The effect of tissue elastic properties and surfactant on alveolar stability

A Minimally Invasive Robotic Tissue Palpation Device

OBJECTIVE

Robot-assisted minimally invasive surgery remains limited by the absence of haptic feedback, which surgeons routinely rely on to assess tissue stiffness. This limitation hinders surgeons' ability to identify and treat abnormal tissues, such as tumors, during robotic surgery.

METHODS

To address this challenge, we developed a robotic tissue palpation device capable of rapidly and non-invasively quantifying the stiffness of soft tissues, allowing surgeons to make objective and data-driven decisions during minimally invasive procedures. We evaluated the effectiveness of our device by measuring the stiffness of phantoms as well as lung, heart, liver, and skin tissues obtained from both rats and swine.

RESULTS

Results demonstrated that our device can accurately determine tissue stiffness and identify tumor mimics. Specifically, in swine lung, we determined elastic modulus (E) values of 9.1 ± 2.3, 16.8 ± 1.8, and 26.0 ± 3.6 kPa under different internal pressure of the lungs (PIP) of 2, 25, and 45 cmH2O, respectively. Using our device, we successfully located a 2-cm tumor mimic embedded at a depth of 5 mm in the lung subpleural region. Additionally, we measured E values of 33.0 ± 5.4, 19.2 ± 2.2, 33.5 ± 8.2, and 22.6 ± 6.0 kPa for swine heart, liver, abdominal skin, and muscle, respectively, which closely matched existing literature data.

CONCLUSION/SIGNIFICANCE

Results suggest that our robotic palpation device can be utilized during surgery, either as a stand-alone or additional tool integrated into existing robotic surgical systems, to enhance treatment outcomes by enabling accurate intraoperative identification of abnormal tissue.

Exposure to Aldehyde Cherry e-Liquid Flavoring and Its Vaping Byproduct Disrupt Pulmonary Surfactant Biophysical Function

Over the past decade, there has been a significant rise in the use of vaping devices, particularly among adolescents, raising concerns for effects on respiratory health. Pressingly, many recent vaping-related lung injuries are unexplained by current knowledge, and the overall implications of vaping for respiratory health are poorly understood. This study investigates the effect of hydrophobic vaping liquid chemicals on the pulmonary surfactant biophysical function. We focus on the commonly used flavoring benzaldehyde and its vaping byproduct, benzaldehyde propylene glycol acetal. The study involves rigorous testing of the surfactant biophysical function in Langmuir trough and constrained sessile drop surfactometer experiments with both protein-free synthetic surfactant and hydrophobic protein-containing clinical surfactant models. The study reveals that exposure to these vaping chemicals significantly interferes with the synthetic and clinical surfactant biophysical function. Further atomistic simulations reveal preferential interactions with SP-B and SP-C surfactant proteins. Additionally, data show surfactant lipid-vaping chemical interactions and suggest significant transfer of vaping chemicals to the experimental subphase, indicating a toxicological mechanism for the alveolar epithelium. Our study, therefore, reveals novel mechanisms for the inhalational toxicity of vaping. This highlights the need to reassess the safety of vaping liquids for respiratory health, particularly the use of aldehyde chemicals as vaping flavorings.

The impact of e-cigarette exposure on different organ systems: A review of recent evidence and future perspectives

The use of electronic cigarettes (e-cigs) is rapidly increasing worldwide and is promoted as a smoking cessation tool. The impact of traditional cigs on human health has been well-defined in both animal and human studies. In contrast, little is known about the adverse effects of e-cigs exposure on human health. This review summarizes the impact of e-cigs exposure on different organ systems based on the rapidly expanding recent evidence from experimental and human studies. A number of growing studies have shown the adverse effects of e-cigs exposure on various organ systems. The summarized data in this review indicate that while e-cigs use causes less adverse effects on different organs compared to traditional cigs, its long-term exposure may lead to serious health effects. Data on short-term organ effects are limited and there is no sufficient evidence on long-term organ effects. Moreover, the adverse effects of secondhand and third hand e-cigs vapour exposure have not been thoroughly investigated in previous studies. Although some studies demonstrated e-cigs used as a smoking cessation tool, there is a lack of strong evidence to support it. While some researchers suggested e-cigs as a safer alternative to tobacco smoking, their long-term exposure health effects remain largely unknown. Therefore, more epidemiological and prospective studies including mechanistic studies are needed to address the potential adverse health effects of e-cigs to draw a firm conclusion about their safe use. A wide variation in e-cigs products and the lack of standardized testing methods are the major barriers to evaluating the existing data. Specific regulatory guidelines for both e-cigs components and the manufacturing process may be effective to protect consumer health.

Surfactant Proteins SP-B and SP-C in Pulmonary Surfactant Monolayers: Physical Properties Controlled by Specific Protein-Lipid Interactions

The lining of the alveoli is covered by pulmonary surfactant, a complex mixture of surface-active lipids and proteins that enables efficient gas exchange between inhaled air and the circulation. Despite decades of advancements in the study of the pulmonary surfactant, the molecular scale behavior of the surfactant and the inherent role of the number of different lipids and proteins in surfactant behavior are not fully understood. The most important proteins in this complex system are the surfactant proteins SP-B and SP-C. Given this, in this work we performed nonequilibrium all-atom molecular dynamics simulations to study the interplay of SP-B and SP-C with multicomponent lipid monolayers mimicking the pulmonary surfactant in composition. The simulations were complemented by z-scan fluorescence correlation spectroscopy and atomic force microscopy measurements. Our state-of-the-art simulation model reproduces experimental pressure-area isotherms and lateral diffusion coefficients. In agreement with previous research, the inclusion of either SP-B and SP-C increases surface pressure, and our simulations provide a molecular scale explanation for this effect: The proteins display preferential lipid interactions with phosphatidylglycerol, they reside predominantly in the lipid acyl chain region, and they partition into the liquid expanded phase or even induce it in an otherwise packed monolayer. The latter effect is also visible in our atomic force microscopy images. The research done contributes to a better understanding of the roles of specific lipids and proteins in surfactant function, thus helping to develop better synthetic products for surfactant replacement therapy used in the treatment of many fatal lung-related injuries and diseases.

Whole-lung finite-element models for mechanical ventilation and respiratory research applications

Mechanical ventilation has been a vital treatment for Covid-19 patients with respiratory failure. Lungs assisted with mechanical ventilators present a wide variability in their response that strongly depends on air-tissue interactions, which motivates the creation of simulation tools to enhance the design of ventilatory protocols. In this work, we aim to create anatomical computational models of the lungs that predict clinically-relevant respiratory variables. To this end, we formulate a continuum poromechanical framework that seamlessly accounts for the air-tissue interaction in the lung parenchyma. Based on this formulation, we construct anatomical finite-element models of the human lungs from computed-tomography images. We simulate the 3D response of lungs connected to mechanical ventilation, from which we recover physiological parameters of high clinical relevance. In particular, we provide a framework to estimate respiratory-system compliance and resistance from continuum lung dynamic simulations. We further study our computational framework in the simulation of the supersyringe method to construct pressure-volume curves. In addition, we run these simulations using several state-of-the-art lung tissue models to understand how the choice of constitutive models impacts the whole-organ mechanical response. We show that the proposed lung model predicts physiological variables, such as airway pressure, flow and volume, that capture many distinctive features observed in mechanical ventilation and the supersyringe method. We further conclude that some constitutive lung tissue models may not adequately capture the physiological behavior of lungs, as measured in terms of lung respiratory-system compliance. Our findings constitute a proof of concept that finite-element poromechanical models of the lungs can be predictive of clinically-relevant variables in respiratory medicine.

Pathological cardiolipin-promoted membrane hemifusion stiffens pulmonary surfactant membranes

Lower tract respiratory diseases such as pneumonia are pervasive, affecting millions of people every year. The stability of the air/water interface in alveoli and the mechanical performance during the breathing cycle are regulated by the structural and elastic properties of pulmonary surfactant membranes (PSMs). Respiratory dysfunctions and pathologies often result in, or are caused by, impairment of the PSMs. However, a gap remains between our knowledge of the etiology of lung diseases and the fundamental properties of PSMs. For example, bacterial pneumonia in humans and mice has been associated with aberrant levels of cardiolipin, a mitochondrial-specific, highly unsaturated 4-tailed anionic phospholipid, in lung fluid, which likely disrupts the structural and mechanical integrity of PSMs. Specifically, cardiolipin is expected to significantly alter PSM elasticity due to its intrinsic molecular properties favoring membrane folding away from a flat configuration. In this paper, we investigate the structural and mechanical properties of the lipidic components of PSMs using lipid-based models as well as bovine extracts affected by the addition of pathological cardiolipin levels. Specifically, using a combination of optical and atomic force microscopy with a surface force apparatus, we demonstrate that cardiolipin strongly promotes hemifusion of PSMs and that these local membrane contacts propagate at larger scales, resulting in global stiffening of lung membranes.

Molecular and cellular cues governing nanomaterial-mucosae interactions: from nanomedicine to nanotoxicology

Mucosal tissues constitute the largest interface between the body and the surrounding environment and they regulate the access of molecules, supramolecular structures, particulate matter, and pathogens into it. All mucosae are characterized by an outer mucus layer that protects the underlying cells from physicochemical, biological and mechanical insults, a mono-layered or stratified epithelium that forms tight junctions and controls the selective transport of solutes across it and associated lymphoid tissues that play a sentinel role. Mucus is a gel-like material comprised mainly of the glycoprotein mucin and water and it displays both hydrophilic and hydrophobic domains, a net negative charge, and high porosity and pore interconnectivity, providing an efficient barrier for the absorption of therapeutic agents. To prolong the residence time, absorption and bioavailability of a broad spectrum of active compounds upon mucosal administration, mucus-penetrating and mucoadhesive particles have been designed by tuning the chemical composition, the size, the density, and the surface properties. The benefits of utilizing nanomaterials that interact intimately with mucosae by different mechanisms in the nanomedicine field have been extensively reported. To ensure the safety of these nanosystems, their compatibility is evaluated in vitro and in vivo in preclinical and clinical trials. Conversely, there is a growing concern about the toxicity of nanomaterials dispersed in air and water effluents that unintentionally come into contact with the airways and the gastrointestinal tract. Thus, deep understanding of the key nanomaterial properties that govern the interplay with mucus and tissues is crucial for the rational design of more efficient drug delivery nanosystems (nanomedicine) and to anticipate the fate and side-effects of nanoparticulate matter upon acute or chronic exposure (nanotoxicology). This review initially overviews the complex structural features of mucosal tissues, including the structure of mucus, the epithelial barrier, the mucosal-associated lymphatic tissues and microbiota. Then, the most relevant investigations attempting to identify and validate the key particle features that govern nanomaterial-mucosa interactions and that are relevant in both nanomedicine and nanotoxicology are discussed in a holistic manner. Finally, the most popular experimental techniques and the incipient use of mathematical and computational models to characterize these interactions are described.

Understanding the Functional Properties of Lipid Heterogeneity in Pulmonary Surfactant Monolayers at the Atomistic Level

Pulmonary surfactant is a complex mixture of lipids and proteins lining the interior of the alveoli, and constitutes the first barrier to both oxygen and pathogens as they progress toward blood circulation. Despite decades of study, the behavior of the pulmonary surfactant at the molecular scale is poorly understood, which hinders the development of effective surfactant replacement therapies, useful in the treatment of several lung-related diseases. In this work, we combined all-atom molecular dynamics simulations, Langmuir trough measurements, and AFM imaging to study synthetic four-component lipid monolayers designed to model protein-free pulmonary surfactant. We characterized the structural and dynamic properties of the monolayers with a special focus on lateral heterogeneity. Remarkably, simulations reproduce almost quantitatively the experimental data on pressure-area isotherms and the presence of lateral heterogeneities highlighted by AFM. Quite surprisingly, the pressure-area isotherms do not show a plateau region, despite the presence of liquid-condensed nanometer-sized domains at surface pressures larger than 20 mN/m. In the simulations, the liquid-condensed domains were small and transient, but they did not coalesce to yield a separate phase. They were only slightly enriched in DPPC and cholesterol, and their chemical composition remained very similar to the overall composition of the monolayer membrane. Instead, they differed from liquid-expanded regions in terms of membrane thickness (in agreement with AFM data), diffusion rates, as well as acyl chain packing and orientation. We hypothesize that such lateral heterogeneities are crucial for lung surfactant function, as they allow both efficient packing, to achieve low surface tension, and sufficient fluidity, critical for rapid adsorption to the air–liquid interface during the breathing cycle.

An integrated 1D breathing lung simulation with relative hysteresis of airway structure and regional pressure for healthy and asthmatic human lungs

This study aims to develop a one-dimensional (1D) computational fluid dynamics (CFD) model with dynamic airway geometry that considers airway wall compliance and acinar dynamics. The proposed 1D model evaluates the pressure distribution and the hysteresis between the pressure and tidal volume (V_tidal) in the central and terminal airways for healthy and asthmatic subjects. Four-dimensional CT images were captured at 11-14 time points during the breathing cycle. The airway diameter and length were reconstructed using a volume-filling method and a stochastic model at respective time points. The obtained values for the airway diameter and length were interpolated via the Akima spline to avoid unboundedness. A 1D energy balance equation considering the effects of wall compliance and parenchymal inertance was solved using the efficient aggregation-based algebraic multigrid solver, a sparse matrix solver, reducing the computational costs by around 90% when compared with the generalized minimal residual solver. In the V_tidal versus displacement in the basal direction (z-coordinate), the inspiration curve was lower than the expiration curve, leading to relative hysteresis. The dynamic deformation model was the major factor influencing the difference in the workload in the central and terminal airways. In contrast, wall compliance and parenchymal inertance appeared only marginally to affect the pressure and workload. The integrated 1D model mimicked dynamic deformation by predicting airway diameter and length at each time point, describing the effects of wall compliance and parenchymal inertance. This computationally efficient model could be utilized to assess breathing mechanism as an alternative to pulmonary function tests.NEW & NOTEWORTHY This study introduces a one-dimensional (1D) computational fluid dynamics (CFD) model mimicking the realistic changes in diameter and length in whole airways and reveals differences in lung deformation between healthy and asthmatic subjects. Utilizing computational models, the effects of parenchymal inertance and airway wall compliance are investigated by changing ventilation frequency and airway wall elastance, respectively.

Heterogeneous structure and surface tension effects on mechanical response in pulmonary acinus: A finite element analysis

BACKGROUND

The pulmonary acinus is a dead-end microstructure that consists of ducts and alveoli. High-resolution micro-CT imaging has recently provided detailed anatomical information of a complete in vivo acinus, but relating its mechanical response with its detailed acinar structure remains challenging. This study aimed to investigate the mechanical response of acinar tissue in a whole acinus for static inflation using computational approaches.

METHODS

We performed finite element analysis of a whole acinus for static inflation. The acinar structure model was generated based on micro-CT images of an intact acinus. A continuum mechanics model of the lung parenchyma was used for acinar tissue material model, and surface tension effects were explicitly included. An anisotropic mechanical field analysis based on a stretch tensor was combined with a curvature-based local structure analysis.

FINDINGS

The airspace of the acinus exhibited nonspherical deformation as a result of the anisotropic deformation of acinar tissue. A strain hotspot occurred at the ridge-shaped region caused by a rod-like deformation of acinar tissue on the ridge. The local structure becomes bowl-shaped for inflation and, without surface tension effects, the surface of the bowl-shaped region primarily experiences isotropic deformation. Surface tension effects suppressed the increase in airspace volume and inner surface area, while facilitating anisotropic deformation on the alveolar surface.

INTERPRETATION

In the lungs, the heterogeneous acinar structure and surface tension induce anisotropic deformation at the acinar and alveolar scales. Further research is needed on structural variation of acini, inter-acini connectivity, or dynamic behavior to understand multiscale lung mechanics.

An estimation of mechanical stress on alveolar walls during repetitive alveolar reopening and closure

Alveolar overdistension and mechanical stresses generated by repetitive opening and closing of small airways and alveoli have been widely recognized as two primary mechanistic factors that may contribute to the development of ventilator-induced lung injury. A long-duration exposure of alveolar epithelial cells to even small, shear stresses could lead to the changes in cytoskeleton and the production of inflammatory mediators. In this paper, we have made an attempt to estimate in situ the magnitudes of mechanical stresses exerted on the alveolar walls during repetitive alveolar reopening by using a tape-peeling model of McEwan and Taylor (35). To this end, we first speculate the possible ranges of capillary number ( Ca) ≡ μU/ γ (a dimensionless combination of surface tension γ, fluid viscosity μ, and alveolar opening velocity U) during in vivo alveolar opening. Subsequent calculations show that increasing respiratory rate or inflation rate serves to increase the values of mechanical stresses. For a normal lung, the predicted maximum shear stresses are <15 dyn/cm2 at all respiratory rates, whereas for a lung with elevated surface tension or viscosity, the maximum shear stress will notably increase, even at a slow respiratory rate. Similarly, the increased pressure gradients in the case of elevated surface or viscosity may lead to a pressure drop >300 dyn/cm2 across a cell, possibly inducing epithelial hydraulic cracks. In addition, we have conceived of a geometrical model of alveolar opening to make a prediction of the positive end-expiratory pressure (PEEP) required to splint open a collapsed alveolus, which as shown by our results, covers a wide range of pressures, from several centimeters to dozens of centimeters of water, strongly depending on the underlying pulmonary conditions. The establishment of adequate regional ventilation-to-perfusion ratios may prevent recruited alveoli from reabsorption atelectasis and accordingly, reduce the required levels of PEEP. The present study and several recent animal experiments likewise suggest that a lung-protective ventilation strategy should not only include small tidal volume and plateau pressure limitations but also consider such cofactors as ventilation frequency and inflation rate.

Composition, structure and mechanical properties define performance of pulmonary surfactant membranes and films

The respiratory surface in the mammalian lung is stabilized by pulmonary surfactant, a membrane-based system composed of multiple lipids and specific proteins, the primary function of which is to minimize the surface tension at the alveolar air-liquid interface, optimizing the mechanics of breathing and avoiding alveolar collapse, especially at the end of expiration. The goal of the present review is to summarize current knowledge regarding the structure, lipid-protein interactions and mechanical features of surfactant membranes and films and how these properties correlate with surfactant biological function inside the lungs. Surfactant mechanical properties can be severely compromised by different agents, which lead to surfactant inhibition and ultimately contributes to the development of pulmonary disorders and pathologies in newborns, children and adults. A detailed comprehension of the unique mechanical and rheological properties of surfactant layers is crucial for the diagnostics and treatment of lung diseases, either by analyzing the contribution of surfactant impairment to the pathophysiology or by improving the formulations in surfactant replacement therapies. Finally, a short review is also included on the most relevant experimental techniques currently employed to evaluate lung surfactant mechanics, rheology, and inhibition and reactivation processes.

A micromechanical model for estimating alveolar wall strain in mechanically ventilated edematous lungs

To elucidate the micromechanics of pulmonary edema has been a significant medical concern, which is beneficial to better guide ventilator settings in clinical practice. In this paper, we present an adjoining two-alveoli model to quantitatively estimate strain and stress of alveolar walls in mechanically ventilated edematous lungs. The model takes into account the geometry of the alveolus, the effect of surface tension, the length-tension properties of parenchyma tissue, and the change in thickness of the alveolar wall. On the one hand, our model supports experimental findings (Perlman CE, Lederer DJ, Bhattacharya J. Am J Respir Cell Mol Biol 44: 34-39, 2011) that the presence of a liquid-filled alveolus protrudes into the neighboring air-filled alveolus with the shared septal strain amounting to a maximum value of 1.374 (corresponding to the maximum stress of 5.12 kPa) even at functional residual capacity; on the other hand, it further shows that the pattern of alveolar expansion appears heterogeneous or homogeneous, strongly depending on differences in air-liquid interface tension on alveolar segments. The proposed model is a preliminary step toward picturing a global topographical distribution of stress and strain on the scale of the lung as a whole to prevent ventilator-induced lung injury.

Visualisation of time-varying respiratory system elastance in experimental ARDS animal models

BACKGROUND

Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection.

METHODS

The single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject.

RESULTS

Six time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP.

CONCLUSIONS

Real-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.

Expiratory model-based method to monitor ARDS disease state

Introduction

Model-based methods can be used to characterise patient-specific condition and response to mechanical ventilation (MV) during treatment for acute respiratory distress syndrome (ARDS). Conventional metrics of respiratory mechanics are based on inspiration only, neglecting data from the expiration cycle. However, it is hypothesised that expiratory data can be used to determine an alternative metric, offering another means to track patient condition and guide positive end expiratory pressure (PEEP) selection.

Methods

Three fully sedated, oleic acid induced ARDS piglets underwent three experimental phases. Phase 1 was a healthy state recruitment manoeuvre. Phase 2 was a progression from a healthy state to an oleic acid induced ARDS state. Phase 3 was an ARDS state recruitment manoeuvre. The expiratory time-constant model parameter was determined for every breathing cycle for each subject. Trends were compared to estimates of lung elastance determined by means of an end-inspiratory pause method and an integral-based method. All experimental procedures, protocols and the use of data in this study were reviewed and approved by the Ethics Committee of the University of Liege Medical Faculty.

Results

The overall median absolute percentage fitting error for the expiratory time-constant model across all three phases was less than 10 %; for each subject, indicating the capability of the model to capture the mechanics of breathing during expiration. Provided the respiratory resistance was constant, the model was able to adequately identify trends and fundamental changes in respiratory mechanics.

Conclusion

Overall, this is a proof of concept study that shows the potential of continuous monitoring of respiratory mechanics in clinical practice. Respiratory system mechanics vary with disease state development and in response to MV settings. Therefore, titrating PEEP to minimal elastance theoretically results in optimal PEEP selection. Trends matched clinical expectation demonstrating robustness and potential for guiding MV therapy. However, further research is required to confirm the use of such real-time methods in actual ARDS patients, both sedated and spontaneously breathing.

Bayesian inference of the lung alveolar spatial model for the identification of alveolar mechanics associated with acute respiratory distress syndrome

Acute respiratory distress syndrome (ARDS) is acute lung failure secondary to severe systemic inflammation, resulting in a derangement of alveolar mechanics (i.e. the dynamic change in alveolar size and shape during tidal ventilation), leading to alveolar instability that can cause further damage to the pulmonary parenchyma. Mechanical ventilation is a mainstay in the treatment of ARDS, but may induce mechano-physical stresses on unstable alveoli, which can paradoxically propagate the cellular and molecular processes exacerbating ARDS pathology. This phenomenon is called ventilator induced lung injury (VILI), and plays a significant role in morbidity and mortality associated with ARDS. In order to identify optimal ventilation strategies to limit VILI and treat ARDS, it is necessary to understand the complex interplay between biological and physical mechanisms of VILI, first at the alveolar level, and then in aggregate at the whole-lung level. Since there is no current consensus about the underlying dynamics of alveolar mechanics, as an initial step we investigate the ventilatory dynamics of an alveolar sac (AS) with the lung alveolar spatial model (LASM), a 3D spatial biomechanical representation of the AS and its interaction with airflow pressure and the surface tension effects of pulmonary surfactant. We use the LASM to identify the mechanical ramifications of alveolar dynamics associated with ARDS. Using graphical processing unit parallel algorithms, we perform Bayesian inference on the model parameters using experimental data from rat lung under control and Tween-induced ARDS conditions. Our results provide two plausible models that recapitulate two fundamental hypotheses about volume change at the alveolar level: (1) increase in alveolar size through isotropic volume change, or (2) minimal change in AS radius with primary expansion of the mouth of the AS, with the implication that the majority of change in lung volume during the respiratory cycle occurs in the alveolar ducts. These two model solutions correspond to significantly different mechanical properties of the tissue, and we discuss the implications of these different properties and the requirements for new experimental data to discriminate between the hypotheses.

Model-based respiratory mechanics to titrate PEEP and monitor disease state for experimental ARDS subjects

Modelling the respiratory mechanics of mechanically ventilated (MV) patients can provide useful information to guide MV therapy. Two model-based methods were evaluated based on data from three experimental acute respiratory distress syndrome (ARDS) induced piglets and validated against values available from ventilators. A single compartment lung model with integral-based parameter identification was found to be effective in capturing fundamental respiratory mechanics during inspiration. The trends matched clinical expectation and provided better resolution than clinically derived linear model metrics. An expiration time constant model also captured the same trend in respiratory elastance. However, the assumption of constant resistance and a slightly higher fitting error results in less insight than the single compartment model. Further research is required to confirm its application in titrating to optimal MV settings.