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

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

Decoherence and the Quantum Zeno Effect

The experiment of Etano et al which demonstrated the quantum Zeno effect (QZE) in an optical experiment was explained by Frerichs and Schenzle without invoking the wave function collapse. In this report it is proposed that the collapse does occur, and it can be explained by the `environment induced decoherence' theory. The environment here consists of the completely quantized field vacuum modes. The spontaneous emission life time of the atom sets a fundamental limit on the requirement of `continuous measurements' for QZE. This limit turns out to be related to the time-energy uncertainty relation discussed by Ghirardi et al.Comment: Based on a poster presented at the "Workshop on Advanced Laser Spectroscopy", I.I.T. Kanpur, India, 25-28 February 1995. RevTeX, one page, two uunecoded post-script figures appended

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

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

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