Evaluation of an EIT reconstruction algorithm using finite difference human thorax models as phantoms

Low Power Contactless Bioimpedance Sensor for Monitoring Breathing Activity

An electronic circuit for contactless detection of impedance changes in a tissue is presented. It operates on the principle of resonant frequency change of the resonator having the observed tissue as a dielectric. The operating frequency reflects the tissue dielectric properties (i.e., the tissue composition and on the tissue physiological changes). The sensor operation was tested within a medical application by measuring the breathing of a patient, which was an easy detectable physiological process. The advantage over conventional contact bioimpedance measurement methods is that no direct contact between the resonator and the body is required. Furthermore, the sensor's wide operating range, ability to adapt to a broad range of measured materials, fast response, low power consumption, and small outline dimensions enables applications not only in the medical sector, but also in other domains. This can be extended, for example, to food industry or production maintenance, where the observed phenomena are reflected in dynamic dielectric properties of the observed object or material.

CT Image-Guided Electrical Impedance Tomography for Medical Imaging

This study presents a computed tomography (CT) image-guided electrical impedance tomography (EIT) method for medical imaging. CT is a robust imaging modality for accurately reconstructing the density structure of the region being scanned. EIT can detect electrical impedance abnormalities to which CT scans may be insensitive, but the poor spatial resolution of EIT is a major concern for medical applications. A cross-gradient method has been introduced for oil and gas exploration to jointly invert multiple geophysical datasets associated with different medium properties in the same geological structure. In this study, we develop a CT image-guided EIT (CEIT) based on the cross-gradient method. We assume that both CT scanning and EIT imaging are conducted for the same medical target. A CT scan is first acquired to help solve the subsequent EIT imaging problem. During EIT imaging, we apply cross gradients between the CT image and the electrical conductivity distribution to iteratively constrain the conductivity inversion. The cross-gradient based method allows the mutual structures of different physical models to be referenced without directly affecting the polarity and amplitude of each model during the inversion. We apply the CEIT method to both numerical simulations and phantom experiments. The effectiveness of CEIT is demonstrated in comparison with conventional EIT. The comparison shows that the CEIT method can significantly improve the quality of conductivity images.

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.

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 MATLAB-Based Boundary Data Simulator for Studying the Resistivity Reconstruction Using Neighbouring Current Pattern

Phantoms are essentially required to generate boundary data for studying the inverse solver performance in electrical impedance tomography (EIT). A MATLAB-based boundary data simulator (BDS) is developed to generate accurate boundary data using neighbouring current pattern for assessing the EIT inverse solvers. Domain diameter, inhomogeneity number, inhomogeneity geometry (shape, size, and position), background conductivity, and inhomogeneity conductivity are all set as BDS input variables. Different sets of boundary data are generated by changing the input variables of the BDS, and resistivity images are reconstructed using electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS). Results show that the BDS generates accurate boundary data for different types of single or multiple objects which are efficient enough to reconstruct the resistivity images for assessing the inverse solver. It is noticed that for the BDS with 2048 elements, the boundary data for all inhomogeneities with a diameter larger than 13.3% of that of the phantom are accurate enough to reconstruct the resistivity images in EIDORS-2D. By comparing the reconstructed image with an original geometry made in BDS, it would be easier to study the inverse solver performance and the origin of the boundary data error can be identified.

Spatial and temporal heterogeneity of regional lung ventilation determined by electrical impedance tomography during pulmonary function testing

Electrical impedance tomography (EIT) is a functional imaging modality capable of tracing continuously regional pulmonary gas volume changes. The aim of our study was to determine if EIT was able to assess spatial and temporal heterogeneity of ventilation during pulmonary function testing in 14 young (37 ± 10 yr, mean age ± SD) and 12 elderly (71 ± 9 yr) subjects without lung disease and in 33 patients with chronic obstructive pulmonary disease (71 ± 9 yr). EIT and spirometry examinations were performed during tidal breathing and a forced vital capacity (FVC) maneuver preceded by full inspiration to total lung capacity. Regional inspiratory vital capacity (IVC); FVC; forced expiratory volume in 1 s (FEV(1)); FEV(1)/FVC; times required to expire 25%, 50%, 75%, and 90% of FVC (t(25), t(50), t(75), t(90)); and tidal volume (V(T)) were determined in 912 EIT image pixels in the chest cross section. Coefficients of variation (CV) were calculated from all pixel values of IVC, FVC, FEV(1), and V(T) to characterize the ventilation heterogeneity. The highest values were found in patients, and no differences existed between the healthy young and elderly subjects. Receiver-operating characteristics curves showed that CV of regional IVC, FVC, FEV(1), and V(T) discriminated the young and elderly subjects from the patients. Frequency distributions of pixel FEV(1)/FVC, t(25), t(50), t(75), and t(90) identified the highest ventilation heterogeneity in patients but distinguished also the healthy young from the elderly subjects. These results indicate that EIT may provide additional information during pulmonary function testing and identify pathologic and age-related spatial and temporal heterogeneity of regional lung function.

Modelling of an oesophageal electrode for cardiac function tomography

There is a need in critical care units for continuous cardiopulmonary monitoring techniques. ECG gated electrical impedance tomography is able to localize the impedance variations occurring during the cardiac cycle. This method is a safe, inexpensive and potentially fast technique for cardiac output imaging but the spatial resolution is presently low, particularly for central locations such as the heart. Many parameters including noise deteriorate the reconstruction result. One of the main obstacles in cardiac imaging at the heart location is the high impedance of lungs and muscles on the dorsal and posterior side of body. In this study we are investigating improvements of the measurement and initial conductivity estimation of the internal electrode by modelling an internal electrode inside the esophagus. We consider 16 electrodes connected around a cylindrical mesh. With the random noise level set near 0.05% of the signal we evaluated the Graz consensus reconstruction algorithm for electrical impedance tomography. The modelling and simulation results showed that the quality of the target in reconstructed images was improved by up to 5 times for amplitude response, position error, resolution, shape deformation and ringing effects with perturbations located in cardiac related positions when using an internal electrode.

EIT images of ventilation: what contributes to the resistivity changes?

One promising application of electrical impedance tomography (EIT) is the monitoring of pulmonary ventilation and edema. Using three-dimensional (3D) finite difference human models as virtual phantoms, the factors that contribute to the observed lung resistivity changes in the EIT images were investigated. The results showed that the factors included not only tissue resistivity or vessel volume changes, but also chest expansion and tissue/organ movement. The chest expansion introduced artifacts in the center of the EIT images, ranging from -2% to 31% of the image magnitude. With the increase of simulated chest expansion, the percentage contribution of chest expansion relative to lung resistivity change in the EIT image remained relatively constant. The averaged resistivity changes in the lung regions caused by chest expansion ranged from 0.65% to 18.31%. Tissue/organ movement resulted in an increased resistivity in the lung region and in the center anterior region of EIT images. The increased resistivity with inspiration observed in the heart region was caused mainly by a drop in the heart position, which reduced the heart area at the electrode level and was replaced by the lung tissue with higher resistivity. This study indicates that for the analysis of EIT, data errors caused by chest expansion and tissue/organ movement need to be considered.

EIT reconstruction algorithms: pitfalls, challenges and recent developments

We review developments, issues and challenges in electrical impedance tomography (EIT) for the 4th Conference on Biomedical Applications of Electrical Impedance Tomography, held at Manchester in 2003. We focus on the necessity for three-dimensional data collection and reconstruction, efficient solution of the forward problem, and both present and future reconstruction algorithms. We also suggest common pitfalls or 'inverse crimes' to avoid.