imaging,the reconstruction of the conductivity change is based on electrical potential measurementsfrom the exterior boundary of the target before and after the change.In this paper, however, images of the conductivitybefore and after the change are reconstructed simultaneously based on the two data sets.The key feature of the approach is that the conductivity after the change is parameterized as a linear combination of the initial state and the change.This allows for modeling independently the spatial characteristics of the background conductivityand the change of the conductivity - by separate regularization functionals.The approach also allows in a straightforward way the restriction of the conductivity change to a localized region of interest inside the domain.While conventional difference imaging reconstruction is based on a global linearization of the observation model, the proposed approach amounts to solving a non-linear inverse problem. The feasibility of the proposed reconstruction method is tested experimentally and with a simulation which demonstrates a potential new medical application of electrical impedance tomography:imaging of vocal folds in voice loading studies.

Evaluation of EIT systems and algorithms for handling full void fraction range in two-phase flow measurement

In the aqueous-based two-phase flow, if the void fraction of dispersed phase exceeds 0.25, conventional electrical impedance tomography (EIT) produces a considerable error due to the linear approximation of the sensitivity back-projection (SBP) method, which limits the EIT’s wider application in the process industry. In this paper, an EIT sensing system which is able to handle full void fraction range in two-phase flow is reported. This EIT system employs a voltage source, conducts true mutual impedance measurement and reconstructs an online image with the modified sensitivity back-projection (MSBP) algorithm. The capability of the Maxwell relationship to convey full void fraction is investigated. The limitation of the linear sensitivity back-projection method is analysed. The MSBP algorithm is used to derive relative conductivity change in the evaluation. A series of static and dynamic experiments demonstrating the mean void fraction obtained using this EIT system has a good agreement with reference void fractions over the range from 0 to 1. The combination of the new EIT system and MSBP algorithm would significantly extend the applications of EIT in industrial process measurement.

NUMERICAL SIMULATION OF ELECTRICAL IMPEDANCE TOMOGRAPHY PROBLEM AND STUDY OF APPROACH BASED ON FINITE VOLUME METHOD

This research has been aimed to carry out a study of peculiarities that arise in a numerical simulation of the electrical impedance tomography (EIT) problem. Static EIT image reconstruction is sensitive to a measurement noise and approximation error. A special consideration has been given to reducing of the approximation error, which originates from numerical implementation drawbacks. This paper presents in detail two numerical approaches for solving EIT forward problem. The finite volume method (FVM) on unstructured triangular mesh is introduced. In order to compare this approach, the finite element (FEM) based forward solver was implemented, which has gained the most popularity among researchers. The calculated potential distribution with the assumed initial conductivity distribution has been compared to the analytical solution of a test Neumann boundary problem and to the results of problem simulation by means of ANSYS FLUENT commercial software. Two approaches to linearized EIT image reconstruction are discussed. Reconstruction of the conductivity distribution is an ill-posed problem, typically requiring a large amount of computation and resolved by minimization techniques. The objective function to be minimized is constructed of measured voltage and calculated boundary voltage on the electrodes. A classical modified Newton type iterative method and the stochastic differential evolution method are employed. A software package has been developed for the problem under investigation. Numerical tests were conducted on simulated data. The obtained results could be helpful to researches tackling the hardware and software issues for medical applications of EIT.

Variability in EIT Images of Lung Ventilation as a Function of Electrode Planes and Body Positions.

This study is aimed at investigating the variability in resistivity changes in the lung region as a function of air volume, electrode plane and body position. Six normal subjects (33.8 ± 4.7 years, range from 26 to 37 years) were studied using the Sheffield Electrical Impedance Tomography (EIT) portable system. Three transverse planes at the level of second intercostal space, the level of the xiphisternal joint, and midway between upper and lower locations were chosen for measurements. For each plane, sixteen electrodes were uniformly positioned around the thorax. Data were collected with the breath held at end expiration and after inspiring 0.5, 1.0, or 1.5 liters of air from end expiration, with the subject in both the supine and sitting position. The average resistivity change in five regions, two 8x8 pixel local regions in the right lung, entire right, entire left and total lung regions, were calculated. The results show the resistivity change averaged over electrode positions and subject positions was 7-9% per liter of air, with a slightly larger resistivity change of 10 % per liter air in the lower electrode plane. There was no significant difference (p>0.05) between supine and sitting. The two 8x8 regions show a larger inter individual variability (coefficient of variation, CV, is from 30% to 382%) compared to the entire left, entire right and total lung (CV is from 11% to 51%). The results for the global regions are more consistent. The large inter individual variability appears to be a problem for clinical applications of EIT, such as regional ventilation. The variability may be mitigated by choosing appropriate electrode plane, body position and region of interest for the analysis.

XVth International Conference on Electrical Bio-Impedance and the XIVth Conference on Electrical Impedance Tomography (Heilbad Heiligenstadt, Germany, 22–25 April 2013)

This issue of Physiological Measurement follows the successful XVth International Conference on Electrical Bio-Impedance (ICEBI) in conjunction with the XIVth International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT) held at Heilbad Heiligenstadt, Germany. The conference was hosted at the Institut für Bioprozess- und Analysenmeßtechnik in Heilbad Heiligenstadt by Uwe Pliquett and Dieter Beckmann with co-organiser Günter Hahn from the University of Göttingen. The conference provided a platform for investigators in all aspects of bio-impedance and EIT to engage in common areas of interest whilst also allowing an opportunity for the community to broaden its outlook in the areas of clinical applications and new technologies associated with both areas of research. It focused on instrumentation, modeling and data processing but also new applications especially for clinical purpose. This upholds the tradition of successful conferences on biomedical applications of bio-impedance and electrical impedance tomography, as was the case with the 13th International Conference on Biomedical Applications of Electrical Impedance Tomography (EIT 2012). The conference was held in China and hosted at Tianjin University. It was co-organized by Professor Xuemin Wang from Tianjin University, Professor Jie Zhang from the University of Kentucky, and Professor Eung Je Woo of Kyung Hee University. The most recent conference is the 14th International Conference on Biomedical Applications of Electrical impedance Tomography (EIT) that was held in Gananoque, Canada in April 2014. This conference will be followed by a focus issue in Physiological Measurement that will be published in 2015. This issue contains papers stemming from discussion and feedback during the 2013 conference in these research areas. It was also an opportunity for new researchers to join the community and propose recent innovations. There were 247 accepted submissions (actually participating: 141 oral and 85 poster) presented at the conference, and all authors were invited to prepare new peer-reviewed papers for inclusion in this issue of Physiological Measurement . The manuscripts were put through a process of careful review before selection. A total of 20 were accepted covering an important range of topics. Both fields of bio-impedance and EIT continue to provide researchers with new challenges, and attract more researchers into these areas as evident by the number of attendees (258) to this conference. The high quality of the research papers in this special issue is clear evidence of the significant advances in the field.

Recovering multiple small inclusions in a three-dimensional domain using a single measurement

We present and test an effective algorithm to recover multiple small heterogeneities inside arbitrary three-dimensional bounded regions. In applications of electrical impedance tomography, such heterogeneities might represent tumours inside the body, weaknesses or cracks in a solid material or subterranean mineral deposits. The algorithm determines the location of all heterogeneities using a single boundary measurement. The only non-linear step in the algorithm is to find roots of a single polynomial of degree . The efficacy of this method is demonstrated by full numerical computation of the three-dimensional forward problem. In addition, the methods employed can give information regarding the shape of irregular heterogeneities.

Monitoring of Regional Lung Ventilation Using Electrical Impedance Tomography After Cardiac Surgery in Infants and Children

Electrical impedance tomography (EIT) is a noninvasive method to monitor regional lung ventilation in infants and children without using radiation. The objective of this prospective study was to determine the value of EIT as an additional monitoring tool to assess regional lung ventilation after pediatric cardiac surgery for congenital heart disease in infants and children. EIT monitoring was performed in a prospective study comprising 30 pediatric patients who were mechanically ventilated after cardiac surgery. Data were analyzed off-line with respect to regional lung ventilation in different clinical situations. EIT data were correlated with respirator settings and arterial carbon dioxide (CO2) partial pressure in the blood. In 29 of 30 patients, regional ventilation of the lung could sufficiently and reliably be monitored by means of EIT. The effects of the transition from mechanical ventilation to spontaneous breathing after extubation on regional lung ventilation were studied. After extubation, a significant decrease of relative impedance changes was evident. In addition, a negative correlation of arterial CO2 partial pressure and relative impedance changes could be shown. EIT was sufficient to discriminate differences of regional lung ventilation in children and adolescents after cardiac surgery. EIT reliably provided additional information on regional lung ventilation in children after cardiac surgery. Neither chest tubes nor pacemaker wires nor the intensive care unit environment interfered with the application of EIT. EIT therefore may be used as an additional real-time monitoring tool in pediatric cardiac intensive care because it is noninvasive.

Whittle-Matérn priors for Bayesian statistical inversion with applications in electrical impedance tomography

We study flexible and proper smoothness priors for Bayesian statistical inverse problems by using Whittle-Matern Gaussian random fields. We review earlier results on finite-difference approximations of certain Whittle-Matern random field in $\mathbb{R}^2$. Then we derive finite-element method approximations and show that the discrete approximations can be expressed as solutions of sparse stochastic matrix equations. Such equations are known to be computationally efficient and useful in inverse problems with a large number of unknowns. &nbsp The presented construction of Whittle-Matern correlation functions allows both isotropic or anisotropic priors with adjustable parameters in correlation length and variance. These parameters can be used, for example, to model spatially varying structural information of unknowns. &nbsp As numerical examples, we apply the developed priors to two-dimensional electrical impedance tomography problems.

Role of Electrical Impedance Tomography in Clinical Practice in Pediatric Respiratory Medicine

This paper summarizes current knowledge about electrical impedance tomography (EIT) and its present and possible applications in clinical practice in pediatric respiratory medicine. EIT is a relatively new technique based on real-time monitoring of bioimpedance. Its possible application in clinical practice related to ventilation and perfusion monitoring in children has gaine increasing attention in recent years. Most of the currently published data is based on studies performed on small and heterogenous groups of patients. Thus the results need to be corroborated in future well-designed clinical trials. Firstly a short theoretical overview summarizing physical principles and main advantages and disadvantages is provided. It is followed by a review of the current data regarding EIT application in ventilation distribution monitoring in healthy individuals. Finally the most important studies utilizing EIT in ventilation and perfusion monitoring in critically ill newborns and children are outlined.

Human CT Measurements of Structure/Electrode Position Changes During Respiration with Electrical Impedance Tomography

For pulmonary applications of Electrical Impedance Tomography (EIT) systems, the electrodes are placed around the chest in a 2D ring, and the images are reconstructed based on the assumptions that the object is rigid and the measured resistivity change in EIT images is only caused by the actual resistivity change of tissue. Structural changes are rarely considered. Previous studies have shown that structural changes which result in tissue/organ and electrode position changes tend to introduce artefacts to EIT images of the thorax. Since EIT reconstruction is an ill-posed inverse problem, any small inaccurate assumptions of object may cause large artefacts in reconstructed images. Accurate information on structure/electrode position changes is a need to understand factors contributing to the measured resistivity changes and to improve EIT reconstruction algorithm. Our previous study using MRI technique showed that chest expansion leads to electrode and tissue/organ movements but not significant as proposed. The accuracy of the measurements by MRI may be limited by its relatively low temporal and spatial resolution. In this study, structure/electrode position changes during respiration cycle in patients who underwent chest CT scans are further investigated. For each patient, sixteen fiduciary markers are equally spaced around the surface, the same as the electrode placement for EIT measurements. A CT scanner with respiration-gated ability is used to acquire images of the thorax. CT thoracic images are retrospectively reconstructed corresponding temporally to specific time periods within respiration cycle (from 0% to 90%, every 10%). The average chest expansions are 2 mm in anterior-posterior and -1.6 mm in lateral directions. Inside tissue/organ move down 9.0±2.5 mm with inspiration of tidal volume (0.54±0.14 liters), ranging from 6 mm to 12 mm. During normal quiet respiration, electrode position changes are smaller than expected. No general patterns of electrode position changes are observed. The results in this study provide guidelines for accommodating the motion that may introduce artefacts to EIT images.

A new high output impedance wideband AC current source with high current swing authority for electrical impedance tomography applications

The Electrical impedance tomography (EIT) is a relatively new technical imaging method for industrial applications, medical imaging and relative researches. The most important part of this system is an AC current source. Its characteristics have efficient effects on the performance of EIT systems. The AC current source must have constant current amplitude over the load and frequency ranges in related applications. In this paper, we could by designing a new topology of current source circuit achieving a current source with higher output impedance in comparison with other current sources which are mostly used in EIT applications. In the new designed current source, the output impedance of old current source will be multiplied by limited gain of second op-amp. Also in new topology, the output voltage and current swing are doubled in comparison with modified Howland current source; because, the load impedance seen from the output leg of second op-amp is decreased.

Evaluation and Real-Time Monitoring of Data Quality in Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a noninvasive method to image conductivity distributions within a body. One promising application of EIT is to monitor ventilation in patients as a real-time bedside tool. Thus, it is essential that an EIT system reliably provide meaningful information, or alert clinicians when this is impossible. Because the reconstructed images are very sensitive to system instabilities (primarily from electrode connection variability and movement), EIT systems should continuously monitor and, if possible, correct for such errors. Motivated by this requirement, we describe a novel approach to quantitatively measure EIT data quality. Our goals are to define the requirements of a data quality metric, develop a metric q which meets these requirements, and an efficient way to calculate it. The developed metric q was validated using data from saline tank experiments and a retrospective clinical study. Additionally, we show that q may be used to compare the performance of EIT systems using phantom measurements. Results suggest that the calculated metric reflects well the quality of reconstructed EIT images for both phantom and clinical data. The proposed measure can thus be used for real-time assessment of EIT data quality and, hence, to indicate the reliability of any derived physiological information.

A GREIT-type linear reconstruction algorithm for EIT using eigenimages

Reconstruction in electrical impedance tomography (EIT) is a nonlinear, ill-posed inverse problem. Based on point-shaped training and evaluation data, the "Graz consensus Reconstruction algorithm for EIT" (GREIT) constitutes a universal, homogenous method. While this is a very reasonable approach to the general problem, we ask the question if an optimized reconstruction method for a specific application of EIT, i.e. thoracic imaging, can be found. Instead of point-shaped training data we propose to use spatially extended training data consisting of eigenimages. To evaluate the quality of reconstruction of the proposed approach, figures of merit (FOMs) derived from the ones used in GREIT are developed. For the application of thoracic imaging, lung-shapes were segmented from a publicly available CT-database (www.dir-lab.com) and used to calculate the novel FOMs. With those, the general feasibility of using eigenimages is demonstrated and compared to the standard approach. In addition, it is shown that by using different sets of training data, the creation of an individually optimized linear method of reconstruction is possible.

Experimental/clinical evaluation of EIT image reconstruction with ℓ1 data and image norms

Electrical impedance tomography (EIT) image reconstruction is ill-posed, and the spatial resolution of reconstructed images is low due to the diffuse propagation of current and limited number of independent measurements. Generally, image reconstruction is formulated using a regularized scheme in which ℓ2 norms are preferred for both the data misfit and image prior terms due to computational convenience which result in smooth solutions. However, recent work on a Primal Dual-Interior Point Method (PDIPM) framework showed its effectiveness in dealing with the minimization problem. ℓ1 norms on data and regularization terms in EIT image reconstruction address both problems of reconstruction with sharp edges and dealing with measurement errors. We aim for a clinical and experimental evaluation of the PDIPM method by selecting scenarios (human lung and dog breathing) with known electrode errors, which require a rigorous regularization and cause the failure of reconstructions with ℓ2 norm. Results demonstrate the applicability of PDIPM algorithms, especially ℓ1 data and regularization norms for clinical applications of EIT showing that ℓ1 solution is not only more robust to measurement errors in clinical setting, but also provides high contrast resolution on organ boundaries.

Biocompatible, High Precision, Wideband, Improved Howland Current Source With Lead-Lag Compensation

The Howland current pump is a popular bioelectrical circuit, useful for delivering precise electrical currents. In applications requiring high precision delivery of alternating current to biological loads, the output impedance of the Howland is a critical figure of merit that limits the precision of the delivered current when the load changes. We explain the minimum operational amplifier requirements to meet a target precision over a wide bandwidth. We also discuss effective compensation strategies for achieving stability without sacrificing high frequency output impedance. A current source suitable for Electrical Impedance Tomography (EIT) was simulated using a SPICE model, and built to verify stable operation. This current source design had stable output impedance of 3.3 MΩ up to 200 kHz, which provides 80 dB precision for our EIT application. We conclude by noting the difficulty in measuring the output impedance, and advise verifying the plausibility of measurements against theoretical limitations.

Influence of regularization in image reconstruction in electrical impedance tomography

The purpose of the application of electrical impedance tomography is to obtain images of areas that are difficult to access inside of the chest and other parts of the human being. Today, this has been applied in other areas of engineering with a view to investigate phenomena for which it is difficult to obtain data for robust research. Electrical Impedance Tomography (EIT) of an inverse problem is nonlinear and ill-conditioned. This requires a careful theoretical approach and practice to get good images. To enhance the images, it is important to be sensitive to various parameters that influence the process of image reconstruction, such as the measured voltage and the current density injected into the electrodes. The impedance contact and current density are both high in a point electrode. To reduce this, a large electrode modeled with a Finite Element Method (FEM) is used. A reduced numbers iterations is found when larges electrodes are used. When FEM models are used the performance of the electrical impedance tomography reconstruction algorithm can be improved.

Designing a very high output resistance current source for medical applications

A new technique is proposed for the design of a current source, in bipolar technology, with a very high output resistance and low output capacitance. Such a technique is useful in electrical impedance tomography applications. The DC relationships of the basic topology are established. Then, based on the analysis of a simplified equivalent circuit, an expression is formulated for the output resistance and tested against simulation results for both ideal and practical biasing circuits. The effect of circuit capacitances, and in particular, the role of the collector-base capacitance of the output transistor, in determining the output impedance as a function of frequency is considered. Finally, a new circuit is shown to have an incremental output resistance exceeding 200 GΩ.

Multi-GPU Jacobian accelerated computing for soft-field tomography

Image reconstruction in soft-field tomography is based on an inverse problem formulation, where a forward model is fitted to the data. In medical applications, where the anatomy presents complex shapes, it is common to use finite element models (FEMs) to represent the volume of interest and solve a partial differential equation that models the physics of the system. Over the last decade, there has been a shifting interest from 2D modeling to 3D modeling, as the underlying physics of most problems are 3D. Although the increased computational power of modern computers allows working with much larger FEM models, the computational time required to reconstruct 3D images on a fine 3D FEM model can be significant, on the order of hours. For example, in electrical impedance tomography (EIT) applications using a dense 3D FEM mesh with half a million elements, a single reconstruction iteration takes approximately 15–20 min with optimized routines running on a modern multi-core PC. It is desirable to accelerate image reconstruction to enable researchers to more easily and rapidly explore data and reconstruction parameters. Furthermore, providing high-speed reconstructions is essential for some promising clinical application of EIT. For 3D problems, 70% of the computing time is spent building the Jacobian matrix, and 25% of the time in forward solving. In this work, we focus on accelerating the Jacobian computation by using single and multiple GPUs. First, we discuss an optimized implementation on a modern multi-core PC architecture and show how computing time is bounded by the CPU-to-memory bandwidth; this factor limits the rate at which data can be fetched by the CPU. Gains associated with the use of multiple CPU cores are minimal, since data operands cannot be fetched fast enough to saturate the processing power of even a single CPU core. GPUs have much faster memory bandwidths compared to CPUs and better parallelism. We are able to obtain acceleration factors of 20 times on a single NVIDIA S1070 GPU, and of 50 times on four GPUs, bringing the Jacobian computing time for a fine 3D mesh from 12 min to 14 s. We regard this as an important step toward gaining interactive reconstruction times in 3D imaging, particularly when coupled in the future with acceleration of the forward problem. While we demonstrate results for EIT, these results apply to any soft-field imaging modality where the Jacobian matrix is computed with the adjoint method.

Toward Morphological Thoracic EIT: Major Signal Sources Correspond to Respective Organ Locations in CT

Lung and cardiovascular monitoring applications of electrical impedance tomography (EIT) require localization of relevant functional structures or organs of interest within the reconstructed images. We describe an algorithm for automatic detection of heart and lung regions in a time series of EIT images. Using EIT reconstruction based on anatomical models, candidate regions are identified in the frequency domain and image-based classification techniques applied. The algorithm was validated on a set of simultaneously recorded EIT and CT data in pigs. In all cases, identified regions in EIT images corresponded to those manually segmented in the matched CT image. Results demonstrate the ability of EIT technology to reconstruct relevant impedance changes at their anatomical locations, provided that information about the thoracic boundary shape (and electrode positions) are used for reconstruction.