Electrical Impedance Tomography Signal Research Articles

Development and Validation of a Portable EIT System for Real-Time Respiratory Monitoring.

This work contributes to the improvement of novel medical technologies for the prevention and treatment of diseases. Electrical impedance tomography (EIT) has gained attention as a valuable tool for non-invasive monitoring providing real-time insights. The purpose of this work is to develop and validate a novel portable EIT system with a small form factor for respiratory monitoring. The device uses a 16-electrode architecture with adjacent stimulation and measurement patterns, an integrated circuit current source and a single high-speed ADC operating with multiplexers to stimulate and measure across all electrodes. Tests were conducted on 25 healthy subjects who performed a pulmonary function test with a flowmeter while using the EIT device. The results showed a good performance of the device, which was able to recognize all respirations correctly, and from the EIT signals and images, correlations of 96.7% were obtained for instantaneous respiratory rate and 96.1% for tidal volume prediction. These results validate the preliminary technical feasibility of the EIT system and demonstrates its potential as a reliable tool for non-invasive respiratory assessment. The significance of this work lies in its potential to democratize advanced respiratory monitoring technologies, making them accessible to a wider population, including those in remote or underserved areas.

The Impact of PEEP on Ventilation Distribution in ARDS.

The first aim of this study was to evaluate the capacity of electrical impedance tomography (EIT) to identify the effect of PEEP on regional ventilation distribution and the regional risk of collapse, overdistention, hypoventilation, and pendelluft in mechanically ventilated patients. The second aim was to evaluate the feasibility of EIT for estimating airway opening pressure (AOP). The EIT signal was recorded both during baseline cyclic ventilation and slow insufflation for one breath for 9 subjects with moderate-to-severe ARDS. From these data, the AOP and volumes insufflated to lung regions with or without the risk of either collapse, overdistention, hypoventilation, or pendelluft were assessed at 3 PEEP levels (5, 10, and 15 cm H2O). PEEP levels were compared by Friedman analysis of variance and the AOP measured by EIT evaluated using an F-test and the Bland and Altman method. The volume for which there was no specific risk significantly decreased at the highest PEEP from 55 ± 31% tidal volume (VT) at PEEP 5 or 82 ± 18% VT at PEEP 10 to 10 ± 30% VT at PEEP 15 (P = .038 between PEEP 5 vs PEEP 15; P = .01 between PEEP 10 vs PEEP 15). The volume associated with overdistention significantly increased with increasing PEEP, whereas that associated with atelectrauma significantly decreased. Pendelluft significantly decreased with increasing PEEP: VT of 8.9 ± 18.6%, 3.6 ± 7.0%, and 3.2 ± 7.1% for PEEP 5, PEEP 10, and PEEP 15, respectively. The center of ventilation tended to increase in the dependent direction with higher PEEP. The AOPs assessed by EIT and from the pressure-volume curve were in good agreement (bias 0.48 cm H2O). Our results suggest that EIT could aid clinicians in making personalized and reasoned choices in setting the PEEP for subjects with ARDS.

Electrical impedance tomography provides information of brain injury during total aortic arch replacement through its correlation with relative difference of neurological biomarkers

Postoperative neurological dysfunction (PND) is one of the most common complications after a total aortic arch replacement (TAAR). Electrical impedance tomography (EIT) monitoring of cerebral hypoxia injury during TAAR is a promising technique for preventing the occurrence of PND. This study aimed to explore the feasibility of electrical impedance tomography (EIT) for warning of potential brain injury during total aortic arch replacement (TAAR) through building the correlation between EIT extracted parameters and variation of neurological biomarkers in serum. Patients with Stanford type A aortic dissection and requiring TAAR who were admitted between December 2021 to March 2022 were included. A 16-electrode EIT system was adopted to monitor each patient’s cerebral impedance intraoperatively. Five parameters of EIT signals regarding to the hypothermic circulatory arrest (HCA) period were extracted. Meanwhile, concentration of four neurological biomarkers in serum were measured regarding to time before and right after surgery, 12 h, 24 h and 48 h after surgery. The correlation between EIT parameters and variation of serum biomarkers were analyzed. A total of 57 TAAR patients were recruited. The correlation between EIT parameters and variation of biomarkers were stronger for patients with postoperative neurological dysfunction (PND(+)) than those without postoperative neurological dysfunction (PND(−)) in general. Particularly, variation of S100B after surgery had significantly moderate correlation with two parameters regarding to the difference of impedance between left and right brain which were MRAIabs and TRAIabs (0.500 and 0.485 with p < 0.05, respectively). In addition, significantly strong correlations were seen between variation of S100B at 24 h and the difference of average resistivity value before and after HCA phase (ΔARVHCA), the slope of electrical impedance during HCA (kHCA) and MRAIabs (0.758, 0.758 and 0.743 with p < 0.05, respectively) for patients with abnormal S100B level before surgery. Strong correlations were seen between variation of TAU after surgery and ΔARVHCA, kHCA and the time integral of electrical impedance for half flow of perfusion (TARVHP) (0.770, 0.794 and 0.818 with p < 0.01, respectively) for patients with abnormal TAU level before surgery. Another two significantly moderate correlations were found between TRAIabs and variation of GFAP at 12 h and 24 h (0.521 and 0.521 with p < 0.05, respectively) for patients with a normal GFAP serum level before surgery. The correlations between EIT parameters and serum level of neurological biomarkers were significant in patients with PND, especially for MRAIabs and TRAIabs, indicating that EIT may become a powerful assistant for providing a real-time warning of brain injury during TAAR from physiological perspective and useful guidance for intensive care units.

Respiratory rate monitoring in ICU patients and healthy volunteers using electrical impedance tomography: a validation study

Objective. The respiratory rate (RR) is considered one of the most informative vital signals. A well-validated standard for RR measurement in mechanically ventilated patient is capnography; a noninvasive technique for expiratory CO2 measurements. Reliable RR measurements in spontaneously breathing patients remains a challenge as continuous mainstream capnography measurements are not available. This study aimed to assess the accuracy of RR measurement using electrical impedance tomography (EIT) in healthy volunteers and intensive care unit (ICU) patients on mechanical ventilation and spontaneously breathing post-extubation. Comparator methods included RR derived from both capnography and bioimpedance electrocardiogram (ECG) measurements. Approach. Twenty healthy volunteers wore an EIT belt and ECG electrodes while breathing through a capnometer within a 10–40 breaths per minute (BPM) range. Nineteen ICU patients underwent similar measurements during pressure support ventilation and spontaneously breathing after extubation from mechanical ventilation. Stable periods with regular breathing and no artefacts were selected, and agreement between measurement methods was assessed using Bland–Altman analysis for repeated measurements. Main result. Bland–Altman analysis revealed a bias less than 0.2 BPM, with tight limits of agreement (LOA) ±1.5 BPM in healthy volunteers and ventilated ICU patients when comparing EIT to capnography. Spontaneously breathing ICU patients had wider LOA (±2.5 BPM) when comparing EIT to ECG bioimpedance, but gold standard comparison was unavailable. RR measurements were stable for 91% of the time for capnography, 68% for EIT, and 64% of the ECG bioimpedance signals. After extubation, the percentage of stable periods decreased to 48% for EIT signals and to 55% for ECG bioimpedance. Significance. In periods of stable breathing, EIT demonstrated excellent RR measurement accuracy in healthy volunteers and ICU patients. However, stability of both EIT and ECG bioimpedance RR measurements declined in spontaneously breathing patients to approximately 50% of the time.

Optimization of lung ventilation and perfusion in anesthetized horses using a ventilation mode with flow-limited expiration.

To investigate the mechanisms underlying the improved arterial oxygenation described with flow-limited expiration (FLEX) ventilation in anesthetized horses. 5 healthy adult research horses. Horses underwent volume-controlled ventilation for 60 minutes (VCV1), followed by 60 minutes of FLEX, and 30 minutes of VCV (VCV2). Main outcomes included the arterial partial pressure of oxygen-to-Fio2 (PF) ratio and electrical impedance tomography (EIT)-derived functional indices at the end of each phase. The EIT data were used to create regional maps of relative lung ventilation and perfusion as well as regional maps of ventilation/perfusion (V/Q) ratios. Ventilation indices derived from EIT included the fraction of expired volume in 1 second (FEV1; %) and the time it took for the EIT signal to drop to 50% of the peak signal at end-inspiration (TClose50; seconds). Data were analyzed with 2-way ANOVA for repeated measures. P < .05 was considered significant. The PF ratio increased significantly with FLEX compared to both VCV1 and VCV2 (P < .01). There were no differences in the relative distribution of ventilation nor perfusion between ventilation strategies. However, when ventilation and perfusion were superimposed and V/Q ratio maps were constructed, FLEX had a homogenizing effect toward values of 1.0. The FEV1 was shorter (P < .01) and the TClose50 was longer (P < .001) in all regions during FLEX compared to both VCV1 and VCV2. Our findings suggest that FLEX ventilation in anesthetized horses enhances regional V/Q matching, likely by prolonging expiratory aeration and reducing airway closure.

Comparing machine learning algorithms for non-invasive detection and classification of failure in piezoresistive bone cement via electrical impedance tomography

At an estimated cost of $8 billion annually in the United States, revision surgeries to total joint replacements represent a substantial financial burden to the health care system and a tremendous mental and physical burden on patients and their caretakers. Fixation failures, such as implant loosening, wear, and mechanical instability of the poly(methyl methacrylate) (PMMA) cement, which bonds the implant to the bone, are the main causes of long-term implant failure. Early and accurate diagnosis of cement failure is critical for developing novel therapeutic strategies and reducing the high risk of a misjudged revision. Unfortunately, prevailing imaging modalities, notably plain radiographs, struggle to detect the precursors of implant failure and are often interpreted incorrectly. Our prior work has shown that the modification of PMMA bone cement with low concentrations of conductive fillers makes it piezoresistive and therefore self-sensing. When combined with a conductivity imaging modality such as electrical impedance tomography (EIT), it is possible to monitor load transfer across the PMMA using cost-effective, physiologically benign, non-contact, and real-time electrical measurements. Despite the ability of EIT for monitoring load transfer across self-sensing PMMA bone cement, it is unable to accurately characterize failure mechanisms. Overcoming this challenge is critical to the success of this technology in practice. Therefore, we herein expand upon our previous results by integrating machine learning techniques with EIT for cement condition characterization with the goal of establishing the feasibility of even off-the-shelf machine learning algorithms to address this important problem. We survey a wide variety of different machine learning algorithms for application to this problem, including neural networks on voltage readings of an EIT phantom for tracking the spatial position of a sample, specifying defect orientation within a sample, and classifying defect types, including cracks and delaminations. In addition, we explore the utilization of principal component analysis (PCA) for pre-treating impedance signals in each of these problems. Within the tested algorithms, our results show clear advantages of neural networks, support vector machines, and K-nearest neighbor algorithms for interpreting EIT signals. We also show that PCA is an effective addition to machine learning. These preliminary results demonstrate that the combination of smart materials, EIT, and machine learning may be a powerful instrumentation tool for diagnosing the origin and evolution of mechanical failure in joint replacements.

Cranial Electrode Belt Position Improves Diagnostic Possibilities of Electrical Impedance Tomography during Laparoscopic Surgery with Capnoperitoneum.

Laparoscopic surgery with capnoperitoneum brings many advantages to patients, but also emphasizes the negative impact of anesthesia and mechanical ventilation on the lungs. Even though many studies use electrical impedance tomography (EIT) for lung monitoring during these surgeries, it is not clear what the best position of the electrode belt on the patient's thorax is, considering the cranial shift of the diaphragm. We monitored 16 patients undergoing a laparoscopic surgery with capnoperitoneum using EIT with two independent electrode belts at different tomographic levels: in the standard position of the 4th-6th intercostal space, as recommended by the manufacturer, and in a more cranial position at the level of the axilla. Functional residual capacity (FRC) was measured, and a recruitment maneuver was performed at the end of the procedure by raising the positive end-expiratory pressure (PEEP) by 5 cmH2O. The results based on the spectral analysis of the EIT signal show that the ventilation-related impedance changes are not detectable by the belt in the standard position. In general, the cranial belt position might be more suitable for the lung monitoring during the capnoperitoneum since the ventilation signal remains dominant in the obtained impedance waveform. FRC was significantly decreased by the capnoperitoneum and remained lower also after desufflation.

Electrical Impedance Tomography Signal Conditioning for Lung Imaging Applications

Electrical impedance tomography (EIT) imaging is capable for human lung imaging based on its continuous self-monitoring capabilities, and suitability for daily routines. This paper introduces a simulation work for EIT signal conditioning circuit and its simulated waveform response using Multisim software. EIT circuit simulations consist of several signal processing circuits for the receiving part of the EIT, band pass filter circuit, amplifier, and analog-to-digital circuit. The system produced a unit function signal of 5V from an input 250 kHz sine function via band pass filter, operational amplifier and AC/DC conversion. The waveform pattern result is presented for each processing stage aim to demonstrate the basic work of an EIT circuitry setup.

Wearable pulmonary monitoring system with integrated functional lung imaging and chest sound recording: a clinical investigation in healthy subjects

Objective. Current wearable respiratory monitoring devices provide a basic assessment of the breathing pattern of the examined subjects. More complex monitoring is needed for healthcare applications in patients with lung diseases. A multi-sensor vest allowing continuous lung imaging by electrical impedance tomography (EIT) and auscultation at six chest locations was developed for such advanced application. The aims of our study were to determine the vest’s capacity to record the intended bio-signals, its safety and the comfort of wearing in a first clinical investigation in healthy adult subjects. Approach. Twenty subjects (age range: 23–65 years) were studied while wearing the vests during a 14-step study protocol comprising phases of quiet and deep breathing, slow and forced full expiration manoeuvres, coughing, breath-holding in seated and three horizontal postures. EIT, chest sound and accelerometer signals were streamed to a tablet using a dedicated application and uploaded to a back-end server. The subjects filled in a questionnaire on the vest properties using a Likert scale. Main results. All subjects completed the full protocol. Good to excellent EIT waveforms and functional EIT images were obtained in 89% of the subjects. Breathing pattern and posture dependent changes in ventilation distribution were properly detected by EIT. Chest sounds were recorded in all subjects. Detection of audible heart sounds was feasible in 44%–67% of the subjects, depending on the sensor location. Accelerometry correctly identified the posture in all subjects. The vests were safe and their properties positively rated, thermal and tactile properties achieved the highest scores. Significance. The functionality and safety of the studied wearable multi-sensor vest and the high level of its acceptance by the study participants were confirmed. Availability of personalized vests might further advance its performance by improving the sensor-skin contact.

Suppressing interferences of EIT on synchronous recording EEG based on comb filter for seizure detection.

The purpose of this study was to eliminate the interferences of electrical impedance tomography (EIT) on synchronous recording electroencephalography (EEG) for seizure detection. The simulated EIT signal generated by COMSOL Multiphysics was superimposed on the clinical EEG signal obtained from the CHB-MIT Scalp EEG Database, and then the spectrum features of superimposed mixed signals were analyzed. According to the spectrum analysis, in addition to high-frequency interference at 51.2 kHz related to the drive current, there was also low-frequency interference caused by switching of electrode pairs, which were used to inject drive current. A low pass filter and a comb filter were used to suppress the high-frequency interference and low-frequency interference, respectively. Simulation results suggested the low-pass filter and comb filter working together effectively filtered out the interference of EIT on EEG in the process of synchronous monitoring. As a result, the normal EEG and epileptic EEG could be recognized effectively. Pearson correlation analysis further confirmed the interference of EIT on EEG was effectively suppressed. This study provides a simple and effective interference suppression method for the synchronous monitoring of EIT and EEG, which could be served as a reference for the synchronous monitoring of EEG and other medical electromagnetic devices.

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).

Wrist Angle Estimation With a Musculoskeletal Model Driven by Electrical Impedance Tomography Signals

Wrist kinematics estimation with muscle signals is a key issue in the field of wearable robots. In this study, we proposed a musculoskeletal-based-method driven by the Electrical Impedance Tomography (EIT) signals for continuously estimating wrist flexion/extension angles. The EIT-based interface can construct the conductivity distribution of the anatomical cross-sectional plane with a soft elastic sensing front-end, which is designed by our group. The estimation method took advantage of the flexor/extensor muscles' spatial information detected by the EIT-based interface to map the signals to the wrist angles. The whole model was designed with a musculoskeletal kinematic model, a muscular geometry model, and a mapping function between the EIT signals and the muscle morphological parameters. We validated the proposed method with intra-subject, inter-subject, and inter-posture cross-validations on 14 subjects in total. The results were compared with two data-driven algorithms (Lasso and kernel-based SVM). The muscle-model-based method was more robust to training data sizes than the other two methods. It achieved an average R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> of 0.97 with 1:10 intra-subject CV and 0.91 with 2:12 inter-subject CV. The model also quickly overcame the effects of posture changes with a short-time feature update. The results of our study are comparable, if not better, to that of state-of-the-art. Future endeavors are worth being paid in this direction to get more promising outcomes.

Inferring Respiratory and Circulatory Parameters from Electrical Impedance Tomography With Deep Recurrent Models.

Electrical impedance tomography (EIT) is a noninvasive imaging modality that allows a continuous assessment of changes in regional bioimpedance of different organs. One of its most common biomedical applications is monitoring regional ventilation distribution in critically ill patients treated in intensive care units. In this work, we put forward a proof-of-principle study that demonstrates how one can reconstruct synchronously measured respiratory or circulatory parameters from the EIT image sequence using a deep learning model trained in an end-to-end fashion. For this purpose, we devise an architecture with a convolutional feature extractor whose output is processed by a recurrent neural network. We demonstrate that one can accurately infer absolute volume, absolute flow, normalized airway pressure and within certain limitations even the normalized arterial blood pressure from the EIT signal alone, in a way that generalizes to unseen patients without prior calibration. As an outlook with direct clinical relevance, we furthermore demonstrate the feasibility of reconstructing the absolute transpulmonary pressure from a combination of EIT and absolute airway pressure, as a way to potentially replace the invasive measurement of esophageal pressure. With these results, we hope to stimulate further studies building on the framework put forward in this work.

Occurrence of pendelluft under pressure support ventilation in patients who failed a spontaneous breathing trial: an observational study

BackgroundPendelluft, the movement of gas within different lung regions, is present in animal models of assisted mechanical ventilation and associated with lung overstretching. Due to rebreathing of CO2 as compared to fresh gas, pendelluft might reduce ventilatory efficiency possibly exacerbating patient’s respiratory workload during weaning. Our aim was to measure pendelluft by electrical impedance tomography (EIT) in patients who failed a spontaneous breathing trial (SBT).MethodsThis is an observational study conducted in a general intensive care unit of a tertiary-level teaching hospital. EIT signal was recorded in 20 patients while pressure support (PS) ventilation was progressively reduced from clinical level (baseline) to 2 cmH2O, as in an SBT; four ventral-to-dorsal lung regions of interest were identified for pendelluft measurement. A regional gas movement (> 6 mL) occurring in a direction opposite to the global EIT signal was considered diagnostic for high pendelluft.ResultsEight patients out of 20 (40%) were classified as high-pendelluft; baseline clinical characteristics did not differ between high- and low-pendelluft patients. At PS reduction, pendelluft and EtCO2 increased more in the high-pendelluft group (p < .001 and .011, respectively). The volume of gas subject to pendelluft moved almost completely from the ventral towards the dorsal lung regions, while the opposite movement was minimal (16.3 [10:32.8] vs. 0 [0:1.8] mL, p = .001). In a subgroup of patients, increased pendelluft volumes positively correlated with markers of respiratory distress such as increased respiratory rate, p0.1, and EtCO2.ConclusionsOccult pendelluft can be measured by EIT, and is frequently present in patients failing an SBT. When present, pendelluft increases with the reduction of ventilator support and is associated with increased EtCO2, suggesting a reduction of the ability to eliminate CO2.

Evaluating and Reducing the Influence of Scalp Dehydration in the Monitoring of Intracranial Dehydration Using Electrical Impedance Tomography

Dehydration treatment is commonly applied to treat intracranial hypertension. We previously utilized electrical impedance tomography (EIT) for noninvasively monitoring the efficacy of dehydration treatments and found it could provide references for the rational use of dehydrating drugs. In addition to brain tissues, scalp undergoes dehydration and can cause impedance changes, which may hamper the monitoring results of intracranial dehydration through EIT. To address this problem, we first conducted simulation and animal experiments to evaluate the impact of scalp dehydration on the monitoring results of EIT during dehydration treatments. With the priori of the spatial distribution of brain structures and the statistical results of the contribution of scalp dehydration to the intracranial reconstructed values of the EIT images obtained from animal experiments, we then proposed a weighting algorithm to reduce the impact of scalp dehydration. The experimental results showed that scalp impedance changes would to some extent reduce the accuracy of EIT in imaging intracranial resistive perturbation and account for 16.7% in overall changes of EIT signal. With the modified algorithm, 69.6% of reconstructed values of scalp dehydration in EIT images were eliminated. And the image contrast (IC) of reconstructed EIT images was improved by 21.0%. Therefore, we conclude that scalp dehydration influences the accuracy of EIT in reflecting intracranial dehydration and our proposed method can reduce the impacts of scalp dehydration.

Early Recognition of Pneumothorax in Neonatal Respiratory Distress Syndrome with Electrical Impedance Tomography.

A female infant, born at 34 weeks of gestation, was admitted to neonatal intensive care unit due to respiratory distress syndrome (RDS). Continuous positive airway pressure (CPAP) was started for respiratory support. She was included in an observational electrical impedance tomography (EIT) study (ClinicalTrials.gov: NCT02962505) at 18 hours of age. Swisstom BB2 EIT monitor with LuMon belt was used for collecting EIT data. Clinicians were blinded for EIT during recording. Patient condition deteriorated after 7 hours of follow-up and clinician ordered a chest X-ray, in which left-sided pneumothorax was confirmed at 17:11 (Figure 1). From 14:10 onwards, retrospective EIT analysis identified the development of pneumothorax by: 1) increased end-expiratory lung impedance (EELI) and 2) decreased tidal EIT signal variation, both at the affected side, resulting from regionally raised air content and reduced ventilation, as well as by 3) decreased EELI at the contralateral side due to mediastinal shift and compression of the lung. All effects were augmented by position change to contralateral side at 15:45. Potentially life-threatening tension pneumothorax may be prevented by early recognition of air leak complications in neonatal RDS. In our case EIT identified it almost 3 hours before the corresponding clinical diagnosis was made.

Time-based pulmonary features from electrical impedance tomography demonstrate ventilation heterogeneity in chronic obstructive pulmonary disease.

Pulmonary electrical impedance tomography (EIT) is a functional imaging technique that allows real-time monitoring of ventilation distribution. Ventilation heterogeneity (VH) is a characteristic feature of chronic obstructive pulmonary disease (COPD) and has previously been quantified using features derived from tidal variations in the amplitude of the EIT signal. However, VH may be better described by time-based metrics, the measurement of which is made possible by the high temporal resolution of EIT. We aimed 1) to quantify VH using novel time-based EIT metrics and 2) to determine the physiological relevance of these metrics by exploring their relationships with complex lung mechanics measured by the forced oscillation technique (FOT). We performed FOT, spirometry, and tidal-breathing EIT measurements in 11 healthy controls and 9 volunteers with COPD. Through offline signal processing, we derived 3 features from the impedance-time (Z-t) curve for each image pixel: 1) tE, mean expiratory time; 2) PHASE, mean time difference between pixel and global Z-t curves; and 3) AMP, mean amplitude of Z-t curve tidal variation. Distribution was quantified by the coefficient of variation (CV) and the heterogeneity index (HI). Both CV and HI of the tE and PHASE features were significantly increased in COPD compared with controls, and both related to spirometry and FOT resistance and reactance measurements. In contrast, distribution of the AMP feature showed no relationships with lung mechanics. These novel time-based EIT metrics of VH reflect complex lung mechanics in COPD and have the potential to allow real-time visualization of pulmonary physiology in spontaneously breathing subjects.NEW & NOTEWORTHY Pulmonary electrical impedance tomography (EIT) is a real-time imaging technique capable of monitoring ventilation with exquisite temporal resolution. We report novel, time-based EIT measurements that not only demonstrate ventilation heterogeneity in chronic obstructive pulmonary disease (COPD), but also reflect oscillatory lung mechanics. These EIT measurements are noninvasive, radiation-free, easy to obtain, and provide real-time visualization of the complex pathophysiology of COPD.

Event-triggered averaging of electrical impedance tomography (EIT) respiratory waveforms as compared to low-pass filtering for removal of cardiac related impedance changes.

Electrical impedance tomography (EIT) is used for bedside ventilation monitoring; cardiac related impedance changes represent a source of noise superimposed on the ventilation signal, commonly removed by low-pass filtering (LPF). We investigated if an alternative approach, based on an event-triggered averaging (ETA) process, is more effective at preserving the actual ventilation waveform. Ten paralyzed patients undergoing volume-controlled ventilation were studied; 30 breaths for each patient were identified to compare LPF and ETA. For ETA the identified breaths were temporally aligned on the beginning of inspiration; the values of the thirty curves at each time point were averaged. The analysis was conducted on the global EIT signal and on four ventral-to-dorsal regions of interest. Global tidal variations by ETA resulted higher than LPF (average difference 139 ± 88 arbitrary units, p = 0.004). Both for global and regional waveforms, minimum and maximum EIT slopes were steeper by ETA as compared to LPF (average difference respectively − 57 ± 60 mL/s and 144 ± 96 mL/s for global signal, p < 0.05); ventilator inspiratory peak airflow correlated with maximum slope measured by ETA (r = 0.902, p < 0.001), but not LPF (p = 0.319). Beginning of inspiration identified on the ventilator waveform and on the global EIT signal by ETA occurred simultaneously, (+ 0.04 ± 0.07 s, p = 0.081), while occurred earlier by LPF (− 0.26 ± 0.1 s, p < 0.001). Removal of cardiac related impedance changes by ETA results in a ventilation signal more similar to the waveforms recorded by the ventilator, particularly regarding the slope of impedance changes and time at the minimum values as compared to LPF.Electronic supplementary materialThe online version of this article (10.1007/s10877-019-00348-2) contains supplementary material, which is available to authorized users.

Heterogeneity of regional inflection points from pressure-volume curves assessed by electrical impedance tomography

BackgroundThe pressure-volume (P-V) curve has been suggested as a bedside tool to set mechanical ventilation; however, it reflects a global behavior of the lung without giving information on the regional mechanical properties. Regional P-V (PVr) curves derived from electrical impedance tomography (EIT) could provide valuable clinical information at bedside, being able to explore the regional mechanics of the lung. In the present study, we hypothesized that regional P-V curves would provide different information from those obtained from global P-V curves, both in terms of upper and lower inflection points. Therefore, we constructed pressure-volume curves for each pixel row from non-dependent to dependent lung regions of patients affected by acute hypoxemic respiratory failure (AHRF) and acute respiratory distress syndrome (ARDS).MethodsWe analyzed slow-inflation P-V maneuvers data from 12 mechanically ventilated patients. During the inflation, the pneumotachograph was used to record flow and airway pressure while the EIT signals were recorded digitally. From each maneuver, global respiratory system P-V curve (PVg) and PVr curves were obtained, each one corresponding to a pixel row within the EIT image. PVg and PVr curves were fitted using a sigmoidal equation, and the upper (UIP) and lower (LIP) inflection points for each curve were mathematically identified; LIP and UIP from PVg were respectively called LIPg and UIPg. From each measurement, the highest regional LIP (LIPrMAX) and the lowest regional UIP (UIPrMIN) were identified and the pressure difference between those two points was defined as linear driving pressure (ΔPLIN).ResultsA significant difference (p < 0.001) was found between LIPrMAX (15.8 [9.2–21.1] cmH2O) and LIPg (2.9 [2.2–8.9] cmH2O); in all measurements, the LIPrMAX was higher than the corresponding LIPg. We found a significant difference (p < 0.005) between UIPrMIN (30.1 [23.5–37.6] cmH2O) and UIPg (40.5 [34.2–45] cmH2O), the UIPrMIN always being lower than the corresponding UIPg. Median ΔPLIN was 12.6 [7.4–20.8] cmH2O and in 56% of cases was < 14 cmH2O.ConclusionsRegional inflection points derived by EIT show high variability reflecting lung heterogeneity. Regional P-V curves obtained by EIT could convey more sensitive information than global lung mechanics on the pressures within which all lung regions express linear compliance.Trial registrationClinicaltrials.gov, NCT02907840. Registered on 20 September 2016.

Evaluation of the use of gold nanoparticle as contrast agent in electrical impedance imaging

Introduction: Electrical Impedance Tomography (EIT) is a real time and minimal invasive imaging modality for detection of lesions in tissues even when their structures show no changes. Early detection of lesion with EIT depends on difference between electrical impedance of targeted tissue and its surroundings. Therefore, finding a contrast agent for EIT that increase this difference could improve its ability for detection of lesions in early stages. In this study, ability of gold nanoparticles (GNP) to use as EIT contrast agent was investigated. Materials and Methods: Turkevich method was used to synthesis spherical shaped GNPs with the size of 20-25 nm. Characterization of size distribution and shape of synthesized NPs were determined by transmission electron microscopy (TEM). Two types of phantoms (chicken fat and muscle paste tissues) were prepared and their electrical impedance was measured by the 4- electrode method. These measurements were done with and without the presence of GNPs. Results: Results show that presence of gold nanoparticles leads to descending in electrical impedance of tissues. This effect is more significant in frequencies below 1 KHz and has different values for the fat and muscle tissues. Reduction in resistive impedance is about 40.24W and1.93W for fat and muscle tissues at frequency 1 KHz, respectively. Increase in EIT signal is a consequence of reduction in electrical impedance. Consequently, presence of GNPs enhances the EIT signal and this enhancement is different for the fat and muscle tissues. Conclusion: As signal enhancement is different for fat and muscle tissues, gold nanoparticles could be considered as EIT contrast agent to improve detection of abnormalities at early stages.