Subtyping emphysematous COPD by respiratory volume change distributions on CT

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.

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.

Advancements in automated classification of chronic obstructive pulmonary disease based on computed tomography imaging features through deep learning approaches

Chronic Obstructive Pulmonary Disease (COPD) represents a global public health issue that significantly impairs patients' quality of life and overall health. As one of the primary causes of chronic respiratory diseases and global mortality, effective diagnosis and classification of COPD are crucial for clinical management. Pulmonary function tests (PFTs) are standard for diagnosing COPD, yet their accuracy is influenced by patient compliance and other factors, and they struggle to detect early disease pathologies. Furthermore, the complexity of COPD pathological changes poses additional challenges for clinical diagnosis, increasing the difficulty for physicians in practice. Recently, deep learning (DL) technologies have demonstrated significant potential in medical image analysis, particularly for the diagnosis and classification of COPD. By analyzing key radiological features such as airway alterations, emphysema, and vascular characteristics in Computed Tomography (CT) scan images, DL enhances diagnostic accuracy and efficiency, providing more precise treatment plans for COPD patients. This article reviews the latest research advancements in DL methods based on principal radiological features of COPD for its classification and discusses the advantages, challenges, and future research directions of DL in this field, aiming to provide new perspectives for the personalized management and treatment of COPD.

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.

Associations of fractional exhaled nitric oxide with airway dimension and mucus plugs on ultra-high-resolution computed tomography in former smokers and nonsmokers with asthma

BACKGROUND

Associations of fractional exhaled nitric oxide (FeNO) with airway wall remodeling and mucus plugs remain to be explored in smokers and nonsmokers with asthma. Ultra-high-resolution computed tomography (U-HRCT), which allows accurate structural quantification of airways >1 mm in diameter, was used in this study to examine whether higher FeNO was associated with thicker walls of the 3rd to 6th generation airways and mucus plugging in patients with asthma.

METHODS

The retrospective analyses included consecutive former smokers and nonsmokers with asthma who underwent U-HRCT in a hospital. The ratio of wall area to summed lumen and wall area was calculated as the wall area percent (WA%). Mucus plugging was visually scored.

RESULTS

Ninety-seven patients with asthma (including 59 former smokers) were classified into low (<20 ppb), middle (20-35 ppb), and high (>35 ppb) FeNO groups (n = 24, 26, and 47). In analysis including all patients and subanalysis including nonsmokers or former smokers, WA% in the 6th generation airways was consistently higher in the high FeNO group than in the low FeNO group, whereas WA% in the 3rd to 5th generation airways was not. In multivariable models, WA% in the 6th generation airways and the rate of mucus plugging were higher in the high FeNO group than in the low FeNO group after adjusting for age, sex, body mass index, smoking status, lung volume, and allergic rhinitis presence.

CONCLUSIONS

Higher FeNO may reflect the inflammation and remodeling of relatively peripheral airways in asthma in both former smokers and nonsmokers.

Longitudinal changes in respiratory reactance in patients with COPD: associations with longitudinal change in air-trapping, exacerbations, and mortality

INTRODUCTION

Air-trapping affects clinical outcomes in patients with chronic obstructive pulmonary disease (COPD) and may be detected by reactance at 5 Hz (X5) on respiratory oscillometry because X5 sensitively reflects the elasticity of the chest wall, airway and lung. However, the longitudinal association between X5 and air-trapping remains to be explored. This study aimed to test whether longitudinal changes in X5 could be associated with air-trapping progression, exacerbations, and mortality in patients with COPD.

METHODS

In this prospective COPD observational study, the follow-up period consisted of the first 4 years to obtain longitudinal changes in X5 and residual volume (RV) and number of exacerbations and the remaining years (year 4 to 10) to test mortality. Patients were divided into large, middle, and small X5 decline groups based on the tertiles of longitudinal change in X5, and mortality after 4 years was compared between the groups.

RESULTS

Patients with COPD (n = 114) were enrolled. The large X5 decline group (n = 38) showed a greater longitudinal change in RV and more exacerbations compared with the small X5 decline group (n = 39) in multivariable models adjusted for age, sex, body mass index, and smoking history. Long-term mortality after the 4-year follow-up was higher in the large X5 decline group than in the small X5 decline group (hazard ratio [95 % confidence interval] = 8.37[1.01, 69.0]) in the multivariable Cox proportional hazard model.

CONCLUSION

Longitudinal changes in respiratory reactance could be associated with progressive air-trapping, exacerbation frequency, and increased mortality in patients with 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.

Depicting and predicting changes of lung after lobectomy for cancer by using CT images

Lobectomy is an effective and well-established therapy for localized lung cancer. This study aimed to assess the lung and lobe change after lobectomy and predict the postoperative lung volume. The study included 135 lung cancer patients from two hospitals who underwent lobectomy (32, right upper lobectomy (RUL); 31, right middle lobectomy (RML); 24, right lower lobectomy (RLL); 26, left upper lobectomy (LUL); 22, left lower lobectomy (LLL)). We initially employ a convolutional neural network model (nnU-Net) for automatically segmenting pulmonary lobes. Subsequently, we assess the volume, effective lung volume (ELV), and attenuation distribution for each lobe as well as the entire lung, before and after lobectomy. Ultimately, we formulate a machine learning model, incorporating linear regression (LR) and multi-layer perceptron (MLP) methods, to predict the postoperative lung volume. Due to the physiological compensation, the decreased TLV is about 10.73%, 8.12%, 13.46%, 11.47%, and 12.03% for the RUL, RML, RLL, LUL, and LLL, respectively. The attenuation distribution in each lobe changed little for all types of lobectomy. LR and MLP models achieved a mean absolute percentage error of 9.8% and 14.2%, respectively. Radiological findings and a predictive model of postoperative lung volume might help plan the lobectomy and improve the prognosis.

Clinical characteristics and natural course of chronic obstructive pulmonary disease and/or asthma in Japanese patients: a summary report of two Hokkaido-based cohort studies

Chronic obstructive pulmonary disease (COPD) and asthma are the most common chronic airway diseases and are characterized by chronic airway inflammation and airflow limitation. Japanese patients with COPD or asthma have characteristics different from those of Westerners. Therefore, understanding the characteristics and clinical course of Japanese patients with COPD and those with asthma, particularly severe asthma, is critical for their management and appropriate treatment. The Hokkaido COPD cohort and Hokkaido-based Investigative Cohort Analysis for Refractory Asthma (Hi-CARAT) are high-quality cohort studies of COPD and asthma in the Japanese population and provide valuable data. This report summarizes the clinical findings from the two cohort studies and provides data for more appropriate management of Japanese patients with COPD and/or asthma. Overall, 279 patients with COPD were followed up for up to 10 years in the Hokkaido COPD cohort study, and 127 with severe asthma were followed up for up to 6 years in the Hi-CARAT study. Seventy-nine patients with mild-to-moderate asthma provided baseline data for the Hi-CARAT study. In each disease, several distinct factors, including systemic status and non-pulmonary factors, were associated with important clinical outcomes, such as lung function decline, exacerbations, impaired quality of life, and mortality. Therefore, multifaceted evaluation based on the characteristics of the Japanese population is necessary for the management of COPD and asthma.

Relationships of computed tomography-based small vessel indices of the lungs with ventilation heterogeneity and high transfer coefficients in non-smokers with asthma

Background: The mechanism of high transfer coefficients of the lungs for carbon monoxide (Kco) in non-smokers with asthma is explained by the redistribution of blood flow to the area with preserved ventilation, to match the ventilation perfusion. Objectives: To examine whether ventilation heterogeneity, assessed by pulmonary function tests, is associated with computed tomography (CT)-based vascular indices and Kco in patients with asthma. Methods: Participants were enrolled from the Hokkaido-based Investigative Cohort Analysis for Refractory Asthma (Hi-CARAT) study that included a prospective asthmatic cohort. Pulmonary function tests including Kco, using single breath methods; total lung capacity (TLC), using multiple breath methods; and CT, were performed on the same day. The ratio of the lung volume assessed using single breath methods (alveolar volume; V_A) to that using multiple breath methods (TLC) was calculated as an index of ventilation heterogeneity. The volume of the pulmonary small vessels <5 mm² in the whole lung (BV5 volume), and number of BV5 at a theoretical surface area of the lungs from the plural surface (BV5 number) were evaluated using chest CT images. Results: The low V_A/TLC group (the lowest quartile) had significantly lower BV5 number, BV5 volume, higher BV5 volume/BV5 number, and higher Kco compared to the high V_A/TLC group (the highest quartile) in 117 non-smokers, but not in 67 smokers. Multivariable analysis showed that low V_A/TLC was associated with low BV5 number, after adjusting for age, sex, weight, lung volume on CT, and CT emphysema index in non-smokers (not in smokers). Conclusion: Ventilation heterogeneity may be associated with low BV5 number and high Kco in non-smokers (not in smokers). Future studies need to determine the dynamic regional system in ventilation, perfusion, and diffusion in asthma.

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.