Electrical Impedance Tomography-based Ventilation Patterns in Patients after Major Surgery.

Rationale: General anesthesia and mechanical ventilation have negative impacts on the respiratory system, causing heterogeneous distribution of lung aeration, but little is known about the ventilation patterns of postoperative patients and their association with clinical outcomes. Objectives: To clarify the phenotypes of ventilation patterns along a gravitational direction after surgery by using electrical impedance tomography (EIT) and to evaluate their association with postoperative pulmonary complications (PPCs) and other relevant clinical outcomes. Methods: Adult postoperative patients at high risk for PPCs, receiving mechanical ventilation on ICU admission (N = 128), were prospectively enrolled between November 18, 2021 and July 18, 2022. PPCs were prospectively scored until hospital discharge, and their association with phenotypes of ventilation patterns was studied. The secondary outcomes were the times to wean from mechanical ventilation and oxygen use and the length of ICU stay. Measurements and Main Results: Three phenotypes of ventilation patterns were revealed by EIT: phenotype 1 (32% [n = 41], a predominance of ventral ventilation), phenotype 2 (41% [n = 52], homogeneous ventilation), and phenotype 3 (27% [n = 35], a predominance of dorsal ventilation). The median PPC score was higher in phenotype 1 and phenotype 3 than in phenotype 2. The median time to wean from mechanical ventilation was longer in phenotype 1 versus phenotype 2. The median duration of ICU stay was longer in phenotype 1 versus phenotype 2. The median time to wean from oxygen use was longer in phenotype 1 and phenotype 3 than in phenotype 2. Conclusions: Inhomogeneous ventilation patterns revealed by EIT on ICU admission were associated with PPCs, delayed weaning from mechanical ventilation and oxygen use, and a longer ICU stay.

Deciphering Mechanisms of Respiratory Fetal-to-Neonatal Transition in Very Preterm Infants.

Rationale: The respiratory mechanisms of a successful transition of preterm infants after birth are largely unknown. Objectives: To describe intrapulmonary gas flows during different breathing patterns directly after birth. Methods: Analysis of electrical impedance tomography data from a previous randomized trial in preterm infants at 26-32 weeks gestational age. Electrical impedance tomography data for individual breaths were extracted, and lung volumes as well as ventilation distribution were calculated for end of inspiration, end of expiratory braking and/or holding maneuver, and end of expiration. Measurements and Main Results: Overall, 10,348 breaths from 33 infants were analyzed. We identified three distinct breath types within the first 10 minutes after birth: tidal breathing (44% of all breaths; sinusoidal breathing without expiratory disruption), braking (50%; expiratory brake with a short duration), and holding (6%; expiratory brake with a long duration). Only after holding breaths did end-expiratory lung volume increase: Median (interquartile range [IQR]) = 2.0 AU/kg (0.6 to 4.3), 0.0 (-1.0 to 1.1), and 0.0 (-1.1 to 0.4), respectively; P < 0.001]. This was mediated by intrathoracic air redistribution to the left and non-gravity-dependent parts of the lung through pendelluft gas flows during braking and/or holding maneuvers. Conclusions: Respiratory transition in preterm infants is characterized by unique breathing patterns. Holding breaths contribute to early lung aeration after birth in preterm infants. This is facilitated by air redistribution during braking/holding maneuvers through pendelluft flow, which may prevent lung liquid reflux in this highly adaptive situation. This study deciphers mechanisms for a successful fetal-to-neonatal transition and increases our pathophysiological understanding of this unique moment in life. Clinical trial registered with www.clinicaltrials.gov (NCT04315636).

Electrical Impedance Tomography to Monitor Hypoxemic Respiratory Failure.

Hypoxemic respiratory failure is one of the leading causes of mortality in intensive care. Frequent assessment of individual physiological characteristics and delivery of personalized mechanical ventilation (MV) settings is a constant challenge for clinicians caring for these patients. Electrical impedance tomography (EIT) is a radiation-free bedside monitoring device that is able to assess regional lung ventilation and changes in aeration. With real-time tomographic functional images of the lungs obtained through a thoracic belt, clinicians can visualize and estimate the distribution of ventilation at different ventilation settings or following procedures such as prone positioning. Several studies have evaluated the performance of EIT to monitor the effects of different MV settings in patients with acute respiratory distress syndrome, allowing more personalized MV. For instance, EIT could help clinicians find the positive end-expiratory pressure that represents a compromise between recruitment and overdistension and assess the effect of prone positioning on ventilation distribution. The clinical impact of the personalization of MV remains to be explored. Despite inherent limitations such as limited spatial resolution, EIT also offers a unique noninvasive bedside assessment of regional ventilation changes in the ICU. This technology offers the possibility of a continuous, operator-free diagnosis and real-time detection of common problems during MV. This review provides an overview of the functioning of EIT, its main indices, and its performance in monitoring patients with acute respiratory failure. Future perspectives for use in intensive care are also addressed.

Electrical Impedance Tomography as a monitoring tool during weaning from mechanical ventilation: an observational study during the spontaneous breathing trial.

BACKGROUND: Prolonged weaning from mechanical ventilation is associated with poor clinical outcome. Therefore, choosing the right moment for weaning and extubation is essential. Electrical Impedance Tomography (EIT) is a promising innovative lung monitoring technique, but its role in supporting weaning decisions is yet uncertain. We aimed to evaluate physiological trends during a T-piece spontaneous breathing trail (SBT) as measured with EIT and the relation between EIT parameters and SBT success or failure. METHODS: This is an observational study in which twenty-four adult patients receiving mechanical ventilation performed an SBT. EIT monitoring was performed around the SBT. Multiple EIT parameters including the end-expiratory lung impedance (EELI), delta Tidal Impedance (ΔZ), Global Inhomogeneity index (GI), Rapid Shallow Breathing Index (RSBIEIT), Respiratory Rate (RREIT) and Minute Ventilation (MVEIT) were computed on a breath-by-breath basis from stable tidal breathing periods. RESULTS: EELI values dropped after the start of the SBT (p < 0.001) and did not recover to baseline after restarting mechanical ventilation. The ΔZ dropped (p < 0.001) but restored to baseline within seconds after restarting mechanical ventilation. Five patients failed the SBT, the GI (p = 0.01) and transcutaneous CO2 (p < 0.001) values significantly increased during the SBT in patients who failed the SBT compared to patients with a successful SBT. CONCLUSION: EIT has the potential to assess changes in ventilation distribution and quantify the inhomogeneity of the lungs during the SBT. High lung inhomogeneity was found during SBT failure. Insight into physiological trends for the individual patient can be obtained with EIT during weaning from mechanical ventilation, but its role in predicting weaning failure requires further study.

First real-time imaging of bronchoscopic lung volume reduction by electrical impedance tomography.

BACKGROUND: Bronchoscopic lung volume reduction (BLVR) with one-way endobronchial valves (EBV) has better outcomes when the target lobe has poor collateral ventilation, resulting in complete lobe atelectasis. High-inspired oxygen fraction (FIO2) promotes atelectasis through faster gas absorption after airway occlusion, but its application during BLVR with EBV has been poorly understood. We aimed to investigate the real-time effects of FIO2 on regional lung volumes and regional ventilation/perfusion by electrical impedance tomography (EIT) during BLVR with EBV. METHODS: Six piglets were submitted to left lower lobe occlusion by a balloon-catheter and EBV valves with FIO2 0.5 and 1.0. Regional end-expiratory lung impedances (EELI) and regional ventilation/perfusion were monitored. Local pocket pressure measurements were obtained (balloon occlusion method). One animal underwent simultaneous acquisitions of computed tomography (CT) and EIT. Regions-of-interest (ROIs) were right and left hemithoraces. RESULTS: Following balloon occlusion, a steep decrease in left ROI-EELI with FIO2 1.0 occurred, 3-fold greater than with 0.5 (p < 0.001). Higher FIO2 also enhanced the final volume reduction (ROI-EELI) achieved by each valve (p < 0.01). CT analysis confirmed the denser atelectasis and greater volume reduction achieved by higher FIO2 (1.0) during balloon occlusion or during valve placement. CT and pocket pressure data agreed well with EIT findings, indicating greater strain redistribution with higher FIO2. CONCLUSIONS: EIT demonstrated in real-time a faster and more complete volume reduction in the occluded lung regions under high FIO2 (1.0), as compared to 0.5. Immediate changes in the ventilation and perfusion of ipsilateral non-target lung regions were also detected, providing better estimates of the full impact of each valve in place. TRIAL REGISTRATION: Not applicable.

Absolute values of regional ventilation-perfusion mismatch in patients with ARDS monitored by electrical impedance tomography and the role of dead space and shunt compensation.

BACKGROUND: Assessment of regional ventilation/perfusion (V'/Q) mismatch using electrical impedance tomography (EIT) represents a promising advancement for personalized management of the acute respiratory distress syndrome (ARDS). However, accuracy is still hindered by the need for invasive monitoring to calibrate ventilation and perfusion. Here, we propose a non-invasive correction that uses only EIT data and characterized patients with more pronounced compensation of V'/Q mismatch. METHODS: We enrolled twenty-one ARDS patients on controlled mechanical ventilation. Cardiac output was measured invasively, and ventilation and perfusion were assessed by EIT. Relative V'/Q maps by EIT were calibrated to absolute values using the minute ventilation to invasive cardiac output (MV/CO) ratio (V'/Q-ABS), left unadjusted (V'/Q-REL), or corrected by MV/CO ratio derived from EIT data (V'/Q-CORR). The ratio between ventilation to dependent regions and perfusion reaching shunted units ( V D ' /QSHUNT) was calculated as an index of more effective hypoxic pulmonary vasoconstriction. The ratio between perfusion to non-dependent regions and ventilation to dead space units (QND/ V DS ' ) was calculated as an index of hypocapnic pneumoconstriction. RESULTS: Our calibration factor correlated with invasive MV/CO (r = 0.65, p < 0.001), showed good accuracy and no apparent bias. Compared to V'/Q-ABS, V'/Q-REL maps overestimated ventilation (p = 0.013) and perfusion (p = 0.002) to low V'/Q units and underestimated ventilation (p = 0.011) and perfusion (p = 0.008) to high V'/Q units. The heterogeneity of ventilation and perfusion reaching different V'/Q compartments was underestimated. V'/Q-CORR maps eliminated all these differences with V'/Q-ABS (p > 0.05). Higher V D ' / Q SHUNT correlated with higher PaO2/FiO2 (r = 0.49, p = 0.025) and lower shunt fraction (ρ = - 0.59, p = 0.005). Higher Q ND / V DS ' correlated with lower PEEP (ρ = - 0.62, p = 0.003) and plateau pressure (ρ = - 0.59, p = 0.005). Lower values of both indexes were associated with less ventilator-free days (p = 0.05 and p = 0.03, respectively). CONCLUSIONS: Regional V'/Q maps calibrated with a non-invasive EIT-only method closely approximate the ones obtained with invasive monitoring. Higher efficiency of shunt compensation improves oxygenation while compensation of dead space is less needed at lower airway pressure. Patients with more effective compensation mechanisms could have better outcomes.

Lung Recruitment Assessed by Electrical Impedance Tomography (RECRUIT): A Multicenter Study of COVID-19 Acute Respiratory Distress Syndrome.

Rationale: Defining lung recruitability is needed for safe positive end-expiratory pressure (PEEP) selection in mechanically ventilated patients. However, there is no simple bedside method including both assessment of recruitability and risks of overdistension as well as personalized PEEP titration. Objectives: To describe the range of recruitability using electrical impedance tomography (EIT), effects of PEEP on recruitability, respiratory mechanics and gas exchange, and a method to select optimal EIT-based PEEP. Methods: This is the analysis of patients with coronavirus disease (COVID-19) from an ongoing multicenter prospective physiological study including patients with moderate-severe acute respiratory distress syndrome of different causes. EIT, ventilator data, hemodynamics, and arterial blood gases were obtained during PEEP titration maneuvers. EIT-based optimal PEEP was defined as the crossing point of the overdistension and collapse curves during a decremental PEEP trial. Recruitability was defined as the amount of modifiable collapse when increasing PEEP from 6 to 24 cm H2O (ΔCollapse24-6). Patients were classified as low, medium, or high recruiters on the basis of tertiles of ΔCollapse24-6. Measurements and Main Results: In 108 patients with COVID-19, recruitability varied from 0.3% to 66.9% and was unrelated to acute respiratory distress syndrome severity. Median EIT-based PEEP differed between groups: 10 versus 13.5 versus 15.5 cm H2O for low versus medium versus high recruitability (P < 0.05). This approach assigned a different PEEP level from the highest compliance approach in 81% of patients. The protocol was well tolerated; in four patients, the PEEP level did not reach 24 cm H2O because of hemodynamic instability. Conclusions: Recruitability varies widely among patients with COVID-19. EIT allows personalizing PEEP setting as a compromise between recruitability and overdistension. Clinical trial registered with www.clinicaltrials.gov (NCT04460859).

Determination of optimal positive end-expiratory pressure using electrical impedance tomography in infants under general anesthesia: Comparison between supine and prone positions.

AIMS: This study determined the optimal positive end-expiratory pressure levels in infants in supine and prone positions under general anesthesia using electrical impedance tomography (EIT). METHODS: This prospective observational single-centre study included infants scheduled for surgery in the prone position. An electrical impedance tomography sensor was applied after inducing general anesthesia. The optimal positive end-expiratory pressure in the supine position was determined in a decremental trial based on EIT and compliance. Subsequently, the patient's position was changed to prone. Electrical impedance tomography parameters, including global inhomogeneity index, regional ventilation delay, opening pressure, the centre of ventilation, and pendelluft volume, were continuously obtained up to 1 h after prone positioning. The optimal positive end-expiratory pressure in the prone position was similarly determined. RESULTS: Data from 30 infants were analyzed. The mean value of electrical impedance tomography-based optimal positive end-expiratory pressure in the prone position was significantly higher than that in the supine position [10.9 (1.6) cmH2O and 6.1 (0.9) cmH2O, respectively (p < .001)]. Significant differences were observed between electrical impedance tomography- and compliance-based optimal positive end-expiratory pressure. Peak and mean airway, plateau, and driving pressures increased 1 h after prone positioning compared with those in the supine position. In addition, the centre of ventilation for balance in ventilation between the ventral and dorsal regions improved. CONCLUSION: The prone position required higher positive end-expiratory pressure than the supine position in mechanically ventilated infants under general anesthesia. EIT is a promising tool to find the optimal positive end-expiratory pressure, which needs to be individualized.

A Coupled Double-Layer Electrical Impedance Tomography-Based Sensing Skin for Pressure and Leak Detection.

There is an extensive need for surface sensors for applications such as tactile sensing for robotics, damage and strain detection for structural health monitoring and leak detection for buried structures. One type of surface sensor is electrical impedance tomography (EIT)-based sensing skins, which use electrically conductive coatings applied on the object's surface to monitor physical or chemical phenomena on the surface. In this article, we propose a sensing skin with two electrically coupled layers separated by an insulator. Based on electrical measurements, the spatial distribution of the electrical coupling between the layers is estimated. This coupling is sensitive to both the pressure distribution on the surface and water entering between the layers through a leak. We present simulations and experimental studies to evaluate the feasibility of the proposed method for pressure sensing and leak detection. The results support the feasibility of the proposed method for both of these applications.

Technical Principles and Clinical Applications of Electrical Impedance Tomography in Pulmonary Monitoring.

Pulmonary monitoring is crucial for the diagnosis and management of respiratory conditions, especially after the epidemic of coronavirus disease. Electrical impedance tomography (EIT) is an alternative non-radioactive tomographic imaging tool for monitoring pulmonary conditions. This review proffers the current EIT technical principles and applications on pulmonary monitoring, which gives a comprehensive summary of EIT applied on the chest and encourages its extensive usage to clinical physicians. The technical principles involving EIT instrumentations and image reconstruction algorithms are explained in detail, and the conditional selection is recommended based on clinical application scenarios. For applications, specifically, the monitoring of ventilation/perfusion (V/Q) is one of the most developed EIT applications. The matching correlation of V/Q could indicate many pulmonary diseases, e.g., the acute respiratory distress syndrome, pneumothorax, pulmonary embolism, and pulmonary edema. Several recently emerging applications like lung transplantation are also briefly introduced as supplementary applications that have potential and are about to be developed in the future. In addition, the limitations, disadvantages, and developing trends of EIT are discussed, indicating that EIT will still be in a long-term development stage before large-scale clinical applications.

Layered Fusion Reconstruction Based on Fuzzy Features for Multi-Conductivity Electrical Impedance Tomography.

In medical imaging, detecting tissue anomalies is vital for accurate diagnosis and effective treatment. Electrical impedance tomography (EIT) is a non-invasive technique that monitors the changes in electrical conductivity within tissues in real time. However, the current challenge lies in simply and accurately reconstructing multi-conductivity distributions. This paper introduces a layered fusion framework for EIT to enhance imaging in multi-conductivity scenarios. The method begins with pre-imaging and extracts the main object from the fuzzy image to form one layer. Then, the voltage difference in the other layer, where the local anomaly is located, is estimated. Finally, the corresponding conductivity distribution is established, and multiple layers are fused to reconstruct the multi-conductivity distribution. The simulation and experimental results demonstrate that compared to traditional methods, the proposed method significantly improves multi-conductivity separation, precise anomaly localization, and robustness without adding uncertain parameters. Notably, the proposed method has demonstrated exceptional accuracy in local anomaly detection, with positional errors as low as 1% and size errors as low as 33%, which significantly outperforms the traditional method with respective minimum errors of 9% and 228%. This method ensures a balance between the simplicity and accuracy of the algorithm. At the same time, it breaks the constraints of traditional linear methods, struggling to identify multi-conductivity distributions, thereby providing new perspectives for clinical EIT.

Posterior Approximate Clustering-Based Sensitivity Matrix Decomposition for Electrical Impedance Tomography.

This paper introduces a sensitivity matrix decomposition regularization (SMDR) method for electric impedance tomography (EIT). Using k-means clustering, the EIT-reconstructed image can be divided into four clusters, derived based on image features, representing posterior information. The sensitivity matrix is then decomposed into distinct work areas based on these clusters. The elimination of smooth edge effects is achieved through differentiation of the images from the decomposed sensitivity matrix and further post-processing reliant on image features. The algorithm ensures low computational complexity and avoids introducing extra parameters. Numerical simulations and experimental data verification highlight the effectiveness of SMDR. The proposed SMDR algorithm demonstrates higher accuracy and robustness compared to the typical Tikhonov regularization and the iterative penalty term-based regularization method (with an improvement of up to 0.1156 in correlation coefficient). Moreover, SMDR achieves a harmonious balance between image fidelity and sparsity, effectively addressing practical application requirements.

Intraoperative individualization of positive-end-expiratory pressure through electrical impedance tomography or esophageal pressure assessment: a systematic review and meta-analysis of randomized controlled trials.

PURPOSE: This systematic review of randomized-controlled trials (RCTs) with meta-analyses aimed to compare the effects on intraoperative arterial oxygen tension to inspired oxygen fraction ratio (PaO2/FiO2), exerted by positive end-expiratory pressure (PEEP) individualized trough electrical impedance tomography (EIT) or esophageal pressure (Pes) assessment (intervention) vs. PEEP not tailored on EIT or Pes (control), in patients undergoing abdominal or pelvic surgery with an open or laparoscopic/robotic approach. METHODS: PUBMED®, EMBASE®, and Cochrane Controlled Clinical trials register were searched for observational studies and RCTs from inception to the end of August 2022. Inclusion criteria were: RCTs comparing PEEP titrated on EIT/Pes assessment vs. PEEP not individualized on EIT/Pes and reporting intraoperative PaO2/FiO2. Two authors independently extracted data from the enrolled investigations. Data are reported as mean difference and 95% confidence interval (CI). RESULTS: Six RCTs were included for a total of 240 patients undergoing general anesthesia for surgery, of whom 117 subjects in the intervention group and 123 subjects in the control group. The intraoperative mean PaO2/FiO2 was 69.6 (95%CI 32.-106.4 ) mmHg higher in the intervention group as compared with the control group with 81.4% between-study heterogeneity (p < 0.01). However, at meta-regression, the between-study heterogeneity diminished to 44.96% when data were moderated for body mass index (estimate 3.45, 95%CI 0.78-6.11, p = 0.011). CONCLUSIONS: In patients undergoing abdominal or pelvic surgery with an open or laparoscopic/robotic approach, PEEP personalized by EIT or Pes allowed the achievement of a better intraoperative oxygenation compared to PEEP not individualized through EIT or Pes. PROSPERO REGISTRATION NUMBER: CRD 42021218306, 30/01/2023.

Respiratory Support Effects over Time on Regional Lung Ventilation Assessed by Electrical Impedance Tomography in Premature Infants.

Background and objectives: Respiratory distress syndrome (RDS) frequently necessitates respiratory support. While non-invasive methods are typically the preferred approach, mechanical ventilation becomes necessary for patients with insufficient response. Our study aimed to compare two common respiratory support modes, volume-targeted mechanical ventilation and non-invasive ventilation continuous positive airway pressure (CPAP) and high-flow nasal cannula (HFNC), using electrical impedance tomography. Materials and Methods: Infants with very low birth weight and gestational ages of less than 32 weeks were eligible for inclusion in the study. All enrolled infants were beyond the transitional period (>72 h of age). The infants were divided into two groups: infants receiving invasive respiratory support through an endotracheal tube and infants receiving non-invasive respiratory support. We used electrical impedance tomography to assess end-expiratory lung impedance (EELZ), DeltaZ, heterogeneity, and regional ventilation distribution. Patients were evaluated at 0, 30, and 60 min after assuming the supine position to examine potential time-related effects. Results: Our study initially enrolled 97 infants, and the final analysis included a cohort of 72 infants. Ventilated infants exhibited significantly larger EELZ compared to their non-invasive counterparts (p = 0.026). DeltaZ was also greater in the invasive respiratory support group (p < 0.001). Heterogeneity was higher in the non-invasive group and did not change significantly over time. The non-invasive group demonstrated significantly greater ventilation in the dependent lung areas compared to intubated patients (p = 0.005). Regional distribution in the left lung was lower than in the right lung in both groups; however, this difference was significantly more pronounced in intubated patients (p < 0.001). Conclusions: Our study revealed that volume-targeted mechanical ventilation results in higher EELZ and DeltaZ compared to spontaneously breathing infants receiving non-invasive respiratory support. However, lung heterogeneity was lower during mechanical ventilation. Our study also reaffirmed that spontaneous breathing promotes greater involvement of the dependent lung compared to mechanical ventilation.

[Application of electrical impedance tomography imaging technology combined with generative adversarial network in pulmonary ventilation monitoring].

Electrical impedance tomography (EIT) plays a crucial role in the monitoring of pulmonary ventilation and regional pulmonary function test. However, the inherent ill-posed nature of EIT algorithms results in significant deviations in the reconstructed conductivity obtained from voltage data contaminated with noise, making it challenging to obtain accurate distribution images of conductivity change as well as clear boundary contours. In order to enhance the image quality of EIT in lung ventilation monitoring, a novel approach integrating the EIT with deep learning algorithm was proposed. Firstly, an optimized operator was introduced to enhance the Kalman filter algorithm, and Tikhonov regularization was incorporated into the state-space expression of the algorithm to obtain the initial lung image reconstructed. Following that, the imaging outcomes were fed into a generative adversarial network model in order to reconstruct accurate lung contours. The simulation experiment results indicate that the proposed method produces pulmonary images with clear boundaries, demonstrating increased robustness against noise interference. This methodology effectively achieves a satisfactory level of visualization and holds potential significance as a reference for the diagnostic purposes of imaging modalities such as computed tomography.

[Research of electrical impedance tomography based on multilayer artificial neural network optimized by Hadamard product for human-chest models].

Electrical impedance tomography (EIT) is a non-radiation, non-invasive visual diagnostic technique. In order to improve the imaging resolution and the removing artifacts capability of the reconstruction algorithms for electrical impedance imaging in human-chest models, the HMANN algorithm was proposed using the Hadamard product to optimize multilayer artificial neural networks (MANN). The reconstructed images of the HMANN algorithm were compared with those of the generalized vector sampled pattern matching (GVSPM) algorithm, truncated singular value decomposition (TSVD) algorithm, backpropagation (BP) neural network algorithm, and traditional MANN algorithm. The simulation results showed that the correlation coefficient of the reconstructed images obtained by the HMANN algorithm was increased by 17.30% in the circular cross-section models compared with the MANN algorithm. It was increased by 13.98% in the lung cross-section models. In the lung cross-section models, some of the correlation coefficients obtained by the HMANN algorithm would decrease. Nevertheless, the HMANN algorithm retained the image information of the MANN algorithm in all models, and the HMANN algorithm had fewer artifacts in the reconstructed images. The distinguishability between the objects and the background was better compared with the traditional MANN algorithm. The algorithm could improve the correlation coefficient of the reconstructed images, and effectively remove the artifacts, which provides a new direction to effectively improve the quality of the reconstructed images for EIT.

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.

Modulation of pulmonary blood flow in patients with acute respiratory failure.

BACKGROUND: Impairment of ventilation and perfusion (V/Q) matching is a common mechanism leading to hypoxemia in patients with acute respiratory failure requiring intensive care unit (ICU) admission. While ventilation has been thoroughly investigated, little progress has been made to monitor pulmonary perfusion at the bedside and treat impaired blood distribution. The study aimed to assess real-time changes in regional pulmonary perfusion in response to a therapeutic intervention. METHODS: Single-center prospective study that enrolled adult patients with ARDS caused by SARS-Cov-2 who were sedated, paralyzed, and mechanically ventilated. The distribution of pulmonary perfusion was assessed through electrical impedance tomography (EIT) after the injection of a 10-ml bolus of hypertonic saline. The therapeutic intervention consisted in the administration of inhaled nitric oxide (iNO), as rescue therapy for refractory hypoxemia. Each patient underwent two 15-min steps at 0 and 20 ppm iNO, respectively. At each step, respiratory, gas exchange, and hemodynamic parameters were recorded, and V/Q distribution was measured, with unchanged ventilatory settings. RESULTS: Ten 65 [56-75] years old patients with moderate (40%) and severe (60%) ARDS were studied 10 [4-20] days after intubation. Gas exchange improved at 20 ppm iNO (PaO2/FiO2 from 86 ± 16 to 110 ± 30 mmHg, p = 0.001; venous admixture from 51 ± 8 to 45 ± 7%, p = 0.0045; dead space from 29 ± 8 to 25 ± 6%, p = 0.008). The respiratory system's elastic properties and ventilation distribution were unaltered by iNO. Hemodynamics did not change after gas initiation (cardiac output 7.6 ± 1.9 vs. 7.7 ± 1.9 L/min, p = 0.66). The EIT pixel perfusion maps showed a variety of patterns of changes in pulmonary blood flow, whose increase positively correlated with PaO2/FiO2 increase (R2 = 0.50, p = 0.049). CONCLUSIONS: The assessment of lung perfusion is feasible at the bedside and blood distribution can be modulated with effects that are visualized in vivo. These findings might lay the foundations for testing new therapies aimed at optimizing the regional perfusion in the lungs.

Visualizing exertional dyspnea in a post-COVID patient using electrical impedance tomography.

PURPOSE AND METHOD: Many post-COVID patients suffer from dyspnea on exertion. To visualize exercise-induced dyspnea, a post-COVID patient and a healthy volunteer underwent an exercise test on a treadmill under stress relevant to everyday life monitored by electrical impedance tomography (EIT). RESULTS: The lung-healthy volunteer showed an even ventilation distribution throughout the assessment, a large ventilated area, and a butterfly-like lung shape with a convex lung rim. The post-COVID patient showed clear differences in the ventilated area compared to the control subject. During exercise, a constantly changing picture of differently ventilated areas is shown. However, especially the anterior regions were under-ventilated and larger areas were partially absent from ventilation. Overall, uncoordinated breathing and an uneven distribution of ventilation dominated the findings. CONCLUSION: EIT is suitable for visualizing disturbed ventilation of the lungs, both at rest and under stress. The potential as a diagnostic tool in dyspnea assessment should be investigated.

Dynamic relative regional lung strain estimated by computed tomography and electrical impedance tomography in ARDS patients.

BACKGROUND: In the acute distress respiratory syndrome (ARDS), specific lung regions can be exposed to excessive strain due to heterogeneous disease, gravity-dependent lung collapse and injurious mechanical ventilation. Computed tomography (CT) is the gold standard for regional strain assessment. An alternative tool could be the electrical impedance tomography (EIT). We aimed to determine whether EIT-based methods can predict the dynamic relative regional strain (DRRS) between two levels of end-expiratory pressure (PEEP) in gravity-non-dependent and dependent lung regions. METHODS: Fourteen ARDS patients underwent CT and EIT acquisitions (at end-inspiratory and end-expiratory) at two levels of PEEP: a low-PEEP based on ARDS-net strategy and a high-PEEP titrated according to EIT. Three EIT-based methods for DRRS were compared to relative CT-based strain: (1) the change of the ratio between EIT ventilation and end-expiratory lung impedance in arbitrary units ([ΔZAU low-PEEP/EELIAU low-PEEP]/[ΔZAU high-PEEP/EELIAU high-PEEP]), (2) the change of ΔZ/EELI ratio calibrated to mL ([ΔZml low-PEEP/EELIml low-PEEP]/[ΔZml high-PEEP/EELIml high-PEEP]) using CT data, and (3) the relative change of ∆ZAU (∆ZAU low-PEEP/∆ZAU high-PEEP). We performed linear regressions analysis and calculated bias and limits of agreement to assess the performance of DRRS by EIT in comparison with CT. RESULTS: The DRRS assessed by (ΔZml low-PEEP/EELIml low-PEEP)/(ΔZml high-PEEP/EELIml high-PEEP) and ∆ZAU low-PEEP/∆ZAU high-PEEP showed good relationship and agreement with the CT method (R2 of 0.9050 and 0.8679, respectively, in non-dependent region; R2 of 0.8373 and 0.6588, respectively, in dependent region; biases ranging from - 0.11 to 0.51 and limits of agreement ranging from - 0.73 to 1.16 for both methods and lung regions). Conversely, DRRS based on EELIAU ([ΔZAU low-PEEP/EELIAU low-PEEP]/[ΔZAU high-PEEP/EELIAU high-PEEP]) exhibited a weak negative relationship and poor agreement with the CT method for both non-dependent and dependent regions (R2 ~ 0.3; bias of 3.11 and 2.08, and limits of agreement of - 2.13 to 8.34 and from - 1.49 to 5.64, respectively). CONCLUSION: Changes in DRRS during a PEEP trial in ARDS patients could be monitored using EIT, based on changes in ΔZmL/EELIml and ∆ZAU. The relative change ∆ZAU offers the advantage of not requiring CT data for calibration.