Electrical Impedance Tomography Measurements Research Articles

Dynamic Relative Regional Lung Strain Estimated by Electrical Impedance Tomography in an Experimental Model of ARDS.

To analyze the role of PEEP on dynamic relative regional strain (DRRS) in a model of ARDS, respective maps were generated by electrical impedance tomography (EIT). Eight ARDS pigs submitted to PEEP steps of 0, 5, 10, and 15 cm H2O at fixed ventilation were evaluated by EIT images. DRRS was calculated as (VT-EIT/EELI)/(VT-EIT[15PEEP]/EELI[15PEEP]), where the tidal volume (VT)-EIT and end-expiratory lung impedance (EELI) are the tidal and end-expiratory change in lung impedance, respectively. The measurement at 15 PEEP was taken as reference (end-expiratory transpulmonary pressure > 0 cm H2O). The relationship between EIT variables (center of ventilation, EELI, and DRRS) and airway pressures was assessed with mixed-effects models using EIT measurements as dependent variables and PEEP as fixed-effect variable. At constant ventilation, respiratory compliance increased progressively with PEEP (lowest value at zero PEEP 10 ± 3 mL/cm H2O and highest value at 15 PEEP 16 ± 6 mL/cm H2O; P < .001), whereas driving pressure decreased with PEEP (highest value at zero PEEP 34 ± 6 cm H2O and lowest value at 15 PEEP 21 ± 4 cm H2O; P < .001). The mixed-effect regression models showed that the center of ventilation moved to dorsal lung areas with a slope of 1.81 (1.44-2.18) % points by each cm H2O of PEEP; P < .001. EELI increased with a slope of 0.05 (0.02-0.07) (arbitrary units) for each cm H2O of PEEP; P < .001. DRRS maps showed that local strain in ventral lung areas decreased with a slope of -0.02 (-0.24 to 0.15) with each cm H2O increase of PEEP; P < .001. EIT-derived DRRS maps showed high strain in ventral lung zones at low levels of PEEP. The findings suggest overdistention of the baby lung.

MO380: Bio-Conductivity Measurement for Electrical Impedance Tomography (EIT) in Chronic Kidney Disease—A Non-Invasive and Portable Monitoring Approach

Abstract BACKGROUND AND AIMS Chronic kidney disease (CKD) is an escalating global health concern, and non-invasive means for early CKD detection is eagerly awaited. Kidneys are water- and electrolytes-rich organs with good bio-conductivity. Kidney fibrosis and tubular atrophy are characteristic pathological changes in CKD [1], and is associated with restricted blood perfusion, fluid diffusion [2,3] and hence reduced bio-conductivity. Electrical impedance tomography (EIT) emerges as a non-invasive, ionizing radiation-free imaging technique measuring dielectric properties of the body parts [4]. This study investigated the relationship of EIT indices and renal function in patients with various stages of CKD. METHOD We prospectively recruited 98 patients with different stages of CKD (Stage 1, n = 16; Stage 2, n = 15; Stage 3, n = 20, Stage 4, n = 36 and Stage 5, n = 11). EIT measurements were performed at two frequencies (33.6 and 100 kHz) using a portable EIT device with an electrode belt consisting of 16 gel electrodes. EIT data was pre-processed and reconstructed as mean conductivity maps. Frequency differencing was then performed between conductivity maps at two frequencies. Kidney-related dielectric parameters were extracted around the kidney region located at lower one-third of the frequency differencing conductivity map. Conductivity changes between frequencies were then computed and further regressed with individual biometrics. Predicted eGFR values was then computed and compared with the standard eGFR scores to evaluate its effectiveness on classifying CDK stages. RESULTS The detected mean bio-conductivity changes were −3.9, −67.5, −133.5, −212.6 and −294.7 (a.u.) in patients with CKD Stage 1, 2, 3, 4 and 5, respectively (Fig. 1A). Patients with more advanced stages of CKD tend to show more reduction in bio-conductivity, and eGFR correlated positively with reduction in bio-conductivity (R2 = 0.37, P &amp;lt; 0.001) (Fig. 1B). EIT-predicted eGFR (eGFREIT) was further computed by the captured conductivity changes and individual biometrics (Fig. 2). eGFREIT showed significant correlation with eGFR measured by blood tests (R2 = 0.54, P &amp;lt; 0.001). CONCLUSION EIT showed good correlation with renal function changes in CKD patients, and thus holds promise to be developed into a non-invasive and portable device for early CKD detection in both clinical and community settings.

Sensitivity Analysis Highlights the Importance of Accurate Head Models for Electrical Impedance Tomography Monitoring of Intracerebral Hemorrhagic Stroke.

Electrical impedance tomography (EIT) has been proposed as a novel tool for diagnosing stroke. However, so far, the clinical feasibility is unresolved. In this study, we aim to investigate the need for accurate head modeling in EIT and how the inhomogeneities of the head contribute to the EIT measurement and affect its feasibility in monitoring the progression of a hemorrhagic stroke. We compared anatomically detailed six- and three-layer finite element models of a human head and computed the resulting scalp electrode potentials and the lead fields of selected electrode configurations. We visualized the resulting EIT measurement sensitivity distributions, computed the scalp electrode potentials, and examined the inverse imaging with selected cases. The effect of accurate tissue geometry and conductivity values on the EIT measurement is assessed with multiple different hemorrhagic perturbation locations and sizes. Our results show that accurate tissue geometries and conductivity values inside the cranial cavity, especially the highly conductive cerebrospinal fluid, significantly affect EIT measurement sensitivity distribution and measured potentials. We can conclude that the three-layer head models commonly used in EIT literature cannot depict the current paths correctly in the head. Thus, our study highlights the need to consider the detailed geometry of the cerebrospinal fluid (CSF) in EIT. The results clearly show that the CSF should be considered in the head EIT calculations.

Impedance-Optical Dual-Modal Cell Culture Imaging With Learning-Based Information Fusion.

While Electrical Impedance Tomography (EIT) has found many biomedicine applications, better image quality is needed to provide quantitative analysis for tissue engineering and regenerative medicine. This paper reports an impedance-optical dual-modal imaging framework that primarily targets at high-quality 3D cell culture imaging and can be extended to other tissue engineering applications. The framework comprises three components, i.e., an impedance-optical dual-modal sensor, the guidance image processing algorithm, and a deep learning model named multi-scale feature cross fusion network (MSFCF-Net) for information fusion. The MSFCF-Net has two inputs, i.e., the EIT measurement and a binary mask image generated by the guidance image processing algorithm, whose input is an RGB microscopic image. The network then effectively fuses the information from the two different imaging modalities and generates the final conductivity image. We assess the performance of the proposed dual-modal framework by numerical simulation and MCF-7 cell imaging experiments. The results show that the proposed method could improve the image quality notably, indicating that impedance-optical joint imaging has the potential to reveal the structural and functional information of tissue-level targets simultaneously.

A Large-Area Flexible Tactile Sensor for Multi-Touch and Force Detection Using Electrical Impedance Tomography

For large area robot skin design, the distribution of rigid components and wires in traditional array sensors leads to the decrease of the flexibility and extensibility of sensors. The flexible sensors based on non-invasive electrical impedance tomography (EIT) can avoid these shortcomings. However, design of a large-area flexible tactile sensors using EIT technique is still challenging due to the tradeoff between manufacturability and spatial resolution. In this study, we proposed a novel non-array EIT-based tactile sensor which is made of a porous elastic polymer and ionic liquid. The sensor free from internal array electrodes is straightforward to manufacture and can cover a large area with low cost. To improve the spatial resolution and touch sensitivity, we adopted a deep learning scheme Pyramid Scene Parsing Network (PSPNet) to postprocess the originally reconstructed images to enhance the sensor tactile perception. With this data-driven method, we achieved a single-point position detection error of 7.5± 4.5 mm without using internal electrodes. To overcome the location dependency of EIT sensing problems, we proposed a method of sub-regional fitting to calibrate the distributed forces for the large-area flexible tactile sensor and obtained a quantitative relationship between the touch force and EIT measurement for the entire sensing area for continuous sensing. The real-time performance of the proposed prototype sensor system demonstrated that we can achieve more accuracy of multi-touch and distributed force detection on the non-array sensors with a temporal resolution of about 1.3 frames/sec for potential applications in human-robot interfaces.

An alternative excitation method for electrical impedance tomography

Electrical impedance tomography (EIT) can be utilized to image the conductivity distribution of material under test. The EIT measurements depend on the quality in the current injection and voltage measuring circuits. The current source plays a vital role in the EIT instruments. In most of the research studies, the push-pull current sources were employed for the source and sink signal generation. It usually requires frequent calibration to achieve proper functioning, especially for the sweeping frequency measurements. In this paper, an alternative excitation method has been proposed for simplifying the design of the current source in EIT instruments, which aims to achieve the performance of the push-pull current source by using a single-ended current source. It could offer the following advantages: (1) hardware simplification and (2) reduced requirements on current source calibration. The corrected measurements could be consistent with that using push-pull excitation, as confirmed by the numerical simulations. In addition, the reconstructed images have also been investigated to illustrate the effectiveness of the proposed method.

Scalp-Mounted Electrical Impedance Tomography of Cerebral Hemodynamics.

An Electrical Impedance Tomography (EIT) system has been developed for dynamic three-dimensional imaging of changes in conductivity distribution in the human head, using scalp-mounted electrodes. We attribute these images to changes in cerebral perfusion. At 100 frames per second (fps), voltage measurement is achieved with full-scale signal-to-noise ratio of 105 dB and common-mode rejection ratio > 90 dB. A novel nonlinear method is presented for 3-D imaging of the difference in conductivity distribution in the head, relative to a reference time. The method achieves much reduced modelling error. It successfully localizes conductivity inclusions in experimental and simulation tests, where previous methods fail. For > 50 human volunteers, the rheoencephalography (REG) waveform is observed in EIT voltage measurements for every volunteer, with peak-to-peak amplitudes up to approx. 50 μVrms. Images are presented of the change in conductivity distribution during the REG/cardiac cycle, at 50 fps, showing maximum local conductivity change of approx. 1% in grey/white matter. A total of 17 tests were performed during short (typically 5s) carotid artery occlusions on 5 volunteers, monitored by Transcranial Doppler ultrasound. From EIT measurements averaged over complete REG/cardiac cycles, 13 occlusion tests showed consistently decreased conductivity of cerebral regions on the occluded side, and increased conductivity on the opposite side. The maximum local conductivity change during occlusion was approx. 20%. The simplicity of the carotid artery intervention provides a striking validation of the scalp-mounted measurement system in imaging cerebral hemodynamics, and the REG images indicate its unique combination of sensitivity and temporal resolution.

Hand Sign Recognition System Based on EIT Imaging and Robust CNN Classification

Hand sign recognition is gaining importance in human-human and in human-machine communication and interaction. Electrical Impedance Tomography (EIT) is thereby very interesting as it provides information on impedance changes in depth of the Section of the arm, which infers muscle contractions. This paper introduces an EIT imaging system for hand sign recognition and monitoring having a low complexity and including an electronic interface with 8 electrodes placed on the forearm, a Gauss-Newton image reconstruction algorithm, a robust CNN based hand sign classification and a virtual hand model for visualization. A database has been collected for EIT measurements in pole mode taken by eight subjects performing the American sign language numbers from 0 to 9. The overall imaging system is validated using a water tank system, where conductive objects can be changed in properties and positions. The correspondence between the reconstructed images and the expected muscle behavior for the hand signs is investigated. A robust Convolutional Neural Network (CNN) classification algorithm was implemented and optimized by implementing an Adam optimizer and conducting a dedicated study to avoid overfitting. The results obtained by CNN are compared to the results by a Support Vector Machine (SVM), and a Softmax classifier. They show a classification accuracy of 95.94%, 75.61%, and 62.9% respectively. In term of subject dependency, the system using the CNN model shows a higher performance, as the accuracy decreases only by 0.72% while increasing the number of subjects from one to eight. Finally, for visualization, a 3D virtual hand model is designed and controlled based on detected hand signs.

Neural networks for classification of strokes in electrical impedance tomography on a 3D head model

&lt;abstract&gt;&lt;p&gt;We consider the problem of the detection of brain hemorrhages from three-dimensional (3D) electrical impedance tomography (EIT) measurements. This is a condition requiring urgent treatment for which EIT might provide a portable and quick diagnosis. We employ two neural network architectures - a fully connected and a convolutional one - for the classification of hemorrhagic and ischemic strokes. The networks are trained on a dataset with $ 40\, 000 $ samples of synthetic electrode measurements generated with the complete electrode model on realistic heads with a 3-layer structure. We consider changes in head anatomy and layers, electrode position, measurement noise and conductivity values. We then test the networks on several datasets of unseen EIT data, with more complex stroke modeling (different shapes and volumes), higher levels of noise and different amounts of electrode misplacement. On most test datasets we achieve $ \geq 90\% $ average accuracy with fully connected neural networks, while the convolutional ones display an average accuracy $ \geq 80\% $. Despite the use of simple neural network architectures, the results obtained are very promising and motivate the applications of EIT-based classification methods on real phantoms and ultimately on human patients.&lt;/p&gt;&lt;/abstract&gt;

Prolonged Continuous Monitoring of Regional Lung Function in Infants with Respiratory Failure.

Rationale: Electrical impedance tomography (EIT) allows instantaneous and continuous visualization of regional ventilation and changes in end-expiratory lung volume at the bedside. There is particular interest in using EIT for monitoring in critically ill neonates and young children with respiratory failure. Previous studies have focused only on short-term monitoring in small populations. The feasibility and safety of prolonged monitoring with EIT in neonates and young children have not been demonstrated yet. Objectives: To evaluate the feasibility and safety of long-term EIT monitoring in a routine clinical setting and to describe changes in ventilation distribution and homogeneity over time and with positioning in a multicenter cohort of neonates and young children with respiratory failure. Methods: At four European University hospitals, we conducted an observational study (NCT02962505) on 200 patients with postmenstrual ages (PMA) between 25 weeks and 36 months, at risk for or suffering from respiratory failure. Continuous EIT data were obtained using a novel textile 32-electrode interface and recorded at 48 images/s for up to 72 hours. Clinicians were blinded to EIT images during the recording. EIT parameters and the effects of body position on ventilation distribution were analyzed offline. Results: The average duration of EIT measurements was 53 ± 20 hours. Skin contact impedance was sufficient to allow image reconstruction for valid ventilation analysis during a median of 92% (interquartile range, 77-98%) of examination time. EIT examinations were well tolerated, with minor skin irritations (temporary redness or imprint) occurring in 10% of patients and no moderate or severe adverse events. Higher ventilation amplitude was found in the dorsal and right lung areas when compared with the ventral and left regions, respectively. Prone positioning resulted in an increase in the ventilation-related EIT signal in the dorsal hemithorax, indicating increased ventilation of the dorsal lung areas. Lateral positioning led to a redistribution of ventilation toward the dependent lung in preterm infants and to the nondependent lung in patients with PMA > 37 weeks. Conclusions: EIT allows continuous long-term monitoring of regional lung function in neonates and young children for up to 72 hours with minimal adverse effects. Our study confirmed the presence of posture-dependent changes in ventilation distribution and their dependency on PMA in a large patient cohort. Clinical trial registered with www.clinicaltrials.gov (NCT02962505).

Comparison of Electrical Impedance Tomography and Ultrasonography for Determination of Solid and Cystic Lesion Resembling Breast Tumor Embedded in Chicken Phantom.

Ultrasonography (US) and Electrical Impedance Tomography (EIT) can be used to detect breast cancer. Ultrasonography is based on non-ionizing radiations without adverse biological effects. A set of electrodes was placed around the torso and a small alternating current (AC) was injected via two of the electrodes into the object. This study aimed to acquire preliminary data to evaluate the EIT method for differentiation of artificial solid and cystic tumors in comparison to standard US.This study used a phantom made from chicken meat. In order to obtain the image of the solid tumor, an olive with carrot insertion was done, and the cystic tumor was created by filling a small balloon with water. GE Logic C5 ultrasound was performed with a 12 MHz linear transducer. For EIT measurement, 16 ECG electrodes and 32 ECG electrodes were placed. Data processing was done using the Graz consensus Reconstruction algorithm for EIT (GREIT) and Newton's One Step Error Reconstructor (NOSER) methods.The artificial solid tumor produced an ultrasound image of an oval, inhomogeneous lesions. The GREIT method with 16 electrodes of artificial solid tumor did not show a match between the reconstructed image and the original object containing 2 anomalies, but a match was found with 32 electrodes. In the NOSER method, both 16 and 32 electrodes showed a match. Ultrasound of the artificial cystic tumor showed an oval, circumscribed, anechoic with posterior enhancement. Both the GREIT and NOSER methods using the artificial cystic tumor showed a match between the reconstructed image and the original object containing two anomalies.EIT has a lower imaging resolution in comparison to ultrasonography, but is progressively maturing as a tool for monitoring and imaging. The solid and cystic anomalies on the phantoms were visualized by the GREIT and NOSER methods except for the solid anomaly with the GREIT 16 electrodes.

Robot-Assisted Electrical Impedance Scanning system for 2D Electrical Impedance Tomography tissue inspection.

The electrical impedance tomography (EIT) technology is an important medical imaging approach to show the electrical characteristics and the homogeneity of a tissue region noninvasively. Recently, this technology has been introduced to the Robot Assisted Minimally Invasive Surgery (RAMIS) for assisting the detection of surgical margin with relevant clinical benefits. Nevertheless, most EIT technologies are based on a fixed multiple-electrodes probe which limits the sensing flexibility and capability significantly. In this study, we present a method for acquiring the EIT measurements during a RAMIS procedure using two already existing robotic forceps as electrodes. The robot controls the forceps tips to a series of predefined positions for injecting excitation current and measuring electric potentials. Given the relative positions of electrodes and the measured electric potentials, the spatial distribution of electrical conductivity in a section view can be reconstructed. Realistic experiments are designed and conducted to simulate two tasks: subsurface abnormal tissue detection and surgical margin localization. According to the reconstructed images, the system is demonstrated to display the location of the abnormal tissue and the contrast of the tissues' conductivity with an accuracy suitable for clinical applications.

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.

Image Reconstruction of Electrical Impedance Tomography Based on Optical Image-Guided Group Sparsity

The low spatial resolution of Electrical Impedance Tomography (EIT) makes it challenging to conduct quantitative analysis of the electrical properties of imaging targets in biomedical applications. We in this paper propose to integrate optical imaging into EIT to improve EIT image quality and report a dual-modal image reconstruction algorithm based on optical image-guided group sparsity (IGGS). IGGS receives an RGB microscopic image and EIT measurements as inputs, extracts the structural features of conductivity distribution from optical images and fuses the information from the two imaging modalities to generate a high-quality conductivity image. The superior performance of IGGS is verified by numerical simulation and real-world experiments. Compared with selected single-modal EIT image reconstruction algorithms, i.e., the classical Tikhonov regularization and the state-of-the-art Structure-Aware Sparse Bayesian Learning and Enhanced Adaptive Group Sparsity with Total Variation, the proposed method presents superiorities in terms of shape preservation, background noise suppression, and differentiation of conductivity contrasts.

Ventilation improvement after pneumonia treatment evaluated with electrical impedance tomography: an observational study

Objective. Due to radiation exposure, not all patients with pneumonia receive chest x-rays or CT measurements to confirm treatment effectiveness. The aim of this study was to examine the ability to use electrical impedance tomography (EIT) to evaluate the treatment effectiveness in such patient group. Approach . A total of 35 consecutive patients with non-severe pneumonia were included in this prospective study. The patients received standard treatment according to our internal protocol. EIT measurements were performed in supine position before the treatment started and on day 6 of the treatment period. The EIT-based global inhomogeneity (GI) index and center of ventilation (CoV) index were calculated. The clinical pulmonary infection score (CPIS) was obtained at both time points. Main r esults. Clinically significant improvements in GI and CoV were found in the patient group (ΔGI: −34% ± 17% and ΔCoV: −10% ± 11%; p<0.001). Although the CPIS was also significantly improved (ΔCPIS −0.70 ± 0.17, p<0.001), no correlations were demonstrated when compared to ΔGI or ΔCoV. Significance. EIT demonstrated individual improvement of ventilation heterogeneity after standard treatment in non-severe pneumonia, and provided different information compared to CPIS. EIT has the potential to become a routine non-invasive, non-radiative tool to assess pneumonia treatment effectiveness.

Separating ventricular activity in thoracic EIT using 4D image-based FEM simulations

Abstract One challenge in central hemodynamic monitoring based on electrical impedance tomography (EIT) is to robustly detect ventricular signal components and the corresponding EIT image region without external monitoring information. Current stimulation and voltage measurement of EIT were simulated with finite element porcine torso models in presence of a multitude of thoracic blood volume shifts. The simulated measurement data was examined for linear dependence on changes in stroke volume. Based on the results the EIT measurement information regarding stroke volume changes is sparse

Anatomical atlas of the upper part of the human head for electroencephalography and bioimpedance applications

Objective. The objective of this work is to develop a 4D (3D+T) statistical anatomical atlas of the electrical properties of the upper part of the human head for cerebral electrophysiology and bioimpedance applications. Approach. The atlas was constructed based on 3D magnetic resonance images (MRI) of 107 human individuals and comprises the electrical properties of the main internal structures and can be adjusted for specific electrical frequencies. T1w+T2w MRI images were used to segment the main structures of the head while angiography MRI was used to segment the main arteries. The proposed atlas also comprises a time-varying model of arterial brain circulation, based on the solution of the Navier–Stokes equation in the main arteries and their vascular territories. Main results. High-resolution, multi-frequency and time-varying anatomical atlases of resistivity, conductivity and relative permittivity were created and evaluated using a forward problem solver for EIT. The atlas was successfully used to simulate electrical impedance tomography measurements indicating the necessity of signal-to-noise between 100 and 125 dB to identify vascular changes due to the cardiac cycle, corroborating previous studies. The source code of the atlas and solver are freely available to download. Significance. Volume conductor problems in cerebral electrophysiology and bioimpedance do not have analytical solutions for nontrivial geometries and require a 3D model of the head and its electrical properties for solving the associated PDEs numerically. Ideally, the model should be made with patient-specific information. In clinical practice, this is not always the case and an average head model is often used. Also, the electrical properties of the tissues might not be completely known due to natural variability. Anatomical atlases are important tools for in silico studies on cerebral circulation and electrophysiology that require statistically consistent data, e.g. machine learning, sensitivity analyses, and as a benchmark to test inverse problem solvers.

System introduction and evaluation of the first Chinese chest EIT device for ICU applications

Chest electrical impedance tomography (EIT) is a promising application which is used to monitor the ventilation and perfusion of the lung at the bedside dynamically. The aim of the study was to introduce the first Chinese made chest EIT device for ICU application (Pulmo EIT-100). The system design of the hardware and software was briefly introduced. The performance of the system was compared to PulmoVista 500 (Dräger Medical) in healthy volunteers. The EIT system Pulmo EIT-100 consists of impedance measurement module, power supply module, PC all-in-one machine, medical cart and accessories. The performance of the system current source and voltage measurement unit was tested. A total of 50 healthy lung volunteers were prospectively examined. Subjects were asked to perform repetitive slow vital capacity (SVC) maneuvers with a spirometer. EIT measurements were performed in the following sequence during each SVC with: (1) Pulmo EIT-100, (2) PulmonVista500, (3) Pulmo EIT-100 and (4) PulmonVista500. Linearity and regional ventilation distribution of the reconstructed images from two devices were compared. The output frequency stability of the current source was 2 ppm. The amplitude error within one hour was less than 0.32‰. The output impedance of the current source was about 50kΩ. The signal-to-noise ratio of each measurement channel was ≥ 60 dB. For fixed resistance measurements, the measured values drifted about 0.08% within one hour. For human subjects, the correlations between the spirometry volume and EIT impedance from two devices were both 0.99 ± 0.01. No statistical significances were found in the parameters investigated. The repeatability (variability) of measures from the same device was comparable. Our EIT device delivers reliable data and might be used for patient measurement in a clinical setting.

Electrical impedance tomography to measure lung ventilation distribution in healthy horses and horses with left-sided cardiac volume overload.

BackgroundLeft‐sided cardiac volume overload (LCVO) can cause fluid accumulation in lung tissue changing the distribution of ventilation, which can be evaluated by electrical impedance tomography (EIT).ObjectivesTo describe and compare EIT variables in horses with naturally occurring compensated and decompensated LCVO and compare them to a healthy cohort.AnimalsFourteen adult horses, including university teaching horses and clinical cases (healthy: 8; LCVO: 4 compensated, 2 decompensated).MethodsIn this prospective cohort study, EIT was used in standing, unsedated horses and analyzed for conventional variables, ventilated right (VAR) and left (VAL) lung area, linear‐plane distribution variables (avg‐max VΔZLine, VΔZLine), global peak flows, inhomogeneity factor, and estimated tidal volume. Horses with decompensated LCVO were assessed before and after administration of furosemide. Variables for healthy and LCVO‐affected horses were compared using a Mann‐Whitney test or unpaired t‐test and observations from compensated and decompensated horses are reported.ResultsCompared to the healthy horses, the LCVO cohort had significantly less VAL (mean difference 3.02; 95% confidence interval .77‐5.2; P = .02), more VAR (−1.13; −2.18 to −.08; P = .04), smaller avg‐max VΔZL Line (2.54; 1.07‐4.00; P = .003) and VΔZL Line (median difference 5.40; 1.71‐9.09; P = .01). Observation of EIT alterations were reflected by clinical signs in horses with decompensated LCVO and after administration of furosemide.Conclusions and Clinical ImportanceEIT measurements of ventilation distribution showed less ventilation in the left lung of horses with LCVO and might be useful as an objective assessment of the ventilation effects of cardiogenic pulmonary disease in horses.

Real-time assessment of global and regional lung ventilation in the anti-gravity straining maneuver using electrical impedance tomography

ObjectiveAnti-gravity straining maneuver (AGSM) helps to reduce the occurrence of gravity-induced visual disturbances and loss of consciousness. An objective assessment of the AGSM is still missing during ground training. This study evaluated the feasibility of using electrical impedance tomography (EIT) to assess the performance of AGSM. MethodsEight undergraduates and eight teachers majoring in aerospace medicine were included in the study. An experienced professor from the department of aerospace medicine reviewed the key points of AGSM with each subject. EIT measurement was performed during AGSM. The global and regional ventilation were used to investigate the characteristics of AGSM. The professor and the subjects rated the performance of AGSM according to the maneuver requirements of AGSM (maximum 16 points) before and after reviewing the ventilations from EIT. ResultsFor global ventilation, the relative depth of gas exchange and duration of exhalation of the teachers were larger than those of the students (p < 0.01), and stability of the teachers was better as well (p < 0.001). No difference in the duration of gas exchange and leakage during exhalation between the teachers and the students was found. For regional ventilation, the teachers had significantly increased ventral ventilation during AGSM implementation (p < 0.001) whereas students did otherwise. Additionally, the differences of rating scores with and without EIT were also significant. Significant reductions were found in rating scores with EIT assessed by the professor (4.5 ± 2.0, p < 0.001) and by the students themselves (3.9 ± 2.2, p < 0.001). The scores were systematically higher when the students rated themselves compared with the professor's rating (p < 0.001 for both with and without EIT). ConclusionThese findings demonstrated that EIT could objectively characterize the maneuver details of AGSM, which might provide a potential tool for real-time assessment of AGSM quality in an objective manner.