Assessing the Progression of Ventilator-Induced Lung Injury in Mice

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

Quantitative characterization of lung structures by morphometrical or stereological analysis of histological 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 physiological/pathophysiological respiratory volume range. Thus, valuable information is being lost. In this perspective article, we argue that investigators performing pulmonary histological studies should consider whether the aims of their studies would benefit from fixation at functional transpulmonary pressures, particularly 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 histological 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 histological approach by fixing lungs at minimal and maximal functional volumes could enable new understanding of pulmonary structure-function relations.

Pressure- and time-dependent alveolar recruitment/derecruitment in a spatially resolved patient-specific computational model for injured human lungs

We present a novel computational model for the dynamics of alveolar recruitment/derecruitment (RD), which reproduces the underlying characteristics typically observed in injured lungs. The basic idea is a pressure- and time-dependent variation of the stress-free reference volume in reduced dimensional viscoelastic elements representing the acinar tissue. We choose a variable reference volume triggered by critical opening and closing pressures in a time-dependent manner from a straightforward mechanical point of view. In the case of (partially and progressively) collapsing alveolar structures, the volume available for expansion during breathing reduces and vice versa, eventually enabling consideration of alveolar collapse and reopening in our model. We further introduce a method for patient-specific determination of the underlying critical parameters of the new alveolar RD dynamics when integrated into the tissue elements, referred to as terminal units, of a spatially resolved physics-based lung model that simulates the human respiratory system in an anatomically correct manner. Relevant patient-specific parameters of the terminal units are herein determined based on medical image data and the macromechanical behavior of the lung during artificial ventilation. We test the whole modeling approach for a real-life scenario by applying it to the clinical data of a mechanically ventilated patient. The generated lung model is capable of reproducing clinical measurements such as tidal volume and pleural pressure during various ventilation maneuvers. We conclude that this new model is an important step toward personalized treatment of ARDS patients by considering potentially harmful mechanisms-such as cyclic RD and overdistension-and might help in the development of relevant protective ventilation strategies to reduce ventilator-induced lung injury (VILI).

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.

Modeling Lung Derecruitment in VILI Due to Fluid-Occlusion: The Role of Emergent Behavior

Ventilator-induced lung injury (VILI) is driven by the processes of volutrauma and atelectrauma, which can act synergistically to compromise the blood-gas barrier. We have postulated that this synergy arises through a rich-get-richer mechanism whereby atelectrauma causes holes to form in the blood-gas barrier while concomitant volutrauma causes susceptible holes to progressively enlarge as VILI worsens. We previously developed an analytical model based on this idea that accurately predicts the progressive increases in lung elastance seen immediately following a recruitment maneuver as VILI progresses over the course of hours. In the present study we extend this model to account for the rate of change of elastance, due to closure of lung units, in the minutes following a recruitment maneuver. We found that the distribution of unit closing velocities throughout the lung can be described by a power law with an exponent of -2 that matches previously published power laws associated with the dynamics of lung recruitment. Our model thus reveals lung collapse as an example of emergent complex behavior and links the dynamics of altered function in the injured lung to structural damage in a way that explains the mechanisms of injury progression arising from the ongoing stresses and strains applied by mechanical ventilation.

PEEP/ FIO2 ARDSNet Scale Grouping of a Single Ventilator for Two Patients: Modeling Tidal Volume Response

BACKGROUND

The COVID-19 pandemic is creating ventilator shortages in many countries that is sparking a conversation about placing multiple patients on a single ventilator. However, on March 26, 2020, six leading medical organizations released a joint statement warning clinicians that attempting this technique could lead to poor outcomes and high mortality. Nevertheless, hospitals around the United States and abroad are considering this technique out of desperation (eg, New York), but there is little data to guide their approach. The overall objective of this study is to utilize a computational model of mechanically ventilated lungs to assess how patient-specific lung mechanics and ventilator settings impact lung tidal volume (V_T).

METHODS

We developed a lumped-parameter computational model of multiple patients connected to a shared ventilator and validated it against a similar experimental study. We used this model to evaluate how patient-specific lung compliance and resistance would impact V_T under 4 ventilator settings of pressure control level, PEEP, breathing frequency, and inspiratory:expiratory ratio.

RESULTS

Our computational model predicts V_T within 10% of experimental measurements. Using this model to perform a parametric study, we provide proof-of-concept for an algorithm to better match patients in different hypothetical scenarios of a single ventilator shared by > 1 patient.

CONCLUSIONS

Assigning patients to preset ventilators based on their required level of support on the lower PEEP/higher [Formula: see text] scale of the National Institute of Health's National Heart, Lung, and Blood Institute ARDS Clinical Network (ARDSNet), secondary to lung mechanics, could be used to overcome some of the legitimate concerns of placing multiple patients on a single ventilator. We emphasize that our results are currently based on a computational model that has not been validated against any preclinical or clinical data. Therefore, clinicians considering this approach should not look to our study as an exact estimate of predicted patient V_T values.

Using injury cost functions from a predictive single-compartment model to assess the severity of mechanical ventilator-induced lung injuries

Identifying safe ventilation patterns for patients with acute respiratory distress syndrome remains challenging because of the delicate balance between gas exchange and selection of ventilator settings to prevent further ventilator-induced lung injury (VILI). Accordingly, this work seeks to link ventilator settings to graded levels of VILI to identify injury cost functions that predict injury by using a computational model to process pressures and flows measured at the airway opening. Pressure-volume loops were acquired over the course of ~2 h of mechanical ventilation in four different groups of BALB/c mice. A cohort of these animals were subjected to an injurious bronchoalveolar lavage before ventilation. The data were analyzed with a single-compartment model that predicts recruitment/derecruitment and tissue distension at each time step in measured pressure-volume loops. We compared several injury cost functions to markers of VILI-induced blood-gas barrier disruption. Of the cost functions considered, we conclude that mechanical power dissipation and strain heterogeneity are the best at distinguishing between graded levels of injury and are good candidates for forecasting the development of VILI. NEW & NOTEWORTHY This work uses a predictive single-compartment model and injury cost functions to assess graded levels of mechanical ventilator-induced lung injury. The most promising measures include strain heterogeneity and mechanical power dissipation.

Alveolar Micromechanics in Bleomycin-induced Lung Injury

Lung injury results in intratidal alveolar recruitment and derecruitment and alveolar collapse, creating stress concentrators that increase strain and aggravate injury. In this work, we sought to describe alveolar micromechanics during mechanical ventilation in bleomycin-induced lung injury and surfactant replacement therapy. Structure and function were assessed in rats 1 day and 3 days after intratracheal bleomycin instillation and after surfactant replacement therapy. Pulmonary system mechanics were measured during ventilation with positive end-expiratory pressures (PEEPs) between 1 and 10 cm H2O, followed by perfusion fixation at end-expiratory pressure at airway opening (Pao) values of 1, 5, 10, and 20 cm H2O for quantitative analyses of lung structure. Lung structure and function were used to parameterize a physiologically based, multicompartment computational model of alveolar micromechanics. In healthy controls, the numbers of open alveoli remained stable in a range of Pao = 1-20 cm H2O, whereas bleomycin-challenged lungs demonstrated progressive alveolar derecruitment with Pao < 10 cm H2O. At Day 3, ∼40% of the alveoli remained closed at high Pao, and alveolar size heterogeneity increased. Simulations of injured lungs predicted that alveolar recruitment pressures were much greater than the derecruitment pressures, so that minimal intratidal recruitment and derecruitment occurred during mechanical ventilation with a tidal volume of 10 ml/kg body weight over a range of PEEPs. However, the simulations also predicted a dramatic increase in alveolar strain with injury that we attribute to alveolar interdependence. These findings suggest that in progressive lung injury, alveolar collapse with increased distension of patent (open) alveoli dominates alveolar micromechanics. PEEP and surfactant substitution reduce alveolar collapse and dynamic strain but increase static strain.

The micromechanics of lung alveoli: structure and function of surfactant and tissue components

The mammalian lung´s structural design is optimized to serve its main function: gas exchange. It takes place in the alveolar region (parenchyma) where air and blood are brought in close proximity over a large surface. Air reaches the alveolar lumen via a conducting airway tree. Blood flows in a capillary network embedded in inter-alveolar septa. The barrier between air and blood consists of a continuous alveolar epithelium (a mosaic of type I and type II alveolar epithelial cells), a continuous capillary endothelium and the connective tissue layer in-between. By virtue of its respiratory movements, the lung has to withstand mechanical challenges throughout life. Alveoli must be protected from over-distension as well as from collapse by inherent stabilizing factors. The mechanical stability of the parenchyma is ensured by two components: a connective tissue fiber network and the surfactant system. The connective tissue fibers form a continuous tensegrity (tension + integrity) backbone consisting of axial, peripheral and septal fibers. Surfactant (surface active agent) is the secretory product of type II alveolar epithelial cells and covers the alveolar epithelium as a biophysically active thin and continuous film. Here, we briefly review the structural components relevant for gas exchange. Then we describe our current understanding of how these components function under normal conditions and how lung injury results in dysfunction of alveolar micromechanics finally leading to lung fibrosis.

Ventilator-induced lung injury and lung mechanics

Mechanical ventilation applies physical stresses to the tissues of the lung and thus may give rise to ventilator-induced lung injury (VILI), particular in patients with acute respiratory distress syndrome (ARDS). The most dire consequences of VILI result from injury to the blood-gas barrier. This allows plasma-derived fluid and proteins to leak into the airspaces where they flood some alveolar regions, while interfering with the functioning of pulmonary surfactant in those regions that remain open. These effects are reflected in commensurately increased values of dynamic lung elastance (EL ), a quantity that in principle is readily measured at the bedside. Recent mathematical/computational modeling studies have shown that the way in which EL varies as a function of both time and positive end-expiratory pressure (PEEP) reflects the nature and degree of lung injury, and can even be used to infer the separate contributions of volutrauma and atelectrauma to VILI. Interrogating such models for minimally injurious regimens of mechanical ventilation that apply to a particular lung may thus lead to personalized approaches to the ventilatory management of ARDS.

Linking lung function to structural damage of alveolar epithelium in ventilator-induced lung injury

Understanding how the mechanisms of ventilator-induced lung injury (VILI), namely atelectrauma and volutrauma, contribute to the failure of the blood-gas barrier and subsequent intrusion of edematous fluid into the airspace is essential for the design of mechanical ventilation strategies that minimize VILI. We ventilated mice with different combinations of tidal volume and positive end-expiratory pressure (PEEP) and linked degradation in lung function measurements to injury of the alveolar epithelium observed via scanning electron microscopy. Ventilating with both high inspiratory plateau pressure and zero PEEP was necessary to cause derangements in lung function as well as visually apparent physical damage to the alveolar epithelium of initially healthy mice. In particular, the epithelial injury was tightly associated with indicators of alveolar collapse. These results support the hypothesis that mechanical damage to the epithelium during VILI is at least partially attributed to atelectrauma-induced damage of alveolar type I epithelial cells.

Alveolar leak develops by a rich-get-richer process in ventilator-induced lung injury

Acute respiratory distress syndrome (ARDS) is a life-threatening condition for which there are currently no medical therapies other than supportive care involving the application of mechanical ventilation. However, mechanical ventilation itself can worsen ARDS by damaging the alveolocapillary barrier in the lungs. This allows plasma-derived fluid and proteins to leak into the airspaces of the lung where they interfere with the functioning of pulmonary surfactant, which increases the stresses of mechanical ventilation and worsens lung injury. Once such ventilator-induced lung injury (VILI) is underway, managing ARDS and saving the patient becomes increasingly problematic. Maintaining an intact alveolar barrier thus represents a crucial management goal, but the biophysical processes that perforate this barrier remain incompletely understood. To study the dynamics of barrier perforation, we subjected initially normal mice to an injurious ventilation regimen that imposed both volutrauma (overdistension injury) and atelectrauma (injury from repetitive reopening of closed airspaces) on the lung, and observed the rate at which macromolecules of various sizes leaked into the airspaces as a function of the degree of overall injury. Computational modeling applied to our findings suggests that perforations in the alveolocapillary barrier appear and progress according to a rich-get-richer mechanism in which the likelihood of a perforation getting larger increases with the size of the perforation. We suggest that atelectrauma causes the perforations after which volutrauma expands them. This mechanism explains why atelectrauma appears to be essential to the initiation of VILI in a normal lung, and why atelectrauma and volutrauma then act synergistically once VILI is underway.

CORP: Measurement of lung function in small animals

The measurement of lung function in mice and rats is crucial for understanding how well small animal models of pulmonary disease recapitulate human clinical pathology but brings with it the challenge of making accurate measurements in animals as small as a mouse. Overcoming these challenges can be achieved in a number of ways, each based on a model idealization of how the lung works as a mechanical system. Accordingly, it is important to understand the theoretical basis on which an assessment of lung function rests to interpret experimental measurements appropriately. It is also crucial to attend to a number of practical issues that determine the quality of the measurements. The most accurate measurements of lung function in small animals are provided by the forced oscillation technique that provides lung resistance and elastance and its multifrequency generalization known as impedance. Measurement quality is maximized when the greatest possible degree of control is exerted over the amplitude and frequency with which air is oscillated in and out of the lungs, the mean or end-expiratory transpulmonary pressure pertaining to when the oscillations are applied, and the immediate past volume history of the lungs. It is also crucial that no spontaneous breathing efforts occur during the measurement period. Finally, there is no substitute for the skill in animal handling and surgical preparation that comes with practice; such a skill should be in place before embarking on any important series of experiments.

Dynamic Mechanical Interactions Between Neighboring Airspaces Determine Cyclic Opening and Closure in Injured Lung

OBJECTIVES

Positive pressure ventilation exposes the lung to mechanical stresses that can exacerbate injury. The exact mechanism of this pathologic process remains elusive. The goal of this study was to describe recruitment/derecruitment at acinar length scales over short-time frames and test the hypothesis that mechanical interdependence between neighboring lung units determines the spatial and temporal distributions of recruitment/derecruitment, using a computational model.

DESIGN

Experimental animal study.

SETTING

International synchrotron radiation laboratory.

SUBJECTS

Four anesthetized rabbits, ventilated in pressure controlled mode.

INTERVENTIONS

The lung was consecutively imaged at ~ 1.5-minute intervals using phase-contrast synchrotron imaging, at positive end-expiratory pressures of 12, 9, 6, 3, and 0 cm H2O before and after lavage and mechanical ventilation induced injury. The extent and spatial distribution of recruitment/derecruitment was analyzed by subtracting subsequent images. In a realistic lung structure, we implemented a mechanistic model in which each unit has individual pressures and speeds of opening and closing. Derecruited and recruited lung fractions (Fderecruited, Frecruited) were computed based on the comparison of the aerated volumes at successive time points.

MEASUREMENTS AND MAIN RESULTS

Alternative recruitment/derecruitment occurred in neighboring alveoli over short-time scales in all tested positive end-expiratory pressure levels and despite stable pressure controlled mode. The computational model reproduced this behavior only when parenchymal interdependence between neighboring acini was accounted for. Simulations closely mimicked the experimental magnitude of Fderecruited and Frecruited when mechanical interdependence was included, while its exclusion gave Frecruited values of zero at positive end-expiratory pressure greater than or equal to 3 cm H2O.

CONCLUSIONS

These findings give further insight into the microscopic behavior of the injured lung and provide a means of testing protective-ventilation strategies to prevent recruitment/derecruitment and subsequent lung damage.

Predicting ventilator-induced lung injury using a lung injury cost function

Managing patients with acute respiratory distress syndrome (ARDS) requires mechanical ventilation that balances the competing goals of sustaining life while avoiding ventilator-induced lung injury (VILI). In particular, it is reasonable to suppose that for any given ARDS patient, there must exist an optimum pair of values for tidal volume (VT) and positive end-expiratory pressure (PEEP) that together minimize the risk for VILI. To find these optimum values, and thus develop a personalized approach to mechanical ventilation in ARDS, we need to be able to predict how injurious a given ventilation regimen will be in any given patient so that the minimally injurious regimen for that patient can be determined. Our goal in the present study was therefore to develop a simple computational model of the mechanical behavior of the injured lung in order to calculate potential injury cost functions to serve as predictors of VILI. We set the model parameters to represent normal, mildly injured, and severely injured lungs and estimated the amount of volutrauma and atelectrauma caused by ventilating these lungs with a range of VT and PEEP. We estimated total VILI in two ways: 1) as the sum of the contributions from volutrauma and atelectrauma and 2) as the product of their contributions. We found the product provided estimates of VILI that are more in line with our previous experimental findings. This model may thus serve as the basis for the objective choice of mechanical ventilation parameters for the injured lung.

Computational Models of Ventilator Induced Lung Injury and Surfactant Dysfunction

Managing acute respiratory distress syndrome (ARDS) invariably involves the administration of mechanical ventilation, the challenge being to avoid the iatrogenic sequellum known as ventilator-induced lung injury (VILI). Devising individualized ventilation strategies in ARDS requires that patient-specific lung physiology be taken into account, and this is greatly aided by the use of computational models of lung mechanical function that can be matched to physiological measurements made in a given patient. In this review, we discuss recent models that have the potential to serve as the basis for devising minimally injurious modes of mechanical ventilation in ARDS patients.

Variable Ventilation as a Diagnostic Tool for the Injured Lung

Mechanical ventilation of patients with acute respiratory distress syndrome (ARDS) is a necessary life support measure which may lead to ventilator-induced lung injury, a complication that can be reduced or ameliorated by using appropriate tidal volumes and positive end-expiratory pressures. However, the optimal mechanical ventilation parameters are almost certainly different for each patient, and will vary with time as the injury status of the lung changes. In order to optimize mechanical ventilation in an individual ARDS patient, therefore, it is necessary to track the manner in which injury status is reflected in the mechanical properties of the lungs. Accordingly, we developed an algorithm for assessing the time-dependent manner in which different lung regions open (recruit) and close (derecruit) as a function of the pressure waveform that is applied to the airways during mechanical ventilation. We used this algorithm to test the notion that variable ventilation provides the dynamic perturbations in lung volume necessary to accurately identify recruitment/derecruitment dynamics in the injured lung. We performed this test on synthetic pressure and flow data generated with established numerical models of lung function corresponding to both healthy mice and mice with lung injury. The data were generated by subjecting the models to a variety of mechanical ventilation regimens including variable ventilation. Our results support the hypothesis that variable ventilation can be used as a diagnostic tool to identify the injury status of the lung in ARDS.