Total Airway Count Research Articles

Automated CT-based Decoupling of the Effects of Airway Narrowing and Wall Thinning on Airway Counts in Chronic Obstructive Pulmonary Disease.

We examine pathways of airway alteration due to wall thinning, narrowing, and obliteration at different COPD severity stages using CT-derived airway metrics. Ex-smokers (N = 649; age mean±std: 69 ± 6years; 52% male) from the COPDGene Iowa cohort (September 2013-July 2017) were studied. Total airway count (TAC), peripheral TAC beyond 7th generation (TACp), and airway wall thickness (WT) were computed from chest CT scans using previously validated automated methods. Causal relationships among demographic, smoking, spirometry, COPD severity, airway counts, WT, and scanner variables were analyzed using causal inference techniques including direct acyclic graphs (DAGs) to quantitatively assess multi-pathway alterations of airways in COPD. TAC, TACp, and WT were significantly lower (p < 0.0001) in mild, moderate, and severe COPD compared to the preserved lung function group. TAC (TACp) losses attributed to narrowing and obliteration of small airways were 4.59, 13.29, and 32.58% (4.64, 17.82, and 45.51%) in mild, moderate, and severe COPD, while the losses attributed to wall thinning were 8.24, 17.01, and 22.95% (12.79, 25.66, and 33.95%) in respective groups. Different pathways of airway alteration in COPD are observed using CT-derived automated airway metrics. Wall thinning is a dominant contributor to both TAC and TACp loss in mild and moderate COPD while narrowing and obliteration of small airways is dominant in severe COPD. This automated CT-based study shows that wall thinning dominates airway alteration in mild and moderate COPD while narrowing and obliteration of small airways leads the alteration process in severe COPD.

Airway Tapering in Chronic Obstructive Pulmonary Disease.

Luminal narrowing is a hallmark feature of airway remodeling in COPD, but current measures focus on airway wall remodeling. Quantification of the natural increase in cumulative cross-sectional area along the length of the human airway tree can facilitate assessment of airway narrowing. We analysed the airway trees of 7641 subjects enrolled in the multicenter COPDGene cohort. Airway luminal tapering was assessed by estimating the slope of the change in cumulative cross-sectional area along the length of the airway tree over successive generations (T-Slope). We performed multivariable regression analyses to test the associations between T-Slope and lung function, St. George's Respiratory Questionnaire (SGRQ), modified Medical Research Council (mMRC) dyspnea score, 6-minute walk distance (6 MWD), FEV1 change, exacerbations, and all-cause mortality after adjusting for demographics, %CT emphysema, and total airway count. The T-Slope decreased with increasing COPD severity: 2.69 (0.70) in nonsmokers and 2.33 (0.70), 2.11 (0.65), 1.78 (0.58), 1.60 (0.53), and 1.57 (0.52) in GOLD stages 0 through 4 respectively (Jonckheere-Terpstra p=0.04). On multivariable analyses, the T-Slope was independently associated with FEV1 (β=0.13 L, 95% CI 0.10 to 0.15, p<0.001), 6MWD (β=15.0 m, 95%CI 10.8 to 19.2, p<0.001), change in FEV1 (β=-4.50 ml·year-1, 95% CI -7.32 to -1.67; p=0.001), exacerbations (IRR=0.78, 95% CI 0.73 to 0.83, p<0.001), and mortality (HR=0.79, 95% CI 0.72 to 0.86, p<0.001). T-Slope is a measure of airway luminal remodeling and is associated with respiratory morbidity and mortality.

Chest CT Airway and Vascular Measurements in Females with COPD or Long-COVID

Chest CT provides a way to quantify pulmonary airway and vascular tree measurements. In patients with COPD, CT airway measurement differences in females are concomitant with worse quality-of-life and other outcomes. CT total airway count (TAC), airway lumen area (LA), and wall thickness (WT) also differ in females with long-COVID. Our objective was to evaluate CT airway and pulmonary vascular and quality-of-life measurements in females with COPD as compared to ex-smokers and patients with long-COVID. Chest CT was acquired 3-months post-COVID-19 infection in females with long-COVID for comparison with the same inspiratory CT in female ex-smokers and COPD patients. TAC, LA, WT, and pulmonary vascular measurements were quantified. Linear regression models were adjusted for confounders including age, height, body-mass-index, lung volume, pack-years and asthma diagnosis. Twenty-one females (53 ± 14 years) with long-COVID, 17 female ex-smokers (69 ± 9 years) and 13 female COPD (67 ± 6 years) patients were evaluated. In the absence of differences in quality-of-life scores, females with long-COVID reported significantly different LA (p = 0.006) compared to ex-smokers but not COPD (p = 0.7); WT% was also different compared to COPD (p = 0.009) but not ex-smokers (p = 0.5). In addition, there was significantly greater pulmonary small vessel volume (BV5) in long-COVID as compared to female ex-smokers (p = 0.045) and COPD (p = 0.003) patients and different large (BV10) vessel volume as compared to COPD (p = 0.03). In females with long-COVID and highly abnormal quality-of-life scores, there was CT evidence of airway remodelling, similar to ex-smokers and patients with COPD, but there was no evidence of pulmonary vascular remodelling.Clinical Trial Registration: www.clinicaltrials.gov NCT05014516 and NCT02279329

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

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

Enhancing COPD classification using combined quantitative computed tomography and texture-based radiomics: a CanCOLD cohort study.

Recent advances in texture-based computed tomography (CT) radiomics have demonstrated its potential for classifying COPD. Participants from the Canadian Cohort Obstructive Lung Disease (CanCOLD) study were evaluated. A total of 108 features were included: eight quantitative CT (qCT), 95 texture-based radiomic and five demographic features. Machine-learning models included demographics along with texture-based radiomics and/or qCT. Combinations of five feature selection and five classification methods were evaluated; a training dataset was used for feature selection and to train the models, and a testing dataset was used for model evaluation. Models for classifying COPD status and severity were evaluated using the area under the receiver operating characteristic curve (AUC) with DeLong's test for comparison. SHapely Additive exPlanations (SHAP) analysis was used to investigate the features selected. A total of 1204 participants were evaluated (n=602 no COPD; n=602 COPD). There were no differences between the groups for sex (p=0.77) or body mass index (p=0.21). For classifying COPD status, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.87) than the combination of demographics and texture-based radiomics (AUC=0.81, p<0.05) or qCT alone (AUC=0.84, p<0.05). Similarly, for classifying COPD severity, the combination of demographics, texture-based radiomics and qCT performed better (AUC=0.81) than demographics and texture-based radiomics (AUC=0.72, p<0.05) or qCT alone (AUC=0.79, p<0.05). Texture-based radiomics and qCT features were among the top five features selected (15th percentile of the CT density histogram, CT total airway count, pack-years, CT grey-level distance zone matrix zone distance entropy, CT low-attenuation clusters) for classifying COPD status. Texture-based radiomics and conventional qCT features in combination improve machine‑learning models for classification of COPD status and severity.

Reduced Total Airway Count and Airway Wall Tapering after Three-Years in Ex-Smokers

Computed tomography (CT) total-airway-count (TAC) and airway wall-thickness differ across chronic obstructive pulmonary disease (COPD) severities, but longitudinal insights are lacking. The aim of this study was to evaluate longitudinal CT airway measurements over three-years in ex-smokers. In this prospective convenience sample study, ex-smokers with (n = 50; 13 female; age = 70 ± 9 years; pack-years = 43 ± 26) and without (n = 40; 17 female; age = 69 ± 10 years; pack-years = 31 ± 17) COPD completed CT, 3He magnetic resonance imaging (MRI), and pulmonary function tests at baseline and three-year follow-up. CT TAC, airway wall-area (WA), lumen-area (LA), and wall-area percent (WA%) were generated. Emphysema was quantified as the relative-area-of-the-lung with attenuation < –950 Hounsfield-units (RA950). MRI ventilation-defect-percent (VDP) was also quantified. Differences over time were evaluated using paired-samples t tests. Multivariable prediction models using the backwards approach were generated. After three-years, forced-expiratory-volume in 1-second (FEV1) was not different in ex-smokers with (p = 0.4) and without (p = 0.5) COPD, whereas RA950 was (p < 0.001, p = 0.02, respectively). In ex-smokers without COPD, there was no change in TAC (p = 0.2); however, LA (p = 0.009) and WA% (p = 0.01) were significantly different. In ex-smokers with COPD, TAC (p < 0.001), WA (p = 0.04), LA (p < 0.001), and WA% (p < 0.001) were significantly different. In all ex-smokers, TAC was related to VDP (baseline: ρ = –0.30, p = 0.005; follow-up: ρ = –0.33, p = 0.002). In significant multivariable models, baseline airway wall-thickness was predictive of TAC worsening. After three-years, in the absence of FEV1 worsening, TAC diminished only in ex-smokers with COPD and airway walls were thinner in all ex-smokers. These longitudinal findings suggest that the evaluation of CT airway remodeling may be a useful clinical tool for predicting disease progression and managing COPD. Clinical trial registration: www.clinicaltrials.gov NCT02279329

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

BackgroundSex 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. MethodsThis 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. ResultsThe 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. ConclusionOlder 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.

CT airway remodelling and chronic cough

RationaleStructural airway changes related to chronic cough (CC) are described in the literature, but so far reported data are rare and non-conclusive. Furthermore, they derive mainly from cohorts with small...

Effects of Benralizumab on Three-Dimensional Computed Tomography Analysis in Severe Eosinophilic Asthma

Introduction: Benralizumab, an anti-interleukin-5 receptor chain monoclonal antibody, is used to treat severe asthma and control asthma symptoms or exacerbations. The aim of this study was to examine the changes in airway morphology using computed tomography (CT) images in accordance with clinical efficacy following the administration of benralizumab. Methods: The clinical efficacy of benralizumab was evaluated in 11 patients with severe asthma by analyzing the changes in parameters, such as the asthma control test, asthma quality of life questionnaire, pulmonary function, and exacerbation count. We also investigated the airway wall thickness of the right bronchus (B1) and the total airway count (TAC) using CT images. Results: Most patients treated with benralizumab showed improvements in asthma symptoms and exacerbations. CT imaging analyses showed a decrease in the right B¹ airway wall thickness and an increase in the TAC. Correlations between blood eosinophil count and changes in CT imaging were observed. Discussion/Conclusion: The data suggested that benralizumab has the potential to improve airway wall thickening and ventilation by alleviating the obstruction and clearing an obstructed airway.

Airway Detection in COPD at Low-Dose CT Using Deep Learning and Multiparametric Freeze and Grow.

To present and validate a fully automated airway detection method at low-dose CT in patients with chronic obstructive pulmonary disease (COPD). In this retrospective study, deep learning (DL) and freeze-and-grow (FG) methods were optimized and applied to automatically detect airways at low-dose CT. Four data sets were used: two data sets consisting of matching standard- and low-dose CT scans from the Genetic Epidemiology of COPD (COPDGene) phase II (2014-2017) cohort (n = 2 × 236; mean age ± SD, 70 years ± 9; 123 women); one data set consisting of low-dose CT scans from the COPDGene phase III (2018-2020) cohort (n = 335; mean age ± SD, 73 years ± 8; 173 women); and one data set consisting of low-dose, anonymized CT scans from the 2003 Dutch-Belgian Randomized Lung Cancer Screening trial (n = 55) acquired by using different CT scanners. Performance measures for different methods were computed and compared by using the Wilcoxon signed rank test. At low-dose CT, 56 294 of 62 480 (90.1%) airways of the reference total airway count (TAC) and 32 109 of 37 864 (84.8%) airways of the peripheral TAC (TACp), detected at standard-dose CT, were detected. Significant losses (P < .001) of 14 526 of 76 453 (19.0%) airways and 884 of 6908 (12.8%) airways in the TAC and 12 256 of 43 462 (28.2%) airways and 699 of 3882 (18.0%) airways in the TACp were observed, respectively, for the multiprotocol and multiscanner data without retraining. When using the automated low-dose CT method, TAC values of 347, 342, 323, and 266 and TACp values of 205, 202, 289, and 141 were observed for those who have never smoked and participants at Global Initiative for Chronic Obstructive Lung Disease stages 0, 1, and 2, respectively, which were superior to the respective values previously reported for matching groups when using a semiautomated method at standard-dose CT. A low-cost, automated CT-based airway detection method was suitable for investigation of airway phenotypes at low-dose CT.Keywords: Airway, Airway Count, Airway Detection, Chronic Obstructive Pulmonary Disease, CT, Deep Learning, Generalizability, Low-Dose CT, Segmentation, Thorax, LungClinical trial registration no. NCT00608764 Supplemental material is available for this article. © RSNA, 2022.

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.

Luminal mucus plugs are spatially associated with airway wall thickening in severe COPD and asthma: A single-centered, retrospective, observational study

BackgroundAirway wall thickening and excess airway mucus occur in asthma and chronic obstructive pulmonary disease (COPD), but few studies have investigated the relationship between them. Our objective was to determine the association between computed tomography (CT) airway wall thickening in segmental airways proximal to airways with or without mucus plugging in patients with asthma and COPD. MethodsMucus plugging was scored using a CT bronchopulmonary segment-based scoring system in asthma and COPD patients. For each of the 19 segmental airways, a mucus plug was defined as complete occlusion of one or more of the daughter branches (sub-segmental airways) by mucus. CT airway measurements were generated for each of the 19 segmental airways: wall-area-percentage (WA%), lumen area (LA), and total airway count (TAC) (VIDA Diagnostics Inc.). Multivariable logistic regression models were constructed for the presence of mucus plugs with corresponding CT measurement and adjusted by covariates; each of the 19 segments was treated as a nested variable. ResultsA total of 33 participants were evaluated. Participants had a mean age of 60 ± 15yrs and there were n = 14 (42%) males. There were 16 (48%) participants with a diagnosis of asthma and 17 (52%) with a COPD diagnosis. The mean FEV1 was 53 ± 21%pred and FEV1/FVC was 54 ± 15%. The mean mucus score in all participants was 15 ± 4 (min = 0, max = 19). Multivariable logistic regression analysis showed the presence of airway mucus was significantly associated with increased CT WA% (β = 7.30, p = 0.004) and reduced TAC (β = −0.06, p = 0.045). ConclusionsThere was increased airway wall thickness and reduced airway counts on CT in segments where there was a distal mucus plug compared to segments without mucus plugs in asthma and COPD.

CT Attenuation and Cross-Sectional Area of the Pectoralis Are Associated With Clinical Characteristics in Chronic Obstructive Pulmonary Disease Patients.

Purpose: Muscle wasting is associated with prognosis in patients with chronic obstructive pulmonary disease (COPD). Computed tomography (CT) could serve as a method for muscle assessment due to its ability to measure both muscle quantity (e.g., cross-sectional muscle area) and muscle quality (e.g., muscle attenuation). Our study aimed to compare the differences in CT-derived pectoralis muscle cross-sectional area (PMA) and pectoralis muscle attenuation (PMT) between COPD patients and healthy controls and explore the association between PMA and PMT measurements and clinical characteristics in patients with COPD. Methods: A total of 252 participants included in our analysis consisted of 80 healthy controls and 172 patients with COPD. PMA and PMT were measured from a single axial slice of the CT scan above the aortic arch. Linear regression analysis was used to determine the correlation between PMA and PMT measurements and clinical characteristics in patients with COPD. Associations were adjusted for age, sex, BMI, FEV1%pred, smoking pack-years, current smoking status, emphysema percentage, and total airway count (TAC) of the right upper lobe apical bronchus (RB1). Results: PMA and PMT were lower in COPD patients, especially those with acute exacerbation, than in healthy controls. PMA and PMT were significantly associated with the severity of emphysema and the TAC of RB1 (p < 0.05). Patients with stable COPD, who had lower PMA and lower PMT, had significantly worse pulmonary function, poorer exercise tolerance, decreased quality of life, and worse dyspnea scores. In addition, patients with acute COPD exacerbation, who had lower PMA and lower PMT, had a higher risk of respiratory failure on admission. Conclusion: CT-derived measurements of the pectoralis muscle may be helpful in detecting declines in muscle quantity and quality and predicting disease severity in patients with COPD.

Pulmonary MRI and Cluster Analysis Help Identify Novel Asthma Phenotypes.

Outside eosinophilia, current clinical asthma phenotypes do not show strong relationships with disease pathogenesis or treatment responses. While chest x-ray computed tomography (CT) phenotypes have previously been explored, functional MRI measurements provide complementary phenotypic information. To derive novel data-driven asthma phenotypic clusters using functional MRI airway biomarkers that better describe airway pathologies in patients. Retrospective. A total of 45 patients with asthma who underwent post-bronchodilator 129 Xe MRI, volume-matched CT, spirometry and plethysmography within a 90-minute visit. Three-dimensional gradient-recalled echo 129 Xe ventilation sequence at 3T. We measured MRI ventilation defect percent (VDP), CT airway wall-area percent (WA%), wall-thickness (WT, WT* [*normalized for age/sex/height]), lumen-area (LA), lumen-diameter (D, D*) and total airway count (TAC). Univariate relationships were utilized to select variables for k-means cluster analysis and phenotypic subgroup generation. Spirometry and plethysmography measurements were compared across imaging-based clusters. Spearman correlation (ρ), one-way analysis of variance (ANOVA) or Kruskal-Wallis tests with post hoc Bonferroni correction for multiple comparisons, significance level 0.05. Based on limited common variance (Kaiser-Meyer-Olkin-measure=0.44), four unique clusters were generated using MRI VDP, TAC, WT* and D* (52 ± 14 years, 27 female). Imaging measurements were significantly different across clusters as was the forced expiratory volume in 1-second (FEV1 %pred ), residual volume/total lung capacity and airways resistance. Asthma-control (P=0.9), quality-of-life scores (P=0.7) and the proportions of severe-asthma (P=0.4) were not significantly different. Cluster1 (n=15/8 female) reflected mildly abnormal CT airway measurements and FEV1 with moderately abnormal VDP. Cluster2 (n=12/12 female) reflected moderately abnormal TAC, WT and FEV1 . In Cluster3 and Cluster4 (n=14/6 female, n=4/1 female, respectively), there was severely reduced TAC, D and FEV1 , but Cluster4 also had significantly worse, severely abnormal VDP (7 ± 5% vs. 41 ± 12%). We generated four proof-of-concept MRI-derived clusters of asthma with distinct structure-function pathologies. Cluster analysis of asthma using 129 Xe MRI in combination with CT biomarkers is feasible and may challenge currently used paradigms for asthma phenotyping and treatment decisions. 3 TECHNICAL EFFICACY: Stage.

Differentiating COPD and asthma using quantitative CT imaging and machine learning.

There are similarities and differences between chronic obstructive pulmonary disease (COPD) and asthma patients in terms of computed tomography (CT) disease-related features. Our objective was to determine the optimal subset of CT imaging features for differentiating COPD and asthma using machine learning. COPD and asthma patients were recruited from Heidelberg University Hospital (Heidelberg, Germany). CT was acquired and 93 features were extracted: percentage of low-attenuating area below -950 HU (LAA950), low-attenuation cluster (LAC) total hole count, estimated airway wall thickness for an idealised airway with an internal perimeter of 10 mm (Pi10), total airway count (TAC), as well as airway inner/outer perimeters/areas and wall thickness for each of five segmental airways, and the average of those five airways. Hybrid feature selection was used to select the optimum number of features, and support vector machine learning was used to classify COPD and asthma. 95 participants were included (n=48 COPD and n=47 asthma); there were no differences between COPD and asthma for age (p=0.25) or forced expiratory volume in 1 s (p=0.31). In a model including all CT features, the accuracy and F1 score were 80% and 81%, respectively. The top features were: LAA950, outer airway perimeter, inner airway perimeter, TAC, outer airway area RB1, inner airway area RB1 and LAC total hole count. In the model with only CT airway features, the accuracy and F1 score were 66% and 68%, respectively. The top features were: inner airway area RB1, outer airway area LB1, outer airway perimeter, inner airway perimeter, Pi10, TAC, airway wall thickness RB1 and TAC LB10. COPD and asthma can be differentiated using machine learning with moderate-to-high accuracy by a subset of only seven CT features.

Association of Total Airway Count on Computed Tomography with Pulmonary Function Decline in Early-Stage COPD: A Population-Based Prospective Cohort Study.

BackgroundIt has been found that the degree of terminal bronchiole destruction is associated with the severity of COPD. However, total airway count (TAC) of CT-visible and its relationship with COPD lung function severity and pulmonary function decline remains controversial. The present study aimed to determine whether TAC is significantly reduced in early-stage COPD (GOLD stage I–II) compared with healthy control subjects and whether TAC is associated with annual decline in pulmonary function in Chinese patients with early-stage COPD.MethodsA total of 176 participants were enrolled in this study, of which 139 participants had undergone at least two spirometry measurements within 7 years (average 5.5 [standard deviation 0.8] years) after baseline data acquisition. CT-visible TAC was measured by summing all airway segments using semi-automated software. Average lumen diameter, average inner area, emphysema index, air trapping, and inspiratory Pi10 were also measured. Multivariable linear analysis was performed to evaluate variables that were significantly related to pulmonary function parameters and to evaluate the correlation between TAC and annual decline in longitudinal pulmonary function.ResultsCompared with healthy control subjects, CT-visible TAC was significantly reduced by 51% in GOLD II and by 31% in GOLD I after adjustment. TAC had the greatest impact on pre-bronchodilator FEV1, pre-bronchodilator FVC, post-bronchodilator FEV1, and post-bronchodilator FEV1/FVC (both p<0.001) among all CT indicators measured. TAC has the best correlation with inspiratory Pi10 (ρ=−0.751, p<0.001), an evaluation indicator of the degree of airway remodeling. TAC was independently associated with annual decline in pre-bronchodilator FEV1 (p=0.023), post-bronchodilator FEV1 (p=0.018), and post-bronchodilator FEV1/FVC (p<0.001).ConclusionThis finding suggests that CT-visible TAC may be an evaluation indicator of the degree of airway remodeling, and was diminished in greater COPD lung function severity, and independently associated with disease progression. Early-stage COPD patients have already occurred lung structural changes and early intervention may be needed to ameliorate the progression of disease.Clinical Trial RegistrationChiCTR-OO-14004264.

Computed tomography total airway count predicts progression to COPD in at-risk smokers.

There is limited understanding of how to identify people at high risk of developing COPD. Our objective was to investigate the association between computed tomography (CT) total airway count (TAC) and incident COPD over 3 years among ever-smokers from the population-based Canadian Cohort Obstructive Lung Disease (CanCOLD) study.CT and spirometry were acquired in ever-smokers at baseline; spirometry was repeated at 3-year follow-up. CT TAC was generated by summing all airway segments in the segmented airway tree (VIDA Diagnostics, Inc.). CT airway wall area, wall thickness for a theoretical airway with 10 mm perimeter (Pi10), and low attenuation areas below −856 HU (LAA856) were also measured. Logistic and mixed effects regression models were constructed to determine the association for CT measurements with development of COPD and forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) decline, respectively.Among 316 at-risk participants evaluated at baseline (65±9 years, 40% female, 18±19 pack-years), incident COPD was detected in 56 participants (18%) over a median 3.1±0.6 years of follow-up. Among CT measurements, only TAC was associated with incident COPD (p=0.03), where a 1-sd decrement in TAC increased the odds ratio for incident COPD by a factor of two. In a multivariable linear regression model, reduced TAC was significantly associated with greater longitudinal FEV1/FVC decline (p=0.03), but no other measurements were significant.CT TAC predicts incident COPD in at-risk smokers, indicating that smokers exhibit early structural changes associated with COPD prior to abnormal spirometry.

Structural airway imaging metrics are differentially associated with persistent chronic bronchitis

BackgroundChronic 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...

Is Computed Tomography Airway Count Related to Asthma Severity and Airway Structure and Function?

Rationale: In patients with asthma, X-ray computed tomography (CT) has provided evidence of thickened airway walls and airway occlusions, but the total number of CT-visible airways and its relationship with disease severity is unknown.Objectives: To measure CT total airway count (TAC) in asthma and evaluate relationships with asthma severity, airway morphology, pulmonary function, and magnetic resonance imaging (MRI) ventilation.Methods: Participants underwent post-bronchodilator inspiratory CT, and prebronchodilator and post-bronchodilator spirometry and hyperpolarized 3He MRI. CT TAC was quantified as the sum of airways in the segmented airway tree, and airway wall area percent (WA%) and lumen area were measured. MRI ventilation abnormalities were quantified as the ventilation defect percent.Measurements and Main Results: We evaluated 70 participants, including 15 Global Initiative for Asthma (GINA) steps 1 to 3, 19 GINA 4, and 36 GINA 5 participants with asthma. As compared with GINA 1 to 3, TAC was significantly diminished in GINA 4 (P = 0.03) and GINA 5 (P = 0.045). Terminal airway intraluminal occlusion was present in 5 (2 GINA 4 and 3 GINA 5) of 70 participants. Sub-subsegmental airways were CT-invisible or missing in 69 out of 70 participants; the most common number of missing sub-subsegments was 10. Participants with ≥10 missing subsegments had worse WA% (P < 0.0001), lumen area (P < 0.0001), and ventilation defect percent (P = 0.03) than those with <10 missing subsegments. In a multivariable model, TAC (standardized regression coefficient = 0.50; P = 0.001) independently predicted FEV1 (R2 = 0.27; P = 0.003) and, in a separate model, TAC (standardized regression coefficient = -0.53; P < 0.0001) independently predicted airway WA% (R2 = 0.32; P = 0.0001).Conclusions: TAC was significantly diminished in participants with greater asthma severity and was related to airway wall thickness and ventilation defects. Fewer airways in severe than in mild asthma challenges our understanding of airway disease in asthma.Clinical trial registered with www.clinicaltrials.gov (NCT02351141).

Regional lung deflation with increased airway volume underlies the functional response to bronchodilators in chronic obstructive pulmonary disease.

Bronchodilators, including long‐acting muscarinic antagonists (LAMAs), improve airflow limitation and lung hyperinflation in patients with chronic obstructive pulmonary disease (COPD). While bronchodilators increase airway caliber and deflate the lungs, little is known about the effects of the local interaction between airway dilation and lung deflation on functional improvements resulting from bronchodilator therapy. This study aimed to explore whether lung deflation with increased airway volume in the upper and lower lung regions would produce different physiological responses to LAMA therapy. Using the clinical data of 41 patients with COPD who underwent spirometry and inspiratory computed tomography (CT) before and 1 year after LAMA treatment, we measured the 1‐year change in the airway tree to lung volume percentage ratio (AWV%) for the right upper, middle, and lower lobes (RUL, RML, and RLL) and the left upper and lower lobes (LUL and LLL), and total airway count (TAC) identifiable on CT in relation to the forced expiratory volume in 1 s (FEV1). The results showed that LAMA treatment significantly increased the FEV1 and AWV% of the RUL, RML, RLL, LUL, and LLL. Increased AWV% in the RLL and LLL, but not in the RUL and LUL, was correlated with increased FEV1. In the multivariate analysis, the increased AWV% in the RLL was associated with the increased FEV1 independent of the change in TAC in the RLL after treatment. This is the first study to show that the physiological improvements after bronchodilator treatment in COPD could be mainly due to the combination of regional deflation and increased airway volume of the lower lobes.