Elucidating the interaction between stretch and stiffness using an agent-based spring network model of progressive pulmonary fibrosis.

Pulmonary fibrosis is a deadly disease that involves the dysregulation of fibroblasts and myofibroblasts, which are mechanosensitive. Previous computational models have succeeded in modeling stiffness-mediated fibroblasts behaviors; however, these models have neglected to consider stretch-mediated behaviors, especially stretch-sensitive channels and the stretch-mediated release of latent TGF-ß. Here, we develop and explore an agent-based model and spring network model hybrid that is capable of recapitulating both stiffness and stretch. Using the model, we evaluate the role of mechanical signaling in homeostasis and disease progression during self-healing and fibrosis, respectively. We develop the model such that there is a fibrotic threshold near which the network tends towards instability and fibrosis or below which the network tends to heal. The healing response is due to the stretch signal, whereas the fibrotic response occurs when the stiffness signal overpowers the stretch signal, creating a positive feedback loop. We also find that by changing the proportional weights of the stretch and stiffness signals, we observe heterogeneity in pathological network structure similar to that seen in human IPF tissue. The system also shows emergent behavior and bifurcations: whether the network will heal or turn fibrotic depends on the initial network organization of the damage, clearly demonstrating structure's pivotal role in healing or fibrosis of the overall network. In summary, these results strongly suggest that the mechanical signaling present in the lungs combined with network effects contribute to both homeostasis and disease progression.

LDCT image biomarkers that matter most for the deep learning classification of indeterminate pulmonary nodules.

BACKGROUND: Continued improvement in deep learning methodologies has increased the rate at which deep neural networks are being evaluated for medical applications, including diagnosis of lung cancer. However, there has been limited exploration of the underlying radiological characteristics that the network relies on to identify lung cancer in computed tomography (CT) images. OBJECTIVE: In this study, we used a combination of image masking and saliency activation maps to systematically explore the contributions of both parenchymal and tumor regions in a CT image to the classification of indeterminate lung nodules. METHODS: We selected individuals from the National Lung Screening Trial (NLST) with solid pulmonary nodules 4-20 mm in diameter. Segmentation masks were used to generate three distinct datasets; 1) an Original Dataset containing the complete low-dose CT scans from the NLST, 2) a Parenchyma-Only Dataset in which the tumor regions were covered by a mask, and 3) a Tumor-Only Dataset in which only the tumor regions were included. RESULTS: The Original Dataset significantly outperformed the Parenchyma-Only Dataset and the Tumor-Only Dataset with an AUC of 80.80 ± 3.77% compared to 76.39 ± 3.16% and 78.11 ± 4.32%, respectively. Gradient-weighted class activation mapping (Grad-CAM) of the Original Dataset showed increased attention was being given to the nodule and the tumor-parenchyma boundary when nodules were classified as malignant. This pattern of attention remained unchanged in the case of the Parenchyma-Only Dataset. Nodule size and first-order statistical features of the nodules were significantly different with the average malignant and benign nodule maximum 3d diameter being 23 mm and 12 mm, respectively. CONCLUSION: We conclude that network performance is linked to textural features of nodules such as kurtosis, entropy and intensity, as well as morphological features such as sphericity and diameter. Furthermore, textural features are more positively associated with malignancy than morphological features.

Time-Controlled Adaptive Ventilation (TCAV): a personalized strategy for lung protection.

Acute respiratory distress syndrome (ARDS) alters the dynamics of lung inflation during mechanical ventilation. Repetitive alveolar collapse and expansion (RACE) predisposes the lung to ventilator-induced lung injury (VILI). Two broad approaches are currently used to minimize VILI: (1) low tidal volume (LVT) with low-moderate positive end-expiratory pressure (PEEP); and (2) open lung approach (OLA). The LVT approach attempts to protect already open lung tissue from overdistension, while simultaneously resting collapsed tissue by excluding it from the cycle of mechanical ventilation. By contrast, the OLA attempts to reinflate potentially recruitable lung, usually over a period of seconds to minutes using higher PEEP used to prevent progressive loss of end-expiratory lung volume (EELV) and RACE. However, even with these protective strategies, clinical studies have shown that ARDS-related mortality remains unacceptably high with a scarcity of effective interventions over the last two decades. One of the main limitations these varied interventions demonstrate to benefit is the observed clinical and pathologic heterogeneity in ARDS. We have developed an alternative ventilation strategy known as the Time Controlled Adaptive Ventilation (TCAV) method of applying the Airway Pressure Release Ventilation (APRV) mode, which takes advantage of the heterogeneous time- and pressure-dependent collapse and reopening of lung units. The TCAV method is a closed-loop system where the expiratory duration personalizes VT and EELV. Personalization of TCAV is informed and tuned with changes in respiratory system compliance (CRS) measured by the slope of the expiratory flow curve during passive exhalation. Two potentially beneficial features of TCAV are: (i) the expiratory duration is personalized to a given patient's lung physiology, which promotes alveolar stabilization by halting the progressive collapse of alveoli, thereby minimizing the time for the reopened lung to collapse again in the next expiration, and (ii) an extended inspiratory phase at a fixed inflation pressure after alveolar stabilization gradually reopens a small amount of tissue with each breath. Subsequently, densely collapsed regions are slowly ratcheted open over a period of hours, or even days. Thus, TCAV has the potential to minimize VILI, reducing ARDS-related morbidity and mortality.

Local fractal dimension of collagen detects increased spatial complexity in fibrosis.

Increase of collagen content and reorganization characterizes fibrosis but quantifying the latter remains challenging. Spatially complex structures are often analyzed via the fractal dimension; however, established methods for calculating this quantity either provide a single dimension for an entire object or a spatially distributed dimension that only considers binary images. These neglect valuable information related to collagen density in images of fibrotic tissue. We sought to develop a fractal analysis that can be applied to 3-dimensional (3D) images of fibrotic tissue. A fractal dimension map for each image was calculated by determining a single fractal dimension for a small area surrounding each image pixel, using fiber thickness as the third dimension. We found that this local fractal dimension increased with age and with progression of fibrosis regardless of collagen content. Our new method of distributed 3D fractal analysis can thus distinguish between changes in collagen content and organization induced by fibrosis.

Sustained vs. Intratidal Recruitment in the Injured Lung During Airway Pressure Release Ventilation: A Computational Modeling Perspective.

INTRODUCTION: During mechanical ventilation, cyclic recruitment and derecruitment (R/D) of alveoli result in focal points of heterogeneous stress throughout the lung. In the acutely injured lung, the rates at which alveoli can be recruited or derecruited may also be altered, requiring longer times at higher pressure levels to be recruited during inspiration, but shorter times at lower pressure levels to minimize collapse during exhalation. In this study, we used a computational model to simulate the effects of airway pressure release ventilation (APRV) on acinar recruitment, with varying inspiratory pressure levels and durations of exhalation. MATERIALS AND METHODS: The computational model consisted of a ventilator pressure source, a distensible breathing circuit, an endotracheal tube, and a porcine lung consisting of recruited and derecruited zones, as well as a transitional zone capable of intratidal R/D. Lung injury was simulated by modifying each acinus with an inflation-dependent surface tension. APRV was simulated for an inhalation duration (Thigh) of 4.0 seconds, inspiratory pressures (Phigh) of 28 and 40 cmH2O, and exhalation durations (Tlow) ranging from 0.2 to 1.5 seconds. RESULTS: Both sustained acinar recruitment and intratidal R/D within the subtree were consistently higher for Phigh of 40 cmH2O vs. 28 cmH2O, regardless of Tlow. Increasing Tlow was associated with decreasing sustained acinar recruitment, but increasing intratidal R/D, within the subtree. Increasing Tlow was associated with decreasing elastance of both the total respiratory system and transitional subtree of the model. CONCLUSIONS: Our computational model demonstrates the confounding effects of cyclic R/D, sustained recruitment, and parenchymal strain stiffening on estimates of total lung elastance during APRV. Increasing inspiratory pressures leads to not only more sustained recruitment of unstable acini but also more intratidal R/D. Our model indicates that higher inspiratory pressures should be used in conjunction with shorter exhalation times, to avoid increasing intratidal R/D.

Full-lung simulations of mechanically ventilated lungs incorporating recruitment/derecruitment dynamics.

This study developed and investigated a comprehensive multiscale computational model of a mechanically ventilated ARDS lung to elucidate the underlying mechanisms contributing to the development or prevention of VILI. This model is built upon a healthy lung model that incorporates realistic airway and alveolar geometry, tissue distensibility, and surfactant dynamics. Key features of the ARDS model include recruitment and derecruitment (RD) dynamics, alveolar tissue viscoelasticity, and surfactant deficiency. This model successfully reproduces realistic pressure-volume (PV) behavior, dynamic surface tension, and time-dependent descriptions of RD events as a function of the ventilation scenario. Simulations of Time-Controlled Adaptive Ventilation (TCAV) modes, with short and long durations of exhalation (T Low - and T Low +, respectively), reveal a higher incidence of RD for T Low + despite reduced surface tensions due to interfacial compression. This finding aligns with experimental evidence emphasizing the critical role of timing in protective ventilation strategies. Quantitative analysis of energy dissipation indicates that while alveolar recruitment contributes only a small fraction of total energy dissipation, its spatial concentration and brief duration may significantly contribute to VILI progression due to its focal nature and higher intensity. Leveraging the computational framework, the model may be extended to facilitate the development of personalized protective ventilation strategies to enhance patient outcomes. As such, this computational modeling approach offers valuable insights into the complex dynamics of VILI that may guide the optimization of ventilation strategies in ARDS management.

Ratchet recruitment in the acute respiratory distress syndrome: lessons from the newborn cry.

Patients with acute respiratory distress syndrome (ARDS) have few treatment options other than supportive mechanical ventilation. The mortality associated with ARDS remains unacceptably high, and mechanical ventilation itself has the potential to increase mortality further by unintended ventilator-induced lung injury (VILI). Thus, there is motivation to improve management of ventilation in patients with ARDS. The immediate goal of mechanical ventilation in ARDS should be to prevent atelectrauma resulting from repetitive alveolar collapse and reopening. However, a long-term goal should be to re-open collapsed and edematous regions of the lung and reduce regions of high mechanical stress that lead to regional volutrauma. In this paper, we consider the proposed strategy used by the full-term newborn to open the fluid-filled lung during the initial breaths of life, by ratcheting tissues opened over a series of initial breaths with brief expirations. The newborn's cry after birth shares key similarities with the Airway Pressure Release Ventilation (APRV) modality, in which the expiratory duration is sufficiently short to minimize end-expiratory derecruitment. Using a simple computational model of the injured lung, we demonstrate that APRV can slowly open even the most recalcitrant alveoli with extended periods of high inspiratory pressure, while reducing alveolar re-collapse with brief expirations. These processes together comprise a ratchet mechanism by which the lung is progressively recruited, similar to the manner in which the newborn lung is aerated during a series of cries, albeit over longer time scales.

The effect of inhaled extrafine beclometasone dipropionate/formoterol fumarate/glycopyrronium bromide on distal and central airway indices, assessed using Functional Respiratory Imaging in COPD (DARWiIN).

BACKGROUND: This study, in patients with symptomatic chronic obstructive pulmonary disease (COPD), explored switching therapy from non-extrafine high-dose inhaled corticosteroid/long-acting ß2-agonist (ICS/LABA; fluticasone propionate/salmeterol [FP/SLM]) to extrafine medium-dose beclometasone dipropionate/formoterol fumarate dihydrate/glycopyrronium (BDP/FF/G), both via dry-powder inhaler. Functional Respiratory Imaging, a quantitative computed tomography method with 3D reconstructions of pulmonary anatomy, was used to assess airway geometry and lung function. METHODS: Patients receiving a stable ICS/LABA regimen for ≥ 8 weeks were switched to FP/SLM 500/50 µg, one inhalation twice-daily (high-dose ICS) for 6 weeks. After baseline assessments (Visit 2 [V2]), therapy was switched to BDP/FF/G 100/6/10 µg, two inhalations twice-daily (medium-dose ICS) for 6 weeks, followed by V3. The primary endpoints were percentage changes in specific image-based airway volume (siVaw) and resistance (siRaw) from baseline to predose at V3 (i.e., chronic effects), assessed at total lung capacity (TLC) in central and distal lung regions. Secondary endpoints included siVaw and siRaw changes from pre-dose to post-dose at V2, and from pre-dose to post-dose at V3 at TLC (i.e., acute effects), and chronic and acute changes in siVaw and siRaw at functional residual capacity (FRC). Pre-dose forced expiratory volume in 1 s (FEV1) and COPD Assessment Test (CAT) were also assessed. RESULTS: There were no significant changes in pre-dose siVaw or siRaw at TLC from baseline to V3, although at FRC there was a significant decrease in mean siRaw in the distal airways (- 63.6%; p = 0.0261). In addition, in the distal airways there were significant acute effects at TLC on mean siVaw and siRaw (siVaw: 39.8% and 62.6%; siRaw: - 51.1% and - 57.2%, V2 and V3, respectively; all p < 0.001) and at FRC at V2 (siVaw: 77.9%; siRaw: - 67.0%; both p < 0.001). At V3, the mean change in pre-dose FEV1 was 62.2 mL (p = 0.0690), and in CAT total score was - 3.30 (p < 0.0001). CONCLUSIONS: In patients with symptomatic COPD receiving high-dose ICS/LABA, adding a long-acting muscarinic antagonist while decreasing the ICS dose by switching to medium-dose extrafine BDP/FF/G was associated with improved airway indices, especially in the distal airways, together with improvements in respiratory health status. Trial registration ClinicalTrials.gov (NCT04876677), first posted 6th May 2021.

An approach to study recruitment/derecruitment dynamics in a patient-specific computational model of an injured human lung.

We present a new approach for physics-based computational modeling of diseased human lungs. Our main object is the development of a model that takes the novel step of incorporating the dynamics of airway recruitment/derecruitment into an anatomically accurate, spatially resolved model of respiratory system mechanics, and the relation of these dynamics to airway dimensions and the biophysical properties of the lining fluid. The importance of our approach is that it potentially allows for more accurate predictions of where mechanical stress foci arise in the lungs, since it is at these locations that injury is thought to arise and propagate from. We match the model to data from a patient with acute respiratory distress syndrome (ARDS) to demonstrate the potential of the model for revealing the underlying derangements in ARDS in a patient-specific manner. To achieve this, the specific geometry of the lung and its heterogeneous pattern of injury are extracted from medical CT images. The mechanical behavior of the model is tailored to the patient's respiratory mechanics using measured ventilation data. In retrospective simulations of various clinically performed, pressure-driven ventilation profiles, the model adequately reproduces clinical quantities measured in the patient such as tidal volume and change in pleural pressure. The model also exhibits physiologically reasonable lung recruitment dynamics and has the spatial resolution to allow the study of local mechanical quantities such as alveolar strains. This modeling approach advances our ability to perform patient-specific studies in silico, opening the way to personalized therapies that will optimize patient outcomes.

Effects of obesity, pneumoperitoneum, and body position on mechanical power of intraoperative ventilation: an observational study.

Mechanical power can describe the complex interaction between the respiratory system and the ventilator and may predict lung injury or pulmonary complications, but the power associated with injury of healthy human lungs is unknown. Body habitus and surgical conditions may alter mechanical power but the effects have not been measured. In a secondary analysis of an observational study of obesity and lung mechanics during robotic laparoscopic surgery, we comprehensively quantified the static elastic, dynamic elastic, and resistive energies comprising mechanical power of ventilation. We stratified by body mass index (BMI) and examined power at four surgical stages: level after intubation, with pneumoperitoneum, in Trendelenburg, and level after releasing the pneumoperitoneum. Esophageal manometry was used to estimate transpulmonary pressures. Mechanical power of ventilation and its bioenergetic components increased over BMI categories. Respiratory system and lung power were nearly doubled in subjects with class 3 obesity compared with lean at all stages. Power dissipated into the respiratory system was increased with class 2 or 3 obesity compared with lean. Increased power of ventilation was associated with decreasing transpulmonary pressures. Body habitus is a prime determinant of increased intraoperative mechanical power. Obesity and surgical conditions increase the energies dissipated into the respiratory system during ventilation. The observed elevations in power may be related to tidal recruitment or atelectasis, and point to specific energetic features of mechanical ventilation of patients with obesity that may be controlled with individualized ventilator settings.NEW & NOTEWORTHY Mechanical power describes the complex interaction between a patient's lungs and the ventilator and may be useful in predicting lung injury. However, its behavior in obesity and during dynamic surgical conditions is not understood. We comprehensively quantified ventilation bioenergetics and effects of body habitus and common surgical conditions. These data show body habitus is a prime determinant of intraoperative mechanical power and provide quantitative context for future translation toward a useful perioperative prognostic measurement.

Visualizing intratumoral injections in lung tumors by endobronchial ultrasound.

Real-time endobronchial ultrasound images are crucial for the accurate placement of the needle in peribronchial lung tumors and lymph nodes for diagnostic sampling. Beyond its role as a diagnostic tool, ultrasound-guided bronchoscopy can also aid the delivery of anti-cancer agents intratumorally, enabling diagnosis, staging, and treatment to occur within the same anesthesia, reducing the patient's burden. However, determining drug retention and distribution in situ remains challenging, albeit pivotal in assessing the success or failure of the therapeutic intervention. We hypothesized that ultrasound images acquired by the bronchoscope during the injection can provide qualitative and quantitative real-time information about drug transport. As a proof-of-concept, we retrospectively analyzed 13 videos of intratumoral cisplatin injections in advanced non-small cell lung cancers. We identified the injection and performed quantitative analysis through image processing and segmentation algorithms and mathematical models in 5 of them. We were able to infer the unlikeliness of a laminar flow through interstitial pores in favor of the emergence of tissue fractures. These data imply that the structural integrity of the tumor is a critical determinant of the ultimate distribution of an intratumorally delivered agent.

An agent-based model of tissue maintenance and self-repair.

We hypothesized that a system that possesses the capacity for ongoing maintenance of its tissues will necessarily also have the capacity to self-heal following a perturbation. We used an agent-based model of tissue maintenance to investigate this idea, and in particular to determine the extent to which the current state of the tissue must influence cell behavior in order for tissue maintenance and self-healing to be stable. We show that a mean level of tissue density is robustly maintained when catabolic agents digest tissue at a rate proportional to local tissue density, but that the spatial heterogeneity of the tissue at homeostasis increases with the rate at which tissue is digested. The rate of self-healing is also increased by increasing either the amount of tissue removed or deposited at each time step by catabolic or anabolic agents, respectively, and by increasing the density of both agent types on the tissue. We also found that tissue maintenance and self-healing are stable with an alternate rule in which cells move preferentially to tissue regions of low density. The most basic form of self-healing can thus be achieved with cells that follow very simple rules of behavior, provided these rules are based in some way on the current state of the local tissue. Straightforward mechanisms can accelerate the rate of self-healing, as might be beneficial to the organism.

Ventilator-Induced Lung Injury as a Dynamic Balance Between Epithelial Cell Damage and Recovery.

Acute respiratory distress syndrome (ARDS) has a high mortality rate that is due in part to ventilator-induced lung injury (VILI). Nevertheless, the majority of patients eventually recover, which means that their innate reparative capacities eventually prevail. Since there are currently no medical therapies for ARDS, minimizing its mortality thus amounts to achieving an optimal balance between spontaneous tissue repair versus the generation of VILI. In order to understand this balance better, we developed a mathematical model of the onset and recovery of VILI that incorporates two hypotheses: (1) a novel multi-hit hypothesis of epithelial barrier failure, and (2) a previously articulated rich-get-richer hypothesis of the interaction between atelectrauma and volutrauma. Together, these concepts explain why VILI appears in a normal lung only after an initial latent period of injurious mechanical ventilation. In addition, they provide a mechanistic explanation for the observed synergy between atelectrauma and volutrauma. The model recapitulates the key features of previously published in vitro measurements of barrier function in an epithelial monolayer and in vivo measurements of lung function in mice subjected to injurious mechanical ventilation. This provides a framework for understanding the dynamic balance between factors responsible for the generation of and recovery from VILI.

Predicting alveolar ventilation heterogeneity in pulmonary fibrosis using a non-uniform polyhedral spring network model.

Pulmonary Fibrosis (PF) is a deadly disease that has limited treatment options and is caused by excessive deposition and cross-linking of collagen leading to stiffening of the lung parenchyma. The link between lung structure and function in PF remains poorly understood, although its spatially heterogeneous nature has important implications for alveolar ventilation. Computational models of lung parenchyma utilize uniform arrays of space-filling shapes to represent individual alveoli, but have inherent anisotropy, whereas actual lung tissue is isotropic on average. We developed a novel Voronoi-based 3D spring network model of the lung parenchyma, the Amorphous Network, that exhibits more 2D and 3D similarity to lung geometry than regular polyhedral networks. In contrast to regular networks that show anisotropic force transmission, the structural randomness in the Amorphous Network dissipates this anisotropy with important implications for mechanotransduction. We then added agents to the network that were allowed to carry out a random walk to mimic the migratory behavior of fibroblasts. To model progressive fibrosis, agents were moved around the network and increased the stiffness of springs along their path. Agents migrated at various path lengths until a certain percentage of the network was stiffened. Alveolar ventilation heterogeneity increased with both percent of the network stiffened, and walk length of the agents, until the percolation threshold was reached. The bulk modulus of the network also increased with both percent of network stiffened and path length. This model thus represents a step forward in the creation of physiologically accurate computational models of lung tissue disease.

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report.

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Lung de-recruitment in the allergic asthma of obesity: evidence from an anatomically based inverse model.

The increase in asthma associated with the obesity epidemic cannot simply be due to airway hyperresponsiveness from chronic lung compression because chronic lung compression is a feature of obesity in general. We therefore sought to investigate what other factors might be at play in the impaired lung function seen in obese individuals with asthma. We measured respiratory system impedance in four groups-Lean Control, Lean Allergic Asthma, Obese Control, and Obese Allergic Asthma-before and after administration of albuterol. Impedance measurements were fit with an anatomically based computational model of lung mechanics that represents the airway tree as a branching structure with a uniform degree of asymmetry and a fixed radius scaling ratio, γ, between branches of sequential order. The two model parameters that define the airway tree, γ and tracheal radius, varied only modestly between the four study groups, indicating relatively minor differences in airway caliber. In contrast, respiratory system elastance was 57, 34, 143, and 271 cmH2O/L, respectively, for the four groups, suggesting that obesity induced significant lung de-recruitment that was exacerbated by allergic asthma. In addition, when the radii of the individual branches of the airway tree were varied randomly, we found that roughly half the terminal airways had to be closed to have the model fit the data well. We conclude that de-recruitment of small airways is a particular feature of Obese Allergic Asthma, and this can be inferred from respiratory system impedance fit with an anatomically based computational model.NEW & NOTEWORTHY Using a novel anatomically based computational model to interpret oscillometry measurements of impedance, we show that respiratory system elastance is increased in obesity and is increased dramatically in individuals with obese allergic asthma. A significant component of this increased elastance in obese allergic asthma appears to be due to closure of small airways rather than alveolar atelectasis, and this closure is partially mitigated by albuterol. These findings potentially point to nonpharmacological therapies in obese allergic asthma aimed at recruiting closed airways.

Peripheral Airway Dysfunction in Obesity and Obese Asthma.

BACKGROUND: The purpose of this study was to investigate physiological phenotypes of asthma in obesity. RESEARCH QUESTION: Do physiological responses during bronchoconstriction distinguish different groups of asthma in people with obesity, and also differentiate from responses simply related to obesity? STUDY DESIGN AND METHODS: Cross-sectional study of people with obesity (31 with asthma and 22 without lung disease). Participants underwent methacholine challenge testing with measurement of spirometry and respiratory system impedance by oscillometry. RESULTS: Participants had class III obesity (BMI, 46.7 ± 6.6 kg/m2 in control subjects and 47.2 ± 8.2 kg/m2 in people with asthma). Most participants had significant changes in peripheral airway impedance in response to methacholine: in control subjects, resistance at 5 Hz measured by oscillometry increased by 45% ± 27% and area under the reactance curve (AX) by 268% ± 236% in response to 16 mg/mL methacholine; in people with asthma, resistance at 5 Hz measured by oscillometry increased by 52% ± 38% and AX by 361% ± 295% in response to provocation concentration producing a 20% fall in FEV1 dose of methacholine. These responses suggest that obesity predisposes to peripheral airway reactivity. Two distinct groups of asthma emerged based on respiratory system impedance: one with lower reactance (baseline AX, 11.8; interquartile range, 9.9-23.4 cm H2O/L) and more concordant bronchoconstriction in central and peripheral airways; the other with high reactance (baseline AX, 46.7; interquartile range, 23.2-53.7 cm H2O/L) and discordant bronchoconstriction responses in central and peripheral airways. The high reactance asthma group included only women, and reported significantly more gastroesophageal reflux disease, worse chest tightness, more wheeze, and more asthma exacerbations than the low reactance group. INTERPRETATION: Peripheral airway reactivity detected by oscillometry is common in obese control subjects and obese people with asthma. There is a subgroup of obese asthma characterized by significant peripheral airway dysfunction by oscillometry out of proportion to spirometric airway dysfunction. This peripheral dysfunction represents clinically significant respiratory disease not readily assessed by spirometry.

Perinodular Parenchymal Features Improve Indeterminate Lung Nodule Classification.

BACKGROUND: Radiomics, defined as quantitative features extracted from images, provide a non-invasive means of assessing malignant versus benign pulmonary nodules. In this study, we evaluate the consistency with which perinodular radiomics extracted from low-dose computed tomography images serve to identify malignant pulmonary nodules. MATERIALS AND METHODS: Using the National Lung Screening Trial (NLST), we selected individuals with pulmonary nodules between 4mm to 20mm in diameter. Nodules were segmented to generate four distinct datasets; 1) a Tumor dataset containing tumor-specific features, 2) a 10 mm Band dataset containing parenchymal features between the segmented nodule boundary and 10mm out from the boundary, 3) a 15mm Band dataset, and 4) a Tumor Size dataset containing the maximum nodule diameter. Models to predict malignancy were constructed using support-vector machine (SVM), random forest (RF), and least absolute shrinkage and selection operator (LASSO) approaches. Ten-fold cross validation with 10 repetitions per fold was used to evaluate the performance of each approach applied to each dataset. RESULTS: With respect to the RF, the Tumor, 10mm Band, and 15mm Band datasets achieved areas under the receiver-operator curve (AUC) of 84.44%, 84.09%, and 81.57%, respectively. Significant differences in performance were observed between the Tumor and 15mm Band datasets (adj. p-value <0.001). However, when combining tumor-specific features with perinodular features, the 10mm Band + Tumor and 15mm Band + Tumor datasets (AUC 87.87% and 86.75%, respectively) performed significantly better than the Tumor Size dataset (66.76%) or the Tumor dataset. Similarly, the AUCs from the SVM and LASSO were 84.71% and 88.91%, respectively, for the 10mm Band + Tumor. CONCLUSIONS: The combined 10mm Band + Tumor dataset improved the differentiation between benign and malignant lung nodules compared to the Tumor datasets across all methodologies. This demonstrates that parenchymal features capture novel diagnostic information beyond that present in the nodule itself. (data agreement: NLST-163).