Whither lung EIT: Where are we, where do we want to go and what do we need to get there?

Research Trends and Hotspots of Medical Electrical Impedance Tomography Algorithms: A Bibliometric Analysis From 1987 to 2021

Electrical impedance tomography (EIT) is a gradually maturing medical imaging technique that relies on computational algorithms for reconstructing and visualizing internal conductivity distributions within the human body. To provide a comprehensive and objective understanding of the current state and trends in the EIT algorithm research, we conducted bibliometric analysis on a 25-year EIT algorithm research dataset sourced from Web of Science Core Collections. We visualized publication characteristics, collaboration patterns, keywords, and co-cited references. The results indicate a steady increase in annual publications over recent decades. The United States, United Kingdom, China, and South Korea contributed 60% of the articles collaboratively. Keyword analysis unveiled three distinct stages in the evolution of EIT algorithm research: the establishment of fundamental algorithm frameworks, optimization for improved imaging performance, and the development of algorithms for clinical applications. Additionally, there has been a shift in research focus from traditional theories to the incorporation of new methods, such as artificial intelligence. Co-cited references suggest that integrating EIT with other established imaging techniques may emerge as a new trend in EIT algorithm research. In summary, EIT algorithms have been a consistent research focus, with current efforts centered on optimizing algorithms to enhance imaging performance. The emerging research trend involves utilizing more diverse and intersecting algorithms.

A noise-controlling method by hybrid current-stimulation and voltage-measurement for electrical impedance tomography (HCSVM-EIT)

Image reconstruction in electrical impedance tomography (EIT) is a typical ill-posed inverse problem, from which the stability of conductivity reconstruction affects the reliability of physiological parameters evaluation. In order to improve the stability, the effect of boundary voltage noise on conductivity reconstruction should be controlled. A noise-controlling method based on hybrid current-stimulation and voltage-measurement for EIT (HCSVM-EIT) is proposed for stable conductivity reconstruction. In HCSVM-EIT, the boundary voltage is measured by one current-stimulation and voltage-measurement pattern (high-SNRpattern) with a higher signal-to-noise ratio (SNR); the sensitivity matrix is calculated by another current-stimulation and voltage-measurement pattern (low-condpattern) with a lower condition number; the boundary voltage is then transformed from thehigh-SNRpattern into thelow-condpattern by multiplying by an optimized transformation matrix for image reconstruction. The stability of conductivity reconstruction is improved by combining the advantages of thehigh-SNRpattern for boundary voltage measurement and thelow-condpattern for sensitivity matrix calculation. The simulation results show that the HCSVM-EIT increases the correlation coefficient (CC) of conductivity reconstruction. The experiment results show that theCCof conductivity reconstruction of the human lower limb is increased from 0.3424 to 0.5580 by 62.97% compared to the quasi-adjacent pattern, and from 0.4942 to 0.5580 by 12.91% compared to the adjacent pattern. In conclusion, the stable conductivity reconstruction with higherCCin HCSVM-EIT improves the reliability of physiological parameters evaluation for disease detection.

Image Reconstruction Using Supervised Learning in Wearable Electrical Impedance Tomography of the Thorax

Electrical impedance tomography (EIT) is a non-invasive technique for visualizing the internal structure of a human body. Capacitively coupled electrical impedance tomography (CCEIT) is a new contactless EIT technique that can potentially be used as a wearable device. Recent studies have shown that a machine learning-based approach is very promising for EIT image reconstruction. Most of the studies concern models containing up to 22 electrodes and focus on using different artificial neural network models, from simple shallow networks to complex convolutional networks. However, the use of convolutional networks in image reconstruction with a higher number of electrodes requires further investigation. In this work, two different architectures of artificial networks were used for CCEIT image reconstruction: a fully connected deep neural network and a conditional generative adversarial network (cGAN). The training dataset was generated by the numerical simulation of a thorax phantom with healthy and illness-affected lungs. Three kinds of illnesses, pneumothorax, pleural effusion, and hydropneumothorax, were modeled using the electrical properties of the tissues. The thorax phantom included the heart, aorta, spine, and lungs. The sensor with 32 area electrodes was used in the numerical model. The ECTsim custom-designed toolbox for Matlab was used to solve the forward problem and measurement simulation. Two artificial neural networks were trained with supervision for image reconstruction. Reconstruction quality was compared between those networks and one-step algebraic reconstruction methods such as linear back projection and pseudoinverse with Tikhonov regularization. This evaluation was based on pixel-to-pixel metrics such as root-mean-square error, structural similarity index, 2D correlation coefficient, and peak signal-to-noise ratio. Additionally, the diagnostic value measured by the ROC AUC metric was used to assess the image quality. The results showed that obtaining information about regional lung function (regions affected by pneumothorax or pleural effusion) is possible using image reconstruction based on supervised learning and deep neural networks in EIT. The results obtained using cGAN are strongly better than those obtained using a fully connected network, especially in the case of noisy measurement data. However, diagnostic value estimation showed that even algebraic methods allow us to obtain satisfactory results.

Lung Imaging Acquisition with Electrical Impedance Tomography: Tackling Common Pitfalls

Electrical impedance tomography is a powerful tool for lung imaging that can be employed at the bedside in multiple clinical scenarios. Diagnosing and preventing interpretation pitfalls will ensure reliable data and allow for appropriate clinical decision-making.

PEEP Titration Is Markedly Affected by Trunk Inclination in Mechanically Ventilated Patients with COVID-19 ARDS: A Physiologic, Cross-Over Study

BACKGROUND

Changing trunk inclination affects lung function in patients with ARDS. However, its impacts on PEEP titration remain unknown. The primary aim of this study was to assess, in mechanically ventilated patients with COVID-19 ARDS, the effects of trunk inclination on PEEP titration. The secondary aim was to compare respiratory mechanics and gas exchange in the semi-recumbent (40° head-of-the-bed) and supine-flat (0°) positions following PEEP titration.

METHODS

Twelve patients were positioned both at 40° and 0° trunk inclination (randomized order). The PEEP associated with the best compromise between overdistension and collapse guided by Electrical Impedance Tomography (PEEPEIT) was set. After 30 min of controlled mechanical ventilation, data regarding respiratory mechanics, gas exchange, and EIT parameters were collected. The same procedure was repeated for the other trunk inclination.

RESULTS

PEEPEIT was lower in the semi-recumbent than in the supine-flat position (8 ± 2 vs. 13 ± 2 cmH2O, p < 0.001). A semi-recumbent position with optimized PEEP resulted in higher PaO2:FiO2 (141 ± 46 vs. 196 ± 99, p = 0.02) and a lower global inhomogeneity index (46 ± 10 vs. 53 ± 11, p = 0.008). After 30 min of observation, a loss of aeration (measured by EIT) was observed only in the supine-flat position (-153 ± 162 vs. 27 ± 203 mL, p = 0.007).

CONCLUSIONS

A semi-recumbent position is associated with lower PEEPEIT and results in better oxygenation, less derecruitment, and more homogenous ventilation compared to the supine-flat position.

Affordable, portable and self-administrable electrical impedance tomography enables global and regional lung function assessment

Accessibility of diagnostic screening and treatment monitoring devices for respiratory diseases is critical in promoting healthcare and reducing sudden complications and mortality. Spirometry is the standard for diagnosing and monitoring several lung diseases. However, it lacks regional assessment capabilities necessary for detecting subtle regional changes in certain diseases. It also requires challenging breathing maneuvers difficult for elderlies, children, and diseased patients. Here, we actualized an affordable, portable, and self-administrable electrical impedance tomography (EIT) system for home-based lung function assessment and telemedicine. Through simultaneous EIT-spirometry trials on healthy subjects, we demonstrated that our device can predict spirometry indicators over a wide range and can provide regional mapping of these indicators. We further developed a close-to-effortless breathing paradigm and tested it by longitudinally monitoring a COVID-19 discharged subject and two healthy controls with results suggesting the paradigm can detect initial deterioration followed by recovery. Overall, the EIT system can be widely applicable for lung function screening and monitoring both at homes and clinics.

Parasitic Effects on Electrical Bioimpedance Systems: Critical Review

Parasitic capacitance represents the main error source in measurement systems based on electrical impedance spectroscopy. The capacitive nature of electrodes' impedance in tetrapolar configuration can give origin to phase errors when electrodes are coupled to parasitic capacitances. Nevertheless, reactive charges in tissue excitation systems are susceptible to instability. Based on such a scenario, mitigating capacitive effects associated with the electrode is a requirement in order to reduce errors in the measurement system. A literature review about the main compensation techniques for parasitic capacitance was carried out. The selected studies were categorized into three groups: (i) compensation in electronic instrumentation; (ii) compensation in measurement processing, and (iii) compensation by negative impedance converters. The three analyzed methods emerged as effective against fixed capacitance. No method seemed capable of mitigating the effects of electrodes' capacitance, that changes in the frequency spectrum. The analysis has revealed the need for a method to compensate varying capacitances, since electrodes' impedance is unknown.

An Ex Vivo Study of Outward Electrical Impedance Tomography (OEIT) for Intravascular Imaging

OBJECTIVE

Atherosclerosis is a chronic immuno-inflammatory condition emerging in arteries and considered the cause of a myriad of cardiovascular diseases. Atherosclerotic lesion characterization through invasive imaging modalities is essential in disease evaluation and determining intervention strategy. Recently, electrical properties of the lesions have been utilized in assessing its vulnerability mainly owing to its capability to differentiate lipid content existing in the lesion, albeit with limited detection resolution. Electrical impedance tomography is the natural extension of conventional spectrometric measurement by incorporating larger number of interrogating electrodes and advanced algorithm to achieve imaging of target objects and thus provides significantly richer information. It is within this context that we develop Outward Electrical Impedance Tomography (OEIT), aimed at intravascular imaging for atherosclerotic lesion characterization.

METHODS

We utilized flexible electronics to establish the 32-electrode OEIT device with outward facing configuration suitable for imaging of vessels. We conducted comprehensive studies through simulation model and ex vivo setup to demonstrate the functionality of OEIT.

RESULTS

Quantitative characterization for OEIT regarding its proximity sensing and conductivity differentiation was achieved using well-controlled experimental conditions. Imaging capability for OEIT was further verified with phantom setup using porcine aorta to emulate in vivo environment.

CONCLUSION

We have successfully demonstrated a novel tool for intravascular imaging, OEIT, with unique advantages for atherosclerosis detection.

SIGNIFICANCE

This study demonstrates for the first time a novel electrical tomography-based platform for intravascular imaging, and we believe it paves the way for further adaptation of OEIT for intravascular detection in more translational settings and offers great potential as an alternative imaging tool for medical diagnosis.

Emerging Trends and Hot Spots of Electrical Impedance Tomography Applications in Clinical Lung Monitoring

Objective

This study explores the emerging trends and hot topics concerning applications on electrical impedance tomography (EIT) in clinical lung monitoring.

Methods

Publications on EIT applications in clinical lung monitoring in 2001–2021 were extracted from the Web of Science Core Collection (WoSCC). The search strategy was “electrical impedance tomography” and “lung.” CiteSpace, a VOS viewer was used to study the citation characteristics, cooperation, and keyword co-occurrence. Moreover, co-cited reference clustering, structural variation analysis (SVA), and future research trends were presented.

Results

Six hundred and thirty-six publications were included for the final analysis. The global annual publications on clinical lung monitoring gradually increased in the last two decades. Germany contributes 32.2% of total global publications. University Medical Center Schleswig-Holstein (84 publications, cited frequency 2,205), Physiological Measurement (105 publications, cited frequency 2,056), and Inéz Frerichs (116 articles, cited frequency 3,609) were the institution, journal, and author with the largest number of article citations in the research field. “Electrical impedance tomography” (occurrences, 304), “mechanical ventilation” (occurrences, 99), and “acute respiratory distress syndrome” (occurrences, 67) were the top most three frequent keywords, “noninvasive monitoring” (Avg, pub, year: 2008.17), and “extracorporeal membrane oxygenation” (Avg, pub, year: 2019.60) were the earliest and latest keywords. The keywords “electrical impedance tomography” (strength 7.88) and co-cited reference “Frerichs I, 2017, THORAX” (strength 47.45) had the highest burst value. “Driving pressure,” “respiratory failure,” and “titration” are the three keywords still maintaining a high brush value until now. The largest and smallest cluster of the co-cited references are “obstructive lung diseases” (#0, size: 97) and “lung perfusion” (#20, size: 5). Co-cited reference “Frerichs I, 2017, THORAX” (modularity change rate: 98.49) has the highest structural variability. Categories with most and least interdisciplinary crossing are “ENGINEERING” and “CRITICAL CARE MEDICINE.”

Conclusions

EIT is a valuable technology for clinical lung monitoring, gradually converting from imaging techniques to the clinic. Research hot spots may continue monitoring techniques, the ventilation distribution of acute respiratory distress syndrome (ARDS), and respiratory therapy strategies. More diversified lung function monitoring studies, such as lung perfusion and interdisciplinary crossing, are potentially emerging research trends.

Evaluation of Pulmonary Structure and Function in Patients with Cystic Fibrosis from Electrical Impedance Tomography Data

Electrical impedance tomography (EIT) is a medical imaging technique in which low frequency, low amplitude electromagnetic fields applied through electrodes on the skin are used to compute the conductivity and/or permittivity inside the body and form functional images from the reconstructed values. This work describes methods of computing EIT-derived surrogate measures of pulmonary function and identifying regions of air trapping and consolidation from functional EIT images. These methods were developed for pediatric patients with cystic fibrosis, for whom a real-time non-ionizing imaging modality can be of great benefit for monitoring disease progression or a pulmonary exacerbation.

Electrical impedance tomography for non-invasive identification of fatty liver infiltrate in overweight individuals

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson's correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = -0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

Monitoring postoperative lung recovery using electrical impedance tomography in post anesthesia care unit: an observational study

With electrical impedance tomography (EIT) recruitment and de-recruitment phenomena can be quantified and monitored at bedside. The aim was to examine the feasibility of EIT with respect to monitor atelectasis formation and resolution in the post anesthesia care unit (PACU). In this observational study, 107 postoperative patients were investigated regarding the presence and recovery of atelectasis described by the EIT-derived parameters Global Inhomogeneity Index (GI Index), tidal impedance variation (TIV), and the changes in end-expiratory lung impedance (ΔEELI). We examined whether the presence of obesity (ADP group) has an influence on pulmonary recovery compared to normal weight patients (NWP group). During the stay at PACU, measurements were taken every 15 min. GI Index, TIV, and ΔEELI were calculated for each time point. 107 patients were monitored and EIT-data of 16 patients were excluded for various reasons. EIT-data of 91 patients were analyzed off-line. Their length of stay averaged 80 min (25th and 75th quartile 52–112). The ADP group demonstrated a significantly higher GI Index at PACU arrival (p < 0.001). This finding disappeared during their stay at the PACU. Additionally, the ADP group showed a significant increase in ΔEELI between PACU arrival and discharge (p = 0.025). Furthermore, TIV showed a significantly lower value during the first 90 min of PACU stay as compared to the time period thereafter (p = 0.036). Our findings demonstrate that obesity has an influence on intraoperative atelectasis formation and de-recruitment during PACU stay. The application of EIT in spontaneously breathing PACU patients seems meaningful in monitoring pulmonary recovery.

Freezing resistance evaluation of rose stems during frost dehardening using electrical impedance tomography

BACKGROUND

Electrical impedance tomography (EIT) has rarely been applied in plant science, particularly to study plant resistance to abiotic and biotic stresses. In this study, we evaluated the freezing resistance of floribunda roses (Rosa Floribunda) during frost dehardening using the EIT technique to identify a new method for rapid and non-destructive measurement of plant freezing resistance.

RESULTS

The current was the excitation source, the boundary voltage value was measured, and then the boundary voltage reconstructed value was formed. Using an imaging algorithm, the two-dimensional (2D) distribution of impedance or impedance variation was reconstructed. The EIT reconstructed values decreased obviously with the decline in freezing temperatures. The EIT reconstructed values of stems had the best fit to the logistic equation, and subsequently, the semi-lethal temperatures were calculated. The freezing resistance results evaluated using EIT reconstructed values were linearly correlated with the results of the traditional electrolyte leakage (EL) method (r = 0.93, P < 0.01).

CONCLUSIONS

In conclusion, after freezing tests, the reconstructed values of EIT images could be used to quantitatively evaluate the freezing resistance of floribunda rose stems. The present study provides a reference for the further application of the EIT technique for non-destructive and rapid detection of plant freezing resistance.

Semi-Siamese U-Net for separation of lung and heart bioimpedance images: A simulation study of thorax EIT

Electrical impedance tomography (EIT) is widely used for bedside monitoring of lung ventilation status. Its goal is to reflect the internal conductivity changes and estimate the electrical properties of the tissues in the thorax. However, poor spatial resolution affects EIT image reconstruction to the extent that the heart and lung-related impedance images are barely distinguishable. Several studies have attempted to tackle this problem, and approaches based on decomposition of EIT images using linear transformations have been developed, and recently, U-Net has become a prominent architecture for semantic segmentation. In this paper, we propose a novel semi-Siamese U-Net specifically tailored for EIT application. It is based on the state-of-the-art U-Net, whose structure is modified and extended, forming shared encoder with parallel decoders and has multi-task weighted losses added to adapt to the individual separation tasks. The trained semi-Siamese U-Net model was evaluated with a test dataset, and the results were compared with those of the classical U-Net in terms of Dice similarity coefficient and mean absolute error. Results showed that compared with the classical U-Net, semi-Siamese U-Net exhibited performance improvements of 11.37% and 3.2% in Dice similarity coefficient, and 3.16% and 5.54% in mean absolute error, in terms of heart and lung-impedance image separation, respectively.

Monitoring lung impedance changes during long-term ventilator-induced lung injury ventilation using electrical impedance tomography

OBJECTIVE

The target of this methodological evaluation was the feasibility of long-term monitoring of changes in lung conditions by time-difference electrical impedance tomography (tdEIT). In contrast to ventilation monitoring by tdEIT, the monitoring of end-expiratory (EELIC) or end-inspiratory (EILIC) lung impedance change always requires a reference measurement.

APPROACH

To determine the stability of the used Pulmovista 500^® EIT system, as a prerequisite it was initially secured on a resistive phantom for 50 h. By comparing the slopes of EELIC for the whole lung area up to 48 h from 36 pigs ventilated at six positive end-expiratory pressure (PEEP) levels from 0 to 18 cmH₂O we found a good agreement (range of r ² = 0.93-1.0) between absolute EIT (aEIT) and tdEIT values. This justified the usage of tdEIT with its superior local resolution compared to aEIT for long-term determination of EELIC.

MAIN RESULTS

The EELIC was between -0.07 Ωm day^-1 at PEEP 4 and -1.04 Ωm day^-1 at PEEP 18 cmH₂O. The complex local time pattern for EELIC was roughly quantified by the new parameter, centre of end-expiratory change (CoEEC), in equivalence to the established centre of ventilation (CoV). The ventrally located mean of the CoV was fairly constant in the range of 42%-46% of thorax diameter; however, on the contrary, the CoEEC shifted from about 40% to about 75% in the dorsal direction for PEEP levels of 14 and 18 cmH₂O.

SIGNIFICANCE

The observed shifts started earlier for higher PEEP levels. Changes of EELI could be precisely monitored over a period of 48 h by tdEIT on pigs.

Pulmonary Ventilation and Pulsatile Perfusion Imaging on Premature Neonates using Simultaneous Multi-Source EIT

We applied our Simultaneous Multi-Source Electrical Impedance Tomography (SMS-EIT) system to detect pulmonary ventilation and pulsatile perfusion on 5 preterm newborns with respiratory distress syndrome under the nasal continuous positive airway pressure (CPAP) treatment. The results show that derived impedance changes have a potential for clinical application to evaluate effects in spontaneously breathing preterm infants with and without CPAP.

Intrapleural Impedance Sensor Real-Time Tracking of Pneumothorax in a Porcine Model of Air Leak

In patients with alveolar-to-pleural air leak due to recent surgery or trauma, clinicians tend to manage chest tubes with suction therapy. Nonsuction therapy is associated with shorter chest tube duration but also a higher risk of pneumothorax. We sought to develop an intrapleural electrical impedance sensor for continuous, real-time monitoring of pneumothorax development in a porcine model of air leak as a means of promoting nonsuction therapy. Using thoracoscopy, 2 chest tubes and the pleural impedance sensor were introduced into the pleural space of 3 pigs. Continuous air leak was introduced through 1 chest tube by carbon dioxide insufflation. The second chest tube was placed to suction then transitioned to no suction at increasingly higher air leaks until pneumothorax developed. Simultaneously, real-time impedance measurements were obtained from the pleural sensor. Fluoroscopy spot images were captured to verify the presence or absence of pneumothorax. Statistical Analysis Software was used throughout. With the chest tube on suction, a fully expanded lung was identified by a distinct pleural electrical impedance respiratory waveform. With transition of the chest tube to water seal, loss of contact of the sensor with the lung resulted in an immediate measurement of infinite electrical impedance. Pneumothorax resolution by restoring suction therapy was detected in real time by a return of the normal respiratory impedance waveform. Pleural electrical impedance monitoring detected pneumothorax development and resolution in real time. This simple technology has the potential to improve the safety and quality of chest tube management.

A 122 fps, 1 MHz Bandwidth Multi-Frequency Wearable EIT Belt Featuring Novel Active Electrode Architecture for Neonatal Thorax Vital Sign Monitoring

A highly integrated, wearable electrical impedance tomography (EIT) belt for neonatal thorax vital multiple sign monitoring is presented. The belt has 16 active electrodes. Each electrode has an application-specific integrated circuit (ASIC) connected to it. The ASIC contains a fully differential current driver, a high-performance instrumentation amplifier, a digital controller, and multiplexors. The belt features a new active electrode architecture that allows programmable flexible electrode current drive and voltage sense patterns under simple digital control. It provides intimate connections to the electrodes for the current drive and to the IA for direct differential voltage measurement, providing superior common-mode rejection ratio. The ASIC was designed in a CMOS 0.35-μm high-voltage technology. The high-specification EIT belt has an image frame rate of 122 fps, a wide operating bandwidth of 1 MHz, and multi-frequency operation. It measures impedance with 98% accuracy and has less than 0.5 Ω and 1° variation across all possible channels. The image results confirmed the advantage of the new active electrode architecture and the benefit of wideband, multi-frequency EIT operation. The system successfully captured high-quality lung-respiration EIT images, breathing cycle, and heart rate. It can also provide boundary-shape information by using an array of MEMS sensors interfaced to the ASICs.

Electrical Impedance Methods in Neuromuscular Assessment: An Overview

Electrical impedance methods have been used as evaluation tools in biological and medical science for well over 100 years. However, only recently have these techniques been applied specifically to the evaluation of conditions affecting nerve and muscle. This specific application, termed electrical impedance myography (EIM), is finding wide application as it can provide a quantitative index of muscle condition that can assist with diagnosis, track disease progression, and assess the beneficial impact of therapy. Using noninvasive surface methods, EIM has been studied in a number of conditions ranging from amyotrophic lateral sclerosis to muscular dystrophy to disuse atrophy. Data support that the technique is sensitive to disease status and can offer the possibility of performing clinical trials with fewer subjects than would otherwise be possible. Recent advances in the field include improved approaches for using EIM as a "virtual biopsy" and the development of combined needle impedance-electromyography technology.

The ACE1 Electrical Impedance Tomography System for Thoracic Imaging

The design and performance of the ACE1 (Active Complex Electrode) electrical impedance tomography system for single-ended phasic voltage measurements is presented. The design of the hardware and calibration procedures allow for reconstruction of conductivity and permittivity images. Phase measurement is achieved with the ACE1 active electrode circuit which measures the amplitude and phase of the voltage and the applied current at the location at which current is injected into the body. An evaluation of the system performance under typical operating conditions includes details of demodulation and calibration and an in-depth look at insightful metrics, such as signal-to-noise ratio variations during a single current pattern. Static and dynamic images of conductivity and permittivity are presented from ACE1 data collected on tank phantoms and human subjects to illustrate the system's utility.

Integrated EIT system for functional lung ventilation imaging

Background

Electrical impedance tomography (EIT) has been used for functional lung imaging of regional air distributions during mechanical ventilation in intensive care units (ICU). From numerous clinical and animal studies focusing on specific lung functions, a consensus about how to use the EIT technique has been formed lately. We present an integrated EIT system implementing the functions proposed in the consensus. The integrated EIT system could improve the usefulness when monitoring of mechanical ventilation for lung protection so that it could facilitate the clinical acceptance of this new technique.

Methods

Using a custom-designed 16-channel EIT system with 50 frames/s temporal resolution, the integrated EIT system software was developed to implement five functional images and six EIT measures that can be observed in real-time screen view and analysis screen view mode, respectively. We evaluated the performance of the integrated EIT system with ten mechanically ventilated porcine subjects in normal and disease models.

Results

Quantitative and simultaneous imaging of tidal volume (TV), end-expiratory lung volume change (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\triangle$$\end{document}▵EELV), compliance, ventilation delay, and overdistension/collapse images were performed. Clinically useful parameters were successfully extracted including anterior/posterior ventilation ratio (A/P ratio), center of ventilation (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{CoV}}_{{x}}$$\end{document}CoVx, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathrm{CoV}}_{{y}}$$\end{document}CoVy), global inhomogeneity (GI), coefficient of variation (CV), ventilation delay and percentile of overdistension/collapse. The integrated EIT system was demonstrated to suggest an optimal positive end-expiratory pressure (PEEP) for lung protective ventilation in normal and in the disease model of an acute injury. Optimal PEEP for normal and disease model was 2.3 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$7.9 \, {\mathrm{cmH}}_{2}\mathrm{O}$$\end{document}7.9cmH2O, respectively.

Conclusions

The proposed integrated approach for functional lung ventilation imaging could facilitate clinical acceptance of the bedside EIT imaging method in ICU. Future clinical studies of applying the proposed methods to human subjects are needed to show the clinical significance of the method for lung protective mechanical ventilation and mechanical ventilator weaning in ICU.

Comparison of bolus- and filtering-based EIT measures of lung perfusion in an animal model

OBJECTIVE

Two main functional imaging approaches have been used to measure regional lung perfusion using electrical impedance tomography (EIT): venous injection of a hypertonic saline contrast agent and imaging of its passage through the heart and lungs, and digital filtering of heart-frequency impedance changes over sequences of EIT images. This paper systematically compares filtering-based perfusion estimates and bolus injection methods to determine to which degree they are related.

APPROACH

EIT data was recorded on seven mechanically ventilated newborn lambs in which ventilation distribution was varied through changes in posture between prone, supine, left- and right-lateral positions. Perfusion images were calculated using frequency filtering and ensemble averaging during both ventilation and apnoea time segments for each posture to compare against contrast agent-based methods using Jaccard distance score.

MAIN RESULTS

Using bolus-based EIT measures of lung perfusion as the reference frequency filtering techniques performed better than ensemble averaging and both techniques performed equally well across apnoea and ventilation data segments.

SIGNIFICANCE

Our results indicate the potential for use of filtering-based EIT measures of heart-frequency activity as a non-invasive proxy for contrast agent injection-based measures of lung perfusion.

A Review of Electrical Impedance Tomography in Lung Applications: Theory and Algorithms for Absolute Images

Electrical Impedance Tomography (EIT) is under fast development, the present paper is a review of some procedures that are contributing to improve spatial resolution and material properties accuracy, admitivitty or impeditivity accuracy. A review of EIT medical applications is presented and they were classified into three broad categories: ARDS patients, obstructive lung diseases and perioperative patients. The use of absolute EIT image may enable the assessment of absolute lung volume, which may significantly improve the clinical acceptance of EIT. The Control Theory, the State Observers more specifically, have a developed theory that can be used for the design and operation of EIT devices. Electrode placement, current injection strategy and electrode electric potential measurements strategy should maximize the number of observable and controllable directions of the state vector space. A non-linear stochastic state observer, the Unscented Kalman Filter, is used directly for the reconstruction of absolute EIT images. Historically, difference images were explored first since they are more stable in the presence of modelling errors. Absolute images require more detailed models of contact impedance, stray capacitance and properly refined finite element mesh where the electric potential gradient is high. Parallelization of the forward program computation is necessary since the solution of the inverse problem often requires frequent solutions of the forward problem. Several reconstruction algorithms benefit by the Bayesian inverse problem approach and the concept of prior information. Anatomic and physiologic information are used to form the prior information. An already tested methodology is presented to build the prior probability density function using an ensemble of CT scans and in vivo impedance measurements. Eight absolute EIT image algorithms are presented.

Comparing D-bar and common regularization-based methods for electrical impedance tomography

Objective:

To compare D-bar difference reconstruction with regularized linear reconstruction in electrical impedance tomography.

Approach:

A standard regularized linear approach using a Laplacian penalty and the GREIT method for comparison to the D-bar difference images. Simulated data was generated using a circular phantom with small objects, as well as a ‘Pac-Man’ shaped conductivity target. An L-curve method was used for parameter selection in both D-bar and the regularized methods.

Main results:

We found that the D-bar method had a more position independent point spread function, was less sensitive to errors in electrode position and behaved differently with respect to additive noise than the regularized methods.

Significance:

The results allow a novel pathway between traditional and D-bar algorithm comparison.

Global and regional degree of obstruction determined by electrical impedance tomography in patients with obstructive ventilatory defect

Background

Electrical impedance tomography is a continuous imaging method capable of measuring lung volume changes. The purpose of this study was to examine whether EIT was capable of evaluating the degree of obstructive ventilatory defect (OVD) on the global and regional level.

Methods

41 healthy subjects with no lung diseases and 67 subjects suffering from obstructive lung diseases were examined using EIT and spirometry during forced vital capacity (FVC) maneuver. The subjects were divided into control group (n = 41), early airway obstruction group (n = 26), mild group (n = 17), moderate group (n = 16) and severe group (n = 8) according to the degree of obstruction. Forced expiratory volume in 1 second (FEV₁) and FEV₁/FVC were determined by EIT. The mode index (MI) was proposed to evaluate the degree of global and regional obstruction; the effectiveness of MI was validated by evaluating posture related change of lung emptying capacity in sitting and supine postures; the degree of regional obstruction was determined according to the cut-off values of MI obtained from receiver operating characteristic (ROC) analysis; regional obstruction was located in the four-quadrant region of interest (ROI) and the contour-map ROI with contour lines at the cut-off values of MI.

Results

Significant differences were found between different groups (P<0.05) and the global MI was 0.93±0.03, 0.86±0.05, 0.81±0.09, 0.73±0.09 and 0.60±0.11 (mean ±SD), respectively. The cut-off MI value was 0.90, 0.83, 0.77, and 0.65, respectively.

Conclusion

The results indicated the potential of EIT to evaluate the degree of obstruction in patients with obstructive ventilatory defect on the global and regional level.

Weaning from Mechanical Ventilation in ARDS: Aspects to Think about for Better Understanding, Evaluation, and Management

Acute respiratory distress syndrome (ARDS) is characterized by severe inflammatory response and hypoxemia. The use of mechanical ventilation (MV) for correction of gas exchange can cause worsening of this inflammatory response, called “ventilator-induced lung injury” (VILI). The process of withdrawing mechanical ventilation, referred to as weaning from MV, may cause worsening of lung injury by spontaneous ventilation. Currently, there are few specific studies in patients with ARDS. Herein, we reviewed the main aspects of spontaneous ventilation and also discussed potential methods to predict the failure of weaning in this patient category. We also reviewed new treatments (modes of mechanical ventilation, neuromuscular blocker use, and extracorporeal membrane oxygenation) that could be considered in weaning ARDS patients from MV.

Regional lung ventilation and perfusion by electrical impedance tomography compared to single-photon emission computed tomography

OBJECTIVE

Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows real-time monitoring of regional lung ventilation ([Formula: see text]) in intensive care patients at bedside. However, for improved guidance of ventilation therapy it would be beneficial to obtain regional ventilation-to-perfusion ratio ([Formula: see text]) by EIT.

APPROACH

In order to further explore the feasibility, we first evaluate a model-based approach, based on semi-negative matrix factorization and a gamma-variate model, to extract regional lung perfusion ([Formula: see text]) from EIT measurements. Subsequently, a combined validation of both [Formula: see text] and [Formula: see text] measured by EIT against single-photon emission computed tomography (SPECT) is performed on data acquired as part of a porcine animal trial. Four pigs were ventilated at two different levels of positive end-expiratory pressure (PEEP 0 and 15 cm H₂O, respectively) in randomized order. Repeated injections of an EIT contrast agent (NaCl 10%) and simultaneous SPECT measurements of [Formula: see text] (81^mKr gas) and [Formula: see text] (99^mTc-labeled albumin) were performed.

MAIN RESULTS

Both [Formula: see text] and [Formula: see text] from EIT and SPECT were compared by correlation analysis. Very strong (r ²  =  0.94 to 0.95) correlations were found for [Formula: see text] and [Formula: see text] in the dorsal-ventral direction at both PEEP levels. Moderate (r ²  =  0.36 to 0.46) and moderate to strong (r ²  =  0.61 to 0.82) correlations resulted for [Formula: see text] and [Formula: see text] in the right-left direction, respectively.

SIGNIFICANCE

The results of combined validation indicate that monitoring of [Formula: see text] and [Formula: see text] by EIT is possible. However, care should be taken when trying to quantify [Formula: see text] by EIT, as imaging artefacts and model bias may void necessary spatial matching.

Pleural electrical impedance is a sensitive, real-time indicator of pneumothorax

BACKGROUND

Chest tube management protocols, particularly in patients with alveolar-pleural air leak due to recent surgery or trauma, are limited by concerns over safety, especially concerns about rapid and occult development of pneumothorax. A continuous, real-time monitor of pneumothorax could improve the quality and safety of chest tube management. We developed a rat model of pneumothorax to test a novel approach of measuring electrical impedance within the pleural space as a monitor of lung expansion.

MATERIALS AND METHODS

Anesthetized Sprague-Dawley rats underwent right thoracotomy. A novel impedance sensor and a thoracostomy tube were introduced into the right pleural space. Pneumothorax of varying volumes ranging from 0.2 to 20 mL was created by syringe injection of air via the thoracostomy tube. Electrical resistance measurements from the pleural sensor and fluoroscopic images were obtained at baseline and after the creation of pneumothorax and results compared.

RESULTS

A statistically significant, dose-dependent increase in electrical resistance was observed with increasing volume of pneumothorax. Resistance measurement allowed for continuous, real-time monitoring of pneumothorax development and the ability to track pneumothorax resolution by aspiration of air via the thoracostomy tube. Pleural resistance measurement demonstrated 100% sensitivity and specificity for all volumes of pneumothorax tested and was significantly more sensitive for pneumothorax detection than fluoroscopy.

CONCLUSIONS

The electrical impedance-based pleural space sensor described in this study provided sensitive and specific pneumothorax detection, which was superior to radiographic analysis. Real-time, continuous monitoring for pneumothorax has the potential to improve the safety, quality, and efficiency of postoperative chest tube management.

Non-Invasive Electrical Impedance Tomography for Multi-Scale Detection of Liver Fat Content

Introduction: Obesity is associated with an increased risk of nonalcoholic fatty liver disease (NAFLD). While Magnetic Resonance Imaging (MRI) is a non-invasive gold standard to detect fatty liver, we demonstrate a low-cost and portable electrical impedance tomography (EIT) approach with circumferential abdominal electrodes for liver conductivity measurements.

Methods and Results: A finite element model (FEM) was established to simulate decremental liver conductivity in response to incremental liver lipid content. To validate the FEM simulation, we performed EIT imaging on an ex vivo porcine liver in a non-conductive tank with 32 circumferentially-embedded electrodes, demonstrating a high-resolution output given a priori information on location and geometry. To further examine EIT capacity in fatty liver detection, we performed EIT measurements in age- and gender-matched New Zealand White rabbits (3 on normal, 3 on high-fat diets). Liver conductivity values were significantly distinct following the high-fat diet (p = 0.003 vs. normal diet, n=3), accompanied by histopathological evidence of hepatic fat accumulation. We further assessed EIT imaging in human subjects with MRI quantification for fat volume fraction based on Dixon procedures, demonstrating average liver conductivity of 0.331 S/m for subjects with low Body-Mass Index (BMI < 25 kg/m²) and 0.286 S/m for high BMI (> 25 kg/m²).

Conclusion: We provide both the theoretical and experimental framework for a multi-scale EIT strategy to detect liver lipid content. Our preliminary studies pave the way to enhance the spatial resolution of EIT as a marker for fatty liver disease and metabolic syndrome.

Accuracy and reliability of noninvasive stroke volume monitoring via ECG-gated 3D electrical impedance tomography in healthy volunteers

Cardiac output (CO) and stroke volume (SV) are parameters of key clinical interest. Many techniques exist to measure CO and SV, but are either invasive or insufficiently accurate in clinical settings. Electrical impedance tomography (EIT) has been suggested as a noninvasive measure of SV, but inconsistent results have been reported. Our goal is to determine the accuracy and reliability of EIT-based SV measurements, and whether advanced image reconstruction approaches can help to improve the estimates. Data were collected on ten healthy volunteers undergoing postural changes and exercise. To overcome the sensitivity to heart displacement and thorax morphology reported in previous work, we used a 3D EIT configuration with 2 planes of 16 electrodes and subject-specific reconstruction models. Various EIT-derived SV estimates were compared to reference measurements derived from the oxygen uptake. Results revealed a dramatic impact of posture on the EIT images. Therefore, the analysis was restricted to measurements in supine position under controlled conditions (low noise and stable heart and lung regions). In these measurements, amplitudes of impedance changes in the heart and lung regions could successfully be derived from EIT using ECG gating. However, despite a subject-specific calibration the heart-related estimates showed an error of 0.0 ± 15.2 mL for absolute SV estimation. For trending of relative SV changes, a concordance rate of 80.9% and an angular error of -1.0 ± 23.0° were obtained. These performances are insufficient for most clinical uses. Similar conclusions were derived from lung-related estimates. Our findings indicate that the key difficulty in EIT-based SV monitoring is that purely amplitude-based features are strongly influenced by other factors (such as posture, electrode contact impedance and lung or heart conductivity). All the data of the present study are made publicly available for further investigations.

Higher order total variation regularization for EIT reconstruction

Electrical impedance tomography (EIT) attempts to reveal the conductivity distribution of a domain based on the electrical boundary condition. This is an ill-posed inverse problem; its solution is very unstable. Total variation (TV) regularization is one of the techniques commonly employed to stabilize reconstructions. However, it is well known that TV regularization induces staircase effects, which are not realistic in clinical applications. To reduce such artifacts, modified TV regularization terms considering a higher order differential operator were developed in several previous studies. One of them is called total generalized variation (TGV) regularization. TGV regularization has been successively applied in image processing in a regular grid context. In this study, we adapted TGV regularization to the finite element model (FEM) framework for EIT reconstruction. Reconstructions using simulation and clinical data were performed. First results indicate that, in comparison to TV regularization, TGV regularization promotes more realistic images. Graphical abstract Reconstructed conductivity changes located on selected vertical lines. For each of the reconstructed images as well as the ground truth image, conductivity changes located along the selected left and right vertical lines are plotted. In these plots, the notation GT in the legend stands for ground truth, TV stands for total variation method, and TGV stands for total generalized variation method. Reconstructed conductivity distributions from the GREIT algorithm are also demonstrated.

Computational method for estimating boundary of abdominal subcutaneous fat for absolute electrical impedance tomography

Abdominal fat accumulation is considered an essential indicator of human health. Electrical impedance tomography has considerable potential for abdominal fat imaging because of the low specific conductivity of human body fat. In this paper, we propose a robust reconstruction method for high-fidelity conductivity imaging by abstraction of the abdominal cross section using a relatively small number of parameters. Toward this end, we assume homogeneous conductivity in the abdominal subcutaneous fat area and characterize its geometrical shape by parameters defined as the ratio of the distance from the center to boundary of subcutaneous fat to the distance from the center to outer boundary in 64 equiangular directions. To estimate the shape parameters, the sensitivity of the noninvasively measured voltages with respect to the shape parameters is formulated for numerical optimization. Numerical simulations are conducted to demonstrate the validity of the proposed method. A 3-dimensional finite element method is used to construct a computer model of the human abdomen. The inverse problems of shape parameters and conductivities are solved concurrently by iterative forward and inverse calculations. As a result, conductivity images are reconstructed with a small systemic error of less than 1% for the estimation of the subcutaneous fat area. A novel method is devised for estimating the boundary of the abdominal subcutaneous fat. The fidelity of the overall reconstructed image to the reference image is significantly improved. The results demonstrate the possibility of realization of an abdominal fat scanner as a low-cost, radiation-free medical device.

Electrical impedance tomography: Amplitudes of cardiac related impedance changes in the lung are highly position dependent

BACKGROUND

Electrical impedance tomography (EIT) is used on the thorax to measure impedance changes due to the presence of air and blood in the lung. This experimental study was performed to investigate the effect of posture on cardiac and respiratory related impedance changes.

METHODS

EIT measurements were performed on 14 healthy subjects in left-, right lateral, prone, supine and upright positions. Simultaneously, tidal volume was recorded with an ultrasonic flowmeter. For image reconstruction, the classic Sheffield back-projection and three variants of the modern GREIT algorithm were applied with two different reference frames. Amplitudes of cardiac- and respiratory impedance changes were extracted and compared between the positions.

RESULTS

We found significant differences in both cardiac and respiratory amplitudes between postures. Especially, supine and upright positions showed dramatic changes in amplitude. These differences between postures were unaffected by the change of reference frames in all reconstruction methods except of the classic Sheffield back projection. Possible sources that explain the observed posture dependency are discussed.

CONCLUSION

Researchers and clinicians need to be aware of this phenomenon when comparing EIT amplitudes in different body positions.

Ventilation inhomogeneity in obstructive lung diseases measured by electrical impedance tomography: a simulation study

Electrical impedance tomography (EIT) has mostly been used in the Intensive Care Unit (ICU) to monitor ventilation distribution but is also promising for the diagnosis in spontaneously breathing patients with obstructive lung diseases. Beside tomographic images, several numerical measures have been proposed to quantitatively assess the lung state. In this study two common measures, the 'Global Inhomogeneity Index' and the 'Coefficient of Variation' were compared regarding their capability to reflect the severity of lung obstruction. A three-dimensional simulation model was used to simulate obstructed lungs, whereby images were reconstructed on a two-dimensional domain. Simulations revealed that minor obstructions are not adequately recognized in the reconstructed images and that obstruction above and below the electrode plane may result in misleading values of inhomogeneity measures. EIT measurements on several electrode planes are necessary to apply these measures in patients with obstructive lung diseases in a promising manner.

Impact of four different recumbencies on the distribution of ventilation in conscious or anaesthetized spontaneously breathing beagle dogs: An electrical impedance tomography study

The aim was to examine the effects of recumbency and anaesthesia on distribution of ventilation in beagle dogs using Electrical Impedance Tomography (EIT). Nine healthy beagle dogs, aging 3.7±1.7 (mean±SD) years and weighing 16.3±1.6 kg, received a series of treatments in a fixed order on a single occasion. Conscious dogs were positioned in right lateral recumbency (RLR) and equipped with 32 EIT electrodes around the thorax. Following five minutes of equilibration, two minutes of EIT recordings were made in each recumbency in the following order: RLR, dorsal (DR), left (LLR) and sternal (SR). The dogs were then positioned in RLR, premedicated (medetomidine 0.01, midazolam 0.1, butorphanol 0.1 mg kg^-1 iv) and pre-oxygenated. Fifteen minutes later anaesthesia was induced with 1 mg kg^-1 propofol iv and maintained with propofol infusion (0.1–0.2 mg kg^-1 minute^-1 iv). After induction, the animals were intubated and allowed to breathe spontaneously (FIO₂ = 1). Recordings of EIT were performed again in four recumbencies similarly to conscious state. Centre of ventilation (COV) and global inhomogeneity (GI) index were calculated from the functional EIT images. Repeated-measures ANOVA and Bonferroni tests were used for statistical analysis (p < 0.05). None of the variables changed in the conscious state. During anaesthesia left-to-right COV increased from 46.8±2.8% in DR to 49.8±2.9% in SR indicating a right shift, and ventral-to-dorsal COV increased from 49.8±1.7% in DR to 51.8±1.1% in LLR indicating a dorsal shift in distribution of ventilation. Recumbency affected distribution of ventilation in anaesthetized but not in conscious dogs. This can be related to loss of respiratory muscle tone (e.g. diaphragm) and changes in thoracic shape. Changing position of thoraco-abdominal organs under the EIT belt should be considered as alternative explanation of these findings.

Real-Time Implementation of Calderón's Method on Subject-Specific Domains

A real-time implementation of Calderón's method for the reconstruction of a 2-D conductivity from electrical impedance tomography data is presented, in which domain-specific modeling is taken into account. This is the first implementation of Calderón's method that accounts for correct modeling of non-symmetric domain boundaries in image reconstruction. The domain-specific Calderón's method is derived and reconstructions from experimental tank data are presented, quantifying the distortion when correct modeling is not included in the reconstruction algorithm. Reconstructions from human subject volunteers are presented, demonstrating the method's effectiveness for imaging changes due to ventilation and perfusion in the human thorax.

Lung imaging: how to get better look inside the lung

In the last years, imaging has played a key role in the diagnosis and monitoring and critical illness, including acute respiratory distress syndrome (ARDS). Chest X-ray (CXR) and computed tomography (CT) are the conventional techniques most performed in the critically ill patients, the latter being the gold standard to assess lung aeration in ARDS patients. In addition, two bedside techniques are now gaining popularity alongside the conventional ones: lung ultrasound (LUS) and electrical impedance tomography (EIT). These techniques do not involve the use of ionizing radiations, are non-invasive and relatively easy to use, and are under extensive investigation as a complement, and for some application a substitution of conventional techniques. At last, positron emission tomography (PET) and magnetic resonance imaging (MRI) can provide functional information on the lung and respiratory function, and are increasingly used in research to improve the understanding of the pathophysiological mechanisms underlying ARDS. The purpose of this review is to give an up-to-date overview of the conventional and emerging imaging techniques available the diagnosis and management of patients with ARDS.

Imaging of regional air distributions in porcine lungs using high-performance electrical impedance tomography system

Electrical impedance tomography (EIT) allows functional imaging of regional lung ventilation for real-time bedside monitoring of mechanically ventilated patients. Images showing time-changes of regional air distributions in the lungs can provide valuable diagnostic information for lung protective mechanical ventilation. This paper reports in vivo porcine imaging experiments of regional lung ventilation using a 16-channel parallel EIT system. Real-time time-difference chest images of 10 animals were reconstructed during mechanical ventilations with a temporal resolution of 50 frame/s. Analyzing the images together with the airway volume-pressure information from the mechanical ventilator, we could successfully produce regional compliance images at PEEP (positive end expiratory pressure) titration. From in vivo animal experiments, we propose the method as a continuous monitoring means for LPV (lung protective ventilation).

Evaluation of lung ventilation distribution in chronic obstructive pulmonary disease patients using the global inhomogeneity index

The global inhomogeneity (GI) index is a electrical impedance tomography (EIT) parameter that quantifies the tidal volume distribution within the lung. In this work the global inhomogeneity index was computed for twenty subjects in order to evaluate his potential use in the detection and follow up of chronic obstructive pulmonary disease (COPD) patients. EIT data of 17 subjects were acquired: 14 patients with the main diagnoses of COPD and 3 healthy subjects which served as a control group. Two or three datasets of around 30 seconds were acquired at 33 scans/s and analysed for each subject. After reconstruction, a tidal EIT image was computed for each breathing cycle and a GI index calculated from it. Results have shown significant differences in GI values between the two groups (0.745 ± 0.007 for COPD and 0.668 ± 0.006 for lung-healthy subject, p <; 0.005). The GI values obtained for each subject have shown small variance between them, which is a good indication of stability. The results suggested that the GI may be useful for the identification and follow up of ventilation problems in patients with COPD.

Coupling of EIT with computational lung modeling for predicting patient-specific ventilatory responses

Providing optimal personalized mechanical ventilation for patients with acute or chronic respiratory failure is still a challenge within a clinical setting for each case anew. In this article, we integrate electrical impedance tomography (EIT) monitoring into a powerful patient-specific computational lung model to create an approach for personalizing protective ventilatory treatment. The underlying computational lung model is based on a single computed tomography scan and able to predict global airflow quantities, as well as local tissue aeration and strains for any ventilation maneuver. For validation, a novel “virtual EIT” module is added to our computational lung model, allowing to simulate EIT images based on the patient's thorax geometry and the results of our numerically predicted tissue aeration. Clinically measured EIT images are not used to calibrate the computational model. Thus they provide an independent method to validate the computational predictions at high temporal resolution. The performance of this coupling approach has been tested in an example patient with acute respiratory distress syndrome. The method shows good agreement between computationally predicted and clinically measured airflow data and EIT images. These results imply that the proposed framework can be used for numerical prediction of patient-specific responses to certain therapeutic measures before applying them to an actual patient. In the long run, definition of patient-specific optimal ventilation protocols might be assisted by computational modeling.

NEW & NOTEWORTHY In this work, we present a patient-specific computational lung model that is able to predict global and local ventilatory quantities for a given patient and any selected ventilation protocol. For the first time, such a predictive lung model is equipped with a virtual electrical impedance tomography module allowing real-time validation of the computed results with the patient measurements. First promising results obtained in an acute respiratory distress syndrome patient show the potential of this approach for personalized computationally guided optimization of mechanical ventilation in future.

Signal-to-Noise Ratio Analysis of a Phase-Sensitive Voltmeter for Electrical Impedance Tomography

In this paper, thorough analysis along with mathematical derivations of the matched filter for a voltmeter used in electrical impedance tomography systems are presented. The effect of the random noise in the system prior to the matched filter, generated by other components, are considered. Employing the presented equations allow system/circuit designers to find the maximum tolerable noise prior to the matched filter that leads to the target signal-to-noise ratio (SNR) of the voltmeter, without having to over-design internal components. A practical model was developed that should fall within 2 dB and 5 dB of the median SNR measurements of signal amplitude and phase, respectively. In order to validate our claims, simulation and experimental measurements have been performed with an analog-to-digital converter (ADC) followed by a digital matched filter, while the noise of the whole system was modeled as the input referred at the ADC input. The input signal was contaminated by a known value of additive white Gaussian noise (AWGN) noise, and the noise level was swept from 3% to 75% of the least significant bit (LSB) of the ADC. Differences between experimental and both simulated and analytical SNR values were less than 0.59 and 0.35 dB for RMS values ≥ 20% of an LSB and less than 1.45 and 2.58 dB for RMS values < 20% of an LSB for the amplitude and phase, respectively. Overall, this study provides a practical model for circuit designers in EIT, and a more accurate error analysis that was previously missing in EIT literature.

A Versatile and Reproducible Multi-Frequency Electrical Impedance Tomography System

A highly versatile Electrical Impedance Tomography (EIT) system, nicknamed the ScouseTom, has been developed. The system allows control over current amplitude, frequency, number of electrodes, injection protocol and data processing. Current is injected using a Keithley 6221 current source, and voltages are recorded with a 24-bit EEG system with minimum bandwidth of 3.2 kHz. Custom PCBs interface with a PC to control the measurement process, electrode addressing and triggering of external stimuli. The performance of the system was characterised using resistor phantoms to represent human scalp recordings, with an SNR of 77.5 dB, stable across a four hour recording and 20 Hz to 20 kHz. In studies of both haeomorrhage using scalp electrodes, and evoked activity using epicortical electrode mats in rats, it was possible to reconstruct images matching established literature at known areas of onset. Data collected using scalp electrode in humans matched known tissue impedance spectra and was stable over frequency. The experimental procedure is software controlled and is readily adaptable to new paradigms. Where possible, commercial or open-source components were used, to minimise the complexity in reproduction. The hardware designs and software for the system have been released under an open source licence, encouraging contributions and allowing for rapid replication.