Airway fractal dimension predicts respiratory morbidity and mortality in COPD

Lung imaging in COPD and asthma

Chronic obstructive pulmonary disease (COPD) and asthma are common lung diseases with heterogeneous clinical presentations. Lung imaging allows evaluations of underlying pathophysiological changes and provides additional personalized approaches for disease management. This narrative review provides an overview of recent advances in chest imaging analysis using various modalities, such as computed tomography (CT), dynamic chest radiography, and magnetic resonance imaging (MRI). Visual CT assessment localizes emphysema subtypes and mucus plugging in the airways. Dedicated software quantifies the severity and spatial distribution of emphysema and the airway tree structure, including the central airway wall thickness, branch count and fractal dimension of the tree, and airway-to-lung size ratio. Nonrigid registration of inspiratory and expiratory CT scans quantifies small airway dysfunction, local volume changes and shape deformations in specific regions. Lung ventilation and diaphragm movement are also evaluated on dynamic chest radiography. Functional MRI detects regional oxygen transfer across the alveolus using inhaled oxygen and ventilation defects and gas diffusion into the alveolar-capillary barrier tissue and red blood cells using inhaled hyperpolarized 129Xe gas. These methods have the potential to determine local functional properties in the lungs that cannot be detected by lung function tests in patients with COPD and asthma. Further studies are needed to apply these technologies in clinical practice, particularly for early disease detection and tailor-made interventions, such as the efficient selection of patients likely to respond to biologics. Moreover, research should focus on the extension of healthy life expectancy in patients at higher risk and with established diseases.

Lower skeletal muscle density and airway structure on computed tomography in asthma

BACKGROUND

Lower skeletal muscle density may reflect muscle adiposity and metabolic dysregulation that potentially impair disease control and lung function independent of high body mass index (BMI) in patients with asthma.

OBJECTIVE

To investigate whether the lower density of pectoralis muscles (PMs) and erector spinae muscles (ESMs) on chest computed tomography was associated with airway structural changes in patients with asthma.

METHODS

Consecutive patients with asthma and healthy controls undergoing chest computed tomography were retrospectively analyzed. The ESM and PM density, areas of subcutaneous adipose tissue near the PM and epicardial adipose tissue, wall area percent of the airways, and airway fractal dimension (AFD) were quantified on computed tomography.

RESULTS

The study included 179 patients with asthma (52% women) and 88 controls (47% women). All the controls were 60 years old or younger. The PM and ESM density in female patients with asthma who were 60 years old or younger were significantly lower than those in controls after adjustment for BMI. In female patients with asthma at all ages, lower PM and ESM density (but not subcutaneous or epicardial adipose tissue area) was associated with greater wall area percent of the airways and lower AFD after adjusting for age, height, BMI, smoking status, blood eosinophil count, and oral corticosteroid use. The only association between ESM density and AFD was found in male patients with asthma.

CONCLUSION

Lower skeletal muscle density may be associated with airway wall thickening and less complexity of the airway luminal tree in female patients with asthma.

Quantification of Airway Structures by Persistent Homology

We propose two types of novel morphological metrics for quantifying the geometry of tubular structures on computed tomography (CT) images. We apply our metrics to identify irregularities in the airway of patients with chronic obstructive pulmonary disease (COPD) and demonstrate that they provide complementary information to the conventional metrics used to assess COPD, such as the tissue density distribution in lung parenchyma and the wall area ratio of the segmented airway. The three-dimensional shape of the airway and its abstraction as a rooted tree with the root at the trachea carina are automatically extracted from a lung CT volume, and the two metrics are computed based on a mathematical tool called persistent homology; treeH0 quantifies the distribution of branch lengths to assess the complexity of the tree-like structure and radialH0 quantifies the irregularities in the luminal radius along the airway. We show our metrics are associated with clinical outcomes.

3D airway geometry analysis of factors in airway navigation failure for lung nodules

BACKGROUND

This study aimed to quantitatively reveal contributing factors to airway navigation failure during radial probe endobronchial ultrasound (R-EBUS) by using geometric analysis in a three-dimensional (3D) space and to investigate the clinical feasibility of prediction models for airway navigation failure.

METHODS

We retrospectively reviewed patients who underwent R-EBUS between January 2017 and December 2018. Geometric quantification was analyzed using in-house software built with open-source python libraries including the Vascular Modeling Toolkit ( http://www.vmtk.org ), simple insight toolkit ( https://sitk.org ), and sci-kit image ( https://scikit-image.org ). We used a machine learning-based approach to explore the utility of these significant factors.

RESULTS

Of the 491 patients who were eligible for analysis (mean age, 65 years +/- 11 [standard deviation]; 274 men), the target lesion was reached in 434 and was not reached in 57. Twenty-seven patients in the failure group were matched with 27 patients in the success group based on propensity scores. Bifurcation angle at the target branch, the least diameter of the last section, and the curvature of the last section are the most significant and stable factors for airway navigation failure. The support vector machine can predict airway navigation failure with an average area under the curve of 0.803.

CONCLUSIONS

Geometric analysis in 3D space revealed that a large bifurcation angle and a narrow and tortuous structure of the closest bronchus from the lesion are associated with airway navigation failure during R-EBUS. The models developed using quantitative computer tomography scan imaging show the potential to predict airway navigation failure.

Expiratory Venous Volume and Arterial Tortuosity are Associated with Disease Severity and Mortality Risk in Patients with COPD: Results from COSYCONET

Purpose

The aim of this study was to evaluate the association between computed tomography (CT) quantitative pulmonary vessel morphology and lung function, disease severity, and mortality risk in patients with chronic obstructive pulmonary disease (COPD).

Patients and Methods

Participants of the prospective nationwide COSYCONET cohort study with paired inspiratory-expiratory CT were included. Fully automatic software, developed in-house, segmented arterial and venous pulmonary vessels and quantified volume and tortuosity on inspiratory and expiratory scans. The association between vessel volume normalised to lung volume and tortuosity versus lung function (forced expiratory volume in 1 sec [FEV1]), air trapping (residual volume to total lung capacity ratio [RV/TLC]), transfer factor for carbon monoxide (TLCO), disease severity in terms of Global Initiative for Chronic Obstructive Lung Disease (GOLD) group D, and mortality were analysed by linear, logistic or Cox proportional hazard regression.

Results

Complete data were available from 138 patients (39% female, mean age 65 years). FEV1, RV/TLC and TLCO, all as % predicted, were significantly (p < 0.05 each) associated with expiratory vessel characteristics, predominantly venous volume and arterial tortuosity. Associations with inspiratory vessel characteristics were absent or negligible. The patterns were similar for relationships between GOLD D and mortality with vessel characteristics. Expiratory venous volume was an independent predictor of mortality, in addition to FEV1.

Conclusion

By using automated software in patients with COPD, clinically relevant information on pulmonary vasculature can be extracted from expiratory CT scans (although not inspiratory scans); in particular, expiratory pulmonary venous volume predicted mortality.

Trial Registration

NCT01245933.

Computed tomography mucus plugs and airway tree structure in patients with chronic obstructive pulmonary disease: Associations with airflow limitation, health-related independence and mortality

BACKGROUND AND OBJECTIVE

Mucus plugs and underlying airway tree structure can affect airflow limitation and prognosis in patients with chronic obstructive pulmonary disease (COPD), but their relative roles are unclear. This study used two COPD cohorts to examine whether mucus plugs on computed tomography (CT) were associated with airflow limitation and clinical outcomes independent of other airway structural changes and emphysema.

METHODS

Based on visual CT assessment, patients with mucus plugs in 0, 1-2 and ≥3 lung segments were assigned to no-, low- and high-mucus groups. Loss of health-related independence and mortality were prospectively recorded for 3 and 10 years in the Kyoto-Himeji and Hokkaido cohorts, respectively. The percentages of the wall area of the central airways (WA%), total airway count (TAC) and emphysema were quantified on CT.

RESULTS

Of 199 and 96 patients in the Kyoto-Himeji and Hokkaido cohorts, 34% and 30%, respectively, had high mucus scores. In both cohorts, TAC was lower in the high-mucus group than in the no-mucus group, whereas their emphysema severity did not differ. High mucus score and low TAC were independently associated with airflow limitation after adjustment for WA% and emphysema. In multivariable models adjusted for WA% and emphysema, TAC, rather than mucus score, was associated with a greater rate of loss of independence, whereas high mucus score, rather than TAC, was associated with increased mortality.

CONCLUSION

Mucus plugs and lower airway branch count on CT had distinct roles in airflow limitation, health-related independence and mortality in patients with COPD.

Airway tree caliber heterogeneity and airflow obstruction among older adults

Smaller mean airway tree caliber is associated with airflow obstruction and chronic obstructive pulmonary disease (COPD). We investigated whether airway tree caliber heterogeneity was associated with airflow obstruction and COPD. Two community-based cohorts (MESA Lung, CanCOLD) and a longitudinal case-control study of COPD (SPIROMICS) performed spirometry and computed tomography measurements of airway lumen diameters at standard anatomical locations (trachea-to-subsegments) and total lung volume. Percent-predicted airway lumen diameters were calculated using sex-specific reference equations accounting for age, height, and lung volume. The association of airway tree caliber heterogeneity, quantified as the standard deviation (SD) of percent-predicted airway lumen diameters, with baseline forced expired volume in 1-second (FEV1), FEV1/forced vital capacity (FEV1/FVC) and COPD, as well as longitudinal spirometry, were assessed using regression models adjusted for age, sex, height, race-ethnicity, and mean airway tree caliber. Among 2,505 MESA Lung participants (means ± SD age: 69 ± 9 yr; 53% female, mean airway tree caliber: 99 ± 10% predicted, airway tree caliber heterogeneity: 14 ± 5%; median follow-up: 6.1 yr), participants in the highest quartile of airway tree caliber heterogeneity exhibited lower FEV1 (adjusted mean difference: -125 mL, 95%CI: -171,-79), lower FEV1/FVC (adjusted mean difference: -0.01, 95%CI: -0.02,-0.01), and higher odds of COPD (adjusted odds ratio: 1.42, 95%CI: 1.01-2.02) when compared with the lowest quartile, whereas longitudinal changes in FEV1 and FEV1/FVC did not differ significantly. Observations in CanCOLD and SPIROMICS were consistent. Among older adults, airway tree caliber heterogeneity was associated with airflow obstruction and COPD at baseline but was not associated with longitudinal changes in spirometry.NEW & NOTEWORTHY In this study, by leveraging two community-based samples and a case-control study of heavy smokers, we show that among older adults, airway tree caliber heterogeneity quantified by CT is associated with airflow obstruction and COPD independent of age, sex, height, race-ethnicity, and dysanapsis. These observations suggest that airway tree caliber heterogeneity is a structural trait associated with low baseline lung function and normal decline trajectory that is relevant to COPD.

A reference equation for lung volume on computed tomography in Japanese middle-aged and elderly adults

BACKGROUND

Effective use of lung volume data measured on computed tomography (CT) requires reference values for specific populations. This study examined whether an equation previously generated for multiple ethnic groups in the United States, including Asians predominantly composed of Chinese people, in the Multi-Ethnic Study of Atherosclerosis (MESA) could be used for Japanese people and, if necessary, to optimize this equation. Moreover, the equation was used to characterize patients with chronic obstructive pulmonary disease (COPD) and lung hyperexpansion.

METHODS

This study included a lung cancer screening CT cohort of asymptomatic never smokers aged ≥40 years from two institutions (n = 364 and 419) to validate and optimize the MESA equation and a COPD cohort (n = 199) to test its applicability.

RESULTS

In all asymptomatic never smokers, the variance explained by the predicted values (R2) based on the original MESA equation was 0.60. The original equation was optimized to minimize the root mean squared error (RMSE) by adjusting the scaling factor but not the age, sex, height, or body mass index terms of the equation. The RMSE changed from 714 ml in the original equation to 637 ml in the optimized equation. In the COPD cohort, lung hyperexpansion, defined based on the 95th percentile of the ratio of measured lung volume to predicted lung volume in never smokers (122 %), was observed in 60 (30 %) patients and was associated with centrilobular emphysema and air trapping on inspiratory/expiratory CT.

CONCLUSIONS

The MESA equation was optimized for Japanese middle-aged and elderly adults.

Multi-site, Multi-domain Airway Tree Modeling

Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach of pulmonary airway segmentation that is closer to the limit of image resolution. Since EXACT'09 pulmonary airway segmentation, limited effort has been directed to the quantitative comparison of newly emerged algorithms driven by the maturity of deep learning based approaches and extensive clinical efforts for resolving finer details of distal airways for early intervention of pulmonary diseases. Thus far, public annotated datasets are extremely limited, hindering the development of data-driven methods and detailed performance evaluation of new algorithms. To provide a benchmark for the medical imaging community, we organized the Multi-site, Multi-domain Airway Tree Modeling (ATM'22), which was held as an official challenge event during the MICCAI 2022 conference. ATM'22 provides large-scale CT scans with detailed pulmonary airway annotation, including 500 CT scans (300 for training, 50 for validation, and 150 for testing). The dataset was collected from different sites and it further included a portion of noisy COVID-19 CTs with ground-glass opacity and consolidation. Twenty-three teams participated in the entire phase of the challenge and the algorithms for the top ten teams are reviewed in this paper. Both quantitative and qualitative results revealed that deep learning models embedded with the topological continuity enhancement achieved superior performance in general. ATM'22 challenge holds as an open-call design, the training data and the gold standard evaluation are available upon successful registration via its homepage (https://atm22.grand-challenge.org/).

Phenotypes, Etiotypes, and Endotypes of Exacerbations of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease is a major health problem with a high prevalence, a rising incidence, and substantial morbidity and mortality. Its course is punctuated by acute episodes of increased respiratory symptoms, termed exacerbations of chronic obstructive pulmonary disease (ECOPD). ECOPD are important events in the natural history of the disease, as they are associated with lung function decline and prolonged negative effects on quality of life. The present-day therapy for ECOPD with short courses of antibiotics and steroids and escalation of bronchodilators has resulted in only modest improvements in outcomes. Recent data indicate that ECOPD are heterogeneous, raising the need to identify distinct etioendophenotypes, incorporating traits of the acute event and of patients who experience recurrent events, to develop novel and targeted therapies. These characterizations can provide a complete clinical picture, the severity of which will dictate acute pharmacological treatment, and may also indicate whether a change in maintenance therapy is needed to reduce the risk of future exacerbations. In this review we discuss the latest knowledge of ECOPD types on the basis of clinical presentation, etiology, natural history, frequency, severity, and biomarkers in an attempt to characterize these events.

Quantitative CT Scan Imaging of the Airways for Diagnosis and Management of Lung Disease

CT scan imaging provides high-resolution images of the lungs in patients with chronic respiratory diseases. Extensive research over the last several decades has focused on developing novel quantitative CT scan airway measurements that reflect abnormal airway structure. Despite many observational studies demonstrating that associations between CT scan airway measurements and clinically important outcomes such as morbidity, mortality, and lung function decline, few quantitative CT scan measurements are applied in clinical practice. This article provides an overview of the relevant methodologic considerations for implementing quantitative CT scan airway analyses and provides a review of the scientific literature involving quantitative CT scan airway measurements used in clinical or randomized trials and observational studies of humans. We also discuss emerging evidence for the clinical usefulness of quantitative CT scan imaging of the airways and discuss what is required to bridge the gap between research and clinical application. CT scan airway measurements continue to improve our understanding of disease pathophysiologic features, diagnosis, and outcomes. However, a literature review revealed a need for studies evaluating clinical benefit when quantitative CT scan imaging is applied in the clinical setting. Technical standards for quantitative CT scan imaging of the airways and high-quality evidence of clinical benefit from management guided by quantitative CT scan imaging of the airways are required.

Lung Imaging in COPD Part 1: Clinical Usefulness

COPD is a condition characterized by chronic airflow obstruction resulting from chronic bronchitis, emphysema, or both. The clinical picture is usually progressive with respiratory symptoms such as exertional dyspnea and chronic cough. For many years, spirometry was used to establish a diagnosis of COPD. Recent advancements in imaging techniques allow quantitative and qualitative analysis of the lung parenchyma as well as related airways and vascular and extrapulmonary manifestations of COPD. These imaging methods may allow prognostication of disease and shed light on the efficacy of pharmacologic and nonpharmacologic interventions. This is the first of a two-part series of articles on the usefulness of imaging methods in COPD, and it highlights useful information that clinicians can obtain from these imaging studies to make more accurate diagnosis and therapeutic decisions.

Radiomics for Improved Detection of Chronic Obstructive Pulmonary Disease in Low-Dose and Standard-Dose Chest CT Scans

Background Approximately half of adults with chronic obstructive pulmonary disease (COPD) remain undiagnosed. Chest CT scans are frequently acquired in clinical practice and present an opportunity to detect COPD. Purpose To assess the performance of radiomics features in COPD diagnosis using standard-dose and low-dose CT models. Materials and Methods This secondary analysis included participants enrolled in the Genetic Epidemiology of COPD, or COPDGene, study at baseline (visit 1) and 10 years after baseline (visit 3). COPD was defined by a forced expiratory volume in the 1st second of expiration to forced vital capacity ratio less than 0.70 at spirometry. The performance of demographics, CT emphysema percentage, radiomics features, and a combined feature set derived from inspiratory CT alone was evaluated. CatBoost (Yandex), a gradient boosting algorithm, was used to perform two classification experiments to detect COPD; the two models were trained and tested on standard-dose CT data from visit 1 (model I) and low-dose CT data from visit 3 (model II). Classification performance of the models was evaluated using area under the receiver operating characteristic curve (AUC) and precision-recall curve analysis. Results A total of 8878 participants (mean age, 57 years ± 9 [SD]; 4180 female, 4698 male) were evaluated. Radiomics features in model I achieved an AUC of 0.90 (95% CI: 0.88, 0.91) in the standard-dose CT test cohort versus demographics (AUC, 0.73; 95% CI: 0.71, 0.76; P < .001), emphysema percentage (AUC, 0.82; 95% CI 0.80, 0.84; P < .001), and combined features (AUC, 0.90; 95% CI: 0.89, 0.92; P = .16). Model II, trained on low-dose CT scans, achieved an AUC of 0.87 (95% CI: 0.83, 0.91) on the 20% held-out test set for radiomics features compared with demographics (AUC, 0.70; 95% CI: 0.64, 0.75; P = .001), emphysema percentage (AUC, 0.74; 95% CI: 0.69, 0.79; P = .002), and combined features (AUC, 0.88; 95% CI: 0.85, 0.92; P = .32). Density and texture features were the majority of the top 10 features in the standard-dose model, whereas shape features of lungs and airways were significant contributors in the low-dose CT model. Conclusion A combination of features representing parenchymal texture and lung and airway shape on inspiratory CT scans can be used to accurately detect COPD. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Vliegenthart in this issue.

Association of age with computed tomography airway tree morphology in male and female never smokers without lung disease history

BACKGROUND

Sex and aging may affect the airway tree structure in patients with airway diseases and even healthy subjects. Using chest computed tomography (CT), this study sought to determine whether age is associated with airway morphological features differently in healthy males and females.

METHODS

This retrospective cross-sectional study consecutively incorporated lung cancer screening CT data of asymptomatic never smokers (n = 431) without lung disease history. Luminal areas were measured at the trachea, main bronchi, bronchus intermedius, segmental and subsegmental bronchus, and the ratio of their geometric mean to total lung volume (airway-to-lung size ratio, ALR) was determined. Airway fractal dimension (AFD) and total airway count (TAC) were calculated for the segmented airway tree resolved on CT.

RESULTS

The lumen areas of the trachea, main bronchi, segmental and subsegmental airways, AFD and TAC visible on CT were smaller in females (n = 220) than in males (n = 211) after adjusting for age, height, and body mass index, while ALR or count of the 1st to 5th generation airways did not differ. Furthermore, in males but not in females, older age was associated with larger lumen sizes of the main bronchi, segmental and subsegmental airways, and ALR. In contrast, neither male nor female had any associations between age and AFD or TAC on CT.

CONCLUSION

Older age was associated with larger lumen size of the relatively central airways and ALR exclusively in males. Aging may have a more profound effect on airway lumen tree caliber in males than in females.

Physiological impacts of computed tomography airway dysanapsis, fractal dimension, and branch count in asymptomatic never smokers

Dysanapsis, a mismatch between airway tree caliber and lung size, contributes to a large variation in lung function on spirometry in healthy subjects. However, it remains unclear whether other morphological features of the airway tree could be associated with the variation in lung function independent of dysanapsis. This study used lung cancer screening chest computed tomography (CT) and spirometry data from asymptomatic never smokers. Dysanapsis and the complexity of airway tree geometry were quantified on CT by measuring airway to lung ratio (ALR) and airway fractal dimension (AFD). Moreover, total airway count (TAC), ratio of airway luminal surface area to volume (SA/V), longitudinal tapering and irregularity of the radius of the internal lumen from the central to peripheral airways (Tapering index and Irregularity index) were quantified. In 431 asymptomatic never smokers without a history of lung diseases, lower ALR was associated with lower forced expiratory volume in 1 s (FEV₁) and FEV₁/forced vital capacity (FEV₁/FVC). The associations of ALR with AFD and TAC (r = 0.41 and 0.13) were weaker than the association between TAC and AFD (r = 0.64). In multivariable models adjusted for age, sex, height, and mean lung density, lower AFD and TAC were associated with lower FEV₁ and FEV₁/FVC independent of ALR, whereas SA/V and Tapering index were not. These results suggest that the smaller airway tree relative to a given lung size and the lower complexity of airway tree shape, including lower branch count, are independently associated with lower lung function in healthy subjects.NEW & NOTEWORTHY This study showed that fractal dimension and total airway count of the airway tree on computed tomography are associated with lung function on spirometry independent of a smaller airway for a given lung size (dysanapsis) in asymptomatic never smokers without a history of lung diseases. In addition to dysanapsis, the morphometric complexity of the airway tree and the airway branch count may cause a substantial variation of lung function in these subjects.

Human treelike tubular structure segmentation: A comprehensive review and future perspectives

Various structures in human physiology follow a treelike morphology, which often expresses complexity at very fine scales. Examples of such structures are intrathoracic airways, retinal blood vessels, and hepatic blood vessels. Large collections of 2D and 3D images have been made available by medical imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), Optical coherence tomography (OCT) and ultrasound in which the spatial arrangement can be observed. Segmentation of these structures in medical imaging is of great importance since the analysis of the structure provides insights into disease diagnosis, treatment planning, and prognosis. Manually labelling extensive data by radiologists is often time-consuming and error-prone. As a result, automated or semi-automated computational models have become a popular research field of medical imaging in the past two decades, and many have been developed to date. In this survey, we aim to provide a comprehensive review of currently publicly available datasets, segmentation algorithms, and evaluation metrics. In addition, current challenges and future research directions are discussed.

Sex Differences in Airways at Chest CT: Results from the COPDGene Cohort

Background The prevalence of chronic obstructive pulmonary disease (COPD) in women is fast approaching that in men, and women experience greater symptom burden. Although sex differences in emphysema have been reported, differences in airways have not been systematically characterized. Purpose To evaluate whether structural differences in airways may underlie some of the sex differences in COPD prevalence and clinical outcomes. Materials and Methods In a secondary analyses of a multicenter study of never-, current-, and former-smokers enrolled from January 2008 to June 2011 and followed up longitudinally until November 2020, airway disease on CT images was quantified using seven metrics: airway wall thickness, wall area percent, and square root of the wall thickness of a hypothetical airway with internal perimeter of 10 mm (referred to as Pi10) for airway wall; and lumen diameter, airway volume, total airway count, and airway fractal dimension for airway lumen. Least-squares mean values for each airway metric were calculated and adjusted for age, height, ethnicity, body mass index, pack-years of smoking, current smoking status, total lung capacity, display field of view, and scanner type. In ever-smokers, associations were tested between each airway metric and postbronchodilator forced expiratory volume in 1 second (FEV1)-to-forced vital capacity (FVC) ratio, modified Medical Research Council dyspnea scale, St George's Respiratory Questionnaire score, and 6-minute walk distance. Multivariable Cox proportional hazards models were created to evaluate the sex-specific association between each airway metric and mortality. Results In never-smokers (n = 420), men had thicker airway walls than women as quantified on CT images for segmental airway wall area percentage (least-squares mean, 47.68 ± 0.61 [standard error] vs 45.78 ± 0.55; difference, -1.90; P = .02), whereas airway lumen dimensions were lower in women than men after accounting for height and total lung capacity (segmental lumen diameter, 8.05 mm ± 0.14 vs 9.05 mm ± 0.16; difference, -1.00 mm; P < .001). In ever-smokers (n = 9363), men had greater segmental airway wall area percentage (least-squares mean, 52.19 ± 0.16 vs 48.89 ± 0.18; difference, -3.30; P < .001), whereas women had narrower segmental lumen diameter (7.80 mm ± 0.05 vs 8.69 mm ± 0.04; difference, -0.89; P < .001). A unit change in each of the airway metrics (higher wall or lower lumen measure) resulted in lower FEV1-to-FVC ratio, more dyspnea, poorer respiratory quality of life, lower 6-minute walk distance, and worse survival in women compared with men (all P < .01). Conclusion Airway lumen sizes quantified at chest CT were smaller in women than in men after accounting for height and lung size, and these lower baseline values in women conferred lower reserves against respiratory morbidity and mortality for equivalent changes compared with men. © RSNA, 2022 Online supplemental material is available for this article.

An Entropy-Based Measure of Complexity: An Application in Lung-Damage

The computed tomography (CT) chest is a tool for diagnostic tests and the early evaluation of lung infections, pulmonary interstitial damage, and complications caused by common pneumonia and COVID-19. Additionally, computer-aided diagnostic systems and methods based on entropy, fractality, and deep learning have been implemented to analyse lung CT images. This article aims to introduce an Entropy-based Measure of Complexity (EMC). In addition, derived from EMC, a Lung Damage Measure (LDM) is introduced to show a medical application. CT scans of 486 healthy subjects, 263 diagnosed with COVID-19, and 329 with pneumonia were analysed using the LDM. The statistical analysis shows a significant difference in LDM between healthy subjects and those suffering from COVID-19 and common pneumonia. The LDM of common pneumonia was the highest, followed by COVID-19 and healthy subjects. Furthermore, LDM increased as much as clinical classification and CO-RADS scores. Thus, LDM is a measure that could be used to determine or confirm the scored severity. On the other hand, the d-summable information model best fits the information obtained by the covering of the CT; thus, it can be the cornerstone for formulating a fractional LDM.

Further evidence for association of YKL-40 with severe asthma airway remodeling

BACKGROUND

The chitinase-like protein YKL-40 is associated with airflow limitation on spirometry and airway remodeling in patients with asthma. It remains unclear whether YKL-40 is associated with morphologic changes in the airways and parenchyma or with future progression of airflow limitation in severe asthma.

OBJECTIVE

To evaluate the association of circulating YKL-40 levels with morphologic changes in the airways and parenchyma and with longitudinal progression of airflow limitation.

METHODS

The patients were participants in the Hokkaido Severe Asthma Cohort Study (n = 127), including smokers. This study consisted of 2 parts. In analysis 1, we analyzed associations between circulating YKL-40 levels and several asthma-related indices, including computed tomography-derived indices of proximal wall area percentage, the complexity of the airways (airway fractal dimension), and the parenchyma (exponent D) cross-sectionally (n = 97). In analysis 2, we evaluated the impact of circulating YKL-40 levels on forced expiratory volume in 1 second (FEV₁) decline longitudinally for a 5-year follow-up (n = 103).

RESULTS

Circulating YKL-40 levels were significantly associated with proximal wall area percentage and airway fractal dimension (r = 0.25, P = .01; r = -0.22, P = .04, respectively), but not with exponent D. The mean annual change in FEV₁ was -33.7 (± 23.3) mL/y, and the circulating YKL-40 level was a significant independent factor associated with annual FEV₁ decline (β = -0.24, P = .02), even after controlling for exponent D (β = -0.26, P = .01).

CONCLUSION

These results provide further evidence for the association of YKL-40 with the pathogenesis of airway remodeling in severe asthma.

Bronchial wall parameters on CT in healthy never-smoking, smoking, COPD, and asthma populations: a systematic review and meta-analysis

Objective

Research on computed tomography (CT) bronchial parameter measurements shows that there are conflicting results on the values for bronchial parameters in the never-smoking, smoking, asthma, and chronic obstructive pulmonary disease (COPD) populations. This review assesses the current CT methods for obtaining bronchial wall parameters and their comparison between populations.

Methods

A systematic review of MEDLINE and Embase was conducted following PRISMA guidelines (last search date 25th October 2021). Methodology data was collected and summarised. Values of percentage wall area (WA%), wall thickness (WT), summary airway measure (Pi10), and luminal area (Ai) were pooled and compared between populations.

Results

A total of 169 articles were included for methodologic review; 66 of these were included for meta-analysis. Most measurements were obtained from multiplanar reconstructions of segmented airways (93 of 169 articles), using various tools and algorithms; third generation airways in the upper and lower lobes were most frequently studied. COPD (12,746) and smoking (15,092) populations were largest across studies and mostly consisted of men (median 64.4%, IQR 61.5 – 66.1%). There were significant differences between populations; the largest WA% was found in COPD (mean SD 62.93 ± 7.41%, n = 6,045), and the asthma population had the largest Pi10 (4.03 ± 0.27 mm, n = 442). Ai normalised to body surface area (Ai/BSA) (12.46 ± 4 mm², n = 134) was largest in the never-smoking population.

Conclusions

Studies on CT-derived bronchial parameter measurements are heterogenous in methodology and population, resulting in challenges to compare outcomes between studies. Significant differences between populations exist for several parameters, most notably in the wall area percentage; however, there is a large overlap in their ranges.

Key Points

• Diverse methodology in measuring airways contributes to overlap in ranges of bronchial parameters among the never-smoking, smoking, COPD, and asthma populations.

• The combined number of never-smoking participants in studies is low, limiting insight into this population and the impact of participant characteristics on bronchial parameters.

• Wall area percent of the right upper lobe apical segment is the most studied (87 articles) and differentiates all except smoking vs asthma populations.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00330-022-08600-1.

Treatment Trials in Young Patients with Chronic Obstructive Pulmonary Disease and Pre-Chronic Obstructive Pulmonary Disease Patients: Time to Move Forward

Chronic obstructive pulmonary disease (COPD) is the end result of a series of dynamic and cumulative gene-environment interactions over a lifetime. The evolving understanding of COPD biology provides novel opportunities for prevention, early diagnosis, and intervention. To advance these concepts, we propose therapeutic trials in two major groups of subjects: "young" individuals with COPD and those with pre-COPD. Given that lungs grow to about 20 years of age and begin to age at approximately 50 years, we consider "young" patients with COPD those patients in the age range of 20-50 years. Pre-COPD relates to individuals of any age who have respiratory symptoms with or without structural and/or functional abnormalities, in the absence of airflow limitation, and who may develop persistent airflow limitation over time. We exclude from the current discussion infants and adolescents because of their unique physiological context and COPD in older adults given their representation in prior randomized controlled trials (RCTs). We highlight the need of RCTs focused on COPD in young patients or pre-COPD to reduce disease progression, providing innovative approaches to identifying and engaging potential study subjects. We detail approaches to RCT design, including potential outcomes such as lung function, patient-reported outcomes, exacerbations, lung imaging, mortality, and composite endpoints. We critically review study design components such as statistical powering and analysis, duration of study treatment, and formats to trial structure, including platform, basket, and umbrella trials. We provide a call to action for treatment RCTs in 1) young adults with COPD and 2) those with pre-COPD at any age.

Recent advances in airway imaging using micro-computed tomography and computed tomography for chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a complex lung disease characterized by a combination of airway disease and emphysema. Emphysema is classified as centrilobular emphysema (CLE), paraseptal emphysema (PSE), or panlobular emphysema (PLE), and airway disease extends from the respiratory, terminal, and preterminal bronchioles to the central segmental airways. Although clinical computed tomography (CT) cannot be used to visualize the small airways, micro-CT has shown that terminal bronchiole disease is more severe in CLE than in PSE and PLE, and micro-CT findings suggest that the loss and luminal narrowing of terminal bronchioles is an early pathological change in CLE. Furthermore, the introduction of ultra-high-resolution CT has enabled direct evaluation of the proximal small (1 to 2-mm diameter) airways, and new CT analytical methods have enabled estimation of small airway disease and prediction of future COPD onset and lung function decline in smokers with and without COPD. This review discusses the literature on micro-CT and the technical advancements in clinical CT analysis for COPD. Hopefully, novel micro-CT findings will improve our understanding of the distinct pathogeneses of the emphysema subtypes to enable exploration of new therapeutic targets, and sophisticated CT imaging methods will be integrated into clinical practice to achieve more personalized management.

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

ABSTRACT

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

Parenchymal destruction in asthma: Fixed airflow obstruction and lung function trajectory

BACKGROUND

Fixed airflow obstruction (FAO) in asthma, particularly in nonsmokers, is generally believed to be caused by airway remodeling. However, parenchymal destruction may also contribute to FAO and longitudinal decline in forced expiratory volume in 1 second (FEV₁).

OBJECTIVES

To evaluate parenchymal destruction, we used emphysema indices, exponent D, and low-attenuation area percentage (LAA%) on computed tomography (CT), and test whether the parenchymal destruction and airway disease are independently associated with FAO and FEV₁ decline in both smoking and nonsmoking asthma.

METHODS

Exponent D, LAA%, wall area percentage at segmental airways, and airway fractal dimension (AFD) in those with asthma were measured on inspiratory CT and compared to those in patients with chronic obstructive pulmonary disease (COPD).

RESULTS

Exponent D was lower and LAA% was higher in COPD (n = 42) and asthma with FAO (n = 101) than in asthma without FAO (n = 88). The decreased exponent D and increased LAA% were associated with FAO regardless of smoking status or asthma severity. In multivariable analysis, decreased exponent D and increased LAA% were associated with an increased odds ratio of FAO and decreased FEV₁, irrespective of wall area percentage and airway fractal dimension. Moreover, decreased exponent D affected the longitudinal decline in FEV₁ in those with severe asthma, independent of smoking status.

CONCLUSIONS

Patients with asthma with FAO showed parenchymal destruction regardless of smoking status and asthma severity. Parenchymal destruction was associated with an accelerated FEV₁ decline, suggesting the involvements of both airway and parenchyma in the pathophysiology of a subgroup of asthma.

Adaptive Capacities and Complexity of Heart Rate Variability in Patients With Chronic Obstructive Pulmonary Disease Throughout Pulmonary Rehabilitation

Introduction

The complexity of bio-signals, like R-R intervals, is considered a reflection of the organism's capacity to adapt. However, this association still remains to be consolidated. We investigated whether the complexity of R-R intervals at rest and during perturbation [6-minute walking test (6MWT)], yielded information regarding adaptive capacities in Chronic Obstructive Pulmonary Disease (COPD) patients during pulmonary rehabilitation (PR).

Methods

In total, 23 COPD patients (64 ± 8 years, with forced expiratory volume in 1 s of 55 ± 19% predicted) were tested three times at the start (T1), middle (T2), and end (T3) of 4 weeks PR. Each time, R-R intervals were measured at rest and during 6MWT. The complexity of R-R intervals was assessed by evenly spaced Detrended Fluctuations Analysis and evaluated by the fractal exponent α and deviation from maximal complexity |1-α|.

Results

The 6MWT distance was significantly increased at T2 and T3 compared to T1. Neither α nor |1-α| at rest and during perturbation significantly changed throughout PR, nor were they consistently associated with 6MWT distances at each time. Throughout the PR program, complexity during the 6MWT was significantly lower compared to the rest. The level of α during 6MWT at T1 was positively correlated with the improvement of the 6MWT distance throughout the PR program.

Discussion

Reduced complexity in COPD patients during acute perturbation at the beginning of PR supports a decreased improvement of the 6MWT distance throughout PR. This result seems consistent with the notion that the complexity reflects the patients' adaptive capacities and could therefore become a clinical indicator in an applied perspective.

Structural airway imaging metrics are differentially associated with persistent chronic bronchitis

BACKGROUND

Chronic bronchitis (CB) is strongly associated with cigarette smoking, but not all smokers develop CB. We aimed to evaluate whether measures of structural airway disease on CT are differentially associated with CB.

METHODS

In smokers between ages 45 and 80 years, and with Global Initiative for Obstructive Lung Disease stages 0-4, CB was defined by the classic definition. Airway disease on CT was quantified by (i) wall area percent (WA%) of segmental airways; (ii) Pi10, the square root of the wall area of a hypothetical airway with 10 mm internal perimeter; (iii) total airway count (TAC) and (iv) airway fractal dimension (AFD), a measure of the complex branching pattern and remodelling of airways. CB was also assessed at the 5-year follow-up visit.

MEASUREMENTS AND MAIN RESULTS

Of 8917 participants, 1734 (19.4%) had CB at baseline. Airway measures were significantly worse in those with CB compared with those without CB: WA% 54.5 (8.8) versus 49.8 (8.3); Pi10 2.58 (0.67) versus 2.28 (0.59) mm; TAC 156.7 (81.6) versus 177.8 (91.1); AFD 1.477 (0.091) versus 1.497 (0.092) (all p<0.001). On follow-up of 5517 participants at 5 years, 399 (7.2%) had persistent CB. With adjustment for between-visits changes in smoking status and lung function, greater WA% and Pi10 were associated with significantly associated with persistent CB, adjusted OR per SD change 1.75, 95% CI 1.56 to 1.97; p<0.001 and 1.66, 95% CI 1.42 to 1.86; p<0.001, respectively. Higher AFD and TAC were associated with significantly lower odds of persistent CB, adjusted OR per SD change 0.76, 95% CI 0.67 to 0.86; p<0.001 and 0.69, 95% CI 0.60 to 0.80; p<0.001, respectively.

CONCLUSIONS

Higher baseline AFD and TAC are associated with a lower risk of persistent CB, irrespective of changes in smoking status, suggesting preserved airway structure can confer a reserve against CB.

Computed Tomography-based Airway Surface Area-to-Volume Ratio for Phenotyping Airway Remodeling in Chronic Obstructive Pulmonary Disease

Rationale: Airway remodeling in chronic obstructive pulmonary disease (COPD) is due to luminal narrowing and/or loss of airways. Existing computed tomographic metrics of airway disease reflect only components of these processes. With progressive airway narrowing, the ratio of the airway luminal surface area to volume (SA/V) should increase, and with predominant airway loss, SA/V should decrease.Objectives: To phenotype airway remodeling in COPD.Methods: We analyzed the airway trees of 4,325 subjects with COPD Global Initiative for Chronic Obstructive Lung Disease stages 0 to 4 and 73 nonsmokers enrolled in the multicenter COPDGene (Genetic Epidemiology of COPD) cohort. Surface area and volume measurements were estimated for the subtracheal airway tree to derive SA/V. We performed multivariable regression analyses to test associations between SA/V and lung function, 6-minute-walk distance, St. George's Respiratory Questionnaire, change in FEV1, and mortality, adjusting for demographics, total airway count, airway wall thickness, and emphysema. On the basis of the change in SA/V over 5 years, we categorized subjects into predominant airway narrowing [positive ∆(SA/V) more than 0] and predominant airway loss [negative ∆(SA/V) less than 0] and compared survival between the two groups.Measurements and Main Results: Airway SA/V was independently associated with FEV1/FVC (β = 0.12; 95% confidence interval [CI], 0.09-0.14; P < 0.001) and FEV1% predicted (β = 20.10; 95% CI, 15.13-25.08; P < 0.001). Airway SA/V was also independently associated with 6-minute-walk distance, respiratory quality of life, and lung function decline. Compared with subjects with predominant airway narrowing (n = 2,914; 66.3%), those with predominant airway loss (n = 1,484; 33.7%) had worse survival (adjusted hazard ratio for all-cause mortality = 1.58; 95% CI, 1.18-2.13; P = 0.002).Conclusions: Computed tomography-based airway SA/V is an imaging biomarker of airway remodeling and provides differential information on predominant airway narrowing and loss in COPD. SA/V is associated with respiratory morbidity, lung function decline, and survival.

Fractal Analysis of Lung Structure in Chronic Obstructive Pulmonary Disease

Chest CT is often used for localizing and quantitating pathologies associated with chronic obstructive pulmonary disease (COPD). While simple measurements of areas and volumes of emphysema and airway structure are common, these methods do not capture the structural complexity of the COPD lung. Since the concept of fractals has been successfully applied to evaluate complexity of the lung, this review is aimed at describing the fractal properties of airway disease, emphysema, and vascular abnormalities in COPD. An object forms a fractal if it exhibits the property of self-similarity at different length scales of evaluations. This fractal property is governed by power-law functions characterized by the fractal dimension (FD). Power-laws can also manifest in other statistical descriptors of structure such as the size distribution of emphysema clusters characterized by the power-law exponent D. Although D is not the same as FD of emphysematous clusters, it is a useful index to characterize the spatial pattern of disease progression and predict clinical outcomes in patients with COPD. The FD of the airway tree shape and the D of the size distribution of airway branches have been proposed indexes of structural assessment and clinical predictions. Simulations are also useful to understand the mechanism of disease progression. Therefore, the power-law and fractal analysis of the parenchyma and airways, especially when combined with computer simulations, could lead to a better understanding of the structural alterations during the progression of COPD and help identify subjects at a high risk of severe COPD.

Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease

BACKGROUNDCurrently recommended traditional spirometry outputs do not reflect the relative contributions of emphysema and airway disease to airflow obstruction. We hypothesized that machine-learning algorithms can be trained on spirometry data to identify these structural phenotypes.METHODSParticipants enrolled in a large multicenter study (COPDGene) were included. The data points from expiratory flow-volume curves were trained using a deep-learning model to predict structural phenotypes of chronic obstructive pulmonary disease (COPD) on CT, and results were compared with traditional spirometry metrics and an optimized random forest classifier. Area under the receiver operating characteristic curve (AUC) and weighted F-score were used to measure the discriminative accuracy of a fully convolutional neural network, random forest, and traditional spirometry metrics to phenotype CT as normal, emphysema-predominant (>5% emphysema), airway-predominant (Pi10 > median), and mixed phenotypes. Similar comparisons were made for the detection of functional small airway disease phenotype (>20% on parametric response mapping).RESULTSAmong 8980 individuals, the neural network was more accurate in discriminating predominant emphysema/airway phenotypes (AUC 0.80, 95%CI 0.79-0.81) compared with traditional measures of spirometry, FEV1/FVC (AUC 0.71, 95%CI 0.69-0.71), FEV1% predicted (AUC 0.70, 95%CI 0.68-0.71), and random forest classifier (AUC 0.78, 95%CI 0.77-0.79). The neural network was also more accurate in discriminating predominant emphysema/small airway phenotypes (AUC 0.91, 95%CI 0.90-0.92) compared with FEV1/FVC (AUC 0.80, 95%CI 0.78-0.82), FEV1% predicted (AUC 0.83, 95%CI 0.80-0.84), and with comparable accuracy with random forest classifier (AUC 0.90, 95%CI 0.88-0.91).CONCLUSIONSStructural phenotypes of COPD can be identified from spirometry using deep-learning and machine-learning approaches, demonstrating their potential to identify individuals for targeted therapies.TRIAL REGISTRATIONClinicalTrials.gov NCT00608764.FUNDINGThis study was supported by NIH grants K23 HL133438 and R21EB027891 and an American Thoracic Foundation 2018 Unrestricted Research Grant. The COPDGene study is supported by NIH grants NHLBI U01 HL089897 and U01 HL089856. The COPDGene study (NCT00608764) is also supported by the COPD Foundation through contributions made to an Industry Advisory Committee comprising AstraZeneca, Boehringer-Ingelheim, GlaxoSmithKline, Novartis, and Sunovion.

Fractal analysis of concurrently prepared latex rubber casts of the bronchial and vascular systems of the human lung

Fractal geometry (FG) is a branch of mathematics that instructively characterizes structural complexity. Branched structures are ubiquitous in both the physical and the biological realms. Fractility has therefore been termed nature's design. The fractal properties of the bronchial (airway) system, the pulmonary artery and the pulmonary vein of the human lung generates large respiratory surface area that is crammed in the lung. Also, it permits the inhaled air to intimately approximate the pulmonary capillary blood across a very thin blood-gas barrier through which gas exchange to occur by diffusion. Here, the bronchial (airway) and vascular systems were simultaneously cast with latex rubber. After corrosion, the bronchial and vascular system casts were physically separated and cleared to expose the branches. The morphogenetic (Weibel's) ordering method was used to categorize the branches on which the diameters and the lengths, as well as the angles of bifurcation, were measured. The fractal dimensions (DF) were determined by plotting the total branch measurements against the mean branch diameters on double logarithmic coordinates (axes). The diameter-determined DF values were 2.714 for the bronchial system, 2.882 for the pulmonary artery and 2.334 for the pulmonary vein while the respective values from lengths were 3.098, 3.916 and 4.041. The diameters yielded DF values that were consistent with the properties of fractal structures (i.e. self-similarity and space-filling). The data obtained here compellingly suggest that the design of the bronchial system, the pulmonary artery and the pulmonary vein of the human lung functionally comply with the Hess-Murray law or 'the principle of minimum work'.

An index of the fractal characteristic of an airway tree is associated with airflow limitations and future body mass index reduction in COPD patients

Disorders of the fractality of an airway tree and a vessel tree have been studied in pulmonary diseases. Here we successfully applied Mishima's D to the bronchial minimal inner cross-sectional area (iCSA) measured in multidetector computed tomography (MDCT) images of chronic obstructive pulmonary disease (COPD) and non-COPD smokers (n = 162), by defining D in the following formula: logN(≥X) = -D × logX + c, where X is a certain iCSA value, N(≥X) is the number of airway branches having iCSA greater than or equal to X, and c is a constant. Mathematically, this D of iCSA was associated with the expected reduction ratio of iCSA at bifurcations, which can be estimated by 2^-1/D. This D of iCSA also correlated weakly with the box-counting fractal dimension and Weibel's reduction ratio over airway generations, which indicated that the airway tree was not a perfect fractal object and that the branch bifurcation was asymmetric. The D of iCSA showed positive correlations with lung function measurements of airflow limitation in study participants. In addition, D of iCSA representing the periphery showed an association with future body mass index reduction, most likely as an indicator of energy efficacy for breathing as predicted by Hess-Murray's law. D of iCSA may be helpful to understanding the pathogenesis of obstructive lung diseases.NEW & NOTEWORTHY An airway tree is a fractal object. We showed that the distribution of minimal inner cross-sectional area (iCSA) of airway branches can be expressed by a fractal index, D, of minimal iCSA. This D was correlated with airflow limitation and future body mass index reduction in chronic obstructive pulmonary disease patients, as predicted by Hess-Murray's law.

Artificial Intelligence in COPD: New Venues to Study a Complex Disease

Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease that can benefit from novel approaches to understanding its evolution and divergent trajectories. Artificial intelligence (AI) has revolutionized how we can use clinical, imaging, and molecular data to understand and model complex systems. AI has shown impressive results in areas related to automated clinical decision making, radiological interpretation and prognostication. The unique nature of COPD and the accessibility to well-phenotyped populations result in an ideal scenario for AI development. This review provides an introduction to AI and deep learning and presents some recent successes in applying AI in COPD. Finally, we will discuss some of the opportunities, challenges, and limitations for AI applications in the context of COPD.

A Genetic Risk Score Associated with Chronic Obstructive Pulmonary Disease Susceptibility and Lung Structure on Computed Tomography

Rationale: Chronic obstructive pulmonary disease (COPD) has been associated with numerous genetic variants, yet the extent to which its genetic risk is mediated by variation in lung structure remains unknown.Objectives: To characterize associations between a genetic risk score (GRS) associated with COPD susceptibility and lung structure on computed tomography (CT).Methods: We analyzed data from MESA Lung (Multi-Ethnic Study of Atherosclerosis Lung Study), a U.S. general population-based cohort, and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study). A weighted GRS was calculated from 83 SNPs that were previously associated with lung function. Lung density, spatially matched airway dimensions, and airway counts were assessed on full-lung CT. Generalized linear models were adjusted for age, age squared, sex, height, principal components of genetic ancestry, smoking status, pack-years, CT model, milliamperes, and total lung volume.Measurements and Main Results: MESA Lung and SPIROMICS contributed 2,517 and 2,339 participants, respectively. Higher GRS was associated with lower lung function and increased COPD risk, as well as lower lung density, smaller airway lumens, and fewer small airways, without effect modification by smoking. Adjustment for CT lung structure, particularly small airway measures, attenuated associations between the GRS and FEV₁/FVC by 100% and 60% in MESA and SPIROMICS, respectively. Lung structure (P < 0.0001), but not the GRS (P > 0.10), improved discrimination of moderate-to-severe COPD cases relative to clinical factors alone.Conclusions: A GRS associated with COPD susceptibility was associated with CT lung structure. Lung structure may be an important mediator of heritability and determinant of personalized COPD risk.

The fractal geometry of bronchial trees differs by strain in mice

Fractal biological structures are pervasive throughout the plant and animal kingdoms, with the mammalian lung being a quintessential example. The lung airway and vascular trees are generated during embryogenesis from a small set of building codes similar to Turing mechanisms that create robust trees ideally suited to their functions. Whereas the blood flow pattern generated by these fractal trees has been shown to be genetically determined, the geometry of the trees has not. We explored a newly established repository providing high-resolution bronchial trees from the four most commonly studied laboratory mice (B6C3F1, BALB/c, C57BL/6 and CD-1). The data fit a fractal model well for all animals with the fractal dimensions ranging from 1.54 to 1.67, indicating that the conducting airway of mice can be considered a self-similar and space-filling structure. We determined that the fractal dimensions of these airway trees differed by strain but not sex, reinforcing the concept that airway branching patterns are encoded within the DNA. The observations also highlight that future study design and interpretations may need to consider differences in airway geometry between mouse strains.NEW & NOTEWORTHY Similar to larger mammals such as humans, the geometries of the bronchial tree in mice are fractal structures that have repeating patterns from the trachea to the terminal branches. The airway geometries of the four most commonly studied mice are different and need to be considered when comparing results that employ different mouse strains. This variability in mouse airway geometries should be incorporated into computer models exploring toxicology and aerosol deposition in mouse models.

Leptin enhances cytokine/chemokine production by normal lung fibroblasts by binding to leptin receptor

BACKGROUND

Obesity is a known risk and exacerbation factor for bronchial asthma. Leptin is an adipokine secreted by adipocytes and enhances energy consumption. Earlier studies have shown that leptin also activates inflammatory cells and structural cells, including airway epithelial cells, thereby exacerbating inflammation. However, little is known about leptin's effect on normal human lung fibroblasts (NHLFs), which are deeply involved in airway remodeling in asthma. This study aimed to elucidate the direct effect of leptin on NHLFs.

METHODS

NHLFs were co-cultured with leptin, and production of cytokines/chemokines was analyzed with real-time PCR and cytometric bead arrays (CBA). Expression of alpha smooth muscle actin (α-SMA) in the lysate of NHLFs stimulated with leptin was assessed by western blotting. Expression of leptin receptor (Ob-R) was analyzed by real-time PCR and flow cytometry. NHLFs were transfected with Ob-R small interference ribonucleic acid (siRNA) by electroporation and used for experiments.

RESULTS

Leptin enhanced production of CCL11/Eotaxin, monocyte chemoattractant protein-1 (CCL2/MCP-1), CXCL8/IL-8, interferon gamma-induced protein 10 (CXCL10/IP-10) and IL-6 by NHLFs at both the protein and messenger ribonucleic acid (mRNA) levels. Leptin also slightly, but significantly, elevated expression of α-SMA. We found robust Ob-R expression on cell surfaces, and transfection with Ob-R siRNA suppressed the enhanced production of CCL11/Eotaxin, CXCL10/IP-10 and IL-6 by leptin, although not completely.

CONCLUSIONS

These findings indicate that leptin may contribute to worsening of asthma in obese patients by enhancing production of inflammatory mediators by binding to Ob-R and accelerating myofibroblast differentiation.

Seeing the forest for the trees: fractal dimensions measure COPD airway remodeling

Chronic obstructive pulmonary disease (COPD) is extremely heterogenous in its effects on airway remodeling. Parsing the complex and interrelated morphologic changes and understanding their contribution to disease severity has posed a significant challenge to the field. In the current issue of the JCI, Bodduluri et al. measured the complex effects of COPD on the airway tree using airway fractal dimension (AFD) on computerized tomography in a large cohort of smokers with and without COPD. They found that lower AFD was independently associated with disease severity and mortality in COPD. This work highlights AFD as a noninvasive approach to analyze complex changes in airway geometry.