Measuring lung resistivity using electrical impedance tomography

Compensation for Electrode Detachment in Electrical Impedance Tomography with Wearable Textile Electrodes

Electrical impedance tomography (EIT) is a radiation-free and noninvasive medical image reconstruction technique in which a current is injected and the reflected voltage is received through electrodes. EIT electrodes require good connection with the skin for data acquisition and image reconstruction. However, detached electrodes are a common occurrence and cause measurement errors in EIT clinical applications. To address these issues, in this study, we proposed a method for detecting faulty electrodes using the differential voltage value of the detached electrode in an EIT system. Additionally, we proposed the voltage-replace and voltage-shift methods to compensate for invalid data from the faulty electrodes. In this study, we present the simulation, experimental, and in vivo chest results of our proposed methods to verify and evaluate the feasibility of this approach.

Dry Wearable Textile Electrodes for Portable Electrical Impedance Tomography

Electrical impedance tomography (EIT), a noninvasive and radiation-free medical imaging technique, has been used for continuous real-time regional lung aeration. However, adhesive electrodes could cause discomfort and increase the risk of skin injury during prolonged measurement. Additionally, the conductive gel between the electrodes and skin could evaporate in long-term usage and deteriorate the signal quality. To address these issues, in this work, textile electrodes integrated with a clothing belt are proposed to achieve EIT lung imaging along with a custom portable EIT system. The simulation and experimental results have verified the validity of the proposed portable EIT system. Furthermore, the imaging results of using the proposed textile electrodes were compared with commercial electrocardiogram electrodes to evaluate their performance.

Quantitative Evaluations with 2d Electrical Resistance Tomography in the Low-Conductivity Solutions Using 3d-Printed Phantoms and Sucrose Crystal Agglomerate Assessments

Crystallization is a significant procedure in the manufacturing of many pharmaceutical and solid food products. In-situ electrical resistance tomography (ERT) is a novel process analytical tool (PAT) to provide a cheap and quick way to test, visualize, and evaluate the progress of crystallization processes. In this work, the spatial accuracy of the nonconductive phantoms in low-conductivity solutions was evaluated. Gauss–Newton, linear back projection, and iterative total variation reconstruction algorithms were used to compare the phantom reconstructions for tap water, industrial-grade saturated sucrose solution, and demineralized water. A cylindrical phantom measuring 10 mm in diameter and a cross-section area of 1.5% of the total beaker area was detected at the center of the beaker. Two phantoms with a 10-mm diameter were visualized separately in noncentral locations. The quantitative evaluations were done for the phantoms with radii ranging from 10 mm to 50 mm in demineralized water. Multiple factors, such as ERT device and sensor development, Finite Element Model (FEM) mesh density and simulations, image reconstruction algorithms, number of iterations, segmentation methods, and morphological image processing methods, were discussed and analyzed to achieve spatial accuracy. The development of ERT imaging modality for the purpose of monitoring crystallization in low-conductivity solutions was performed satisfactorily.

Review on Electrical Impedance Tomography: Artificial Intelligence Methods and its Applications

Electrical impedance tomography (EIT) has been a hot topic among researchers for the last 30 years. It is a new imaging method and has evolved over the last few decades. By injecting a small amount of current, the electrical properties of tissues are determined and measurements of the resulting voltages are taken. By using a reconstructing algorithm these voltages then transformed into a tomographic image. EIT contains no identified threats and as compared to magnetic resonance imaging (MRI) and computed tomography (CT) scans (imaging techniques), it is cheaper in cost as well. In this paper, a comprehensive review of efforts and advancements undertaken and achieved in recent work to improve this technology and the role of artificial intelligence to solve this non-linear, ill-posed problem are presented. In addition, a review of EIT clinical based applications has also been presented.

Real-Time Identification of Upper Airway Occlusion Using Electrical Impedance Tomography

STUDY OBJECTIVES

Real-time monitoring of upper airway collapse during sleep could be instrumental for studies in biomechanics of obstructive sleep apnea (OSA) and selecting individualized treatment modalities. Although some imaging techniques are used under sedated sleep, none are available during the entire natural sleep process. We hypothesized that electrical impedance tomography (EIT) can be used for noninvasive continuous imaging of the upper airway during natural sleep and quantifying upper airway collapse in terms of its size.

METHODS

After determining surface landmarks to attach the electrodes for monitoring the retroglossal airway, EIT was conducted in 10 healthy participants. As a feasibility test of EIT in detecting upper airway collapse, transient airway closure was induced by the swallowing maneuver. These EIT images were confirmed by simultaneous magnetic resonance imaging (MRI) scans. Subsequently, EIT scans were conducted in 7 healthy participants and 10 patients with OSA under nonsedated sleep to determine whether it could identify upper airway narrowing or collapse. Respiratory events were identified by concurrent polysomnography (PSG).

RESULTS

Swallowing-induced airway closure was identified successfully in all 10 participants on simultaneous EIT and MRI scans. Sizes and positions of the upper airway closures in reconstructed EIT images were well correlated with those in magnetic resonance images. Obstructive hypopnea and apnea were detected successfully by EIT in 10 patients with OSA, and no significant changes in EIT data were observed in 7 healthy participants during concurrent EIT and PSG tests. Additionally, conductivity changes in the airway were greater during obstructive apnea than during hypopnea (64.3% versus 26.3%, respectively; P < .001) compared with those during baseline respiration.

CONCLUSIONS

EIT could be a useful real-time monitoring device for detecting upper airway narrowing or collapse during natural sleep in patients with OSA. Currently, changes in the upper airway size can be estimated with good accuracy, but shape estimation needs future improvements in the EIT image quality.

Conductivity Anisotropy Influence on Acoustic Sources for Magnetoacoustic Tomography With Magnetic Induction

OBJECTIVE

As the multi-physics imaging approach, magnetoacoustic tomography with magnetic induction (MAT-MI) attracts more and more attentions, focusing on image reconstruction for conductivity isotropic tissues.

METHODS

By introducing vector analyses to electromagnetic stimulation and magnetoacoustic excitation for a single-layer cylindrical conductivity anisotropic model, the acoustic source strength (ASS) of MAT-MI is derived in explicit formula and the influence of the anisotropic conductivity tensor is also analyzed.

RESULTS

Theoretical and numerical studies demonstrate that the ASS generated at the tissue boundary is composed of an alternating current (AC) fluctuation and a direct current (DC) bias, where the distribution of the AC fluctuation with respect to the spatial angle exhibits a double-period cosine function, and the DC bias remains constant at each angle. The dependences of the AC fluctuation and the DC bias on the anisotropic component ratio (ACR) and the conductivity tensor are proved by numerical results, which are also verified by the special cases of the zero AC fluctuation for the conductivity isotropic medium and the negative DC bias of the low-conductivity medium.

CONCLUSION

With the measurements of the ASS around the model, the anisotropic conductivity tensor can be reconstructed by the amplitudes of the AC fluctuation and the DC bias with the conductivity of the isotropic surrounding medium.

SIGNIFICANCE

The favorable results provide a new method for anisotropic conductivity measurement, and suggest the application potential of MAT-MI in biomedical imaging and nondestructive testing for conductivity anisotropic tissues.

Modelling Tumor Treating Fields for the treatment of lung-based tumors

Tumor Treating Fields (TTFields), low-intensity electric fields in the frequency range of 100-500 kHz, exhibit antimitotic activity in cancer cells. TTFields were approved by the U. S. Food and Drug Administration for the treatment of recurrent glioblastoma in 2011. Preclinical evidence and pilot studies suggest that TTFields could be effective for treating certain types of lung cancer, and that treatment efficacy depends on the electric field intensity. To optimize TTFields delivery to the lungs, it is important to understand how TTFields distribute within the chest. Here we present simulations showing how TTFields are distributed in the thorax and torso, and demonstrate how the electric field distribution within the body can be controlled by personalizing the layout of the arrays used to deliver the field.

Alternating electric fields (TTFields) in combination with paclitaxel are therapeutically effective against ovarian cancer cells in vitro and in vivo

Long-term survival rates for advanced ovarian cancer patients have not changed appreciably over the past four decades; therefore, development of new, effective treatment modalities remains a high priority. Tumor Treating Fields (TTFields), a clinically active anticancer modality utilize low-intensity, intermediate frequency, alternating electric fields. The goal of this study was to evaluate the efficacy of combining TTFields with paclitaxel against ovarian cancer cells in vitro and in vivo. In vitro application of TTFields on human ovarian cancer cell lines led to a significant reduction in cell counts as compared to untreated cells. The effect was found to be frequency and intensity dependent. Further reduction in the number of viable cells was achieved when TTFields treatment was combined with paclitaxel. The in vivo effect of the combined treatment was tested in mice orthotopically implanted with MOSE-L_TICv cells. In this model, combined treatment led to a significant reduction in tumor luminescence and in tumor weight as compared to untreated mice. The feasibility of effective local delivery of TTFields to the human abdomen was examined using finite element mesh simulations performed using the Sim4life software. These simulations demonstrated that electric fields intensities inside and in the vicinity of the ovaries of a realistic human computational phantom are about 1 and 2 V/cm pk-pk, respectively, which is within the range of intensities required for TTFields effect. These results suggest that prospective clinical investigation of the combination of TTFields and paclitaxel is warranted.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

Estimation of respiration rate from three-dimensional acceleration data based on body sensor network

Respiratory monitoring is widely used in clinical and healthcare practice to detect abnormal cardiopulmonary function during ordinary and routine activities. There are several approaches to estimate respiratory rate, including accelerometer(s) worn on the torso that are capable of sensing the inclination changes due to breathing. In this article, we present an adaptive band-pass filtering method combined with principal component analysis to derive the respiratory rate from three-dimensional acceleration data, using a body sensor network platform previously developed by us. In situ experiments with 12 subjects indicated that our method was capable of offering dynamic respiration rate estimation during various body activities such as sitting, walking, running, and sleeping. The experimental studies also suggested that our frequency spectrum-based method was more robust, resilient to motion artifact, and therefore outperformed those algorithms primarily based on spatial acceleration information.

Affinity-based turbidity sensor for glucose monitoring by optical coherence tomography: toward the development of an implantable sensor

We investigated the feasibility of constructing an implantable optical-based sensor for seminoninvasive continuous monitoring of analytes. In this novel sensor, analyte concentration-dependent changes induced in the degree of optical turbidity of the sensing element can be accurately monitored by optical coherence tomography (OCT), an interferometric technique. To demonstrate proof-of-concept, we engineered a sensor for monitoring glucose concentration that enabled us to quantitatively monitor the glucose-specific changes induced in bulk scattering (turbidity) of the sensor. The sensor consists of a glucose-permeable membrane housing that contains a suspension of macroporous hydrogel particles and concanavalin A (ConA), a glucose-specific lectin, that are designed to alter the optical scattering of the sensor as a function of glucose concentration. The mechanism of modulation of bulk turbidity in the sensor is based on glucose-specific affinity binding of ConA to pendant glucose residues of macroporous hydrogel particles. The affinity-based modulation of the scattering coefficient was significantly enhanced by optimizing particle size, particle size distribution, and ConA concentration. Successful operation of the sensor was demonstrated under in vitro condition where excellent reversibility and stability (160 days) of prototype sensors with good overall response over the physiological glucose concentration range (2.5-20 mM) and good accuracy (standard deviation 5%) were observed. Furthermore, to assess the feasibility of using the novel sensor as one that can be implanted under skin, the sensor was covered by a 0.4 mm thick tissue phantom where it was demonstrable that the response of the sensor to 10 mM glucose change could still be measured in the presence of a layer of tissue shielding the sensor aiming to simulate in vivo condition. In summary, we have demonstrated that it is feasible to develop an affinity-based turbidity sensor that can exhibit a highly specific optical response as a function of changes in local glucose concentration and such response can be accurately monitored by OCT suggesting that the novel sensor can potentially be engineered to be used as an implantable sensor for in vivo monitoring of analytes.

Analysis of resting noise characteristics of three EIT systems in order to compare suitability for time difference imaging with scalp electrodes during epileptic seizures

Electrical impedance tomography measurements in clinical applications are limited by an undesired noise component. We have investigated the noise in three systems suitable for imaging epileptic seizures, the UCH Mark1b, UCH Mark2.5 and KHU Mark1 16 channel, at applied frequencies in three steps from 1 to 100 kHz, by varying load impedance, single terminal or multiplexed measurements, and in test objects of increasing complexity from a resistor to a saline filled tank and human volunteer. The noise was white, and increased from about 0.03% rms on the resistor to 0.08% on the human; it increased with load but was independent of use of the multiplexer. The KHU Mark1 delivered the best performance with noise spectra of about 0.02%, which could be further reduced by averaging to a level where reliable imaging of changes of about 0.1% estimated during epileptic seizures appears plausible.

Monitoring lung fluid content in CHF patients under intravenous diuretics treatment using bio-impedance measurements

A pulmonary edema monitoring system (PulmoTrace, CardioInspect, Tel-Aviv University, Israel) was evaluated for tracking lung resistivity during diuretics treatment in congestive heart failure (CHF) patients. The system incorporates a bio-impedance measurement algorithm and enables, by employing an eight-electrode thoracic belt, the assessment of both the left- and right-lung resistivity values. A clinical study was conducted on a group of 13 CHF patients under intravenous diuretics treatment. The group was measured twice-before the beginning of treatment and following a period of a couple of hours. An increase of 8% of the mean lung resistivity (median value) was found between the two measuring sessions, which indicates a dehydration of the lungs, and a significant correlation (R=0.73, p=0.004) was found between the lung resistivity change and the urine output. In conjunction with previously reported results, which demonstrated the system's reproducibility and long-term monitoring capabilities, this study further supports the diagnostics value of the system.

A reconstruction algorithm for breast cancer imaging with electrical impedance tomography in mammography geometry

The conductivity and permittivity of breast tumors are known to differ significantly from those of normal breast tissues, and electrical impedance tomography (EIT) is being studied as a modality for breast cancer imaging to exploit these differences. At present, X-ray mammography is the primary standard imaging modality used for breast cancer screening in clinical practice, so it is desirable to study EIT in the geometry of mammography. This paper presents a forward model of a simplified mammography geometry and a reconstruction algorithm for breast tumor imaging using EIT techniques. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for a homogeneous conductivity distribution and is validated by experiment using a phantom tank. A reconstruction algorithm for breast tumor imaging based on a linearization approach and the proposed forward model is presented. It is found that the proposed reconstruction algorithm performs well in the phantom experiment, and that the locations of a 5-mm-cube metal target and a 6-mm-cube agar target could be recovered at a target depth of 15 mm using a 32 electrode system.

A simplified model of mammography geometry for breast cancer imaging with electrical impedance tomography

One recent application area of EIT is the detection of breast cancer by imaging the conductivity and the permittivity distribution inside the breast. The present "gold standard" for breast cancer detection is X-ray mammography, and it is desirable that the EIT and the X-ray mammography use the same geometry. This work presents a simplified model of the mammography geometry for EIT imaging. The mammography geometry is modeled as a rectangular box with electrode arrays on the top and bottom planes. A forward model for the electrical impedance imaging problem is derived for the homogeneous conductivity distribution and validated by experiment using a phantom tank. The effect of unmodeled surface on the sides of the electrodes is studied.

Excitation patterns in three-dimensional electrical impedance tomography

Electrical impedance tomography (EIT) is a non-invasive technique that aims to reconstruct images of internal electrical properties of a domain, based on electrical measurements on the periphery. Improvements in instrumentation and numerical modeling have led to three-dimensional (3D) imaging. The availability of 3D modeling and imaging raises the question of identifying the best possible excitation patterns that will yield to data, which can be used to produce the best image reconstruction of internal properties. In this work, we describe our 3D finite element model of EIT. Through singular value decomposition as well as examples of reconstructed images, we show that for a homogenous female breast model with four layers of electrodes, a driving pattern where each excitation plane is a sinusoidal pattern out-of-phase with its neighboring plane produces better qualitative images. However, in terms of quantitative imaging an excitation pattern where all electrode layers are in phase produces better results.

Electrical impedance tomography using the extended Kalman filter

In this paper, we propose an algorithm that, using the extended Kalman filter, solves the inverse problem of estimating the conductivity/resistivity distribution in electrical impedance tomography (EIT). The algorithm estimates conductivity/resistivity in a wide range. The purpose of this investigation is to provide information for setting and controlling air volume and pressure delivered to patients under artificial ventilation. We show that, when the standard deviation of the measurement noise level raises up to 5% of the maximal measured voltage, the conductivity estimates converge to the expected vector within 7% accuracy of the maximal conductivity value, under numerical simulations, with spatial a priori information. A two-phase identification procedure is proposed. A cylindrical phantom with saline solution is used for experimental evaluation. An abrupt modification on the resistivity distribution of this solution is caused by the immersion of a glass object. Estimates of electrode contact impedances and images of the glass object are presented.

Markov chain Monte Carlo techniques and spatial–temporal modelling for medical EIT

Many imaging problems such as imaging with electrical impedance tomography (EIT) can be shown to be inverse problems: that is either there is no unique solution or the solution does not depend continuously on the data. As a consequence solution of inverse problems based on measured data alone is unstable, particularly if the mapping between the solution distribution and the measurements is also nonlinear as in EIT. To deliver a practical stable solution, it is necessary to make considerable use of prior information or regularization techniques. The role of a Bayesian approach is therefore of fundamental importance, especially when coupled with Markov chain Monte Carlo (MCMC) sampling to provide information about solution behaviour. Spatial smoothing is a commonly used approach to regularization. In the human thorax EIT example considered here nonlinearity increases the difficulty of imaging, using only boundary data, leading to reconstructions which are often rather too smooth. In particular, in medical imaging the resistivity distribution usually contains substantial jumps at the boundaries of different anatomical regions. With spatial smoothing these boundaries can be masked by blurring. This paper focuses on the medical application of EIT to monitor lung and cardiac function and uses explicit geometric information regarding anatomical structure and incorporates temporal correlation. Some simple properties are assumed known, or at least reliably estimated from separate studies, whereas others are estimated from the voltage measurements. This structural formulation will also allow direct estimation of clinically important quantities, such as ejection fraction and residual capacity, along with assessment of precision.

Generation of anisotropic-smoothness regularization filters for EIT

In the inverse conductivity problem, as in any ill-posed inverse problem, regularization techniques are necessary in order to stabilize inversion. A common way to implement regularization in electrical impedance tomography is to use Tikhonov regularization. The inverse problem is formulated as a minimization of two terms: the mismatch of the measurements against the model, and the regularization functional. Most commonly, differential operators are used as regularization functionals, leading to smooth solutions. Whenever the imaged region presents discontinuities in the conductivity distribution, such as interorgan boundaries, the smoothness prior is not consistent with the actual situation. In these cases, the reconstruction is enhanced by relaxing the smoothness constraints in the direction normal to the discontinuity. In this paper, we derive a method for generating Gaussian anisotropic regularization filters. The filters are generated on the basis of the prior structural information, allowing a better reconstruction of conductivity profiles matching these priors. When incorporating prior information into a reconstruction algorithm, the risk is of biasing the inverse solutions toward the assumed distributions. Simulations show that, with a careful selection of the regularization parameters, the reconstruction algorithm is still able to detect conductivities patterns that violate the prior information. A generalized singular-value decomposition analysis of the effects of the anisotropic filters on regularization is presented in the last sections of the paper.

Pulmonary edema induced by allergen challenge in the rat: noninvasive assessment by magnetic resonance imaging

The course of pulmonary edema formation after an intratracheal (i.t.) instillation of ovalbumin was followed noninvasively by magnetic resonance imaging (MRI) in actively sensitized Brown Norway (BN) rats. Changes in edema volume assessed by MRI mimicked the results from the analysis of the number and activation of inflammatory cells recovered from the broncho-alveolar lavage (BAL) fluid. Rats treated with budesonide did not develop edema following challenge with ovalbumin, and these animals showed a significant decrease in BAL fluid inflammatory cell numbers and eosinophil peroxidase and myeloperoxidase activities. Thus, following lung edema formation by MRI provides a reliable means of assessing pulmonary inflammation after allergen challenge. Unlike BAL fluid analysis, which requires killing animals at each time point, this method is noninvasive. MRI could be of importance for the noninvasive profiling of anti-inflammatory drugs in animal models of asthma and in the clinic. Magn Reson Med 45:88-95, 2001.

Use of a priori information in estimating tissue resistivities--a simulation study

Accurate estimation of tissue resistivities in vivo is needed to construct reliable human body volume conductor models in solving forward and inverse bioelectric field problems. The necessary data for the estimation can be obtained by using the four-electrode impedance measurement technique, usually employed in electrical impedance tomography. In this study, a priori geometrical information with statistical properties of regional resistivities and linearization error as well as instrumentation noise has been incorporated into a new resistivity estimation algorithm which is called a statistically constrained minimum mean squares error estimator (MiMSEE) to improve estimation accuracy. MiMSEE intakes geometrical information from the image which is obtained by using a high-resolution imaging modality. This study is an extension of earlier work by Eyüboğlu et al and obtains simulated measurements from two numerical models containing five and six regions on a background region. Also, estimations are repeated by using up to eight multiple current electrode pairs, in order to observe the effect of estimation performance while increasing the number of measurements up to 96. The results are compared with a conventional least squares error estimator (LSEE) which is used in one-pass algorithms. It is shown that the MiMSEE estimation error is up to 27 times smaller than the LSEE error which is realized for a small, high-contrast region, for example the aorta. In estimating the regional resistivities, the MiMSEE algorithm requires 25.8 (for the five-region resistivity distribution) and 22.2 (for the six-region resistivity distribution) times more computational time than the LSEE. This gap between the computational times of the two algorithms decreases as the number of regions increases.

Quantification of blood volume by electrical impedance tomography using a tissue-equivalent phantom

An in vivo electrical impedance tomography (EIT) system was designed to accurately estimate quantities of intra-peritoneal blood in the abdominal cavity. For this it is essential that the response is relatively independent of the position of the high conductivity anomaly (blood) in the body. The sensitivity of the system to the introduction of blood-equivalent resistivity anomalies was assessed by using a cylindrical tissue-equivalent phantom. It was found that a satisfactorily uniform response of the system in both radial (transverse) and axial (longitudinal) directions in the phantom could be achieved by filtering resistivity profile images obtained by EIT measurement, and by using extended electrodes to collect data. Post-processing of single impedance images gave rise to a quantity denoted the resistivity index. A filter was then used to remove the remaining radial variation of the resistivity index. It was calculated by evaluating the resistivity index of a number of theoretically calculated images, and constructing a correction filter similar to those used to remove lens imperfections, such as coma, in optical components. The 30% increase in the resistivity index observed when an anomaly was moved to the maximum extent allowed by the filter calculation (0.75 of the phantom radius) was reduced by the filter to 6%. A study of the axial dependence observed in the resistivity index using electrodes extended in the axial direction by +/-5 cm found that the variation in resistivity index with axial position was about half of that observed using small circular electrodes similar to those used in the Sheffield mark I system.

Tikhonov regularization and prior information in electrical impedance tomography

The solution of impedance distribution in electrical impedance tomography is a nonlinear inverse problem that requires the use of a regularization method. The generalized Tikhonov regularization methods have been popular in the solution of many inverse problems. The regularization matrices that are usually used with the Tikhonov method are more or less ad hoc and the implicit prior assumptions are, thus, in many cases inappropriate. In this paper, we propose an approach to the construction of the regularization matrix that conforms to the prior assumptions on the impedance distribution. The approach is based on the construction of an approximating subspace for the expected impedance distributions. It is shown by simulations that the reconstructions obtained with the proposed method are better than with two other schemes of the same type when the prior is compatible with the true object. On the other hand, when the prior is incompatible with the true object, the method will still give reasonable estimates.

Monitoring changes in lung air and liquid volumes with electrical impedance tomography

Electrical impedance tomography (EIT) uses electrical measurements at electrodes placed around the thorax to image changes in the conductivity distribution within the thorax. This technique is well suited to studying pulmonary function because the movement of air, blood, and extravascular fluid induces significant conductivity changes within the thorax. We conducted three experimental protocols in a total of 19 dogs to assess the accuracy with which EIT can quantify changes in the volumes of both gas and fluid in the lungs. In the first protocol, lung volume increments from 50 to 1,000 ml were applied with a large syringe. EIT measured these volume changes with an average error of 27 +/- 6 ml. In the second protocol, EIT measurements were made at end expiration and end inspiration during regular ventilation with tidal volume ranging from 100 to 1,000 ml. The average error in the EIT estimates of tidal volume was 90 +/- 43 ml. In the third protocol, lung liquid volume was measured by instilling 5% albumin solution into a lung lobe in increments ranging from 10 to 100 ml. EIT measured these volume changes with an average error of 10 +/- 10 ml and was also able to detect into which lobe the fluid had been instilled. These results indicate that EIT can noninvasively measure changes in the volumes of both gas and fluid in the lungs with clinically useful accuracy.

The electrical and dielectric properties of human bone tissue and their relationship with density and bone mineral content

In this study, we examined the electrical properties of wet human cortical and cancellous bone tissue from distal tibia and their relationship to the wet, dry, and ash tissue densities. The resistivity and specific capacitance of both cortical and cancellous bone were determined for different frequencies and directions (orientation). The wet, dry, and ash tissue densities of the bone samples were measured, and the ash content was determined. Correlation and regression analysis was used to examine the possible relationships among the electrical properties and the tissue densities for cancellous and cortical bone specimens separately as well as for all of the bone specimens combined. Highly significant positive correlations (p < 0.001) were found between the wet density of bone and the dry and ash densities. The specific capacitance of the cancellous bone specimens in all three orthogonal directions showed significant (p < 0.01) positive correlations with the wet, dry, and ash densities. In general, the specific capacitance depended more on density for all bone specimens, and only a weak relationship was found between the resistivity of human cortical bone and density.

Comparison of the electrical and dielectric behavior of wet human cortical and cancellous bone tissue from the distal tibia

We compared the electrical and dielectric properties of wet human cortical and cancellous bone tissue from the distal tibia. The relationships between the electrical and dielectric behavior of cortical and cancellous bone and variables of measurement such as frequency and direction (orientation) were evaluated. In general, the resistivity of human cortical bone was found to be approximately 3.1 times more than that of cancellous bone in the longitudinal direction and least 25 times more in the transverse directions. The dielectric permittivity of human cortical bone was approximately 3.9 times that of cancellous bone in the longitudinal direction, whereas in the transverse directions it was about 0.65 times greater. Measurement variables such as frequency and orientation appeared to affect cancellous and cortical bone differently. Strong correlations were found between the electrical properties in one direction and the electrical properties in the other two directions; however, these relationships differed for the samples of cortical and cancellous bone.

Estimation of tissue resistivities from multiple-electrode impedance measurements

In order to measure in vivo resistivity of tissues in the thorax, the possibility of combining anatomical data extracted from high-resolution images with multiple-electrode impedance measurements, a priori knowledge of the range of tissue resistivities, and a priori data on the instrumentation noise is assessed in this study. A statistically constrained minimum-mean-square error estimator (MIMSEE) that minimizes the effects of linearization errors and instrumentation noise is developed and compared to the conventional least-squares error estimator (LSEE). The MIMSEE requires a priori signal and noise information. The statistical constraint signal information was obtained from a priori knowledge of the physiologically allowed range of regional resistivities. The noise constraint information was obtained from a priori knowledge of the linearization error and the instrumentation noise. The torso potentials were simulated by employing a three-dimensional canine torso model. The model consists of four different conductivity regions: heart, right lung, left lung, and body. It is demonstrated that the statistically constrained MIMSEE performs significantly better than the LSEE in determining resistivities. The results based on the torso model indicate that regional resistivities can be estimated to within 40% accuracy of their true values by utilizing a statistically constrained MIMSEE, even if the instrumentation noise is comparable to the measured torso potentials. The errors obtained using the LSEE with the same linearized transfer function and level of instrumentation noise were about five times larger than those obtained using the MIMSEE. For larger measurement errors the MIMSEE performs even better when compared to the LSEE.

Time-harmonic impedance tomography using the T-matrix method

A time-harmonic formulation for the electrical impedance tomography (EIT) inverse problem accounting for electrodynamic effects is derived. This work abandons the standard electrostatic impedance model for a full-wave T-matrix model. The advantage of this method is an accurate physical model that includes finite frequency effects, such as diffusion phenomena, and electrode contact impedance effects. This model offers the potential for increased resolution and larger invertible contrast objects than other methods when used on experimental data, because it may represent a more realistic physical model. Also, an accurate gradient matrix is used in the Newton iterative method so the image reconstruction converges in a few iterations. These advantages are realized with no increase in the computational complexity of this algorithm, compared to the static finite element model. A calibration technique is suggested for measurement systems, to test the validity of a theoretical model that includes electrode contact impedance effects.

Walsh function current patterns and data synthesis for electrical impedance tomography

A data collection method which uses Walsh functions as injection current patterns is presented. This method can satisfy two conditions: the optimality of current patterns in every iteration and the single-time data measurement condition. The use of Walsh functions simplifies the design of current sources since only two levels of current (+1 and -1) are required, whereas sinusoidal injection requires a digital-to-analog converter to produce many different values of currents. Compared to diagonal or neighboring type of pulses as injection current patterns, Walsh injection current patterns provide more information about the interior of the subject since Walsh function simulate low and high spatial frequency patterns. Therefore, Walsh function injection uses the simplicity of pulse type injection and yields the better distinguishability or SNR of sinusoidal injection.