Low volume ventilation of pre-injured lungs degrades lung function via stress concentration and progressive alveolar collapse.

Mechanical ventilation can cause ventilation-induced lung injury (VILI). The concept of stress concentrations suggests that surfactant dysfunction-induced microatelectases might impose injurious stresses on adjacent, open alveoli and function as germinal centers for injury propagation. The aim of the present study was to quantify the histopathological pattern of VILI progression and to test the hypothesis that injury progresses at the interface between microatelectases and ventilated lung parenchyma during low positive end-expiratory pressure (PEEP) ventilation. Bleomycin was used to induce lung injury with microatelectases in rats. Lungs were then mechanically ventilated for up to 6 hours at PEEP=1cmH2O and compared to bleomycin treated group ventilated protectively with PEEP=5cmH2O to minimize microatelectases. Lung mechanics were measured during ventilation. Afterwards lungs were fixed at end-inspiration or end-expiration for design-based stereology. Prior to VILI, bleomycin challenge reduced the number of open alveoli (N(alvair,par)) by 29%. No differences between end-inspiration and end-expiration were observed. Collapsed alveoli clustered in areas with a radius up to 56 µm. After PEEP=5cmH2O ventilation for 6 hours, N(alvair,par) remained stable while PEEP=1cmH2O ventilation led to an additional loss of aerated alveoli by 26%, mainly due to collapse, with a small fraction partly edema filled. Alveolar loss strongly correlated to worsening of tissue elastance, quasi-static compliance and inspiratory capacity. The radius of areas of collapsed alveoli increased to 94 µm, suggesting growth of the microatelectases. These data provide evidence that alveoli become unstable in neighborhood of microatelectases which most likely occurs due to by stress concentration-induced local vascular leak and surfactant dysfunction.

The fix is not yet in: recommendation for fixation of lungs within physiologic/pathophysiologic volume range in preclinical pulmonary structure-function studies.

Quantitative characterization of lung structures by morphometric or stereologic analysis of histologic sections is a powerful means of elucidating pulmonary structure-function relations. The overwhelming majority of studies, however, fix lungs for histology at pressures outside the physiologic/pathophysiologic respiratory volume range. Thus valuable information is being lost. In this perspective article, we argue that investigators performing pulmonary histologic studies should consider whether the aims of their studies would benefit from fixation at functional transpulmonary pressures, particular those of end-inspiration and end-expiration. We survey the pressures at which lungs are typically fixed in preclinical structure-function studies; provide examples of conditions that would benefit from histologic evaluation at functional lung volumes; summarize available fixation methods; discuss alternative imaging modalities; and discuss challenges to implementing the suggested approach and means of addressing those challenges. We aim to persuade investigators that modifying or complementing the traditional histologic approach by fixing lungs at minimal and maximal functional volumes could enable new understanding of pulmonary structure-function relations.

A scale-free model of acute and ventilator-induced lung injury: a network theory approach inspired by seismology.

Introduction: Acute respiratory distress syndrome (ARDS) presents a significant clinical challenge, with ventilator-induced lung injury (VILI) being a critical complication arising from life-saving mechanical ventilation. Understanding the spatial and temporal dynamics of VILI can inform therapeutic strategies to mitigate lung damage and improve outcomes. Methods: Histological sections from initially healthy mice and pulmonary lavage-injured mice subjected to a second hit of VILI were segmented with Ilastik to define regions of lung injury. A scale-free network approach was applied to assess the correlation between injury regions, with regions of injury represented as 'nodes' in the network and 'edges' quantifying the degree of correlation between nodes. A simulated time series analysis was conducted to emulate the temporal sequence of injury events. Results: Automated segmentation identified different lung regions in good agreement with manual scoring, achieving a sensitivity of 78% and a specificity of 85% across 'injury' pixels. Overall accuracy across 'injury', 'air', and 'other' pixels was 81%. The size of injured regions followed a power-law distribution, suggesting a 'rich-get-richer' phenomenon in the distribution of lung injury. Network analysis revealed a scale-free distribution of injury correlations, highlighting hubs of injury that could serve as focal points for therapeutic intervention. Simulated time series analysis further supported the concept of secondary injury events following an initial insult, with patterns resembling those observed in seismological studies of aftershocks. Conclusion: The size distribution of injured regions underscores the spatially heterogeneous nature of acute and ventilator-induced lung injury. The application of network theory demonstrates the emergence of injury 'hubs' that are consistent with a 'rich-get-richer' dynamic. Simulated time series analysis demonstrates that the progression of injury events in the lung could follow spatiotemporal patterns similar to the progression of aftershocks in seismology, providing new insights into the mechanisms of injury distribution and propagation. Both phenomena suggest a potential for interventions targeting these injury 'hubs' to reduce the impact of VILI in ARDS management.

Exploring alveolar recruitability using positive end-expiratory pressure in mice overexpressing TGF-ß1: a structure-function analysis.

Pre-injured lungs are prone to injury progression in response to mechanical ventilation. Heterogeneous ventilation due to (micro)atelectases imparts injurious strains on open alveoli (known as volutrauma). Hence, recruitment of (micro)atelectases by positive end-expiratory pressure (PEEP) is necessary to interrupt this vicious circle of injury but needs to be balanced against acinar overdistension. In this study, the lung-protective potential of alveolar recruitment was investigated and balanced against overdistension in pre-injured lungs. Mice, treated with empty vector (AdCl) or adenoviral active TGF-ß1 (AdTGF-ß1) were subjected to lung mechanical measurements during descending PEEP ventilation from 12 to 0 cmH2O. At each PEEP level, recruitability tests consisting of two recruitment maneuvers followed by repetitive forced oscillation perturbations to determine tissue elastance (H) and damping (G) were performed. Finally, lungs were fixed by vascular perfusion at end-expiratory airway opening pressures (Pao) of 20, 10, 5 and 2 cmH2O after a recruitment maneuver, and processed for design-based stereology to quantify derecruitment and distension. H and G were significantly elevated in AdTGF-ß1 compared to AdCl across PEEP levels. H was minimized at PEEP = 5-8 cmH2O and increased at lower and higher PEEP in both groups. These findings correlated with increasing septal wall folding (= derecruitment) and reduced density of alveolar number and surface area (= distension), respectively. In AdTGF-ß1 exposed mice, 27% of alveoli remained derecruited at Pao = 20 cmH2O. A further decrease in Pao down to 2 cmH2O showed derecruitment of an additional 1.1 million alveoli (48%), which was linked with an increase in alveolar size heterogeneity at Pao = 2-5 cmH2O. In AdCl, decreased Pao resulted in septal folding with virtually no alveolar collapse. In essence, in healthy mice alveoli do not derecruit at low PEEP ventilation. The potential of alveolar recruitability in AdTGF-ß1 exposed mice is high. H is optimized at PEEP 5-8 cmH2O. Lower PEEP folds and larger PEEP stretches septa which results in higher H and is more pronounced in AdTGF-ß1 than in AdCl. The increased alveolar size heterogeneity at Pao = 5 cmH2O argues for the use of PEEP = 8 cmH2O for lung protective mechanical ventilation in this animal model.

Quantifiable identification of flow-limited ventilator dyssynchrony with the deformed lung ventilator model.

BACKGROUND: Ventilator dyssynchrony (VD) can worsen lung injury and is challenging to detect and quantify due to the complex variability in the dyssynchronous breaths. While machine learning (ML) approaches are useful for automating VD detection from the ventilator waveform data, scalable severity quantification and its association with pathogenesis and ventilator mechanics remain challenging. OBJECTIVE: We develop a systematic framework to quantify pathophysiological features observed in ventilator waveform signals such that they can be used to create feature-based severity stratification of VD breaths. METHODS: A mathematical model was developed to represent the pressure and volume waveforms of individual breaths in a feature-based parametric form. Model estimates of respiratory effort strength were used to assess the severity of flow-limited (FL)-VD breaths compared to normal breaths. A total of 93,007 breath waveforms from 13 patients were analyzed. RESULTS: A novel model-defined continuous severity marker was developed and used to estimate breath phenotypes of FL-VD breaths. The phenotypes had a predictive accuracy of over 97% with respect to the previously developed ML-VD identification algorithm. To understand the incidence of FL-VD breaths and their association with the patient state, these phenotypes were further successfully correlated with ventilator-measured parameters and electronic health records. CONCLUSION: This work provides a computational pipeline to identify and quantify the severity of FL-VD breaths and paves the way for a large-scale study of VD causes and effects. This approach has direct application to clinical practice and in meaningful knowledge extraction from the ventilator waveform data.

Antenatal Endotoxin Induces Dysanapsis in Experimental Bronchopulmonary Dysplasia.

Bronchopulmonary dysplasia (BPD), the chronic lung disease of prematurity, is characterized by impaired lung development with sustained functional abnormalities due to alterations of airways and the distal lung. Although clinical studies have shown striking associations between antenatal stress and BPD, little is known about the underlying pathogenetic mechanisms. Whether dysanapsis, the concept of discordant growth of the airways and parenchyma, contributes to late respiratory disease as a result of antenatal stress is unknown. We hypothesized that antenatal endotoxin (ETX) impairs juvenile lung function as a result of altered central airway and distal lung structure, suggesting the presence of dysanapsis in this preclinical BPD model. Fetal rats were exposed to intraamniotic ETX (10 µg) or saline solution (control) 2 days before term. We performed extensive structural and functional evaluation of the proximal airways and distal lung in 2-week-old rats. Distal lung structure was quantified by stereology. Conducting airway diameters were measured using micro-computed tomography. Lung function was assessed during invasive ventilation to quantify baseline mechanics, response to methacholine challenge, and spirometry. ETX-exposed pups exhibited distal lung simplification, decreased alveolar surface area, and decreased parenchyma-airway attachments. ETX-exposed pups exhibited decreased tracheal and second- and third-generation airway diameters. ETX increased respiratory system resistance and decreased lung compliance at baseline. Only Newtonian resistance, specific to large airways, exhibited increased methacholine reactivity in ETX-exposed pups compared with controls. ETX-exposed pups had a decreased ratio of FEV in 0.1 second to FVC and a normal FEV in 0.1 second, paralleling the clinical definition of dysanapsis. Antenatal ETX causes abnormalities of the central airways and distal lung growth, suggesting that dysanapsis contributes to abnormal lung function in juvenile rats.

Lung and Heart Biology of the Dp16 Mouse Model of down Syndrome: Implications for Studying Cardiopulmonary Disease.

(1) Background: We sought to investigate the baseline lung and heart biology of the Dp16 mouse model of Down syndrome (DS) as a prelude to the investigation of recurrent respiratory tract infection. (2) Methods: In controls vs. Dp16 mice, we compared peripheral blood cell and plasma analytes. We examined baseline gene expression in lungs and hearts for key parameters related to susceptibility of lung infection. We investigated lung and heart protein expression and performed lung morphometry. Finally, and for the first time each in a model of DS, we performed pulmonary function testing and a hemodynamic assessment of cardiac function. (3) Results: Dp16 mice circulate unique blood plasma cytokines and chemokines. Dp16 mouse lungs over-express the mRNA of triplicated genes, but not necessarily corresponding proteins. We found a sex-specific decrease in the protein expression of interferon α receptors, yet an increased signal transducer and activator of transcription (STAT)-3 and phospho-STAT3. Platelet-activating factor receptor protein was not elevated in Dp16 mice. The lungs of Dp16 mice showed increased stiffness and mean linear intercept and contained bronchus-associated lymphoid tissue. The heart ventricles of Dp16 mice displayed hypotonicity. Finally, Dp16 mice required more ketamine to achieve an anesthetized state. (4) Conclusions: The Dp16 mouse model of DS displays key aspects of lung heart biology akin to people with DS. As such, it has the potential to be an extremely valuable model of recurrent severe respiratory tract infection in DS.

Volumetric versus distortional deformation in rat lungs.

There are several lung diseases that lead to alterations in regional lung mechanics, including acute respiratory distress syndrome. Such alterations can lead to localized underventilation of the affected areas resulting in the overdistension of the surrounding healthy regions. They can also lead to the surrounding alveoli expanding unevenly or distorting. Therefore, the quantification of the regional deformation in the lungs offers insights into identifying the regions at risk of lung injury. Although few recent studies have developed image processing techniques to quantify the regional volumetric deformation in the lung from dynamic imaging, the presence and extent of distortional deformation in the lung, and its correlation with volumetric deformation, remain poorly understood. In this study, we present a method that uses the four-dimensional displacement field obtained from image registration to quantify both regional volumetric and distortional deformation in the lung. We used dynamic computed tomography scans in a healthy rat over the course of one respiratory cycle in free breathing. Non-rigid image registration was performed to quantify voxel displacement during respiration. The deformation gradient was calculated using the displacement field and its determinant was used to quantify regional volumetric deformation. Regional distortion was calculated as the ratio of maximum to minimum principal stretches using the isochoric part of the Cauchy green tensor. We found an inverse correlation between volumetric strains and distortion indicating that poorly expanding alveoli tend to experience larger distortion. The combination of regional volumetric strains and distortion may serve as high-fidelity biomarkers to identify the regions at risk of most adverse lung injuries.

Differential effects of two-hit models of acute and ventilator-induced lung injury on lung structure, function, and inflammation.

Acute respiratory distress syndrome (ARDS) and acute lung injury have a diverse spectrum of causative factors including sepsis, aspiration of gastric contents, and near drowning. Clinical management of severe lung injury typically includes mechanical ventilation to maintain gas exchange which can lead to ventilator-induced lung injury (VILI). The cause of respiratory failure is acknowledged to affect the degree of lung inflammation, changes in lung structure, and the mechanical function of the injured lung. However, these differential effects of injury and the role of etiology in the structure-function relationship are not fully understood. To address this knowledge gap we caused lung injury with intratracheal hydrochloric acid (HCL) or endotoxin (LPS) 2 days prior to ventilation or with an injurious lavage (LAV) immediately prior to ventilation. These injury groups were then ventilated with high inspiratory pressures and positive end expiratory pressure (PEEP) = 0 cmH2O to cause VILI and model the clinical course of ARDS followed by supportive ventilation. The effects of injury were quantified using invasive lung function measurements recorded during PEEP ladders where the end-expiratory pressure was increased from 0 to 15 cm H2O and decreased back to 0 cmH2O in steps of 3 cmH2O. Design-based stereology was used to quantify the parenchymal structure of lungs air-inflated to 2, 5, and 10 cmH2O. Pro-inflammatory gene expression was measured with real-time quantitative polymerase chain reaction and alveolocapillary leak was estimated by measuring bronchoalveolar lavage protein content. The LAV group had small, stiff lungs that were recruitable at higher pressures, but did not demonstrate substantial inflammation. The LPS group showed septal swelling and high pro-inflammatory gene expression that was exacerbated by VILI. Despite widespread alveolar collapse, elastance in LPS was only modestly elevated above healthy mice (CTL) and there was no evidence of recruitability. The HCL group showed increased elastance and some recruitability, although to a lesser degree than LAV. Pro-inflammatory gene expression was elevated, but less than LPS, and the airspace dimensions were reduced. Taken together, those data highlight how different modes of injury, in combination with a 2nd hit of VILI, yield markedly different effects.

Modeling Ventilator-Induced Lung Injury and Neutrophil Infiltration to Infer Injury Interdependence.

Acute respiratory distress syndrome (ARDS) and ventilator-induced lung injury (VILI) are heterogeneous conditions. The spatiotemporal evolution of these heterogeneities is complex, and it is difficult to elucidate the mechanisms driving its progression. Through previous quantitative analyses, we explored the distributions of cellular injury and neutrophil infiltration in experimental VILI and discovered that VILI progression is characterized by both the formation of new injury in quasi-random locations and the expansion of existing injury clusters. Distributions of neutrophil infiltration do not correlate with cell injury progression and suggest a systemic response. To further examine the dynamics of VILI, we have developed a novel computational model that simulates damage (cellular injury progression and neutrophil infiltration) using a stochastic approach. Optimization of the model parameters to fit experimental data reveals that the range and strength of interdependence between existing and new damaged regions both increase as mechanical ventilation patterns become more injurious. The interdependence of cellular injury can be attributed to mechanical tethering forces, while the interdependence of neutrophils is likely due to longer-range cell signaling pathways.

CNP-miR146a improves outcomes in a two-hit acute- and ventilator-induced lung injury model.

Acute respiratory distress syndrome (ARDS) has high mortality (~40 %) and requires the lifesaving intervention of mechanical ventilation. A variety of systemic inflammatory insults can progress to ARDS, and the inflamed and injured lung is susceptible to ventilator-induced lung injury (VILI). Strategies to mitigate the inflammatory response while restoring pulmonary function are limited, thus we sought to determine if treatment with CNP-miR146a, a conjugate of novel free radical scavenging cerium oxide nanoparticles (CNP) to the anti-inflammatory microRNA (miR)-146a, would protect murine lungs from acute lung injury (ALI) induced with intratracheal endotoxin and subsequent VILI. Lung injury severity and treatment efficacy were evaluated via lung mechanical function, relative gene expression of inflammatory biomarkers, and lung morphometry (stereology). CNP-miR146a reduced the severity of ALI and slowed the progression of VILI, evidenced by improvements in inflammatory biomarkers, atelectasis, gas volumes in the parenchymal airspaces, and the stiffness of the pulmonary system.

Acinar micromechanics in health and lung injury: what we have learned from quantitative morphology.

Within the pulmonary acini ventilation and blood perfusion are brought together on a huge surface area separated by a very thin blood-gas barrier of tissue components to allow efficient gas exchange. During ventilation pulmonary acini are cyclically subjected to deformations which become manifest in changes of the dimensions of both alveolar and ductal airspaces as well as the interalveolar septa, composed of a dense capillary network and the delicate tissue layer forming the blood-gas barrier. These ventilation-related changes are referred to as micromechanics. In lung diseases, abnormalities in acinar micromechanics can be linked with injurious stresses and strains acting on the blood-gas barrier. The mechanisms by which interalveolar septa and the blood-gas barrier adapt to an increase in alveolar volume have been suggested to include unfolding, stretching, or changes in shape other than stretching and unfolding. Folding results in the formation of pleats in which alveolar epithelium is not exposed to air and parts of the blood-gas barrier are folded on each other. The opening of a collapsed alveolus (recruitment) can be considered as an extreme variant of septal wall unfolding. Alveolar recruitment can be detected with imaging techniques which achieve light microscopic resolution. Unfolding of pleats and stretching of the blood-gas barrier, however, require electron microscopic resolution to identify the basement membrane. While stretching results in an increase of the area of the basement membrane, unfolding of pleats and shape changes do not. Real time visualization of these processes, however, is currently not possible. In this review we provide an overview of septal wall micromechanics with focus on unfolding/folding as well as stretching. At the same time we provide a state-of-the-art design-based stereology methodology to quantify microarchitecture of alveoli and interalveolar septa based on different imaging techniques and design-based stereology.

Hypothesis-driven modeling of the human lung-ventilator system: A characterization tool for Acute Respiratory Distress Syndrome research.

Mechanical ventilation is an essential tool in the management of Acute Respiratory Distress Syndrome (ARDS), but it exposes patients to the risk of ventilator-induced lung injury (VILI). The human lung-ventilator system (LVS) involves the interaction of complex anatomy with a mechanical apparatus, which limits the ability of process-based models to provide individualized clinical support. This work proposes a hypothesis-driven strategy for LVS modeling in which robust personalization is achieved using a pre-defined parameter basis in a non-physiological model. Model inversion, here via windowed data assimilation, forges observed waveforms into interpretable parameter values that characterize the data rather than quantifying physiological processes. Accurate, model-based inference on human-ventilator data indicates model flexibility and utility over a variety of breath types, including those from dyssynchronous LVSs. Estimated parameters generate static characterizations of the data that are 50%-70% more accurate than breath-wise single-compartment model estimates. They also retain sufficient information to distinguish between the types of breath they represent. However, the fidelity and interpretability of model characterizations are tied to parameter definitions and model resolution. These additional factors must be considered in conjunction with the objectives of specific applications, such as identifying and tracking the development of human VILI.

Identifying low-dimensional trajectories of mechanically-ventilated patient systems: Empirical phenotypes of joint patient+care processes to enhance temporal analysis in ARDS research.

Mechanically ventilated patients generate waveform data that corresponds to patient interaction with unnatural forcing. This breath information includes both patient and apparatus sources, imbuing data with broad heterogeneity resulting from ventilator settings, patient efforts, patient-ventilator dyssynchronies, injuries, and other clinical therapies. Lung-protective ventilator settings outlined in respiratory care protocols lack personalization, and the connections between clinical outcomes and injuries resulting from mechanical ventilation remain poorly understood. Intra- and inter-patient heterogeneity and the volume of data comprising lung-ventilator system (LVS) observations limit broader and longer-time analysis of such systems. This work presents a computational pipeline for resolving LVS systems by tracking the evolution of data-conditioned model parameters and ventilator information. For individuals, the method presents LVS trajectory in a manageable way through low-dimensional representation of phenotypic breath waveforms. More general phenotypes across patients are also developed by aggregating patient-personalized estimates with additional normalization. The effectiveness of this process is demonstrated through application to multi-day observational series of 35 patients, which reveals the complexity of changes in the LVS over time. Considerable variations in breath behavior independent of the ventilator are revealed, suggesting the need to incorporate care factors such as patient sedation and posture in future analysis. The pipeline also identifies structural similarity in pressure-volume (pV) loop characterizations at the cohort level. The design invites active learning to incorporate clinical practitioner expertise into various methodological stages and algorithm choices.

Engineering Hybrid-Hydrogels Comprised of Healthy or Diseased Decellularized Extracellular Matrix to Study Pulmonary Fibrosis.

Idiopathic pulmonary fibrosis is a chronic disease characterized by progressive lung scarring that inhibits gas exchange. Evidence suggests fibroblast-matrix interactions are a prominent driver of disease. However, available preclinical models limit our ability to study these interactions. We present a technique for synthesizing phototunable poly(ethylene glycol) (PEG)-based hybrid-hydrogels comprising healthy or fibrotic decellularized extracellular matrix (dECM) to decouple mechanical properties from composition and elucidate their roles in fibroblast activation. Here, we engineered and characterized phototunable hybrid-hydrogels using molecular techniques such as ninhydrin and Ellman's assays to assess dECM functionalization, and parallel-plate rheology to measure hydrogel mechanical properties. These biomaterials were employed to investigate the activation of fibroblasts from dual-transgenic Col1a1-GFP and αSMA-RFP reporter mice in response to changes in composition and mechanical properties. We show that reacting functionalized dECM from healthy or bleomycin-injured mouse lungs with PEG alpha-methacrylate (αMA) in an off-stoichiometry Michael-addition reaction created soft hydrogels mimicking a healthy lung elastic modulus (4.99 ± 0.98 kPa). Photoinitiated stiffening increased the material modulus to fibrotic values (11.48 ± 1.80 kPa). Percent activation of primary murine fibroblasts expressing Col1a1 and αSMA increased by approximately 40% following dynamic stiffening of both healthy and bleomycin hybrid-hydrogels. There were no significant differences between fibroblast activation on stiffened healthy versus stiffened bleomycin-injured hybrid-hydrogels. Phototunable hybrid-hydrogels provide an important platform for probing cell-matrix interactions and developing a deeper understanding of fibrotic activation in pulmonary fibrosis. Our results suggest that mechanical properties are a more significant contributor to fibroblast activation than biochemical composition within the scope of the hybrid-hydrogel platform evaluated in this study. Supplementary Information: The online version contains supplementary material available at 10.1007/s12195-022-00726-y.

Cigarette smoke-induced airspace disease in mice develops independently of HIF-1α signaling in leukocytes.

The pathogenesis of chronic obstructive pulmonary disease (COPD), a prevalent disease primarily caused by cigarette smoke exposure, is incompletely elucidated. Studies in humans and mice have suggested that hypoxia-inducible factor-1α (HIF-1α) may play a role. Reduced lung levels of HIF-1α are associated with decreased vascular density, whereas increased leukocyte HIF-1α may be responsible for increased inflammation. To elucidate the specific role of leukocyte HIF-1α in COPD, we exposed transgenic mice with conditional deletion or overexpression of HIF-1α in leukocytes to cigarette smoke for 7 mo. Outcomes included pulmonary physiology, aerated lung volumes via microcomputed tomography, lung morphometry and histology, and cardiopulmonary hemodynamics. On aggregate, cigarette smoke increased the aerated lung volume, quasi-static lung compliance, inspiratory capacity of all strains while reducing the total alveolar septal volume. Independent of smoke exposure, mice with leukocyte-specific HIF-1α overexpression had increased quasi-static compliance, inspiratory capacity, and alveolar septal volume compared with mice with leukocyte-specific HIF-1α deletion. However, the overall development of cigarette smoke-induced lung disease did not vary relative to control mice for either of the conditional strains. This suggests that the development of murine cigarette smoke-induced airspace disease occurs independently of leukocyte HIF-1α signaling.

Spatiotemporal distribution of cellular injury and leukocytes during the progression of ventilator-induced lung injury.

Supportive mechanical ventilation is a necessary lifesaving treatment for acute respiratory distress syndrome (ARDS). This intervention often leads to injury exacerbation by ventilator-induced lung injury (VILI). Patterns of injury in ARDS and VILI are recognized to be heterogeneous; however, quantification of these injury distributions remains incomplete. Developing a more detailed understanding of injury heterogeneity, particularly how it varies in space and time, can help elucidate the mechanisms of VILI pathogenesis. Ultimately, this knowledge can be used to develop protective ventilation strategies that slow disease progression. To expand existing knowledge of VILI heterogeneity, we document the spatial evolution of cellular injury distribution and leukocyte infiltration, on the micro- and macroscales, during protective and injurious mechanical ventilation. We ventilated naïve mice using either high inspiratory pressure and zero positive end-expiratory pressure ventilation or low tidal volume with positive end-expiratory pressure. Distributions of cellular injury, identified with propidium iodide staining, were microscopically analyzed at three levels of injury severity. Cellular injury initiated in diffuse, quasi-random patterns, and progressed through expansion of high-density regions of injured cells termed "injury clusters." The density profile of the expanding injury regions suggests that stress shielding occurs, protecting the already injured regions from further damage. Spatial distribution of leukocytes did not correlate with that of cellular injury or ventilation-induced changes in lung function. These results suggest that protective ventilation protocols should protect the interface between healthy and injured regions to stymie injury propagation.

Computational lung modelling in respiratory medicine.

Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure-function relationship in the lung.