Impact of model shape mismatch on reconstruction quality in electrical impedance tomography

Rapid patient-specific FEM meshes from 3D smart-phone based scans

Objective.The objective of this study was to describe and evaluate a smart-phone based method to rapidly generate subject-specific finite element method (FEM) meshes. More accurate FEM meshes should lead to more accurate thoracic electrical impedance tomography (EIT) images.Approach.The method was evaluated on an iPhone®that utilized an app called Heges, to obtain 3D scans (colored, surface triangulations), a custom belt, and custom open-source software developed to produce the subject-specific meshes. The approach was quantitatively validated via mannequin and volunteer tests using an infrared tracker as the gold standard, and qualitatively assessed in a series of tidal-breathing EIT images recorded from 9 subjects.Main results.The subject-specific meshes can be generated in as little as 6.3 min, which requires on average 3.4 min of user interaction. The mannequin tests yielded high levels of precision and accuracy at 3.2 ± 0.4 mm and 4.0 ± 0.3 mm root mean square error (RMSE), respectively. Errors on volunteers were only slightly larger (5.2 ± 2.1 mm RMSE precision and 7.7 ± 2.9 mm RMSE accuracy), illustrating the practical RMSE of the method.Significance.Easy-to-generate, subject-specific meshes could be utilized in the thoracic EIT community, potentially reducing geometric-based artifacts and improving the clinical utility of EIT.

Evaluation of adjacent and opposite current injection patterns for a wearable chest electrical impedance tomography system

Objective.Wearable electrical impedance tomography (EIT) can be used to monitor regional lung ventilation and perfusion at the bedside. Due to its special system architecture, the amplitude of the injected current is usually limited compared to stationary EIT system. This study aims to evaluate the performance of current injection patterns with various low-amplitude currents in healthy volunteers.Approach.A total of 96 test sets of EIT measurement was recorded in 12 healthy subjects by employing adjacent and opposite current injection patterns with four amplitudes of small current (i.e. 1 mA, 500 uA, 250 uA and 125 uA). The performance of the two injection patterns with various currents was evaluated in terms of signal-to-noise ratio (SNR) of thorax impedance, EIT image metrics and EIT-based clinical parameters.Main results.Compared with adjacent injection, opposite injection had higher SNR (p< 0.01), less inverse artifacts (p< 0.01), and less boundary artifacts (p< 0.01) with the same current amplitude. In addition, opposite injection exhibited more stable EIT-based clinical parameters (p< 0.01) across the current range. For adjacent injection, significant differences were found for three EIT image metrics (p< 0.05) and four EIT-based clinical parameters (p< 0.01) between the group of 125 uA and the other groups.Significance.For better performance of wearable pulmonary EIT, currents greater than 250 uA should be used in opposite injection, 500 uA in adjacent one, to ensure a high level of SNR, a high quality of reconstructed image as well as a high reliability of clinical parameters.

Three-dimensional electrical impedance tomography to study regional ventilation/perfusion ratios in anesthetized pigs

This study aimed to develop a three-dimensional (3-D) method for assessing ventilation/perfusion (V/Q̇) ratios in a pig model of hemodynamic perturbations using electrical impedance tomography (EIT). To evaluate the physiological coherence of changes in EIT-derived V/Q̇ ratios, global EIT-derived V/Q̇ mismatches were compared with global gold standards. The study found regional heterogeneity in the distribution of V/Q̇ ratios in both the ventrodorsal and craniocaudal directions. Although global EIT-derived indices of V/Q̇ mismatch consistently underestimated both low and high V/Q̇ mismatch compared with global gold standards, the direction of the change was similar. We made the software available at no cost for other researchers to use. Future studies should compare regional V/Q̇ ratios determined by our method against other regional, high-resolution methods.NEW & NOTEWORTHY In this study, we introduce a novel 3-D method for assessing ventilation-perfusion (V/Q̇) ratios using electrical impedance tomography (EIT). Heterogeneity in V/Q̇ distribution showcases the significant potential for enhanced understanding of pulmonary conditions. This work signifies a substantial step forward in the application of EIT for monitoring and managing lung diseases.

Evaluation of Different Contrast Agents for Regional Lung Perfusion Measurement Using Electrical Impedance Tomography: An Experimental Pilot Study

Monitoring regional blood flow distribution in the lungs appears to be useful for individually optimizing ventilation therapy. Electrical impedance tomography (EIT) can be used at the bedside for indicator-based regional lung perfusion measurement. Hypertonic saline is widely used as a contrast agent but could be problematic for clinical use due to potential side effects. In five ventilated healthy pigs, we investigated the suitability of five different injectable and clinically approved solutions as contrast agents for EIT-based lung perfusion measurement. Signal extraction success rate, signal strength, and image quality were analyzed after repeated 10 mL bolus injections during temporary apnea. The best results were obtained using NaCl 5.85% and sodium-bicarbonate 8.4% with optimal success rates (100%, each), the highest signal strengths (100 ± 25% and 64 ± 17%), and image qualities (r = 0.98 ± 0.02 and 0.95 ± 0.07). Iomeprol 400 mg/mL (non-ionic iodinated X-ray contrast medium) and Glucose 5% (non-ionic glucose solution) resulted in mostly well usable signals with above average success rates (87% and 89%), acceptable signal strength (32 ± 8% and 16 + 3%), and sufficient image qualities (r = 0.80 ± 0.19 and 0.72 ± 0.21). Isotonic balanced crystalloid solution failed due to a poor success rate (42%), low signal strength (10 ± 4%), and image quality (r = 0.43 ± 0.28). While Iomeprol might enable simultaneous EIT and X-ray measurements, glucose might help to avoid sodium and chloride overload. Further research should address optimal doses to balance reliability and potential side effects.

Structural priors represented by discrete cosine transform improve EIT functional imaging

Structural prior information can improve electrical impedance tomography (EIT) reconstruction. In this contribution, we introduce a discrete cosine transformation-based (DCT-based) EIT reconstruction algorithm to demonstrate a way to incorporate the structural prior with the EIT reconstruction process. Structural prior information is obtained from other available imaging methods, e.g., thorax-CT. The DCT-based approach creates a functional EIT image of regional lung ventilation while preserving the introduced structural information. This leads to an easier interpretation in clinical settings while maintaining the advantages of EIT in terms of bedside monitoring during mechanical ventilation. Structural priors introduced in the DCT-based approach are of two categories in terms of different levels of information included: a contour prior only differentiates lung and non-lung region, while a detail prior includes information, such as atelectasis, within the lung area. To demonstrate the increased interpretability of the EIT image through structural prior in the DCT-based approach, the DCT-based reconstructions were compared with reconstructions from a widely applied one-step Gauss-Newton solver with background prior and from the advanced GREIT algorithm. The comparisons were conducted both on simulation data and retrospective patient data. In the simulation, we used two sets of forward models to simulate different lung conditions. A contour prior and a detail prior were derived from simulation ground truth. With these two structural priors, the reconstructions from the DCT-based approach were compared with the reconstructions from both the one-step Gauss-Newton solver and the GREIT. The difference between the reconstructions and the simulation ground truth is calculated by the ℓ2-norm image difference. In retrospective patient data analysis, datasets from six lung disease patients were included. For each patient, a detail prior was derived from the patient's CT, respectively. The detail prior was used for the reconstructions using the DCT-based approach, which was compared with the reconstructions from the GREIT. The reconstructions from the DCT-based approach are more comprehensive and interpretable in terms of preserving the structure specified by the priors, both in simulation and retrospective patient data analysis. In simulation analysis, the ℓ2-norm image difference of the DCT-based approach with a contour prior decreased on average by 34% from GREIT and 49% from the Gauss-Newton solver with background prior; for reconstructions of the DCT-based approach with detail prior, on average the ℓ2-norm image difference is 53% less than GREIT and 63% less than the reconstruction with background prior. In retrospective patient data analysis, the reconstructions from both the DCT-based approach and GREIT can indicate the current patient status, but the DCT-based approach yields more interpretable results. However, it is worth noting that the preserved structure in the DCT-based approach is derived from another imaging method, not from the EIT measurement. If the structural prior is outdated or wrong, the result might be misleadingly interpreted, which induces false clinical conclusions. Further research in terms of evaluating the validity of the structural prior and detecting the outdated prior is necessary.

The calculation of electrical impedance tomography based silent spaces requires individual thorax and lung contours

OBJECTIVE

The present study evaluates the influence of different thorax contours (generic vs individual) on the parameter "silent spaces" computed from electrical impedance tomography (EIT) measurements.

APPROACH

Six patients with acute respiratory distress syndrome were analyzed retrospectively. EIT measurements were performed and the silent spaces were calculated based on (1) patient-specific contours Sind, (2) generic adult male contours SEidorsA and (3) generic neonate contours SEidorsN.

MAIN RESULTS

The differences among all studied subjects were 5±6% and 8±7% for Sind vs. SEidorsA, Sind vs. SEidorsN, respectively (median ± interquartile range). Sind values were higher than the generic ones in two patients.

SIGNIFICANCE

In the present study, we demonstrated the differences in values when the silent spaces were calculated based on different body and organ contours. To our knowledge, this study was the first one showing explicitly that silent spaces calculated with generic thorax and lung contours might lead to results with different locations and values as compared to the calculation with subject-specific models. Interpretations of silent spaces should be proceeded with caution.

Effects of PEEP on the relationship between tidal volume and total impedance change measured via electrical impedance tomography (EIT)

Electrical impedance tomography (EIT) is used in lung physiology monitoring. There is evidence that EIT is linearly associated with global tidal volume (VT) in clinically healthy patients where no positive end-expiratory pressure (PEEP) is applied. This linearity has not been challenged by altering lung conditions. The aim of this study was to determine the effect of PEEP on VT estimation, using EIT technology and spirometry, and observe the stability of the relationship under changing lung conditions. Twelve male castrated cattle (Steer), mean age 7.8 months (SD ± 1.7) were premedicated with xylazine followed by anaesthesia induction with ketamine and maintenance with halothane in oxygen via an endotracheal tube. An EIT belt was applied around the thorax at the level of the fifth intercostal space. Volume controlled ventilation was used. PEEP was increased in a stepwise manner from 0 to 5, 10 and 15 cmH₂O. At each PEEP, the VT was increased stepwise from 5 to 10 and 15 mL kg^-1. After a minute of stabilisation, total impedance change (VT_EIT), using EIT and VT measured by a spirometer connected to a flow-partitioning device (VT_Spiro) was recorded for the following minute before changing ventilator settings. Data was analysed using linear regression and multi variable analysis. There was a linear relationship between VT_EIT and VT_Spiro at all levels of PEEP with an R² of 0.71, 0.68, 0.63 and 0.63 at 0, 5, 10 and 15 cmH₂O, respectively. The variance in VT_EIT was best described by peak inspiratory pressure (PIP) and PEEP (adjusted R² 0.82) while variance in VT_Spiro was best described by PIP and airway deadspace (adjusted R² 0.76). The relationship between VT_EIT and VT_Spiro remains linear with changes in tidal volume, and stable across altered lung conditions. This may have application for monitoring and assessment in vivo.

A Point-Matching Method of Moment with Sparse Bayesian Learning Applied and Evaluated in Dynamic Lung Electrical Impedance Tomography

Dynamic lung imaging is a major application of Electrical Impedance Tomography (EIT) due to EIT's exceptional temporal resolution, low cost and absence of radiation. EIT however lacks in spatial resolution and the image reconstruction is very sensitive to mismatches between the actual object's and the reconstruction domain's geometries, as well as to the signal noise. The non-linear nature of the reconstruction problem may also be a concern, since the lungs' significant conductivity changes due to inhalation and exhalation. In this paper, a recently introduced method of moment is combined with a sparse Bayesian learning approach to address the non-linearity issue, provide robustness to the reconstruction problem and reduce image artefacts. To evaluate the proposed methodology, we construct three CT-based time-variant 3D thoracic structures including the basic thoracic tissues and considering 5 different breath states from end-expiration to end-inspiration. The Graz consensus reconstruction algorithm for EIT (GREIT), the correlation coefficient (CC), the root mean square error (RMSE) and the full-reference (FR) metrics are applied for the image quality assessment. Qualitative and quantitative comparison with traditional and more advanced reconstruction techniques reveals that the proposed method shows improved performance in the majority of cases and metrics. Finally, the approach is applied to single-breath online in-vivo data to qualitatively verify its applicability.

Assessment of Postnatal Pulmonary Adaption in Bovine Neonates Using Electric Impedance Tomography (EIT)

Several aspects of postnatal pulmonary adaption in the bovine neonate remain unclear, particularly the dynamics and regional ventilation of the lungs. We used electric impedance tomography (EIT) to measure changes in ventilation in the first 3 weeks of life in 20 non-sedated neonatal calves born without difficulty in sternal recumbency. Arterial blood gas variables were determined in the first 24 h after birth. Immediately after birth, dorsal parts of the lungs had 4.53% ± 2.82% nondependent silent spaces (NSS), and ventral parts had 5.23% ± 2.66% dependent silent spaces (DSS). The latter increased in the first hour, presumably because of gravity-driven ventral movement of residual amniotic fluid. The remaining lung regions had good ventilation immediately after birth, and the percentage of lung regions with high ventilation increased significantly during the study period. The centre of ventilation was always dorsal to and on the right of the theoretical centre of ventilation. The right lung was responsible for a significantly larger proportion of ventilation (63.84% ± 12.74%, p < 0.00001) compared with the left lung. In the right lung, the centrodorsal lung area was the most ventilated, whereas, in the left lung, it was the centroventral area. Tidal impedance changes, serving as a surrogate for tidal volume, increased in the first 3 weeks of life (p < 0.00001). This study shows the dynamic changes in lung ventilation in the bovine neonate according to EIT measurements. The findings form a basis for the recognition of structural and functional lung disorders in neonatal calves.

A model-based source separation algorithm for lung perfusion imaging using electrical impedance tomography

Objective. Electrical impedance tomography (EIT) for lung perfusion imaging is attracting considerable interest in intensive care, as it might open up entirely new ways to adjust ventilation therapy. A promising technique is bolus injection of a conductive indicator to the central venous catheter, which yields the indicator-based signal (IBS). Lung perfusion images are then typically obtained from the IBS using the maximum slope technique. However, the low spatial resolution of EIT results in a partial volume effect (PVE), which requires further processing to avoid regional bias.Approach. In this work, we repose the extraction of lung perfusion images from the IBS as a source separation problem to account for the PVE. We then propose a model-based algorithm, called gamma decomposition (GD), to derive an efficient solution. The GD algorithm uses a signal model to transform the IBS into a parameter space where the source signals of heart and lung are separable by clustering in space and time. Subsequently, it reconstructs lung model signals from which lung perfusion images are unambiguously extracted.Main results. We evaluate the GD algorithm on EIT data of a prospective animal trial with eight pigs. The results show that it enables lung perfusion imaging using EIT at different stages of regional impairment. Furthermore, parameters of the source signals seem to represent physiological properties of the cardio-pulmonary system.Significance. This work represents an important advance in IBS processing that will likely reduce bias of EIT perfusion images and thus eventually enable imaging of regional ventilation/perfusion (V/Q) ratio.

Dynamic lung behavior under high G acceleration monitored with electrical impedance tomography

OBJECTIVE

During launch and atmospheric re-entry in suborbital space flights, astronauts are exposed to high G-acceleration. These acceleration levels influence gas exchange inside the lung and can potentially lead to hypoxaemia. The distribution of air inside the lung can be monitored by Electrical Impedance Tomography (EIT). This imaging technique might reveal how high gravitational forces affect the dynamic behavior of ventilation and impair gas exchange resulting in hypoxaemia.

APPROACH

We performed a trial in a long-arm centrifuge with ten participants lying supine while being exposed to +2, +4 and +6\,G_x(chest-to-back acceleration) to study the magnitude of accelerations experienced during suborbital spaceflight.

MAIN RESULTS

First, the tomographic images revealed that the dorsal region of the lung emptied faster than the ventral region. Second, the ventilated area shifted from dorsal to ventral. Consequently, alveolar pressure in the dorsal area reached the pressure of the upper airways before the ventral area emptied completely. Finally, the upper airways collapsed and the end-expiratory volume increased. This resulted in ventral gas trapping with restricted gas exchange.

SIGNIFICANCE

At +4_xchanges in ventilation distribution varied considerably between subjects potentially due to variation in individual physical conditions. However, at +6\,G_xall participants were affected similarly and the influence of high gravitational conditions was pronounced.

Evaluation of Thoracic Equivalent Multiport Circuits Using an Electrical Impedance Tomography Hardware Simulation Interface

Electrical impedance tomography is a low-cost, safe, and high temporal resolution medical imaging modality which finds extensive application in real-time thoracic impedance imaging. Thoracic impedance changes can reveal important information about the physiological condition of patients’ lungs. In this way, electrical impedance tomography can be a valuable tool for monitoring patients. However, this technique is very sensitive to measurement noise or possible minor signal errors, coming from either the hardware, the electrodes, or even particular biological signals. Thus, the design of a good performance electrical impedance tomography hardware setup which properly interacts with the tissue examined is both an essential and a challenging concept. In this paper, we adopt an extensive simulation approach, which combines the system’s analogue and digital hardware, along with equivalent circuits of 3D finite element models that represent thoracic cavities. Each thoracic finite element model is created in MATLAB based on existing CT images, while the tissues’ conductivity and permittivity values for a selected frequency are acquired from a database using Python. The model is transferred to a multiport RLC network, embedded in the system’s hardware which is simulated at LT SPICE. The voltage output data are transferred to MATLAB where the electrical impedance tomography signal sampling and digital processing is also simulated. Finally, image reconstructions are performed in MATLAB, using the EIDORS library tool and considering the signal noise levels and different electrode and signal sampling configurations (ADC bits, sampling frequency, number of taps).

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

OBJECTIVE

Anti-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.

METHODS

Eight 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.

RESULTS

For 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).

CONCLUSION

These 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.

Lung regions identified with CT improve the value of global inhomogeneity index measured with electrical impedance tomography

Background

The global inhomogeneity (GI) index is a functional electrical impedance tomography (EIT) parameter which is used clinically to assess ventilation distribution. However, GI may underestimate the actual heterogeneity when the size of lung regions is underestimated. We propose a novel method to use anatomical information to correct the GI index calculation.

Methods

EIT measurements were performed at the level of the fifth intercostal space in six patients with acute respiratory distress syndrome. The thorax and lungs were segmented automatically from serial individual CT scans. The anatomically derived lung regions were calculated in EIT images from simulating a homogeneous ventilation distribution in a finite element model. The conventional approach (GI_meas,func ), analyzes images in functionally-defined lung regions, while our proposed measure (GI_meas,anat ) is based on analysis in anatomically-defined regions. We additionally define a simulated comparison (GI_sim,anat ) to determine the lower limit of the GI measure for a homogenous distribution of ventilation.

Results

As expected, the conventional GI_meas,func [0.382 (0.088), median (interquartile range)] were significantly lower than the proposed GI_meas,anat [0.823 (0.152), P<0.05], and were much closer to the lower limit GI_sim,anat [0.343 (0.039)]. Both GI_meas,anat and GI_meas,func were strongly correlated with arterial oxygen partial pressure to fractional inspired oxygen ratio (R=-0.88, P<0.05), whereas GI_sim,anat (R=0.23) was not. GI_meas,anat had a linear-regression slope 3.2 times that of GI_meas,func suggesting a higher sensitivity to the changes in lung condition.

Conclusions

The proposed GI_meas,anat (or shortened as GI_anat ) is an improved measure of ventilation inhomogeneity over GI, and better reflects portion of non-ventilated regions due to alveolar collapse or overdistension.

Model Selection Based Algorithm in Neonatal Chest EIT

This paper presents a new method for selecting a patient specific forward model to compensate for anatomical variations in electrical impedance tomography (EIT) monitoring of neonates. The method uses a combination of shape sensors and absolute reconstruction. It takes advantage of a probabilistic approach which automatically selects the best estimated forward model fit from pre-stored library models. Absolute/static image reconstruction is performed as the core of the posterior probability calculations. The validity and reliability of the algorithm in detecting a suitable model in the presence of measurement noise is studied with simulated and measured data from 11 patients. The paper also demonstrates the potential improvements on the clinical parameters extracted from EIT images by considering a unique case study with a neonate patient undergoing computed tomography imaging as clinical indication prior to EIT monitoring. Two well-known image reconstruction techniques, namely GREIT and tSVD, are implemented to create the final tidal images. The impacts of appropriate model selection on the clinical extracted parameters such as center of ventilation and silent spaces are investigated. The results show significant improvements to the final reconstructed images and more importantly to the clinical EIT parameters extracted from the images that are crucial for decision-making and further interventions.

Regional Lung Perfusion Analysis in Experimental ARDS by Electrical Impedance and Computed Tomography

Electrical impedance tomography is clinically used to trace ventilation related changes in electrical conductivity of lung tissue. Estimating regional pulmonary perfusion using electrical impedance tomography is still a matter of research. To support clinical decision making, reliable bedside information of pulmonary perfusion is needed. We introduce a method to robustly detect pulmonary perfusion based on indicator-enhanced electrical impedance tomography and validate it by dynamic multidetector computed tomography in two experimental models of acute respiratory distress syndrome. The acute injury was induced in a sublobar segment of the right lung by saline lavage or endotoxin instillation in eight anesthetized mechanically ventilated pigs. For electrical impedance tomography measurements, a conductive bolus (10% saline solution) was injected into the right ventricle during breath hold. Electrical impedance tomography perfusion images were reconstructed by linear and normalized Gauss-Newton reconstruction on a finite element mesh with subsequent element-wise signal and feature analysis. An iodinated contrast agent was used to compute pulmonary blood flow via dynamic multidetector computed tomography. Spatial perfusion was estimated based on first-pass indicator dilution for both electrical impedance and multidetector computed tomography and compared by Pearson correlation and Bland-Altman analysis. Strong correlation was found in dorsoventral (r = 0.92) and in right-to-left directions (r = 0.85) with good limits of agreement of 8.74% in eight lung segments. With a robust electrical impedance tomography perfusion estimation method, we found strong agreement between multidetector computed and electrical impedance tomography perfusion in healthy and regionally injured lungs and demonstrated feasibility of electrical impedance tomography perfusion imaging.

Electrical Impedance Tomography - Recent Applications and Developments

Electrical impedance tomography (EIT) is a low-cost noninvasive imaging method. The main purpose of this paper is to highlight the main aspects of the EIT method and to review the recent advances and developments. The advances in instrumentation and in the different image reconstruction methods and systems are demonstrated in this review. The main applications of the EIT are presented and a special attention made to the papers published during the last years (from 2015 until 2020). The advantages and limitations of EIT are also presented. In conclusion, EIT is a promising imaging approach with a strong potential that has a large margin of progression before reaching the maturity phase.

Synchronized Inflations Generate Greater Gravity-Dependent Lung Ventilation in Neonates

OBJECTIVE

To describe the regional distribution patterns of tidal ventilation within the lung during mechanical ventilation that is synchronous or asynchronous with an infant's own breathing effort.

STUDY DESIGN

Intubated infants receiving synchronized mechanical ventilation at The Royal Children's Hospital neonatal intensive care unit were studied. During four 10-minute periods of routine care, regional distribution of tidal volume (V_T; electrical impedance tomography), delivered pressure, and airway flow (Florian Respiratory Monitor) were measured for every inflation. Post hoc, each inflation was then classified as synchronous or asynchronous from video data of the ventilator screen, and the distribution of absolute V_T and delivered ventilation characteristics determined.

RESULTS

In total, 2749 inflations (2462 synchronous) were analyzed in 19 infants; mean (SD) age 28 (30) days, gestational age 35 (5) weeks. Synchronous inflations were associated with a shorter respiratory cycle (P = .004) and more homogenous V_T (center of ventilation) along the right (0%) to left (100%) lung plane; 45.3 (8.6)% vs 48.8 (9.4)% (uniform ventilation 46%). The gravity-dependent center of ventilation was a mean (95% CI) 2.1 (-0.5, 4.6)% toward the dependent lung during synchronous inflations. Tidal ventilation relative to anatomical lung size was more homogenous during synchronized inflations in the dependent lung.

CONCLUSIONS

Synchronous mechanical ventilator lung inflations generate more gravity-dependent lung ventilation and more uniform right-to-left ventilation than asynchronous inflations.

Beneficial techniques for spatio-temporal imaging in electrical impedance tomography

OBJECTIVE

Electrical impedance tomography (EIT) typically reconstructs individual images from electrical voltage measurements at pairs of electrodes due to current driven through other electrode pairs on a body. EIT images have low spatial resolution, but excellent temporal resolution. There are four methods for integrating temporal data into an EIT reconstruction: filtering over measurements, filtering over images, combined spatial and temporal (spatio-temporal) regularization, and Kalman filtering. These spatio-temporal methods have not been directly compared, making it difficult to evaluate relative performance and choose an appropriate method for particular use cases.

APPROACH

We (i) develop a common framework, (ii) develop comparison metrics, (iii) perform simulation and tank studies which directly compare algorithms, and (iv) report on relative advantages of the different algorithms.

MAIN RESULTS

Temporal filtering is well understood, but often not considered as part of the imaging process despite a direct impact on image reconstruction quality. Spatio-temporal regularized techniques are not yet efficient but offer tantalizing advantages. Kalman filtering enables adaptive filtering for time-varying measurement/image noise at the cost of often over-regularized (sub-optimal) images which can now be understood in the same framework as the other techniques. Further research into efficient implementations of Gauss-Newton spatio-temporal regularization will allow temporal and spatial covariance to be explicitly defined for longer time series (n > 10 frames) where temporal regularization can be more effective. For the immediate analysis of temporally varying images, we recommend the use of adaptive (time-varying) temporal filtering of measurements followed by adaptive spatial regularization (hyperparameter selection) as the most computationally efficient and effective approach currently available.

SIGNIFICANCE

The analysis of variation within regions of an EIT image to extract physiological measures (functional imaging), has become an important EIT technique where temporal and spatial aspects of analysis are tightly integrated. This work gives guidance on available methods and suggests directions for future research.

Reconstruction algorithm for frequency-differential EIT using absolute values

OBJECTIVE

Tissues in the body differ by their frequency-dependent conductivity. Frequency-differential electrical impedance tomography (fdEIT) is a promising technique to reconstruct the distribution of tissue inside the body by injecting current at two frequencies and measuring the resulting surface-potential.

APPROACH

The Gauss-Newton method is one way to map the surface measurements to a conductivity image. Usually, the minimization function contains only weighted differential measurement data and a regularization. This traditional method is extended by absolute measurement data to improve fdEIT reconstruction results. The key challenge of unknown torso geometries and electrode displacement has been addressed for the reconstruction of different lung pathologies.

MAIN RESULTS

The frequency-dependent conductivity of the background was reconstructed precisely and a contrast between organs was achieved. The algorithm shows good performance compared to GREIT and the traditional Gauss-Newton method with respect to the figures of merit of GREIT.

SIGNIFICANCE

The reconstruction is robust in the presence of noise. One application of the algorithm might be the detection and monitoring of lung diseases like edema or atelectasis.

Torso shape detection to improve lung monitoring

OBJECTIVE

Newborns with lung immaturity often require continuous monitoring and treatment of their lung ventilation in intensive care units, especially if born preterm. Recent studies indicate that electrical impedance tomography (EIT) is feasible in newborn infants and children, and can quantitatively identify changes in regional lung aeration and ventilation following alterations to respiratory conditions. Information on the patient-specific shape of the torso and its role in minimizing the artefacts in the reconstructed images can improve the accuracy of the clinical parameters obtained from EIT. Currently, only idealized models or those segmented from CT scans are usually adopted.

APPROACH

This study presents and compares two methodologies that can detect the patient-specific torso shape by means of wearable devices based on (1) previously reported bend sensor technology, and (2) a novel approach based on the use of accelerometers.

MAIN RESULTS

The reconstruction of different phantoms, taking into account anatomical asymmetries and different sizes, are produced for comparison.

SIGNIFICANCE

As a result, the accelerometers are more versatile than bend sensors, which cannot be used on bigger cross-sections. The computational study estimates the optimal number of accelerometers required in order to generate an image reconstruction comparable to the use of a CT scan as the forward model. Furthermore, since the patient position is crucial to monitoring lung ventilation, the orientation of the phantoms is automatically detected by the accelerometer-based method.

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.

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.

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.

Effects of individualized electrical impedance tomography and image reconstruction settings upon the assessment of regional ventilation distribution: Comparison to 4-dimensional computed tomography in a porcine model

Electrical impedance tomography (EIT) is a promising imaging technique for bedside monitoring of lung function. It is easily applicable, cheap and requires no ionizing radiation, but clinical interpretation of EIT-images is still not standardized. One of the reasons for this is the ill-posed nature of EIT, allowing a range of possible images to be produced–rather than a single explicit solution. Thus, to further advance the EIT technology for clinical application, thorough examinations of EIT-image reconstruction settings–i.e., mathematical parameters and addition of a priori (e.g., anatomical) information–is essential. In the present work, regional ventilation distribution profiles derived from different EIT finite-element reconstruction models and settings (for GREIT and Gauss Newton) were compared to regional aeration profiles assessed by the gold-standard of 4-dimensional computed tomography (4DCT) by calculating the root mean squared error (RMSE). Specifically, non-individualized reconstruction models (based on circular and averaged thoracic contours) and individualized reconstruction models (based on true thoracic contours) were compared. Our results suggest that GREIT with noise figure of 0.15 and non-uniform background works best for the assessment of regional ventilation distribution by EIT, as verified versus 4DCT. Furthermore, the RMSE of anteroposterior ventilation profiles decreased from 2.53±0.62% to 1.67±0.49% while correlation increased from 0.77 to 0.89 after embedding anatomical information into the reconstruction models. In conclusion, the present work reveals that anatomically enhanced EIT-image reconstruction is superior to non-individualized reconstruction models, but further investigations in humans, so as to standardize reconstruction settings, is warranted.

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.

Lobe based image reconstruction in Electrical Impedance Tomography

PURPOSE

Electrical Impedance Tomography (EIT) is an imaging modality used to generate two-dimensional cross-sectional images representing impedance change in the thorax. The impedance of lung tissue changes with change in air content of the lungs; hence, EIT can be used to examine regional lung ventilation in patients with abnormal lungs. In lung EIT, electrodes are attached around the circumference of the thorax to inject small alternating currents and measure resulting voltages. In contrast to X-ray computed tomography (CT), EIT images do not depict a thorax slice of well defined thickness, but instead visualize a lens-shaped region around the electrode plane, which results from diffuse current propagation in the thorax. Usually, this is considered a drawback, since image interpretation is impeded if 'off-plane' conductivity changes are projected onto the reconstructed two-dimensional image. In this paper we describe an approach that takes advantage of current propagation below and above the electrode plane. The approach enables estimation of the individual conductivity change in each lung lobe from boundary voltage measurements. This could be used to monitor disease progression in patients with obstructive lung diseases, such as chronic obstructive pulmonary disease (COPD) or cystic fibrosis (CF) and to obtain a more comprehensive insight into the pathophysiology of the lung.

METHODS

Electrode voltages resulting from different conductivities in each lung lobe were simulated utilizing a realistic 3D finite element model (FEM) of the human thorax and the lungs. Overall 200 different patterns of conductivity change were simulated. A 'lobe reconstruction' algorithm was developed, applying patient-specific anatomical information in the reconstruction process. A standard EIT image reconstruction algorithm and the proposed 'lobe reconstruction' algorithm were used to estimate conductivity change in the lobes. The agreement between simulated and reconstructed conductivity change in particular lobes were compared using Bland-Altman plots, correlation plots and linear regression. To test the applicability of the approach in a realistic scenario, EIT measurements of a patient suffering from cystic fibrosis (CF) were carried out.

RESULTS

Conductivity changes in each lobe generate specific patterns of voltage change. These can be used to estimate the conductivity change in lobes from measured boundary voltage. The correlation coefficient between simulated and reconstructed conductivity change in particular lobes is r > 0.89 for all lobes. Unknown position of the electrode plane leads to over- or underestimation of reconstructed conductivity change. Slight mismatches (± 5% of the forward model height) between the actual position of the electrode plane and the position used in the reconstruction model lead to regression coefficients of 0.7 to 1.3 between simulated and reconstructed conductivity change in the lobes.

CONCLUSION

The presented approach enhances common reconstruction methods by providing information about anatomically assignable units and thus facilitates image interpretation, since impedance change and thus ventilation of each lobe is directly determined in the reconstructions.

Compensation for large thorax excursions in EIT imaging

Besides the application of EIT in the intensive care unit it has recently also been used in spontaneously breathing patients suffering from asthma bronchiole, cystic fibrosis (CF) or chronic obstructive pulmonary disease (COPD). In these cases large thorax excursions during deep inspiration, e.g. during lung function testing, lead to artifacts in the reconstructed images. In this paper we introduce a new approach to compensate for image artifacts resulting from excursion induced changes in boundary voltages. It is shown in a simulation study that boundary voltage change due to thorax excursion on a homogeneous model can be used to modify the measured voltages and thus reduce the impact of thorax excursion on the reconstructed images. The applicability of the method on human subjects is demonstrated utilizing a motion-tracking-system. The proposed technique leads to fewer artifacts in the reconstructed images and improves image quality without substantial increase in computational effort, making the approach suitable for real-time imaging of lung ventilation. This might help to establish EIT as a supplemental tool for lung function tests in spontaneously breathing patients to support clinicians in diagnosis and monitoring of disease progression.

Structural-functional lung imaging using a combined CT-EIT and a Discrete Cosine Transformation reconstruction method

Lung EIT is a functional imaging method that utilizes electrical currents to reconstruct images of conductivity changes inside the thorax. This technique is radiation free and applicable at the bedside, but lacks of spatial resolution compared to morphological imaging methods such as X-ray computed tomography (CT). In this article we describe an approach for EIT image reconstruction using morphologic information obtained from other structural imaging modalities. This leads to recon- structed images of lung ventilation that can easily be superimposed with structural CT or MRI images, which facilitates image interpretation. The approach is based on a Discrete Cosine Transformation (DCT) of an image of the considered transversal thorax slice. The use of DCT enables reduction of the dimensionality of the reconstruction and ensures that only conductivity changes of the lungs are reconstructed and displayed. The DCT based approach is well suited to fuse morphological image information with functional lung imaging at low computational costs. Results on simulated data indicate that this approach preserves the morphological structures of the lungs and avoids blurring of the solution. Images from patient measurements reveal the capabilities of the method and demonstrate benefits in possible applications.

An individualized approach to sustained inflation duration at birth improves outcomes in newborn preterm lambs

A sustained first inflation (SI) at birth may aid lung liquid clearance and aeration, but the impact of SI duration relative to the volume-response of the lung is poorly understood. We compared three SI strategies: 1) variable duration defined by attaining volume equilibrium using real-time electrical impedance tomography (EIT; SIplat); 2) 30 s beyond equilibrium (SIlong); 3) short 30-s SI (SI30); and 4) positive pressure ventilation without SI (no-SI) on spatiotemporal aeration and ventilation (EIT), gas exchange, lung mechanics, and regional early markers of injury in preterm lambs. Fifty-nine fetal-instrumented lambs were ventilated for 60 min after applying the allocated first inflation strategy. At study completion molecular and histological markers of lung injury were analyzed. The time to SI volume equilibrium, and resultant volume, were highly variable; mean (SD) 55 (34) s, coefficient of variability 59%. SIplat and SIlong resulted in better lung mechanics, gas exchange and lower ventilator settings than both no-SI and SI30. At 60 min, alveolar-arterial difference in oxygen was a mean (95% confidence interval) 130 (13, 249) higher in SI30 vs. SIlong group (two-way ANOVA). These differences were due to better spatiotemporal aeration and tidal ventilation, although all groups showed redistribution of aeration towards the nondependent lung by 60 min. Histological lung injury scores mirrored spatiotemporal change in aeration and were greatest in SI30 group ( P < 0.01, Kruskal-Wallis test). An individualized volume-response approach to SI was effective in optimizing aeration, homogeneous tidal ventilation, and respiratory outcomes, while an inadequate SI duration had no benefit over positive pressure ventilation alone.

Influence of heart motion on cardiac output estimation by means of electrical impedance tomography: a case study

Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.

Electrical impedance tomography imaging of the cardiopulmonary system

PURPOSE OF REVIEW

This review article summarizes the recent advances in electrical impedance tomography (EIT) related to cardiopulmonary imaging and monitoring on the background of the 30-year development of this technology.

RECENT FINDINGS

EIT is expected to become a bedside tool for monitoring and guiding ventilator therapy. In this context, several studies applied EIT to determine spatial ventilation distribution during different ventilation modes and settings. EIT was increasingly combined with other signals, such as airway pressure, enabling the assessment of regional respiratory system mechanics. EIT was for the first time used prospectively to define ventilator settings in an experimental and a clinical study. Increased neonatal and paediatric use of EIT was noted. Only few studies focused on cardiac function and lung perfusion. Advanced radiological imaging techniques were applied to assess EIT performance in detecting regional lung ventilation. New approaches to improve the quality of thoracic EIT images were proposed.

SUMMARY

EIT is not routinely used in a clinical setting, but the interest in EIT is evident. The major task for EIT research is to provide the clinicians with guidelines how to conduct, analyse and interpret EIT examinations and combine them with other medical techniques so as to meaningfully impact the clinical decision-making.

Steps towards 3D Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) is a promising imaging technique to visualize the dynamics of regional lung ventilation. 2D EIT has shown promise in monitoring ventilation therapy, with the drawback of only displaying a single horizontal slice of the lungs. Until now there are no generally accepted approaches available to generate meaningful 3D images in real-time. This paper describes general problems and first attempts to overcome those that may extend to a hierarchical scheme for 3D EIT imaging.

Functional validation and comparison framework for EIT lung imaging

INTRODUCTION

Electrical impedance tomography (EIT) is an emerging clinical tool for monitoring ventilation distribution in mechanically ventilated patients, for which many image reconstruction algorithms have been suggested. We propose an experimental framework to assess such algorithms with respect to their ability to correctly represent well-defined physiological changes. We defined a set of clinically relevant ventilation conditions and induced them experimentally in 8 pigs by controlling three ventilator settings (tidal volume, positive end-expiratory pressure and the fraction of inspired oxygen). In this way, large and discrete shifts in global and regional lung air content were elicited.

METHODS

We use the framework to compare twelve 2D EIT reconstruction algorithms, including backprojection (the original and still most frequently used algorithm), GREIT (a more recent consensus algorithm for lung imaging), truncated singular value decomposition (TSVD), several variants of the one-step Gauss-Newton approach and two iterative algorithms. We consider the effects of using a 3D finite element model, assuming non-uniform background conductivity, noise modeling, reconstructing for electrode movement, total variation (TV) reconstruction, robust error norms, smoothing priors, and using difference vs. normalized difference data.

RESULTS AND CONCLUSIONS

Our results indicate that, while variation in appearance of images reconstructed from the same data is not negligible, clinically relevant parameters do not vary considerably among the advanced algorithms. Among the analysed algorithms, several advanced algorithms perform well, while some others are significantly worse. Given its vintage and ad-hoc formulation backprojection works surprisingly well, supporting the validity of previous studies in lung EIT.

Choice of reconstructed tissue properties affects interpretation of lung EIT images

Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization.

Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

Determination of respiratory gas flow by electrical impedance tomography in an animal model of mechanical ventilation

Background

A recent method determines regional gas flow of the lung by electrical impedance tomography (EIT). The aim of this study is to show the applicability of this method in a porcine model of mechanical ventilation in healthy and diseased lungs. Our primary hypothesis is that global gas flow measured by EIT can be correlated with spirometry. Our secondary hypothesis is that regional analysis of respiratory gas flow delivers physiologically meaningful results.

Methods

In two sets of experiments n = 7 healthy pigs and n = 6 pigs before and after induction of lavage lung injury were investigated. EIT of the lung and spirometry were registered synchronously during ongoing mechanical ventilation. In-vivo aeration of the lung was analysed in four regions-of-interest (ROI) by EIT: 1) global, 2) ventral (non-dependent), 3) middle and 4) dorsal (dependent) ROI. Respiratory gas flow was calculated by the first derivative of the regional aeration curve. Four phases of the respiratory cycle were discriminated. They delivered peak and late inspiratory and expiratory gas flow (PIF, LIF, PEF, LEF) characterizing early or late inspiration or expiration.

Results

Linear regression analysis of EIT and spirometry in healthy pigs revealed a very good correlation measuring peak flow and a good correlation detecting late flow. PIF_EIT = 0.702 · PIF_spiro + 117.4, r² = 0.809; PEF_EIT = 0.690 · PEF_spiro-124.2, r² = 0.760; LIF_EIT = 0.909 · LIF_spiro + 27.32, r² = 0.572 and LEF_EIT = 0.858 · LEF_spiro-10.94, r² = 0.647. EIT derived absolute gas flow was generally smaller than data from spirometry. Regional gas flow was distributed heterogeneously during different phases of the respiratory cycle. But, the regional distribution of gas flow stayed stable during different ventilator settings. Moderate lung injury changed the regional pattern of gas flow.

Conclusions

We conclude that the presented method is able to determine global respiratory gas flow of the lung in different phases of the respiratory cycle. Additionally, it delivers meaningful insight into regional pulmonary characteristics, i.e. the regional ability of the lung to take up and to release air.

Monitoring respiration: what the clinician needs to know

A recent large prospective cohort study showed an unexpectedly high in-hospital mortality after major non-cardiac surgery in Europe, as well as a high incidence of postoperative pulmonary complications. The direct effect of postoperative respiratory complications on mortality is still under investigation, for intensive care unit (ICU) and in the perioperative period. Although respiratory monitoring has not been actually proven to affect in-hospital mortality, it plays an important role in patient care, leading to appropriate setting of ventilatory support as well as risk stratification. The aim of this article is to provide an overview of various respiratory monitoring techniques including the role of conventional and most recent methods in the perioperative period and in critically ill patients. The most recent techniques proposed for bedside respiratory monitoring, including lung imaging, are presented and discussed, comparing them to those actually considered as gold standards.