Impact of extended lung protection during mechanical ventilation on lung recovery in patients with COVID-19 ARDS: a phase II randomized controlled trial.

BACKGROUND: Protective ventilation seems crucial during early Acute Respiratory Distress Syndrome (ARDS), but the optimal duration of lung protection remains undefined. High driving pressures (ΔP) and excessive patient ventilatory drive may hinder lung recovery, resulting in self-inflicted lung injury. The hidden nature of the ΔP generated by patient effort complicates the situation further. Our study aimed to assess the feasibility of an extended lung protection strategy that includes a stepwise protocol to control the patient ventilatory drive, assessing its impact on lung recovery. METHODS: We conducted a single-center randomized study on patients with moderate/severe COVID-19-ARDS with low respiratory system compliance (CRS < 0.6 (mL/Kg)/cmH2O). The intervention group received a ventilation strategy guided by Electrical Impedance Tomography aimed at minimizing ΔP and patient ventilatory drive. The control group received the ARDSNet low-PEEP strategy. The primary outcome was the modified lung injury score (mLIS), a composite measure that integrated daily measurements of CRS, along with oxygen requirements, oxygenation, and X-rays up to day 28. The mLIS score was also hierarchically adjusted for survival and extubation rates. RESULTS: The study ended prematurely after three consecutive months without patient enrollment, attributed to the pandemic subsiding. The intention-to-treat analysis included 76 patients, with 37 randomized to the intervention group. The average mLIS score up to 28 days was not different between groups (P = 0.95, primary outcome). However, the intervention group showed a faster improvement in the mLIS (1.4 vs. 7.2 days to reach 63% of maximum improvement; P < 0.001), driven by oxygenation and sustained improvement of X-ray (P = 0.001). The intervention group demonstrated a sustained increase in CRS up to day 28 (P = 0.009) and also experienced a shorter time from randomization to room-air breathing (P = 0.02). Survival at 28 days and time until liberation from the ventilator were not different between groups. CONCLUSIONS: The implementation of an individualized PEEP strategy alongside extended lung protection appears viable. Promising secondary outcomes suggested a faster lung recovery, endorsing further examination of this strategy in a larger trial. Clinical trial registration This trial was registered with ClinicalTrials.gov (number NCT04497454) on August 04, 2020.

Regional pulmonary perfusion, blood volume, and their relationship change in experimental early ARDS.

Regional pulmonary perfusion (Q) has been investigated using blood volume (Fb) imaging as an easier-to-measure surrogate. However, it is unclear if changing pulmonary conditions could affect their relationship. We hypothesized that vascular changes in early acute respiratory distress syndrome (ARDS) affect Q and Fb differently. Five sheep were anesthetized and received lung protective mechanical ventilation for 20 h while endotoxin was continuously infused. Using dynamic 18F-FDG and 13NN Positron Emission Tomography (PET), regional Fb and Q were analysed in 30 regions of interest (ROIs) and normalized by tissue content (Fbn and Qn, respectively). After 20 h, the lung injury showed characteristics of early ARDS, including gas exchange and lung mechanics. PET images of Fbn and Qn showed substantial differences between baseline and lung injury. Lung injury caused a significant change in the Fbn-Qn relationship compared to baseline (p < 0.001). The best models at baseline and lung injury were Fbn = 0.32 + 0.690Qn and Fbn = 1.684Qn-0.538Qn2, respectively. Endotoxine-associated early ARDS changed the relationship between Fb and Q, shifting from linear to curvilinear. Effects of endotoxin exposure on the vasoactive blood flow regulation were most likely the key factor for this change limiting the quantitative accuracy of Fb imaging as a surrogate for regional Q.

Machine Learning for the Design and the Simulation of Radiofrequency Magnetic Resonance Coils: Literature Review, Challenges, and Perspectives.

Radiofrequency (RF) coils for magnetic resonance imaging (MRI) applications serve to generate RF fields to excite the nuclei in the sample (transmit coil) and to pick up the RF signals emitted by the nuclei (receive coil). For the purpose of optimizing the image quality, the performance of RF coils has to be maximized. In particular, the transmit coil has to provide a homogeneous RF magnetic field, while the receive coil has to provide the highest signal-to-noise ratio (SNR). Thus, particular attention must be paid to the coil simulation and design phases, which can be performed with different computer simulation techniques. Being largely used in many sectors of engineering and sciences, machine learning (ML) is a promising method among the different emerging strategies for coil simulation and design. Starting from the applications of ML algorithms in MRI and a short description of the RF coil's performance parameters, this narrative review describes the applications of such techniques for the simulation and design of RF coils for MRI, by including deep learning (DL) and ML-based algorithms for solving electromagnetic problems.

Influence of Fractional Inspired Oxygen Tension on Lung Perfusion Distribution, Regional Ventilation, and Lung Volume during Mechanical Ventilation of Supine Healthy Swine.

BACKGROUND: Lower fractional inspired oxygen tension (Fio2) during general anesthesia can reduce lung atelectasis. The objectives are to evaluate the effect of two Fio2 (0.4 and 1) during low positive end-expiratory pressure (PEEP) ventilation over lung perfusion distribution, volume, and regional ventilation. These variables were evaluated at two PEEP levels and unilateral lung atelectasis. METHODS: In this exploratory study, 10 healthy female piglets (32.3 ± 3.4 kg) underwent mechanical ventilation in two atelectasis models: (1) bilateral gravitational atelectasis (n = 6), induced by changes in PEEP and Fio2 in three combinations: high PEEP with low Fio2 (Fio2 = 0.4), zero PEEP (PEEP0) with low Fio2 (Fio2 = 0.4), and PEEP0 with high Fio2 (Fio2 = 1); and (2) unilateral atelectasis (n = 6), induced by left bronchial occlusion, with the left lung aerated (Fio2 = 0.21) and low aerated (Fio2 = 1; n = 5 for this step). Measurements were conducted after 10 min in each step, encompassing assessment of respiratory mechanics, oxygenation, and hemodynamics; lung ventilation and perfusion by electrical impedance tomography; and lung aeration and perfusion by computed tomography. RESULTS: During bilateral gravitational atelectasis, PEEP reduction increased atelectasis in dorsal regions, decreased respiratory compliance, and distributed lung ventilation to ventral regions with a parallel shift of perfusion to the same areas. With PEEP0, there were no differences between low and high Fio2 in respiratory compliance (23.9 ± 6.5 ml/cm H2O vs. 21.9 ± 5.0; P = 0.441), regional ventilation, and regional perfusion, despite higher lung collapse (18.6 ± 7.6% vs. 32.7 ± 14.5%; P = 0.045) with high Fio2. During unilateral lung atelectasis, the deaerated lung had a lower shunt (19.3 ± 3.6% vs. 25.3 ± 5.5%; P = 0.045) and lower computed tomography perfusion to the left lung (8.8 ± 1.8% vs. 23.8 ± 7.1%; P = 0.007). CONCLUSIONS: PEEP0 with low Fio2, compared with high Fio2, did not produce significant changes in respiratory system compliance, regional lung ventilation, and perfusion despite significantly lower lung collapse. After left bronchial occlusion, the shrinkage of the parenchyma with Fio2 = 1 enhanced hypoxic pulmonary vasoconstriction, reducing intrapulmonary shunt and perfusion of the nonventilated areas.

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.

The Use of the Oxygenation Stretch Index to Predict Outcomes in Mechanically Ventilated Patients With COVID-19 ARDS.

BACKGROUND: In ARDS caused by COVID-19 pneumonia, appropriate adjustment of physiologic parameters based on lung stretch or oxygenation may optimize the ventilatory strategy. This study aims to describe the prognostic performance on 60-d mortality of single and composite respiratory variables in subjects with COVID-19 ARDS who are on mechanical ventilation with a lung-protective strategy, including the oxygenation stretch index combining oxygenation and driving pressure (ΔP). METHODS: This single-center observational cohort study enrolled 166 subjects on mechanical ventilation and diagnosed with COVID-19 ARDS. We evaluated their clinical and physiologic characteristics. The primary study outcome was 60-d mortality. Prognostic factors were evaluated through receiver operating characteristic analysis, Cox proportional hazards regression model, and Kaplan-Meier survival curves. RESULTS: Mortality at day 60 was 18.1%, and hospital mortality was 22.9%. Oxygenation, ΔP, and composite variables were tested: oxygenation stretch index ([Formula: see text]/[Formula: see text] divided by ΔP) and ΔP × 4 + breathing frequency (f) (ΔP × 4 + f). At both day 1 and day 2 after inclusion, the oxygenation stretch index had the best area under the receiver operating characteristic curve (oxygenation stretch index on day 1 0.76 (95% CI 0.67-0.84) and on day 2 0.83 (95% CI 0.76-0.91) to predict 60-d mortality, although without significant difference from other indexes. In multivariable Cox regression, ΔP, [Formula: see text]/[Formula: see text], ΔP × 4 + f, and oxygenation stretch index were all associated with 60-d mortality. When dichotomizing the variables, ΔP ≥ 14, [Formula: see text]/[Formula: see text] ≤ 152 mm Hg, ΔP × 4 + f ≥ 80, and oxygenation stretch index < 7.7 showed lower 60-d survival probability. At day 2, after optimization of ventilatory settings, the subjects who persisted with the worse cutoff values for the oxygenation stretch index showed a lower probability of survival at 60 d compared with day 1; this was not the case for other parameters. CONCLUSIONS: The oxygenation stretch index, which combines [Formula: see text]/[Formula: see text] and ΔP, is associated with mortality and may be useful to predict clinical outcomes in COVID-19 ARDS.

Worsening of lung perfusion to tissue density distributions during early acute lung injury.

Lung perfusion magnitude and distribution are essential for oxygenation and, potentially, lung inflammation and protection during acute respiratory distress syndrome (ARDS). Yet, perfusion patterns and their relationship to inflammation are unknown pre-ARDS. We aimed to assess perfusion/density ratios and spatial perfusion-density distributions and associate these to lung inflammation, during early lung injury in large animals at different physiological conditions caused by different systemic inflammation and positive end-expiratory pressure (PEEP) levels. Sheep were protectively ventilated (16-24 h) and imaged for lung density, pulmonary capillary perfusion (13Nitrogen-saline), and inflammation (18F-fluorodeoxyglucose) using positron emission and computed tomography. We studied four conditions: permissive atelectasis (PEEP = 0 cmH2O); and ARDSNet low-stretch PEEP-setting strategy with supine moderate or mild endotoxemia, and prone mild endotoxemia. Perfusion/density heterogeneity increased pre-ARDS in all groups. Perfusion redistribution to density depended on ventilation strategy and endotoxemia level, producing more atelectasis in mild than moderate endotoxemia (P = 0.010) with the oxygenation-based PEEP-setting strategy. The spatial distribution of 18F-fluorodeoxyglucose uptake was related to local Q/D (P < 0.001 for Q/D group interaction). Moderate endotoxemia yielded markedly low/zero perfusion in normal-low density lung, with 13Nitrogen-saline perfusion indicating nondependent capillary obliteration. Prone animals' perfusion was remarkably homogeneously distributed with density. Lung perfusion redistributes heterogeneously to density during pre-ARDS protective ventilation in animals. This is associated with increased inflammation, nondependent capillary obliteration, and lung derecruitment susceptibility depending on endotoxemia level and ventilation strategy.NEW & NOTEWORTHY Perfusion redistribution does not follow lung density redistribution in the first 16-24 h of systemic endotoxemia and protective tidal volume mechanical ventilation. The same oxygenation-based positive end-expiratory pressure (PEEP)-setting strategy can lead at different endotoxemia levels to different perfusion redistributions, PEEP values, and lung aerations, worsening lung biomechanical conditions. During early acute lung injury, regional perfusion-to-tissue density ratio is associated with increased neutrophilic inflammation, and susceptibility to nondependent capillary occlusion and lung derecruitment, potentially marking and/or driving lung injury.

Learning-Based Approaches to Current Identification from Magnetic Sensors.

Direct measurement of electric currents can be prevented by poor accessibility or prohibitive technical conditions. In such cases, magnetic sensors can be used to measure the field in regions adjacent to the sources, and the measured data then can be used to estimate source currents. Unfortunately, this is classified as an Electromagnetic Inverse Problem (EIP), and data from sensors must be cautiously treated to obtain meaningful current measurements. The usual approach requires using suited regularization schemes. On the other hand, behavioral approaches are recently spreading for this class of problems. The reconstructed model is not obliged to follow the physics equations, and this implies approximations which must be accurately controlled, especially if aiming to reconstruct an inverse model from examples. In this paper, a systematic study of the role of different learning parameters (or rules) on the (re-)construction of an EIP model is proposed, in comparison with more assessed regularization techniques. Attention is particularly devoted to linear EIPs, and in this class, a benchmark problem is used to illustrate in practice the results. It is shown that, by applying classical regularization methods and analogous correcting actions in behavioral models, similar results can be obtained. Both classical methodologies and neural approaches are described and compared in the paper.

YOLO-S: A Lightweight and Accurate YOLO-like Network for Small Target Selection in Aerial Imagery.

Small target detection is still a challenging task, especially when looking at fast and accurate solutions for mobile or edge applications. In this work, we present YOLO-S, a simple, fast, and efficient network. It exploits a small feature extractor, as well as skip connection, via both bypass and concatenation, and a reshape-passthrough layer to promote feature reuse across network and combine low-level positional information with more meaningful high-level information. Performances are evaluated on AIRES, a novel dataset acquired in Europe, and VEDAI, benchmarking the proposed YOLO-S architecture with four baselines. We also demonstrate that a transitional learning task over a combined dataset based on DOTAv2 and VEDAI can enhance the overall accuracy with respect to more general features transferred from COCO data. YOLO-S is from 25% to 50% faster than YOLOv3 and only 15-25% slower than Tiny-YOLOv3, outperforming also YOLOv3 by a 15% in terms of accuracy (mAP) on the VEDAI dataset. Simulations on SARD dataset also prove its suitability for search and rescue operations. In addition, YOLO-S has roughly 90% of Tiny-YOLOv3's parameters and one half FLOPs of YOLOv3, making possible the deployment for low-power industrial applications.

Mixed-integer quadratic programming approach for noninvasive estimation of respiratory effort profile during pressure support ventilation.

Information about respiratory mechanics such as resistance, elastance, and muscular pressure is important to mitigate ventilator-induced lung injury. Particularly during pressure support ventilation, the available options to quantify breathing effort and calculate respiratory system mechanics are often invasive or complex. We herein propose a robust and flexible estimation of respiratory effort better than current methods. We developed a method for non-invasively estimating breathing effort using only flow and pressure signals. Mixed-integer quadratic programming (MIQP) was employed, and the binary variables were the switching moments of the respiratory effort waveform. Mathematical constraints, based on ventilation physiology, were set for some variables to restrict feasible solutions. Simulated and patient data were used to verify our method, and the results were compared to an established estimation methodology. Our algorithm successfully estimated the respiratory effort, resistance, and elastance of the respiratory system, resulting in more robust performance and faster solver times than a previously proposed algorithm that used quadratic programming (QP) techniques. In a numerical simulation benchmark, the worst-case errors for resistance and elastance were 25% and 23% for QP versus <0.1% and <0.1% for MIQP, whose solver times were 4.7 s and 0.5 s, respectively. This approach can estimate several breathing effort profiles and identify the respiratory system's mechanical properties in invasively ventilated critically ill patients.

Phrenic Nerve Block and Respiratory Effort in Pigs and Critically Ill Patients with Acute Lung Injury.

BACKGROUND: Strong spontaneous inspiratory efforts can be difficult to control and prohibit protective mechanical ventilation. Instead of using deep sedation and neuromuscular blockade, the authors hypothesized that perineural administration of lidocaine around the phrenic nerve would reduce tidal volume (VT) and peak transpulmonary pressure in spontaneously breathing patients with acute respiratory distress syndrome. METHODS: An established animal model of acute respiratory distress syndrome with six female pigs was used in a proof-of-concept study. The authors then evaluated this technique in nine mechanically ventilated patients under pressure support exhibiting driving pressure greater than 15 cm H2O or VT greater than 10 ml/kg of predicted body weight. Esophageal and transpulmonary pressures, electrical activity of the diaphragm, and electrical impedance tomography were measured in pigs and patients. Ultrasound imaging and a nerve stimulator were used to identify the phrenic nerve, and perineural lidocaine was administered sequentially around the left and right phrenic nerves. RESULTS: Results are presented as median [interquartile range, 25th to 75th percentiles]. In pigs, VT decreased from 7.4 ml/kg [7.2 to 8.4] to 5.9 ml/kg [5.5 to 6.6] (P < 0.001), as did peak transpulmonary pressure (25.8 cm H2O [20.2 to 27.2] to 17.7 cm H2O [13.8 to 18.8]; P < 0.001) and driving pressure (28.7 cm H2O [20.4 to 30.8] to 19.4 cm H2O [15.2 to 22.9]; P < 0.001). Ventilation in the most dependent part decreased from 29.3% [26.4 to 29.5] to 20.1% [15.3 to 20.8] (P < 0.001). In patients, VT decreased (8.2 ml/ kg [7.9 to 11.1] to 6.0 ml/ kg [5.7 to 6.7]; P < 0.001), as did driving pressure (24.7 cm H2O [20.4 to 34.5] to 18.4 cm H2O [16.8 to 20.7]; P < 0.001). Esophageal pressure, peak transpulmonary pressure, and electrical activity of the diaphragm also decreased. Dependent ventilation only slightly decreased from 11.5% [8.5 to 12.6] to 7.9% [5.3 to 8.6] (P = 0.005). Respiratory rate did not vary. Variables recovered 1 to 12.7 h [6.7 to 13.7] after phrenic nerve block. CONCLUSIONS: Phrenic nerve block is feasible, lasts around 12 h, and reduces VT and driving pressure without changing respiratory rate in patients under assisted ventilation.

Sequential lateral positioning as a new lung recruitment maneuver: an exploratory study in early mechanically ventilated Covid-19 ARDS patients.

BACKGROUND: A sequential change in body position from supine-to-both lateral positions under constant ventilatory settings could be used as a postural recruitment maneuver in case of acute respiratory distress syndrome (ARDS), provided that sufficient positive end-expiratory pressure (PEEP) prevents derecruitment. This study aims to evaluate the feasibility and physiological effects of a sequential postural recruitment maneuver in early mechanically ventilated COVID-19 ARDS patients. METHODS: A cohort of 15 patients receiving lung-protective mechanical ventilation in volume-controlled with PEEP based on recruitability were prospectively enrolled and evaluated in five sequentially applied positions for 30 min each: Supine-baseline; Lateral-1st side; 2nd Supine; Lateral-2nd side; Supine-final. PEEP level was selected using the recruitment-to-inflation ratio (R/I ratio) based on which patients received PEEP 12 cmH2O for R/I ratio ≤ 0.5 or PEEP 15 cmH2O for R/I ratio > 0.5. At the end of each period, we measured respiratory mechanics, arterial blood gases, lung ultrasound aeration, end-expiratory lung impedance (EELI), and regional distribution of ventilation and perfusion using electric impedance tomography (EIT). RESULTS: Comparing supine baseline and final, respiratory compliance (29 ± 9 vs 32 ± 8 mL/cmH2O; p < 0.01) and PaO2/FIO2 ratio (138 ± 36 vs 164 ± 46 mmHg; p < 0.01) increased, while driving pressure (13 ± 2 vs 11 ± 2 cmH2O; p < 0.01) and lung ultrasound consolidation score decreased [5 (4-5) vs 2 (1-4); p < 0.01]. EELI decreased ventrally (218 ± 205 mL; p < 0.01) and increased dorsally (192 ± 475 mL; p = 0.02), while regional compliance increased in both ventral (11.5 ± 0.7 vs 12.9 ± 0.8 mL/cmH2O; p < 0.01) and dorsal regions (17.1 ± 1.8 vs 18.8 ± 1.8 mL/cmH2O; p < 0.01). Dorsal distribution of perfusion increased (64.8 ± 7.3% vs 66.3 ± 7.2%; p = 0.01). CONCLUSIONS: Without increasing airway pressure, a sequential postural recruitment maneuver improves global and regional respiratory mechanics and gas exchange along with a redistribution of EELI from ventral to dorsal lung areas and less consolidation. Trial registration ClinicalTrials.gov, NCT04475068. Registered 17 July 2020, https://clinicaltrials.gov/ct2/show/NCT04475068.

Hourly Water Level Forecasting in an Hydroelectric Basin Using Spatial Interpolation and Artificial Intelligence.

In this work, a new hydroelectric basin modelling approach is described and applied to the Pontecosi basin, Italy. Several types of data sources were used to learn the model: a number of weather stations, satellite observations, the reanalysis dataset, and basin data. With the goal of predicting the water level of the basin, the model was composed by three cascade modules. Firstly, different spatial interpolation methods, such as Kriging, Radial Basis Function, and Natural Neighbours, were compared and applied to interpolate the weather stations data nearby the basin area to infer the main environmental variables (air temperature, air humidity, precipitation, and wind speed) in the basin area. Then, using these variables as inputs, a neural network was trained to predict the mean soil moisture concentration over the area, also to improve the low availability due to satellite orbits. Finally, a non-linear auto regressive exogenous input (NARX) model was trained to simulate the basin level with different prediction horizons, using the data from the previous modules and past basin data (water level, discharge flow rate, and turbine flow rate). Accurate predictions of the basin water level were achieved within 1 to 6 h ahead, with mean absolute errors (MAE) between 2 cm and 10 cm, respectively.

Fault Prediction and Early-Detection in Large PV Power Plants Based on Self-Organizing Maps.

In this paper, a novel and flexible solution for fault prediction based on data collected from Supervisory Control and Data Acquisition (SCADA) system is presented. Generic fault/status prediction is offered by means of a data driven approach based on a self-organizing map (SOM) and the definition of an original Key Performance Indicator (KPI). The model has been assessed on a park of three photovoltaic (PV) plants with installed capacity up to 10 MW, and on more than sixty inverter modules of three different technology brands. The results indicate that the proposed method is effective in predicting incipient generic faults in average up to 7 days in advance with true positives rate up to 95%. The model is easily deployable for on-line monitoring of anomalies on new PV plants and technologies, requiring only the availability of historical SCADA data, fault taxonomy and inverter electrical datasheet.

Physiological mechanism and spatial distribution of increased alveolar dead-space in early ARDS: An experimental study.

BACKGROUND: We aimed to investigate the physiological mechanism and spatial distribution of increased physiological dead-space, an early marker of ARDS mortality, in the initial stages of ARDS. We hypothesized that: increased dead-space results from the spatial redistribution of pulmonary perfusion, not ventilation; such redistribution is not related to thromboembolism (ie, areas with perfusion = 0 and infinite ventilation-perfusion ratio, V ˙ / Q ˙ ), but rather to moderate shifts of perfusion increasing V ˙ / Q ˙ in non-dependent regions. METHODS: Five healthy anesthetized sheep received protective ventilation for 20 hours, while endotoxin was continuously infused. Maps of voxel-level lung ventilation, perfusion, V ˙ / Q ˙ , CO2 partial pressures, and alveolar dead-space fraction were estimated from positron emission tomography at baseline and 20 hours. RESULTS: Alveolar dead-space fraction increased during the 20 hours (+0.05, P = .031), mainly in non-dependent regions (+0.03, P = .031). This was mediated by perfusion redistribution away from non-dependent regions (-5.9%, P = .031), while the spatial distribution of ventilation did not change, resulting in increased V ˙ / Q ˙ in non-dependent regions. The increased alveolar dead-space derived mostly from areas with intermediate V ˙ / Q ˙ (0.5≤ V ˙ / Q ˙ ≤10), not areas of nearly "complete" dead-space ( V ˙ / Q ˙ >10). CONCLUSIONS: In this early ARDS model, increases in alveolar dead-space occur within 20 hours due to the regional redistribution of perfusion and not ventilation. This moderate redistribution suggests changes in the interplay between active and passive perfusion redistribution mechanisms (including hypoxic vasoconstriction and gravitational effects), not the appearance of thromboembolism. Hence, the association between mortality and increased dead-space possibly arises from the former, reflecting gas-exchange inefficiency due to perfusion heterogeneity. Such heterogeneity results from the injury and exhaustion of compensatory mechanisms for perfusion redistribution.

Intraoperative pulmonary hyperdistention estimated by transthoracic lung ultrasound: A pilot study.

INTRODUCTION: Transthoracic lung ultrasound can assess atelectasis reversal and is considered as unable to detect associated hyperdistention. In this study, we describe an ultrasound pattern highly suggestive of pulmonary hyperdistention. METHODS: Eighteen patients with normal lungs undergoing lower abdominal surgery were studied. Electrical impedance tomography was calibrated, followed by anaesthetic induction, intubation and mechanical ventilation. To reverse posterior atelectasis, a recruitment manoeuvre was performed. Positive-end expiratory pressure (PEEP) titration was then obtained during a descending trial - 20, 18, 16, 14, 12, 10, 8, 6 and 4cmH2O. Ultrasound and electrical impedance tomography data were collected at each PEEP level and interpreted by two independent observers. Spearman correlation test and receiving operating characteristic curve were used to compare lung ultrasound and electrical impedance tomography data. RESULTS: The number of horizontal A lines increased linearly with PEEP: from 3 (0, 5) at PEEP 4cmH2O to 10 (8, 13) at PEEP 20cmH2O. The increase number of A lines was associated with a parallel and significant decrease in intercostal space thickness (p=0.001). The lung ultrasound threshold for detecting pulmonary hyperdistention was defined as the number of A lines counted at the PEEP preceding the PEEP providing the best respiratory compliance. Six A lines was the median threshold for detecting pulmonary hyperdistention. The area under the receiving operating characteristic curve was 0.947. CONCLUSIONS: Intraoperative transthoracic lung ultrasound can detect lung hyperdistention during a PEEP descending trial. Six or more A lines detected in normally aerated regions can be considered as indicating lung hyperdistention. TRIAL REGISTRATION: NCT02314845 Registered on ClinicalTrials.gov.

Inflammatory Activity in Atelectatic and Normally Aerated Regions During Early Acute Lung Injury.

RATIONALE AND OBJECTIVES: Pulmonary atelectasis presumably promotes and facilitates lung injury. However, data are limited on its direct and remote relation to inflammation. We aimed to assess regional 2-deoxy-2-[18F]-fluoro-D-glucose (18F-FDG) kinetics representative of inflammation in atelectatic and normally aerated regions in models of early lung injury. MATERIALS AND METHODS: We studied supine sheep in four groups: Permissive Atelectasis (n = 6)-16 hours protective tidal volume (VT) and zero positive end-expiratory pressure; Mild (n = 5) and Moderate Endotoxemia (n = 6)- 20-24 hours protective ventilation and intravenous lipopolysaccharide (Mild = 2.5 and Moderate = 10.0 ng/kg/min), and Surfactant Depletion (n = 6)-saline lung lavage and 4 hours high VT. Measurements performed immediately after anesthesia induction served as controls (n = 8). Atelectasis was defined as regions of gas fraction <0.1 in transmission or computed tomography scans. 18F-FDG kinetics measured with positron emission tomography were analyzed with a three-compartment model. RESULTS: 18F-FDG net uptake rate in atelectatic tissue was larger during Moderate Endotoxemia (0.0092 ± 0.0019/min) than controls (0.0051 ± 0.0014/min, p = 0.01). 18F-FDG phosphorylation rate in atelectatic tissue was larger in both endotoxemia groups (0.0287 ± 0.0075/min) than controls (0.0198 ± 0.0039/min, p = 0.05) while the 18F-FDG volume of distribution was not significantly different among groups. Additionally, normally aerated regions showed larger 18F-FDG uptake during Permissive Atelectasis (0.0031 ± 0.0005/min, p < 0.01), Mild (0.0028 ± 0.0006/min, p = 0.04), and Moderate Endotoxemia (0.0039 ± 0.0005/min, p < 0.01) than controls (0.0020 ± 0.0003/min). CONCLUSION: Atelectatic regions present increased metabolic activation during moderate endotoxemia mostly due to increased 18F-FDG phosphorylation, indicative of increased cellular metabolic activation. Increased 18F-FDG uptake in normally aerated regions during permissive atelectasis suggests an injurious remote effect of atelectasis even with protective tidal volumes.