Advances in electrical impedance tomography and bioimpedance including applications in COVID-19 diagnosis and treatment

This focus collection aims at presenting recent advances in electrical impedance tomography (EIT) including algorithms, hardware and clinical applications. As the opportunity to attend conferences has been considerably reduced due to the COVID-19 pandemic, this collection will provide a unique opportunity for the community to continue to report new studies and applications, and broaden the outlook into new clinical areas including COVID-19 patients and new technologies such as biosensors, machine learning and image analysis

Analysis and compensation for errors in electrical impedance tomography images and ventilation-­related measures due to serial data collection

Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study was to determine the extent to which this affects derived parameters. Raw EIT data were acquired with the GOE­MF II EIT device (CareFusion, Höchberg, Germany) at a scan rate of 13 images/s during both spontaneous breathing and mechanical ventilation. Boundary data for periods of undisturbed tidal breathing were corrected for serial data collection errors using a Fourier based algorithm. Images were reconstructed for both the corrected and original data using the GREIT algorithm, and parameters describing the filling characteristics of the right and left lung derived on a breath by breath basis. Values from the original and corrected data were compared using paired t­ tests. Of the 33 data sets, 23 showed significant differences in filling index for at least one region, 11 had significant differences in calculated tidal impedance change and 12 had significantly different filling fractions (p = 0.05). We conclude that serial collection errors should be corrected before image reconstruction to avoid clinically misleading results

Analysis and compensation for errors in electrical impedance tomography images and ventilation-­related measures due to serial data collection

Electrical impedance tomography (EIT) is increasingly being used as a bedside tool for monitoring regional lung ventilation. However, most clinical systems use serial data collection which, if uncorrected, results in image distortion, particularly at high breathing rates. The objective of this study was to determine the extent to which this affects derived parameters. Raw EIT data were acquired with the GOE­MF II EIT device (CareFusion, Höchberg, Germany) at a scan rate of 13 images/s during both spontaneous breathing and mechanical ventilation. Boundary data for periods of undisturbed tidal breathing were corrected for serial data collection errors using a Fourier based algorithm. Images were reconstructed for both the corrected and original data using the GREIT algorithm, and parameters describing the filling characteristics of the right and left lung derived on a breath by breath basis. Values from the original and corrected data were compared using paired t­ tests. Of the 33 data sets, 23 showed significant differences in filling index for at least one region, 11 had significant differences in calculated tidal impedance change and 12 had significantly different filling fractions (p = 0.05). We conclude that serial collection errors should be corrected before image reconstruction to avoid clinically misleading results

Electrical impedance tomography reveals pathophysiology of neonatal pneumothorax during NAVA

Pneumothorax is a potentially life‐threatening complication of neonatal respiratory distress syndrome (RDS). We describe a case of a tension pneumothorax that occurred during neurally adjusted ventilatory assist (NAVA) in a preterm infant suffering from RDS. The infant was included in a multicenter study examining the role of electrical impedance tomography (EIT) in intensive care and therefore continuously monitored with this imaging method. The attending physicians were blinded for EIT findings but offline analysis revealed the potential of EIT to clarify the underlying cause of this complication, which in this case was heterogeneous lung disease resulting in uneven ventilation distribution. Instantaneous increase in end‐expiratory lung impedance on the affected side was observed at time of the air leak. Real‐time bedside availability of EIT data could have modified the treatment decisions made

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\u3e0.05) 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

Effects of patient recumbency position on neonatal chest EIT

This paper investigates the overlooked effects of the patient recumbency positions on one of the key clinically used parameters in chest electrical impedance tomography (EIT) monitoring – the silent spaces. This parameter could impact medical decisions and interventions by indicating how well each lung is being ventilated. Yet it is largely dependent on assumptions of prior model at the reconstruction stage and the closely linked region of interest (ROI) during the final calculations. The potential effect of switching recumbency modes on silent spaces as a results of internal organ movements and consequently changes in initial assumptions, has been studied. The displacement and deformations caused by posture changes from supine to lateral recumbent were evaluated via simulations considering the simultaneous gravity-dependent movement and/or deformations of heart, mediastinum, lungs and the diaphragm. The reliability of simulations was verified against reference radiography images of an 18-month-old infant in supine and decubitus lateral positions. Inspecting a set of 10 patients from age range of 1 to 2 years old revealed improvements of up to 30% in the silent space parameters when applying posture consistent amendments as opposed to fixed model/ROI to each individual. To minimize the influence of image reconstruction technique on the results two different EIT reconstruction algorithms were implemented. The outcome emphasized the importance of including recumbency situation during chest EIT monitoring within the considered age range

A direct D-bar reconstruction algorithm for recovering a complex conductivity in 2-D

A direct reconstruction algorithm for complex conductivities in $W^{2,\infty}(\Omega)$, where $\Omega$ is a bounded, simply connected Lipschitz domain in $\mathbb{R}^2$, is presented. The framework is based on the uniqueness proof by Francini [Inverse Problems 20 2000], but equations relating the Dirichlet-to-Neumann to the scattering transform and the exponentially growing solutions are not present in that work, and are derived here. The algorithm constitutes the first D-bar method for the reconstruction of conductivities and permittivities in two dimensions. Reconstructions of numerically simulated chest phantoms with discontinuities at the organ boundaries are included.Comment: This is an author-created, un-copyedited version of an article accepted for publication in [insert name of journal]. IOP Publishing Ltd is not responsible for any errors or omissions in this version of the manuscript or any version derived from it. The Version of Record is available online at 10.1088/0266-5611/28/9/09500

Towards a thoracic conductive phantom for EIT

Phantom experiments are a crucial step for testing new hardware or imaging algorithms for electrical impedance tomography (EIT) studies. However, constructing an accurate phantom for EIT research remains critical; some studies have attempted to model the skull and breasts, and even fewer, as yet, have considered the thorax. In this study, a critical comparison between the electrical properties (impedance) of three materials is undertaken: a polyurethane foam, a silicone mixture and a thermoplastic polyurethane filament. The latter was identified as the most promising material and adopted for the development of a flexible neonatal torso. The validation is performed by the EIT image reconstruction of the air filled cavities, which mimic the lung regions. The methodology is reproducible for the creation of any phantom that requires a slight flexibility