Imaging the acute respiratory distress syndrome: past, present and future

Personalized ventilation adjustment in ARDS: A systematic review and meta-analysis of image, driving pressure, transpulmonary pressure, and mechanical power

BACKGROUND

Acute Respiratory Distress Syndrome (ARDS) necessitates personalized treatment strategies due to its heterogeneity, aiming to mitigate Ventilator-Induced Lung Injury (VILI). Advanced monitoring techniques, including imaging, driving pressure, transpulmonary pressure, and mechanical power, present potential avenues for tailored interventions.

OBJECTIVE

To review some of the most important techniques for achieving greater personalization of mechanical ventilation in ARDS patients as evaluated in randomized clinical trials, by analyzing their effect on three clinically relevant aspects: mortality, ventilator-free days, and gas exchange.

METHODS

Following PRISMA guidelines, we conducted a systematic review and meta-analysis of Randomized Clinical Trials (RCTs) involving adult ARDS patients undergoing personalized ventilation adjustments. Outcomes were mortality (primary end-point), ventilator-free days, and oxygenation improvement.

RESULTS

Among 493 identified studies, 13 RCTs (n = 1255) met inclusion criteria. No personalized ventilation strategy demonstrated superior outcomes compared to traditional protocols. Meta-analysis revealed no significant reduction in mortality with image-guided (RR 0.88, 95 % CI 0.70-1.11), driving pressure-guided (RR 0.61, 95 % CI 0.29-1.30), or transpulmonary pressure-guided (RR 0.85, 95 % CI 0.58-1.24) strategies. Ventilator-free days and oxygenation outcomes showed no significant differences.

CONCLUSION

Our study does not support the superiority of personalized ventilation techniques over traditional protocols in ARDS patients. Further research is needed to standardize ventilation strategies and determine their impact on mechanical ventilation outcomes.

Pleural lung sliding quantification using a speckle tracking technology: A feasibility study on 30 healthy volunteers

INTRODUCTION

Speckle tracking technology quantifies lung sliding and detects lung sliding abolition in case of pneumothorax on selected ultrasound loops through the analysis of acoustic markers.

OBJECTIVES

We aimed to test the ability of speckle tracking technology to quantify lung sliding using a pleural strain value (PS).

METHODS

We performed a prospective study in 30 healthy volunteers in whom we assessed the pleural speckle tracking using ultrasound loops. Seven breathing conditions with and without non-invasive ventilation were tested. Two observers analyzed the ultrasound loops in four lung areas (anterior and posterior, left and right) and compared the obtained PS values. The first endpoint was to determine the feasibility of the PS measurement in different breathing conditions. The secondary endpoints were to assess the intra- and inter-observer's reliability of the measurement to compare PS values between anterior and posterior lung areas and to explore their correlations with the measured tidal volume.

RESULTS

We analyzed 1624 ultrasound loops from 29 patients after one volunteer's exclusion. Feasibility of this method was rated at 90.8 [95%CI: 89.6 - 92.4]%. The intra-observer reliability measured through Intraclass Correlation Coefficients was 0.96 [95%CI: 0.91-0.98] and 0.93 [95%CI: 0.86-0.97] depending on the operator. The inter-observer reliability was 0.89 [95%CI: 0.78-0.95]. The PS values were significantly lower in the anterior lung areas compared with the posterior areas in all breathing conditions. A weak positive correlation was found in all the lung areas when a positive end expiratory pressure was applied with r = 0.26 [95%CI: 0.12;0.39]; p < 0.01.

CONCLUSION

Speckle tracking lung sliding quantification with PS was applicable in most conditions with an excellent intra- and inter-observer reliability. More studies in patients under invasive mechanical ventilation are needed to explore the correlation between PS values of pleural sliding and tidal volumes.

CLINICAL REGISTRATION

NCT05415605.

Effects of Positive End-expiratory Pressure on Pulmonary Perfusion Distribution and Intrapulmonary Shunt during One-lung Ventilation in Pigs: A Randomized Crossover Study

BACKGROUND

During one-lung ventilation (OLV), positive end-expiratory pressure (PEEP) can improve lung aeration but might overdistend lung units and increase intrapulmonary shunt. The authors hypothesized that higher PEEP shifts pulmonary perfusion from the ventilated to the nonventilated lung, resulting in a U-shaped relationship with intrapulmonary shunt during OLV.

METHODS

In nine anesthetized female pigs, a thoracotomy was performed and intravenous lipopolysaccharide infused to mimic the inflammatory response of thoracic surgery. Animals underwent OLV in supine position with PEEP of 0 cm H2O, 5 cm H2O, titrated to best respiratory system compliance, and 15 cm H2O (PEEP0, PEEP5, PEEPtitr, and PEEP15, respectively, 45 min each, Latin square sequence). Respiratory, hemodynamic, and gas exchange variables were measured. The distributions of perfusion and ventilation were determined by IV fluorescent microspheres and computed tomography, respectively.

RESULTS

Compared to two-lung ventilation, the driving pressure increased with OLV, irrespective of the PEEP level. During OLV, cardiac output was lower at PEEP15 (5.5 ± 1.5 l/min) than PEEP0 (7.6 ± 3 l/min) and PEEP5 (7.4 ± 2.9 l/min; P = 0.004), while the intrapulmonary shunt was highest at PEEP0 (PEEP0: 48.1% ± 14.4%; PEEP5: 42.4% ± 14.8%; PEEPtitr: 37.8% ± 11.0%; PEEP15: 39.0% ± 10.7%; P = 0.027). The relative perfusion of the ventilated lung did not differ among PEEP levels (PEEP0: 65.0% ± 10.6%; PEEP5: 68.7% ± 8.7%; PEEPtitr: 68.2% ± 10.5%; PEEP15: 58.4% ± 12.8%; P = 0.096), but the centers of relative perfusion and ventilation in the ventilated lung shifted from ventral to dorsal and from cranial to caudal zones with increasing PEEP.

CONCLUSIONS

In this experimental model of thoracic surgery, higher PEEP during OLV did not shift the perfusion from the ventilated to the nonventilated lung, thus not increasing intrapulmonary shunt.

EDITOR’S PERSPECTIVE

Back to the future: the novel art of digital auscultation applied in a prospective observational study of critically ill Covid-19 patients

BACKGROUND

The Covid-19 pandemic has caused immense pressure on Intensive Care Units (ICU). In patients with severe ARDS due to Covid-19, respiratory mechanics are important for determining the severity of lung damage. Lung auscultation could not be used during the pandemic despite its merit. The main objective of this study was to investigate associations between lung auscultatory sound features and lung mechanical properties, length of stay (LOS) and survival, in adults with severe Covid-19 ARDS.

METHODS

Consecutive patients admitted to a large ICU between 2020 and 2021 (n = 173) were included. Digital stethoscopes obtained auscultatory sounds and stored them in an on-line database for replay and further processing using advanced AI techniques. Correlation and regression analysis explored relationships between digital auscultation findings and lung mechanics or the ICU outcome. The resulting annotated lung sounds database is also publicly available as supplementary material.

RESULTS

The presence of squawks was associated with the ICU LOS, outcome and 90-day mortality. Other features (age, SOFA score & oxygenation index upon admission, minimum crackle entropy) had significant impact on outcome. Additional features affecting the 90-d survival were age and mean crackle entropy. Multivariate logistic regression showed that survival was affected by age, baseline SOFA, baseline oxygenation index and minimum crackle entropy.

CONCLUSIONS

Respiratory mechanics were associated with various adventitious sounds, whereas the lung sound analytics and the presence of certain adventitious sounds correlated with the ICU outcome and the 90-d survival. Spectral features of crackles sounds can serve as prognostic factors for survival, highlighting the importance of digital auscultation.

Advanced Respiratory Monitoring during Extracorporeal Membrane Oxygenation

Advanced respiratory monitoring encompasses a diverse range of mini- or noninvasive tools used to evaluate various aspects of respiratory function in patients experiencing acute respiratory failure, including those requiring extracorporeal membrane oxygenation (ECMO) support. Among these techniques, key modalities include esophageal pressure measurement (including derived pressures), lung and respiratory muscle ultrasounds, electrical impedance tomography, the monitoring of diaphragm electrical activity, and assessment of flow index. These tools play a critical role in assessing essential parameters such as lung recruitment and overdistention, lung aeration and morphology, ventilation/perfusion distribution, inspiratory effort, respiratory drive, respiratory muscle contraction, and patient-ventilator synchrony. In contrast to conventional methods, advanced respiratory monitoring offers a deeper understanding of pathological changes in lung aeration caused by underlying diseases. Moreover, it allows for meticulous tracking of responses to therapeutic interventions, aiding in the development of personalized respiratory support strategies aimed at preserving lung function and respiratory muscle integrity. The integration of advanced respiratory monitoring represents a significant advancement in the clinical management of acute respiratory failure. It serves as a cornerstone in scenarios where treatment strategies rely on tailored approaches, empowering clinicians to make informed decisions about intervention selection and adjustment. By enabling real-time assessment and modification of respiratory support, advanced monitoring not only optimizes care for patients with acute respiratory distress syndrome but also contributes to improved outcomes and enhanced patient safety.

[Artificial intelligence in intensive care medicine]

The integration of artificial intelligence (AI) into intensive care medicine has made considerable progress in recent studies, particularly in the areas of predictive analytics, early detection of complications, and the development of decision support systems. The main challenges remain availability and quality of data, reduction of bias and the need for explainable results from algorithms and models. Methods to explain these systems are essential to increase trust, understanding, and ethical considerations among healthcare professionals and patients. Proper training of healthcare professionals in AI principles, terminology, ethical considerations, and practical application is crucial for the successful use of AI. Careful assessment of the impact of AI on patient autonomy and data protection is essential for its responsible use in intensive care medicine. A balance between ethical and practical considerations must be maintained to ensure patient-centered care while complying with data protection regulations. Synergistic collaboration between clinicians, AI engineers, and regulators is critical to realizing the full potential of AI in intensive care medicine and maximizing its positive impact on patient care. Future research and development efforts should focus on improving AI models for real-time predictions, increasing the accuracy and utility of AI-based closed-loop systems, and overcoming ethical, technical, and regulatory challenges, especially in generative AI systems.

ERS International Congress 2023: highlights from the Respiratory Intensive Care Assembly

Early career members of Assembly 2 (Respiratory Intensive Care) attended the 2023 European Respiratory Society International Congress in Milan, Italy. The conference covered acute and chronic respiratory failure. Sessions of interest to our assembly members and to those interested in respiratory critical care are summarised in this article and include the latest updates in respiratory intensive care, in particular acute respiratory distress syndrome and mechanical ventilation.

ARDS Mortality Prediction Model Using Evolving Clinical Data and Chest Radiograph Analysis

INTRODUCTION

Within primary ARDS, SARS-CoV-2-associated ARDS (C-ARDS) emerged in late 2019, reaching its peak during the subsequent two years. Recent efforts in ARDS research have concentrated on phenotyping this heterogeneous syndrome to enhance comprehension of its pathophysiology.

METHODS AND RESULTS

A retrospective study was conducted on C-ARDS patients from April 2020 to February 2021, encompassing 110 participants with a mean age of 63.2 ± 11.92 (26-83 years). Of these, 61.2% (68) were male, and 25% (17) experienced severe ARDS, resulting in a mortality rate of 47.3% (52). Ventilation settings, arterial blood gases, and chest X-ray (CXR) were evaluated on the first day of invasive mechanical ventilation and between days two and three. CXR images were scrutinized using a convolutional neural network (CNN). A binary logistic regression model for predicting C-ARDS mortality was developed based on the most influential variables: age, PaO2/FiO2 ratio (P/F) on days one and three, CNN-extracted CXR features, and age. Initial performance assessment on test data (23 patients out of the 110) revealed an area under the receiver operating characteristic (ROC) curve of 0.862 with a 95% confidence interval (0.654-0.969).

CONCLUSION

Integrating data available in all intensive care units enables the prediction of C-ARDS mortality by utilizing evolving P/F ratios and CXR. This approach can assist in tailoring treatment plans and initiating early discussions to escalate care and extracorporeal life support. Machine learning algorithms for imaging classification can uncover otherwise inaccessible patterns, potentially evolving into another form of ARDS phenotyping. The combined features of these algorithms and clinical variables demonstrate superior performance compared to either element alone.

Effectiveness and safety of awake prone positioning in COVID-19-related acute hypoxaemic respiratory failure: an overview of systematic reviews

OBJECTIVE

To evaluate and summarize systematic reviews of the effects and safety of awake prone positioning for COVID-19-related acute hypoxaemic respiratory failure.

METHODS

A comprehensive search was conducted on PubMed, Embase, the Cochrane Library, Web of Science, CNKI, CSPD, CCD and CBM from their inception to March 28, 2023. Systematic reviews (SRs) of awake prone positioning (APP) for COVID-19-related acute hypoxaemic respiratory failure in adults were included. Two reviewers screened the eligible articles, and four reviewers in pairs extracted data and assessed the methodological quality/certainty of the evidence of all included SRs by AMSTAR 2 and GRADE tools. The overlap of primary studies was measured by calculating corrected covered areas. Data from the included reviews were synthesized with a narrative description.

RESULTS

A total of 11 SRs were included. The methodological quality of SRs included 1 "High", 4 "Moderate", 2 "Low" and 4 "Critically low" by AMSTAR 2. With the GRADE system, no high-quality evidence was found, and only 14 outcomes provided moderate-quality evidence. Data synthesis of the included SR outcomes showed that APP reduced the risk of requiring intubation (11 SRs) and improving oxygenation (3 SRs), whereas reduced significant mortality was not found in RCT-based SRs. No significant difference was observed in the incidence of adverse events between groups (8 SRs). The corrected covered area index was 27%, which shows very high overlap among studies.

CONCLUSION

The available SRs suggest that APP has benefits in terms of reducing intubation rates and improving oxygenation for COVID-19-related acute hypoxemic respiratory failure, without an increased risk of adverse events. The conclusion should be treated with caution because of the generally low quality of methodology and evidence.

TRIAL REGISTRATION

The protocol for this review was registered with PROSPERO: CRD42023400986. Registered 15 April 2023.

Blocking P2Y2 purinergic receptor prevents the development of lipopolysaccharide-induced acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is associated with high morbidity and mortality resulting from a direct or indirect injury of the lung. It is characterized by a rapid alveolar injury, lung inflammation with neutrophil accumulation, elevated permeability of the microvascular-barrier leading to an aggregation of protein-rich fluid in the lungs, followed by impaired oxygenation in the arteries and eventual respiratory failure. Very recently, we have shown an involvement of the Gq-coupled P2Y2 purinergic receptor (P2RY2) in allergic airway inflammation (AAI). In the current study, we aimed to elucidate the contribution of the P2RY2 in lipopolysaccharide (LPS)-induced ARDS mouse model. We found that the expression of P2ry2 in neutrophils, macrophages and lung tissue from animals with LPS-induced ARDS was strongly upregulated at mRNA level. In addition, ATP-neutralization by apyrase in vivo markedly attenuated inflammation and blocking of P2RY2 by non-selective antagonist suramin partially decreased inflammation. This was indicated by a reduction in the number of neutrophils, concentration of proinflammatory cytokines in the BALF, microvascular plasma leakage and reduced features of inflammation in histological analysis of the lung. P2RY2 blocking has also attenuated polymorphonuclear neutrophil (PMN) migration into the interstitium of the lungs in ARDS mouse model. Consistently, treatment of P2ry2 deficient mice with LPS lead to an amelioration of the inflammatory response showed by reduced number of neutrophils and concentrations of proinflammatory cytokines. In attempts to identify the cell type specific role of P2RY2, a series of experiments with conditional P2ry2 knockout animals were performed. We observed that P2ry2 expression in neutrophils, but not in the airway epithelial cells or CD4+ cells, was associated with the inflammatory features caused by ARDS. Altogether, our findings imply for the first time that increased endogenous ATP concentration via activation of P2RY2 is related to the pathogenesis of LPS-induced lung inflammation and may represent a potential therapeutic target for the treatment of ARDS and predictably assess new treatments in ARDS.

The role of neutrophil extracellular traps in sepsis and sepsis-related acute lung injury

Neutrophils release neutrophil extracellular traps (NETs) to trap pathogenic microorganisms. NETs are involved in the inflammatory response and bacterial killing and clearance. However, their excessive activation can lead to an inflammatory storm in the body, which may damage tissues and cause organ dysfunction. Organ dysfunction is the main pathophysiological cause of sepsis and also a cause of the high mortality rate in sepsis. Acute lung injury caused by sepsis accounts for the highest proportion of organ damage in sepsis. NET formation can lead to the development of sepsis because by promoting the release of interleukin-1 beta, interleukin-8, and tumor necrosis factor-alpha, thereby accelerating acute lung injury. In this review, we describe the critical role of NETs in sepsis-associated acute lung injury and review the current knowledge and novel therapeutic approaches.

The perinatal period should be considered in neonatal acute respiratory distress syndrome: comparison of the Montreux definition vs. the second pediatric acute lung injury consensus conference definition

Background

The recently developed Montreux definition for neonatal acute respiratory distress syndrome (ARDS) partially differs from the Second Pediatric Acute Lung Injury Consensus Conference (PALICC-2) definition. Here, we compare the Montreux and PALICC-2 definitions regarding morbidity, mortality, and prognosis of neonatal cases of ARDS in order to evaluate which definition is more appropriate for newborns.

Methods

Neonates admitted to our neonatal intensive care unit between 1 January 2018 and 30 September 2019 who met the Montreux or PALICC-2 definition of neonatal ARDS were retrospectively analyzed (n = 472). One comparison was made between application of the Montreux and PALICC-2 definitions to neonates outside the perinatal period (> 7 d after birth). A second comparison was made between a diagnosis of neonatal ARDS within (≤ 7 d of birth) and outside (> 7 d after birth) the perinatal period using the Montreux definition.

Results

No significant differences in morbidity, mortality, severity, therapies, or prognosis were observed between neonates in the extra perinatal group according to the Montreux and PALICC-2 definitions. However, epidemiology, clinical course, and prognosis of neonatal ARDS within the perinatal period did differ from those outside the perinatal period according to the Montreux definition.

Conclusion

Neonates with ARDS within the perinatal period have unique triggers, epidemiology, clinical course, and prognosis, yet a similar pathobiology pattern, to neonates at other ages. Therefore, it may be essential to consider the perinatal period when defining neonatal ARDS.

Explainable artificial intelligence-based prediction of poor neurological outcome from head computed tomography in the immediate post-resuscitation phase

Predicting poor neurological outcomes after resuscitation is important for planning treatment strategies. We constructed an explainable artificial intelligence-based prognostic model using head computed tomography (CT) scans taken immediately within 3 h of resuscitation from cardiac arrest and compared its predictive accuracy with that of previous methods using gray-to-white matter ratio (GWR). We included 321 consecutive patients admitted to our institution after resuscitation for out-of-hospital cardiopulmonary arrest with circulation resumption over 6 years. A machine learning model using head CT images with transfer learning was used to predict the neurological outcomes at 1 month. These predictions were compared with the predictions of GWR for multiple regions of interest in head CT using receiver operating characteristic (ROC)-area under curve (AUC) and precision recall (PR)-AUC. The regions of focus were visualized using a heatmap. Both methods had similar ROC-AUCs, but the machine learning model had a higher PR-AUC (0.73 vs. 0.58). The machine learning-focused area of interest for classification was the boundary between gray and white matter, which overlapped with the area of focus when diagnosing hypoxic- ischemic brain injury. The machine learning model for predicting poor outcomes had superior accuracy to conventional methods and could help optimize treatment.

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.

Differences in clinical characteristics and quantitative lung CT features between vaccinated and not vaccinated hospitalized COVID-19 patients in Italy

BACKGROUND

To evaluate the differences in the clinical characteristics and severity of lung impairment, assessed by quantitative lung CT scan, between vaccinated and non-vaccinated hospitalized patients with COVID-19; and to identify the variables with best prognostic prediction according to SARS-CoV-2 vaccination status. We recorded clinical, laboratory and quantitative lung CT scan data in 684 consecutive patients [580 (84.8%) vaccinated, and 104 (15.2%) non-vaccinated], admitted between January and December 2021.

RESULTS

Vaccinated patients were significantly older 78 [69-84] vs 67 [53-79] years and with more comorbidities. Vaccinated and non-vaccinated patients had similar PaO2/FiO2 (300 [252-342] vs 307 [247-357] mmHg; respiratory rate 22 [8-26] vs 19 [18-26] bpm); total lung weight (918 [780-1069] vs 954 [802-1149] g), lung gas volume (2579 [1801-3628] vs 2370 [1675-3289] mL) and non-aerated tissue fraction (10 [7.3-16.0] vs 8.5 [6.0-14.1] %). The overall crude hospital mortality was similar between the vaccinated and non-vaccinated group (23.1% vs 21.2%). However, Cox regression analysis, adjusted for age, ethnicity, age unadjusted Charlson Comorbidity Index and calendar month of admission, showed a 40% reduction in hospital mortality in the vaccinated patients (HRadj = 0.60, 95%CI 0.38-0.95).

CONCLUSIONS

Hospitalized vaccinated patients with COVID-19, although older and with more comorbidities, presented a similar impairment in gas exchange and lung CT scan compared to non-vaccinated patients, but were at a lower risk of mortality.

Advanced Point-of-care Bedside Monitoring for Acute Respiratory Failure

Advanced respiratory monitoring involves several mini- or noninvasive tools, applicable at bedside, focused on assessing lung aeration and morphology, lung recruitment and overdistention, ventilation-perfusion distribution, inspiratory effort, respiratory drive, respiratory muscle contraction, and patient-ventilator asynchrony, in dealing with acute respiratory failure. Compared to a conventional approach, advanced respiratory monitoring has the potential to provide more insights into the pathologic modifications of lung aeration induced by the underlying disease, follow the response to therapies, and support clinicians in setting up a respiratory support strategy aimed at protecting the lung and respiratory muscles. Thus, in the clinical management of the acute respiratory failure, advanced respiratory monitoring could play a key role when a therapeutic strategy, relying on individualization of the treatments, is adopted.

Precision of CT-derived alveolar recruitment assessed by human observers and a machine learning algorithm in moderate and severe ARDS

BACKGROUND

Assessing measurement error in alveolar recruitment on computed tomography (CT) is of paramount importance to select a reliable threshold identifying patients with high potential for alveolar recruitment and to rationalize positive end-expiratory pressure (PEEP) setting in acute respiratory distress syndrome (ARDS). The aim of this study was to assess both intra- and inter-observer smallest real difference (SRD) exceeding measurement error of recruitment using both human and machine learning-made lung segmentation (i.e., delineation) on CT. This single-center observational study was performed on adult ARDS patients. CT were acquired at end-expiration and end-inspiration at the PEEP level selected by clinicians, and at end-expiration at PEEP 5 and 15 cmH₂O. Two human observers and a machine learning algorithm performed lung segmentation. Recruitment was computed as the weight change of the non-aerated compartment on CT between PEEP 5 and 15 cmH₂O.

RESULTS

Thirteen patients were included, of whom 11 (85%) presented a severe ARDS. Intra- and inter-observer measurements of recruitment were virtually unbiased, with 95% confidence intervals (CI_95%) encompassing zero. The intra-observer SRD of recruitment amounted to 3.5 [CI_95% 2.4-5.2]% of lung weight. The human-human inter-observer SRD of recruitment was slightly higher amounting to 5.7 [CI_95% 4.0-8.0]% of lung weight, as was the human-machine SRD (5.9 [CI_95% 4.3-7.8]% of lung weight). Regarding other CT measurements, both intra-observer and inter-observer SRD were close to zero for the CT-measurements focusing on aerated lung (end-expiratory lung volume, hyperinflation), and higher for the CT-measurements relying on accurate segmentation of the non-aerated lung (lung weight, tidal recruitment…). The average symmetric surface distance between lung segmentation masks was significatively lower in intra-observer comparisons (0.8 mm [interquartile range (IQR) 0.6-0.9]) as compared to human-human (1.0 mm [IQR 0.8-1.3] and human-machine inter-observer comparisons (1.1 mm [IQR 0.9-1.3]).

CONCLUSIONS

The SRD exceeding intra-observer experimental error in the measurement of alveolar recruitment may be conservatively set to 5% (i.e., the upper value of the CI_95%). Human-machine and human-human inter-observer measurement errors with CT are of similar magnitude, suggesting that machine learning segmentation algorithms are credible alternative to humans for quantifying alveolar recruitment on CT.

Dead space ventilation-related indices: bedside tools to evaluate the ventilation and perfusion relationship in patients with acute respiratory distress syndrome

Cumulative evidence has demonstrated that the ventilatory ratio closely correlates with mortality in acute respiratory distress syndrome (ARDS), and a primary feature in coronavirus disease 2019 (COVID-19)-ARDS is increased dead space that has been reported recently. Thus, new attention has been given to this group of dead space ventilation-related indices, such as physiological dead space fraction, ventilatory ratio, and end-tidal-to-arterial PCO₂ ratio, which, albeit distinctive, are all global indices with which to assess the relationship between ventilation and perfusion. These parameters have already been applied to positive end expiratory pressure titration, prediction of responses to the prone position and the field of extracorporeal life support for patients suffering from ARDS. Dead space ventilation-related indices remain hampered by several deflects; notwithstanding, for this catastrophic syndrome, they may facilitate better stratifications and identifications of subphenotypes, thereby providing therapy tailored to individual needs.

Use of radiolabeled hyaluronic acid for preclinical assessment of inflammatory injury and acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is accompanied by a dramatic increase in lung hyaluronic acid (HA), leading to a dose-dependent reduction of pulmonary oxygenation. This pattern is associated with severe infections, such as COVID-19, and other important lung injury etiologies. HA actively participates in molecular pathways involved in the cytokine storm of COVID-19-induced ARDS. The objective of this study was to evaluate an imaging approach of radiolabeled HA for assessment of dysregulated HA deposition in mouse models with skin inflammation and lipopolysaccharide (LPS)-induced ARDS using a novel portable intensified Quantum Imaging Detector (iQID) gamma camera system.

METHODS

HA of 10 kDa molecular weight (HA10) was radiolabeled with 125I and 99mTc respectively to produce [125I]I-HA10 and [99mTc]Tc-HA10, followed by comparative studies on stability, in vivo biodistribution, and uptake at inflammatory skin sites in mice with 12-O-tetradecanoylphorbol-13-acetate (TPA)-inflamed ears. [99mTc]Tc-HA10 was used for iQID in vivo dynamic imaging of mice with ARDS induced by intratracheal instillation of LPS.

RESULTS

[99mTc]Tc-HA10 and [125I]I-HA10 had similar biodistribution and localization at inflammatory sites. [99mTc]Tc-HA10 was shown to be feasible in measuring skin injury and monitoring skin wound healing. [99mTc]Tc-HA10 dynamic pulmonary images yielded good visualization of radioactive uptake in the lungs. There was significantly increased lung uptake and slower lung washout in mice with LPS-induced ARDS than in control mice. Postmortem biodistribution measurement of [99mTc]TcHA10 (%ID/g) was 11.0 ± 3.9 vs. 1.3 ± 0.3 in the ARDS mice (n = 6) and controls (n = 6) (P < 0.001), consistent with upregulated HA expression as determined by enzyme-linked immunosorbent assay (ELISA) and immunohistochemistry (IHC) staining.

CONCLUSIONS

[99mTc]Tc-HA10 is promising as a biomarker for evaluating HA dysregulation that contributes to pulmonary injury in ARDS. Rapid iQID imaging of [99mTc]Tc-HA10 clearance from injured lungs may provide a functional template for timely assessment and quantitative monitoring of pulmonary pathophysiology and intervention in ARDS.