Relationship of CT-quantified emphysema, small airways disease and bronchial wall dimensions with physiological, inflammatory and infective measures in COPD

Early Diagnosis of High-Risk Chronic Obstructive Pulmonary Disease Based on Quantitative High-Resolution Computed Tomography Measurements

Purpose

Quantitative computed tomography (QCT) techniques, focusing on airway anatomy and emphysema, may help to detect early structural changes of COPD disease. This retrospective study aims to identify high-risk COPD participants by using QCT measurements.

Patients and Methods

We enrolled 140 participants from the Second Affiliated Hospital of Shenyang Medical College who completed inspiratory high-resolution CT scans, pulmonary function tests (PFTs), and clinical characteristics recorded. They were diagnosed Non-COPD by PFT value of FEV1/FVC >70% and divided into two groups according percentage predicted FEV1 (FEV1%), low-risk COPD group: FEV1% ≥ 95%, high-risk group: 80% < FEV1% < 95%. The QCT measurements were analyzed by the Student's t-test (or Mann-Whitney U-test) method. Then, feature candidates were identified using the LASSO method. Meanwhile, the correlation between QCT measurements and PFTs was assessed by the Spearman rank correlation test. Furthermore, support vector machine (SVM) was performed to identify high-risk COPD participants. The performance of the models was evaluated in terms of accuracy (ACC), sensitivity (SEN), specificity (SPE), F1-score, and area under the ROC curve (AUC), with p <0.05 considered statistically significant.

Results

The SVM based on QCT measurements achieved good performance in identifying high-risk COPD patients with 85.71% of ACC, 88.34% of SEN, 84.00% of SPE, 83.33% of F1-score, and 0.93 of AUC. Further, QCT measurements integration of clinical data improved the performance with an ACC of 90.48%. The emphysema index (%LAA-950) of left lower lung was negatively correlated with PFTs (P < 0.001). The airway anatomy indexes of lumen diameter (LD) were correlated with PFTs.

Conclusion

QCT measurements combined with clinical information could provide an effective tool for an early diagnosis of high-risk COPD. The QCT indexes can be used to assess the pulmonary function status of high-risk COPD.

The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review

Background and Objective

Chronic obstructive pulmonary disease (COPD) is a significant contributor to global morbidity and mortality. Quantitative computed tomography (QCT), a non-invasive imaging modality, offers the potential to assess lung structure and function in COPD patients. Amidst the coronavirus disease 2019 (COVID-19) pandemic, chest computed tomography (CT) scans have emerged as a viable alternative for assessing pulmonary function (e.g., spirometry), minimizing the risk of aerosolized virus transmission. However, the clinical application of QCT measurements is not yet widespread enough, necessitating broader validation to determine its usefulness in COPD management.

Methods

We conducted a search in the PubMed database in English from January 1, 2013 to April 20, 2023, using keywords and controlled vocabulary related to QCT, COPD, and cohort studies.

Key Content and Findings

Existing studies have demonstrated the potential of QCT in providing valuable information on lung volume, airway geometry, airway wall thickness, emphysema, and lung tissue density in COPD patients. Moreover, QCT values have shown robust correlations with pulmonary function tests, and can predict exacerbation risk and mortality in patients with COPD. QCT can even discern COPD subtypes based on phenotypic characteristics such as emphysema predominance, supporting targeted management and interventions.

Conclusions

QCT has shown promise in cohort studies related to COPD, since it can provide critical insights into the pathogenesis and progression of the disease. Further research is necessary to determine the clinical significance of QCT measurements for COPD management.

Analysis of Airway Thickening and Serum Cytokines in COPD Patients with Frequent Exacerbations: A Heart of the Matter

Background

Differences in lung function for Chronic Obstructive Pulmonary Disease (COPD) cause bias in the findings when identifying frequent exacerbator phenotype-related causes. The aim of this study was to determine whether computed tomographic (CT) biomarkers and circulating inflammatory biomarkers were associated with the COPD frequent exacerbator phenotype after eliminating the differences in lung function between a frequent exacerbator (FE) group and a non-frequent exacerbator (NFE) group.

Methods

A total of 212 patients with stable COPD were divided into a FE group (n=106) and a NFE group (n=106) according to their exacerbation history. These patients were assessed by spirometry, quantitative CT measurements and blood sample measurements during their stable phase. Univariate and multivariate logistic regression were used to assess the association between airway thickening or serum cytokines and the COPD frequent exacerbator phenotype. Receiver operating characteristic (ROC) curves were calculated for Pi10, WA%, IL-1β and IL-4 to identify frequent exacerbators.

Results

Compared with NFE group, FE group had a greater inner perimeter wall thickness of a 10 mm diameter bronchiole (Pi10), a greater airway wall area percentage (WA%) and higher concentrations of IL-1β and IL-4 (p<0.001). After adjusting for sex, age, BMI, FEV1%pred and smoking pack-years, Pi10, WA%, IL-β and IL-4 were independently associated with a frequent exacerbator phenotype (p<0.001). Additionally, there was an increase in the odds ratio of the frequent exacerbator phenotype with increasing Pi10, WA%, IL-4, and IL-1β (p for trend <0.001). The ROC curve demonstrated that IL-1β had a significantly larger calculated area under the curve (p < 0.05) than Pi10, WA% and IL-4.

Conclusion

Pi10, WA%, IL-4, and IL-1β were independently associated with the frequent exacerbator phenotype among patients with stable COPD, suggesting that chronic airway and systemic inflammation contribute to the frequent exacerbator phenotype.

Trial Registration

This trial was registered in Chinese Clinical Trial Registry (https://www.chictr.org.cn). Its registration number is ChiCTR2000038700, and date of registration is September 29, 2020.

Computer-assisted evaluation of small airway disease in CT scans of Iran-Iraq war victims of chemical warfare by a locally developed software: comparison between different quantitative methods

OBJECTIVE

Diagnosis of small airway disease on computed tomography (CT) scans is challenging in patients with a history of chemical warfare exposure. We developed a software package based on different methodologies to identify and quantify small airway disease in CT images. The primary aim was to identify the best automatic methodology for detecting small airway disease in CT scans of Iran-Iraq War victims of chemical warfare.

METHODS

This retrospective case-control study enrolled 46 patients with a history of chemical warfare exposure and 27 controls with inspiratory/expiratory (I/E) CT scans and spirometry tests. Image data were automatically segmented, and inspiratory images were registered into the expiratory images' frame using the locally developed software. Parametric response mapping (PRM) and air trapping index (ATI) mapping were performed on the CT images. Conventional QCT methods, including expiratory/inspiratory mean lung attenuation (E/I MLA) ratio, normal density E/I (ND E/I) MLA ratio, attenuation volume Index (AVI), %low attenuation areas (LAA) < -856 in exhale scans, and %LAA < -950 in inhale scans were also computed. QCT measurements were correlated with spirometry results and compared across the two study groups.

RESULTS

The correlation analysis showed a significant negative relationship between three air trapping (AT) measurements (PRM, ATI, and %LAAExp < -856) and spirometry parameters (Fev1, Fvc, Fev1/Fvc, and MMEF). Moreover, %LAAExp < -856 had the highest significant negative correlation with Fev1/Fvc (r = -0.643, P-value < 0.001). Three AT measurements demonstrated a significant difference between the study groups. The E/I ratio was also significantly different between the two groups (P-value < 0.001). Binary logistic regression models showed PRMFsad, %LAAExp < -856, and ATI as significant and strong predictors of the study outcome. Optimal cut-points for PRMFsad = 19%, %LAAExp < -856 = 23%, and ATI = 27% were identified to classify the participants into two groups with high accuracy.

CONCLUSION

QCT methods, including PRM, ATI, and %LAAExp < -856 can greatly advance the identification and quantification of SAD in chemical warfare victims. The results should be verified in well-designed prospective studies involving a large population.

Clinical Implications of Low Absolute Blood Eosinophil Count in the SPIROMICS COPD Cohort

BACKGROUND

The Global Initiative for Chronic Obstructive Lung Disease (GOLD) considers blood eosinophil counts < 100 cells/μL (BEC≤100) in people with COPD to predict poor inhaled corticosteroid (ICS) responsiveness. However, the BEC≤100 phenotype is inadequately characterized, especially in advanced COPD.

RESEARCH QUESTION

Are there differences between GOLD group D patients with high BEC and those with low BEC regarding baseline characteristics and longitudinal outcomes?

STUDY DESIGN AND METHODS

We used multivariable mixed models and logistic regression to contrast clinical characteristics and outcomes of BEC≤100 vs BEC > 100 (BEC100+) in all subjects with COPD (n = 1,414) and GOLD group D subjects (n = 185) not receiving ICS.

RESULTS

We identified n = 485 with BEC≤100 (n = 61 GOLD group D) and n = 929 people with BEC100+ (n = 124 GOLD group D). BEC≤100 status was stable at 6 weeks and approximately 52 weeks (intraclass correlations of 0.78 and 0.71, respectively). Compared with BEC100+, BEC≤100 comprised more women, with greater current smoking, and less frequent childhood asthma. Among all analyzed participants, the two BEC-defined subsets showed similar rates of lung function decline (mean slope, BEC≤100 vs BEC100+, -50 vs -39 mL/y; P = .140), exacerbations (0.40 vs 0.36/y; P = .098), subsequent ICS initiation (2.5% vs 4.4%; P = .071), and mortality (7.8% vs 8.4%; P = .715). However, in GOLD group D, people with BEC≤100 showed higher exacerbation rates within 365 days of enrollment (0.62 vs 0.33/y; P = .002) and total follow-up (1.16 vs 0.83/y; P = .014). They also had greater lung function decline (mean slope of -68 mL/y vs -23 mL/y; P = .036) and had greater emphysema at baseline (voxels < 950 Hounsfield units at total lung capacity of 7.46% vs 4.61%; P = .029).

INTERPRETATION

In non-ICS-treated GOLD group D COPD, people with BEC≤100 had more baseline emphysema, prospective exacerbations, and lung function decline. Our analysis has identified a particularly vulnerable subpopulation of people with COPD, suggesting the need for studies focused specifically on their therapeutic treatment.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov; No.: NCT01969344; URL: www.

CLINICALTRIALS

gov.

A Computer-based Analysis for Identification and Quantification of Small Airway Disease in Lung Computed Tomography Images: A Comprehensive Review for Radiologists

Computed tomography (CT) imaging is being increasingly used in clinical practice for detailed characterization of lung diseases. Respiratory diseases involve various components of the lung, including the small airways. Evaluation of small airway disease on CT images is challenging as the airways cannot be visualized directly by a CT scanner. Small airway disease can manifest as pulmonary air trapping (AT). Although AT may be sometimes seen as mosaic attenuation on expiratory CT images, it is difficult to identify diffuse AT visually. Computer technology advances over the past decades have provided methods for objective quantification of small airway disease on CT images. Quantitative CT (QCT) methods are being rapidly developed to quantify underlying lung diseases with greater precision than subjective visual assessment of CT images. A growing body of evidence suggests that QCT methods can be practical tools in the clinical setting to identify and quantify abnormal regions of the lung accurately and reproducibly. This review aimed to describe the available methods for the identification and quantification of small airway disease on CT images and to discuss the challenges of implementing QCT metrics in clinical care for patients with small airway disease.

Prediction of exercise-induced desaturation in COPD patients without resting hypoxemia: a retrospective study

Background

There is no universally accepted criterion for assessing exercise-induced desaturation (EID). The purpose of this study is to compare the two methods regularly used for determining EID in COPD patients, as well as to explore the risk factors and predictors related to EID.

Methods

The 6MWT was performed with continuous SpO₂ monitoring on patients with stable COPD. Using two methods (method A: “SpO_2rest–SpO_2min ≥ 4% and/or SpO_2min < 90%”, method B: “SpO_2rest–SpO_2end ≥ 4% and/or SpO_2end < 90%”) as EID determination criteria to assess the incidence of EID. The differences and consistency of the two methods are compared. Moreover, we collected data through the pulmonary function test, mMRC dyspnea score, COPD assessment test, BODE index and CT-defined emphysema. Univariate and multivariate logistic regression analyses were used to identify factors affecting the EID. For the parameters that predict EID in 6MWT, a receiver operating characteristic (ROC) curve analysis was employed.

Results

The analysis included 124 patients. The overall incidence of EID was 62.1% by using method A as the criterion and 51.6% by method B. All of the EID patients found by method B were included in the EID patients identified by method A, as well as 13 new-EID patients. The difference in diagnostic outcomes between the two approaches was not statistically significant (P > 0.05), but they were in excellent agreement (Kappa = 0.807, P = 0.001). Logistic regression analyses found that D_LCO SB% pred, D_LCO/VA% pred, CAT score, mean density, PD15, emphysema volume and %LAA were significant determinants of the EID. For predicting EID, the ROC analysis produced AUC and cutoffs of 0.689 and 50.45% (D_LCO SB% pred), 0.707 and 75.0% (D_LCO/VA% pred), 0.727 and 15 points (CAT score), 0.691 and − 955.00HU (PD15), 0.671 and − 856.46HU (mean density), 0.668 and 338.14 ml (emphysema volume) and 0.656 and 7.63% (%LAA), respectively.

Conclusions

Two methods evaluating EID in this research are in a good agreement, method A can find more EID patients by focusing on SpO_2min. When conditions are constrained, it is also sufficient to assess EID in COPD patients by method B. In terms of the predictors of EID, D_LCO SB% pred, D_LCO/VA% pred, CAT score and CT-defined emphysema are all statistically significant test variables to determine EID.

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study

Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate the clinical and imaging significance of increasing emphysema severity as graded by a deep learning algorithm on sequential CT scans in cigarette smokers. Materials and Methods A secondary analysis of the prospective Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study participants was performed and included baseline and 5-year follow-up CT scans from 2007 to 2017. Emphysema was classified automatically according to the Fleischner emphysema grading system at baseline and 5-year follow-up using a deep learning model. Baseline and change in clinical and imaging parameters at 5-year follow-up were compared in participants whose emphysema progressed versus those who did not. Kaplan-Meier analysis and multivariable Cox regression were used to assess the relationship between emphysema score progression and mortality. Results A total of 5056 participants (mean age, 60 years ± 9 [SD]; 2566 men) were evaluated. At 5-year follow-up, 1293 of the 5056 participants (26%) had emphysema progression according to the Fleischner grading system. This group demonstrated progressive airflow obstruction (forced expiratory volume in 1 second [percent predicted]: -3.4 vs -1.8), a greater decline in 6-minute walk distance (-177 m vs -124 m), and greater progression in quantitative emphysema extent (adjusted lung density: -1.4 g/L vs 0.5 g/L; percentage of lung voxels with CT attenuation less than -950 HU: 0.6 vs 0.2) than those with nonprogressive emphysema (P < .001 for each). Multivariable Cox regression analysis showed a higher mortality rate in the group with emphysema progression, with an estimated hazard ratio of 1.5 (95% CI: 1.2, 1.8; P < .001). Conclusion An increase in Fleischner emphysema grade on sequential CT scans using an automated deep learning algorithm was associated with increased functional impairment and increased risk of mortality. ClinicalTrials.gov registration no. NCT00608764 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Grenier in this issue.

Correlations between Volumetric Capnography and Automated Quantitative Computed Tomography Analysis in Patients with Severe COPD

Background: In chronic obstructive pulmonary disease (COPD), morphological analysis made by computed tomography (CT) is usually correlated with spirometry as the main functional tool. In this study, quantitative CT analysis (QCT) was compared with volumetric capnography (VCap), alongside spirometry and the 6-min walk test (6MWT). Methods: Twenty-seven patients with severe/very severe COPD were included, compared with nineteen control subjects. All participants performed spirometry and chest high resolution CT scans that were analyzed with fully-automated software. The COPD group was also submitted to VCap and 6MWT. Results: COPD patients (65.07 ± 8.25 years) showed an average FEV1 of 1.2 L (44% of the predicted) and the control group (34.36 ± 8.78 years). VCap × QCT: positive correlations were observed with bronchial wall thickening and negative correlations with diameter and area of the bronchial lumen. Spirometry × QCT: positive correlations were observed between post-BD FVC, FEV1 and FEF 25–75% and diameter and luminal area of the airways and FVC and lung and vascular volumes (emphysema). Negative correlation was observed between post-BD FVC and FEV1 when compared with Pi10 (internal perimeter of 10 mm). 6MWT vs. QCT: negative correlations were observed between the distance covered with relative wall thickness (airways) and vascular volume and peripheral vascular volume (vasculature). Conclusion: Relevant correlations between QCT and pulmonary function variables were found, including the VCap, highlighting the importance of structural analysis in conjunction with a multidimensional functional assessment. This is the first study to correlate airway and parenchyma QCT with VCap.

Bullous Parametric Response Map for Functional Localization of COPD

Advanced bronchoscopic lung volume reduction treatment (BLVR) is now a routine care option for treating patients with severe emphysema. Patterns of low attenuation clusters indicating emphysema and functional small airway disease (fSAD) on paired CT, which may provide additional insights to the target selection of the segmental or subsegmental lobe of the treatments, require further investigation. The low attenuation clusters (LACS) were segmented to identify the scalar and spatial distribution of the lung destructions, in terms of 10 fractions scales of low attenuation density (LAD) located in upper lobes and lower lobes. The LACs of functional small airway disease (fSAD) were delineated by applying the technique of parametric response map (PRM) on the co-registered CT image data. Both emphysematous LACs of inspiratory CT and fSAD LACs on expiratory CT were used to derive the coefficients of the predictive model for estimating the airflow limitation. The voxel-wise severity is then predicted using the regional LACs on the co-registered CT to indicate the functional localization, namely, the bullous parametric response map (BPRM). A total of 100 subjects, 88 patients with mild to very severe COPD and 12 control participants with normal lung functions (FEV₁/FVC % > 70%), were evaluated. Pearson’s correlations between FEV₁/FVC% and LAV%_HU-950 of severe emphysema are − 0.55 comparing to − 0.67 and − 0.62 of LAV%_HU-856 of air-trapping and LAV%_fSAD respectively. Pearson’s correlation between FEV₁/FVC% and FEV₁/FVC% predicted by the proposed model using LAD% of HU-950 and fSAD on BPRM is 0.82 (p < 0.01). The result of the Bullous Parametric Response Map (BPRM) is capable of identifying the less functional area of the lung, where the BLVR treatment is aimed at removing from a hyperinflated area of emphysematous regions.

Subtyping preserved ratio impaired spirometry (PRISm) by using quantitative HRCT imaging characteristics

BACKGROUND

Preserved Ratio Impaired Spirometry (PRISm) is defined as FEV1/FVC ≥ 70% and FEV1 < 80%pred by pulmonary function test (PFT). It has highly prevalence and is associated with increased respiratory symptoms, systemic inflammation, and mortality. However, there are few radiological studies related to PRISm. The purpose of this study was to investigate the quantitative high-resolution computed tomography (HRCT) characteristics of PRISm and to evaluate the correlation between quantitative HRCT parameters and pulmonary function parameters, with the goal of establishing a nomogram model for predicting PRISm based on quantitative HRCT.

METHODS

A prospective and continuous study was performed in 488 respiratory outpatients from February 2020 to February 2021. All patients underwent both deep inspiratory and expiratory CT examinations, and received pulmonary function test (PFT) within 1 month. According to the exclusion criteria and Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification standard, 94 cases of normal pulmonary function, 51 cases of PRISm and 48 cases of mild to moderate chronic obstructive lung disease (COPD) were included in the study. The lung parenchyma, parametric response mapping (PRM), airway and vessel parameters were measured by automatic segmentation software (Aview). One-way analysis of variance (ANOVA) was used to compare the differences in clinical features, pulmonary function parameters and quantitative CT parameters. Spearman rank correlation analysis was used to evaluate the correlation between CT quantitative index and pulmonary function parameters. The predictors were obtained by binary logistics regression analysis respectively in normal and PRISm as well as PRISm and mild to moderate COPD, and the nomogram model was established.

RESULTS

There were significant differences in pulmonary function parameters among the three groups (P < 0.001). The differences in pulmonary parenchyma parameters such as emphysema index (EI), pixel indices-1 (PI-1) and PI-15 were mainly between mild to moderate COPD and the other two groups. The differences of airway parameters and pulmonary vascular parameters were mainly between normal and the other two groups, but were not found between PRISm and mild to moderate COPD. Especially there were significant differences in mean lung density (MLD) and the percent of normal in PRM (PRM^Normal) among the three groups. Most of the pulmonary quantitative CT parameters had mild to moderate correlation with pulmonary function parameters. The predictors of the nomogram model using binary logistics regression analysis to distinguish normal from PRISm were smoking, MLD, the percent of functional small airways disease (fSAD) in PRM (PRM^fSAD) and Lumen area. It had a good goodness of fit (χ² = 0.31, P < 0.001) with the area under curve (AUC) value of 0.786. The predictor of distinguishing PRISm from mild to moderate COPD were PRM^Emph (P < 0.001, AUC = 0.852).

CONCLUSIONS

PRISm was significantly different from subjects with normal pulmonary function in small airway and vessel lesions, which was more inclined to mild to moderate COPD, but there was no increase in pulmonary parenchymal attenuation. The nomogram based on quantitative HRCT parameters has good predictive value and provide more objective evidence for the early screening of PRISm.

Artificial Intelligence has Similar Performance to Subjective Assessment of Emphysema Severity on Chest CT

RATIONALE AND OBJECTIVES

To compare an artificial intelligence (AI)-based prototype and subjective grading for predicting disease severity in patients with emphysema.

METHODS

Our IRB approved HIPAA-compliant study included 113 adults (71±8 years; 47 females, 66 males) who had both non-contrast chest CT and pulmonary function tests performed within a span of 2 months. The disease severity was classified based on the forced expiratory volume in 1 second (FEV1 as % of predicted) into mild, moderate, and severe. 2 thoracic radiologists (RA), blinded to the clinical and AI results, graded severity of emphysema on a 5-point scale suggested by the Fleischner Society for each lobe. The whole lung scores were derived from the summation of lobar scores. Thin-section CT images were processed with the AI-Rad Companion Chest prototype (Siemens Healthineers) to quantify low attenuation areas (LAA < - 950 HU) in whole lung and each lobe separately. Bronchial abnormality was assessed by both radiologists and a fully automated software (Philips Healthcare).

RESULTS

Both AI (AUC of 0.77; 95% CI: 0.68 - 0.85) and RA (AUC: 0.76, 95% CI: 0.65 - 0.84) emphysema quantification could differentiate mild, moderate, and severe disease based on FEV1. There was a strong positive correlation between AI and RA (r = 0.72 - 0.80; p <0.001). The combination of emphysema and bronchial abnormality quantification from radiologists' and AI assessment could differentiate between different severities with AUC of 0.80 - 0.82 and 0.87, respectively.

CONCLUSION

The assessed AI-prototypes can predict the disease severity in patients with emphysema with the same predictive value as the radiologists.

Identifying a Heart Rate Recovery Criterion After a 6-Minute Walk Test in COPD

BACKGROUND

Slow heart rate recovery (HRR) after exercise is associated with autonomic dysfunction and increased mortality. What HRR criterion at 1-minute after a 6-minute walk test (6MWT) best defines pulmonary impairment?.

STUDY DESIGN AND METHODS

A total of 5008 phase 2 COPDGene (NCT00608764) participants with smoking history were included. A total of 2127 had COPD and, of these, 385 were followed-up 5-years later. Lung surgery, transplant, bronchiectasis, atrial fibrillation, heart failure and pacemakers were exclusionary. HR was measured from pulse oximetry at end-walk and after 1-min seated recovery. A receiver operator characteristic (ROC) identified optimal HRR cut-off. Generalized linear regression determined HRR association with spirometry, chest CT, symptoms and exacerbations.

RESULTS

HRR after 6MWT (bt/min) was categorized in quintiles: ≤5 (23.0% of participants), 6-10 (20.7%), 11-15 (18.9%), 16-22 (18.5%) and ≥23 (18.9%). Compared to HRR≤5, HRR≥11 was associated with (p<0.001): lower pre-walk HR and 1-min post HR; greater end-walk HR; greater 6MWD; greater FEV1%pred; lower airway wall area and wall thickness. HRR was positively associated with FEV1%pred and negatively associated with airway wall thickness. An optimal HRR ≤10 bt/min yielded an area under the ROC curve of 0.62 (95% CI 0.58-0.66) for identifying FEV1<30%pred. HRR≥11 bt/min was the lowest HRR associated with consistently less impairment in 6MWT, spirometry and CT variables. In COPD, HRR≤10 bt/min was associated with (p<0.001): ≥2 exacerbations in the previous year (OR=1.76[1.33-2.34]); CAT≥10 (OR=1.42[1.18-1.71]); mMRC≥2 (OR=1.42[1.19-1.69]); GOLD 4 (OR=1.98[1.44-2.73]) and GOLD D (OR=1.51[1.18-1.95]). HRR≤10 bt/min was predicted COPD exacerbations at 5-year follow-up (RR=1.83[1.07-3.12], P=0.027).

CONCLUSION

HRR≤10 bt/min after 6MWT in COPD is associated with more severe expiratory flow limitation, airway wall thickening, worse dyspnoea and quality of life, and future exacerbations, suggesting that an abnormal HRR≤10 bt/min after a 6MWT may be used in a comprehensive assessment in COPD for risk of severity, symptoms and future exacerbations.

CT-defined emphysema in COPD patients and risk for change in desaturation status in 6-min walk test

BACKGROUND

Emphysema and exercise induced desaturation (EID) are both related to poorer COPD prognosis. More knowledge of associations between emphysema and desaturation is needed for more efficient disease management.

RESEARCH QUESTION

Is emphysema a risk factor for both new and repeated desaturation, and is emphysema of more or less importance than other known risk factors?

METHODS

283 COPD patients completed a 6-min walk test (6MWT) at baseline and one year later in the Bergen COPD cohort study 2006-2011. Degree of emphysema was assessed as percent of low attenuation areas (%LAA) under -950 Hounsfield units using high-resolution computed tomography at baseline. We performed multinomial logistic regression analysis, receiver operating curves (ROC) and area under the curve (AUC) estimations. Dominance analysis was used to rank emphysema and risk factors in terms of importance.

RESULTS

A one percent increase in %LAA increases the relative risk (RR) of new desaturation by 10 % (RR 1.1 (95%CI 1.1, 1.2)) and for repeated desaturation by 20 % (RR 1.2 (95%CI 1.1, 1.3)). Compared with other important desaturation risk factors, %LAA ranked as number one in the dominance analysis, accounting for 50 % and 37 % of the predicted variance for new and repeated desaturators, respectively. FEV₁% predicted accounted for 9 % and 24 %, and resting SpO₂ accounted for 22 % and 21 % for new and repeated desaturation.

CONCLUSION

Emphysema increases the risk of developing and repeatedly experiencing EID. Emphysema seems to be a more important risk factor for desaturation than FEV₁% predicted and resting saturation.

Imbalance Between Injury and Defense in the COPD Emphysematous Phenotype

The chronic obstructive pulmonary disease (COPD) emphysematous phenotype is characterized by destruction of lung tissue structure. Patients with this phenotype usually present with typical emphysema-like changes on chest computed Tomography CT, experience higher mortality and poorer prognosis, and are insensitive to routine pharmacological COPD therapy. However, the pathogenesis for the COPD emphysematous phenotype remains unclear, resulting in diagnostic and therapeutic challenges. The imbalance between injury and defense mechanisms is essential in the progression of many pulmonary diseases. Thus, in this review, we focus on the pathogenesis of the COPD emphysematous phenotype and discuss the pathophysiological processes involved in disease progression, from the perspective of injury and defense imbalance.

The CT pulmonary vascular parameters and disease severity in COPD patients on acute exacerbation: a correlation analysis

BACKGROUND

It is necessary to analyze the CT pulmonary vascular parameters and disease severity in chronic obstructive pulmonary disease (COPD) patients to provide evidence support for the management of COPD.

METHODS

COPD patients on acute exacerbation admitted to our hospital from COPD patients from January 2019 to March 2020 was selected. The characteristics and ratio of the cross-sectional area (CSA) of small pulmonary vessels to the total area of the lung field, and the ratio of pulmonary artery and aorta (PA/A) cross-sectional diameter in patients with COPD were analyzed.

RESULTS

A total of 128 COPD patients were included. There were significant differences in the duration of COPD, smoking history, the PaO2, PaCO2, pH, and FEV1, FVC and FEV1/FVC among COPD patients with different severity (all p < 0.05). The duration of COPD, smoking, PaO2, PaCO2, CSA and PA/A were correlated with the COPD severity (all p < 0.05). Both CSA, PA/A were correlated with post BD FEV1 (all p < 0.05). The cutoff value of CSA and PA/A for the diagnosis of severe COPD was 0.61 and 0.87 respectively, and the AUC of CSA and PA/A for the diagnosis of severe COPD was 0.724 and 0.782 respectively.

CONCLUSIONS

Patients with CSA ≤ 0.61 and PA/A ≥ 0.87 may have higher risks for severe COPD, and more studies are needed in the future to further elucidate the management of COPD.

Using Novel Computed Tomography Analysis to Describe the Contribution and Distribution of Emphysema and Small Airways Disease in Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation, caused by emphysema and small airways disease (SAD). Computed tomography (CT) coupled with image analysis enables the quantification of these abnormalities; however, the optimum method for doing so has not been determined.Objectives: This study aims to compare two CT quantitative analysis techniques, disease probability measure (DPM) and parametric response mapping (PRM), and assess their relationship with specific physiological measures of SAD.Methods: Subjects with mild to moderate COPD, never smokers, and healthy ex-smokers were recruited. Each had airway oscillometry and multiple-breath nitrogen washout, measuring peripheral airway resistance, peripheral airway reactance, and acinar airway inhomogeneity. Subjects also had an inspiratory and expiratory chest CT, with DPM and PRM analysis performed by coregistering images and classifying each voxel as normal, emphysema, or nonemphysematous gas trapping related to SAD.Results: Thirty-eight subjects with COPD, 18 never smokers, and 23 healthy ex-smokers were recruited. There were strong associations between DPM and PRM analysis when measuring gas trapping (ρ = 0.87; P < 0.001) and emphysema (ρ = 0.99; P < 0.001). DPM assigned significantly more voxels as emphysema and gas trapped than PRM (P < 0.001). Both techniques showed significantly greater emphysema and gas trapping in subjects with COPD than in never smokers and ex-smokers (P < 0.001). All CT measures had significant associations with peripheral airway resistance and reactance, with disease probability measure of nonemphysematous gas trapping related to SAD having the strongest independent association with peripheral airway resistance (β = 0.42; P = 0.001) and peripheral airway reactance (β = 0.41; P = 0.001). Emphysema measures had the strongest associations with acinar airway inhomogeneity (β = 0.35-0.38).Conclusions: These results provide further validation for the use of DPM/PRM analysis in COPD by demonstrating significant relationships with specific physiological measures of SAD.

Extracellular Vesicles as Mediators of Cellular Cross Talk in the Lung Microenvironment

The human lung is a complex tissue subdivided into several regions that differ in size, function, and resident cell types. Despite years of intensive research, we still do not fully understand the cross talk between these different regions and diverse cell populations in the lung and how this is altered in the development of chronic respiratory disease. The discovery of extracellular vesicles (EVs), small membrane vesicles released from cells for intercellular communication, has added another layer of complexity to cellular cross talk in the complex lung microenvironment. EVs from patients with chronic obstructive pulmonary disease, asthma, or sarcoidosis have been shown to carry microRNAs, proteins, and lipids that may contribute to inflammation or tissue degeneration. Here, we summarize the contribution of these small vesicles in the interplay of several different cell types in the lung microenvironment, with a focus on the development of chronic respiratory diseases. Although there are already many studies demonstrating the adverse effects of EVs in the diseased lung, we still have substantial knowledge gaps regarding the concrete role of EV involvement in lung disease, which should be addressed in future studies.

Assessing pulmonary hypertension in COPD. Is there a role for computed tomography?

Pulmonary hypertension (PH) is a common complication of chronic obstructive pulmonary disease (COPD) and is associated with increased morbidity and mortality. Reference standard method to diagnose PH is right heart catheterization. Several non-invasive imaging techniques have been employed in the detection of PH. Among them, computed tomography (CT) is the most commonly used for phenotyping and detecting complications of COPD. Several CT findings have also been described in patients with severe PH. Nevertheless, CT analysis is currently based on visual findings which can lead to reproducibility failure. Therefore, there is a need for quantification in order to assess objective criteria. In this review, progresses in automated analyses of CT parameters and their values in predicting PH and COPD outcomes are presented.

The importance of CT quantitative evaluation of emphysema in lung cancer screening cohort with negative findings by visual evaluation

INTRODUCTION

One-stop quantitative evaluation of emphysema and lung nodule in lung cancer screening is very important for patient.

OBJECTIVE

To evaluate the quantitative emphysema in the large-sample low-dose CT lung cancer screening cohort with negative CT findings by subjective visual assessment.

METHODS

One thousand, two hundred and thirty-one participants with negative visual evaluation were included in this retrospective study. The lungs were automatically segmented and the following were calculated: total lung volume (TLV), total emphysema volume (TEV), emphysema index (EI), 15th percentile lung density and mean lung density. EI ≥6% was defined as emphysema. The quantitative parameters were compared between different genders and ages. The quantitative parameters and risk factors were compared between emphysema and non-emphysema groups.

RESULTS

The proportion of smokers, TLV, TEV and EI of men were greater than that of women (P < 0.001). No correlation was found between age and volumes; the TEV and EI of people older than 60 years were greater than those younger than 60 years (P < 0.05) by age categorisation. One hundred and two participants showed emphysema, accounting for 8.29%. The incidence of emphysema in men was greater than that in women in total (P < 0.05). All the CT quantitative parameters were significantly different between emphysema and non-emphysema groups. The ratio of male, secondhand smoke exposure and chronic bronchitis history was greater in emphysema than that in the non-emphysema group (P < 0.05).

CONCLUSION

CT quantitative emphysema evaluation is recommended in people older than 60 years, especially in males, providing more precise information, aiding the early diagnosis of emphysema and informing early intervention.

Role of medical and molecular imaging in COPD

Chronic obstructive pulmonary disease (COPD) is expected to climb on the podium of the leading causes of mortality worldwide in the upcoming decade. Clinical diagnosis of COPD has classically relied upon detecting irreversible airflow obstruction on pulmonary function testing as a global assessment of pulmonary physiology. However, the outcome is still not favorable to decrease mortality due to COPD. Progress made in both medical and molecular imaging fields are beginning to offer additional tools to address this clinical problem. This review aims to describe medical and molecular imaging modalities used to diagnose COPD and to select patients for appropriate treatments and to monitor response to therapy.

1H-NMR-based metabolic profiling of healthy individuals and high-resolution CT-classified phenotypes of COPD with treatment of tiotropium bromide

Background

Heterogeneity of COPD results in different therapeutic effects for different patients receiving the same treatment. COPD patients need to be individually treated according to their own characteristics. The purpose of this study was to explore the differences in different CT phenotypic COPD by molecular metabolites through the use of metabolomics.

Methods

According to the characteristics of CT imaging, 42 COPD patients were grouped into phenotype E (n=20) or phenotype M (n=24). Each COPD patient received tiotropium bromide powder for inhalation for a therapeutic period of 3 months. All subjects were assigned into phenotype E in pre-therapy (EB, n=20), phenotype E in post-therapy (EA, n=20), phenotype M in pre-therapy (MB, n=22), phenotype M in post-therapy (MA, n=22), or normal control (N, n=24). The method of metabolomics based on ¹H nuclear magnetic resonance (¹H-NMR) was used to compare the changes in serum metabolites between COPD patients and normal controls and between different phenotypes of COPD patients in pre- and post-therapy.

Results

Patients with COPD phenotype E responded better to tiotropium bromide than patients with COPD phenotype M in terms of pulmonary function and COPD assessment test scores. There were differences in metabolites in COPD patients vs normal control people. Differences were also observed between different COPD phenotypic patients receiving the treatment in comparison with those who did not receive treatment. The changes of metabolites involved lactate, phenylalanine, fructose, glycine, asparagine, citric acid, pyruvic acid, proline, acetone, ornithine, lipid, pyridoxine, maltose, betaine, lipoprotein, and so on. These identified metabolites covered the metabolic pathways of amino acids, carbohydrates, lipids, genetic materials, and vitamin.

Conclusion

The efficacy of tiotropium bromide on COPD phenotype E is better than that of phenotype M. Metabolites detected by ¹H-NMR metabolomics have potentialities of differentiation of COPD and healthy people, discrimination of different COPD phenotypes, and giving insight into the individualized treatment of COPD.

Impact of radiologically stratified exacerbations: insights into pneumonia aetiology in COPD

Background

COPD patients have increased risk of developing pneumonia, which is associated with poor outcomes. It can be symptomatically indistinguishable from exacerbations, making diagnosis challenging. Studies of pneumonia in COPD have focused on hospitalised patients and are not representative of the ambulant COPD population. Therefore, we sought to determine the incidence and aetiology of acute exacerbation events with evidence of pneumonic radiographic infiltrates in an outpatient COPD cohort.

Methods

One hundred twenty-seven patients with moderate to very severe COPD aged 42–85 years underwent blood and sputum sampling over one year, at monthly stable visits and within 72 h of exacerbation symptom onset. 343 exacerbations with chest radiographs were included.

Results

20.1% of exacerbations had pneumonic infiltrates. Presence of infiltrate was highly seasonal (Winter vs summer OR 3.056, p = 0.027). In paired analyses these exacerbation events had greater increases in systemic inflammation. Bacterial detection rate was higher in the pneumonic group, with Haemophilus influenzae the most common bacteria in both radiological groups. Viral detection and sputum microbiota did not differ with chest radiograph appearance.

Conclusions

In an outpatient COPD cohort, pneumonic infiltrates at exacerbation were common, and associated with more intense inflammation. Bacterial pathogen detection and lung microbiota were not distinct, suggesting that exacerbations and pneumonia in COPD share common infectious triggers and represent a continuum of severity rather than distinct aetiological events.

Trial registration

Trial registration Number: NCT01360398.

Electronic supplementary material

The online version of this article (10.1186/s12931-018-0842-8) contains supplementary material, which is available to authorized users.