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.

Data acquisition for a patient-directed intervention protocol in the dynamic intensive care unit setting.

Methods to easily, accurately, and efficiently obtain data in an ICU-based clinical trial can be challenging in this high-tech setting. Patient medical status and the dynamic nature of this clinical setting further complicate data collection. The purpose of this paper is to describe the modifications of commercially available headphones and the application of a data logging device to capture frequency and length of protocol use (music listening or headphones only for noise cancellation) without burdening participants or busy ICU nurses. With the automatic capture of protocol use by research participants, there have been no instances of lost data for this clinical trial.

A novel impedance-based tomography approach for stenotic plaque detection: a simulation study.

Rupture of high-risk, vulnerable plaques is responsible for coronary thrombosis, the main cause of unstable angina, acute myocardial infarction, and sudden cardiac death, therefore techniques capable of detecting vulnerable plaques play an important role in evaluating the coronary arteries. By taking advantage of the significantly low electrical conductivity of plaques, an impedance-based tomography approach was proposed in this study for detecting stenotic plaques. Image reconstructions, carried out with the differential imaging method, yield fairly good cross-sectional images of the modeled conductivity changes induced by atheroma, and demonstrate the feasibility of the proposed approach for plaque detection.

GREIT: a unified approach to 2D linear EIT reconstruction of lung images.

Electrical impedance tomography (EIT) is an attractive method for clinically monitoring patients during mechanical ventilation, because it can provide a non-invasive continuous image of pulmonary impedance which indicates the distribution of ventilation. However, most clinical and physiological research in lung EIT is done using older and proprietary algorithms; this is an obstacle to interpretation of EIT images because the reconstructed images are not well characterized. To address this issue, we develop a consensus linear reconstruction algorithm for lung EIT, called GREIT (Graz consensus Reconstruction algorithm for EIT). This paper describes the unified approach to linear image reconstruction developed for GREIT. The framework for the linear reconstruction algorithm consists of (1) detailed finite element models of a representative adult and neonatal thorax, (2) consensus on the performance figures of merit for EIT image reconstruction and (3) a systematic approach to optimize a linear reconstruction matrix to desired performance measures. Consensus figures of merit, in order of importance, are (a) uniform amplitude response, (b) small and uniform position error, (c) small ringing artefacts, (d) uniform resolution, (e) limited shape deformation and (f) high resolution. Such figures of merit must be attained while maintaining small noise amplification and small sensitivity to electrode and boundary movement. This approach represents the consensus of a large and representative group of experts in EIT algorithm design and clinical applications for pulmonary monitoring. All software and data to implement and test the algorithm have been made available under an open source license which allows free research and commercial use.

A simulation study on the effect of thoracic conductivity inhomogeneities on sensitivity distributions.

A high-resolution 3D finite difference model of the electrical conductivity distribution in a human thorax based on a 43-slice MRI data set along with lead field theory was used to examine the effect of thoracic conductivity inhomogeneities on sensitivity distributions. The electrode configurations used in the present study were based on an eight-electrode array positioned evenly around the thoracic model at a level close the nipple line. Sensitivity distributions of each possible adjacent pair current excitation pattern for both the homogeneous thoracic model and the heterogeneous thoracic model were evaluated. The results show that thoracic inhomogeneities significantly perturb sensitivity distribution patterns. Although for a given thoracic geometry the electrode configuration gives the overall sensitivity distribution features, sharp large local changes occur near the boundaries between different tissues in the heterogeneous model. The results of sensitivity distributions of the heterogeneous thoracic model demonstrate the feasibility of impedance source localization. Selectivity can be used to as a guide to finding favorable electrode configuration for regional impedance monitoring.

The contribution of the lungs to thoracic impedance measurements: a simulation study based on a high resolution finite difference model.

A high resolution electrical finite difference model of the human thorax based on a 43 slice MRI data set along with lead field theory was used to examine the contribution of the lungs to the total impedance for a typical mid-thoracic 2D EIT eight and sixteen electrode configuration. Regional analysis of the thoracic sources of impedance revealed that the maximum contribution of lungs to the total impedance was approximately 22% for the eight electrode array and 25% for the sixteen electrode array. Analysis of impedance distribution of the lungs using a mid-thoracic application showed that the contribution of impedance of each slice followed closely the volume of the lungs in the given slice. This suggests that the mid-thoracic application gives results reflecting the entire lung. The contributions of the lung impedance for the various electrode positions showed that the eight electrode configuration had a more smooth change between adjacent electrodes compared to the 16 electrode arrangement.

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.

Improved lung edema monitoring with coronary vein pacing leads: a simulation study.

This computer simulation study compared the ability of left ventricular coronary vein (LV) pacemaker leads against right ventricular (RV) and right atrial (RA) leads to monitor lung edema using electrical impedance measurements. MRI images were used to construct electrical models of the thorax. Four lead configurations were tested with increases of pulmonary edema, intravascular fluids and heart dilation. The impedance changes observed at end systole with severe lung edema were 8.5%, 11.2%, 12.3% and 26.8% for the RA, RV, RV coil and LV configurations, respectively. Sensitivities in ohms per litre of lung fluid were 19.15, 19.15, 25.07 and 52.11 for the same configurations. The impedance changes for intravascular fluid overload with constant lung status were 1%, 1.3%, 9.2% and 6.4% while the sensitivities were 2, 2, 17 and 11 ohms per litre of intravascular fluid, respectively. Regional analysis of the thoracic sources of impedance revealed a high sensitivity near pacing electrodes and generator, and a low sensitivity to the right lung and all pulmonary vessels. Simulations showed that LV leads have a threefold advantage in sensitivity when monitoring lung edema in comparison to conventional RV leads. To monitor vascular and lung fluids independently, combined impedance configurations may be used. Regional sensitivities must be taken into account for proper clinical interpretation of impedance changes.

Determining the relationship of heart rate and blood pressure using voluntary cardio-respiratory synchronization (VCRS).

Voluntary cardio-respiratory synchronization (VCRS) was used to investigate heart rate and blood pressure changes in the supine position in 21 subjects. VCRS involves a breathing pattern that is synchronized with the cardiac cycle. The signals to inhale and exhale are derived from the ECG. In this study, the subjects inspired for four heart beats and expired for four heart beats for 35 cycles. This technique is designed to have the heart beat occur at exactly the same phase in the respiratory cycle and lends itself to the study of the influence of the respiration cycle on heart rate and blood pressure changes. The heart rate and blood pressure changed simultaneously in the same direction, with the largest significant positive change occurring on the second heart beat during inspiration. The authors discuss the potential of VCRS for research, and clinical applications as a respiration modulator for hypertension therapy or increased heart rate variability.

Comparison of R-wave detection errors of four wireless heart rate belts in the presence of noise.

Four commercial wireless chest belts (Vetta, Nashbar, Polar and new Polar) were assessed for their susceptibility to noises in R-wave detection. A normal ECG signal was generated using a LionHeart simulator (Bio-tek Instruments, Inc.) with a fixed RR interval (750 ms) and R-wave amplitude (1 mV). Different levels of EMG and baseline wanderings (sinusoidal waves) were recorded from a healthy subject and a Quartec Model MFG-1 generator, respectively. They were added to the ECG signal in a BioPac system (BioPac systems Inc., Santa Barbara, CA) to simulate an ECG in physiological noise. The BioPac system applied the 'contaminated' ECG to the belts via a voltage divider. A PC-based Polar Precision Performance system was used to receive the detected R-wave pulses transmitted from the wireless belts and to calculate the RR intervals. Two types of detection errors were observed in the RR intervals: small time shifts, the potentially non-fixable small variance, and missed/false beats, the abnormally large and potentially fixable intervals. Results showed that small time shifts exist in all tests ranging from -10 ms to 10 ms and increase with the level of EMG before missed/false beats occur. Missed/false beats occur only when EMG level is beyond the threshold of 0.4 mV, 1.6 mV, 1.2 mV and 1.2 mV for Vetta, Nashbar, Polar and new Polar, respectively. The potential to detect and fix EMG introduced missed/false beats showed that this type of error could only be improved when the added EMG was below a certain value. Results also showed that no missed/false beats occur when the frequency and amplitude of sinusoidal waves were below 1 Hz and 5 mV.

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

A finite difference model of the human thorax with 113,400 control volumes (nodes) based on ECG gated MRI images was used to evaluate the Sheffield DAS-01P EIT system. Sixteen simulated electrode positions equally spaced around the thorax model at approximately the fourth intercostals space level were selected. Pairs of adjacent positions were excited sequentially by injecting current in a manner similar to that used by the Sheffield DAS-01P EIT system. The resulting voltages on the non-excited electrode positions were calculated and used to reconstruct the image using the Sheffield filtered back projection algorithm. By changing the resistivities of the lungs, the ventricles and the atria over a range of 1% to 40%, the resulting changes in the images were quantified by measuring the average resistivity change over a region defined automatically by two thresholds, 40% or 80% of the average of the first four pixels with the largest change. The results show that the changes observed in the images are consistently less than the changes in the model, but changed in a nearly linear manner as a function of resistivity in the model. For 40% resistivity changes in the model for right lung, right ventricle and right atrium, the observed resistivity changes in the region of interest (ROI, defined by the 80% threshold) of the images are 32% for the right lung, 11% for the right ventricle and 5.5% for the right atrium, which suggests strong volume dependence of EIT imaging. The effect of structural (size) change between end diastole and end systole was also studied, which showed large resistivity changes caused in the heart region of the constructed image. The study demonstrates that the Sheffield DAS-01P EIT reconstruction algorithm tracks the change occurring in the lungs most closely and with proper scaling may be used to observe physiological changes.