Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes

Development and validation of a mortality risk prediction model for chronic obstructive pulmonary disease: a cross-sectional study using probabilistic graphical modelling

Background

Chronic Obstructive Pulmonary Disease (COPD) is a leading cause of mortality. Predicting mortality risk in patients with COPD can be important for disease management strategies. Although all-cause mortality predictors have been developed previously, limited research exists on factors directly affecting COPD-specific mortality.

Methods

In a retrospective study, we used probabilistic graphs to analyse clinical cross-sectional data (COPDGene cohort), including demographics, spirometry, quantitative chest imaging, and symptom features, as well as gene expression data. COPDGene recruited current and former smokers, aged 45-80 years with >10 pack-years smoking history, from across the USA (Phase 1, 11/2007-4/2011) and invited them for a follow-up visit (Phase 2, 7/2013-7/2017). ECLIPSE cohort recruited current and former smokers (COPD patients and controls from USA and Europe), aged 45-80 with smoking history >10 pack-years (12/2005-11/2007). We applied graphical models on multi-modal data COPDGene Phase 1 participants to identify factors directly affecting all-cause and COPD-specific mortality (primary outcomes); and on Phase 2 follow-up cohort to identify additional molecular and social factors affecting mortality. We used penalized Cox regression with features selected by the causal graph to build VAPORED, a mortality risk prediction model. VAPORED was compared to existing scores (BODE: BMI, airflow obstruction, dyspnoea, exercise capacity; ADO: age, dyspnoea, airflow obstruction) on the ability to rank individuals by mortality risk, using four evaluation metrics (concordance, concordance probability estimate (CPE), cumulative/dynamic (C/D) area under the receiver operating characteristic curve (AUC), and integrated C/D AUC). The results were validated in ECLIPSE.

Findings

Graphical models, applied on the COPDGene Phase 1 samples (n = 8610), identified 11 and 7 variables directly linked to all-cause and COPD-specific mortality, respectively. Although many appear in both models, non-lung comorbidities appear only in the all-cause model, while forced vital capacity (FVC %predicted) appears in COPD-specific mortality model only. Additionally, the graph model of Phase 2 data (n = 3182) identified internet access, CD4 T cells and platelets to be linked to lower mortality risk. Furthermore, using the 7 variables linked to COPD-specific mortality (forced expiratory volume in 1 s/forced vital capacity (FEV1/FVC) ration, FVC %predicted, age, history of pneumonia, oxygen saturation, 6-min walk distance, dyspnoea) we developed VAPORED mortality risk score, which we validated on the ECLIPSE cohort (3-yr all-cause mortality data, n = 2312). VAPORED performed significantly better than ADO, BODE, and updated BODE indices in predicting all-cause mortality in ECLIPSE in terms of concordance (VAPORED [0.719] vs ADO [0.693; FDR p-value 0.014], BODE [0.695; FDR p-value 0.020], and updated BODE [0.694; FDR p-value 0.021]); CPE (VAPORED [0.714] vs ADO [0.673; FDR p-value <0.0001], BODE [0.662; FDR p-value <0.0001], and updated BODE [0.646; FDR p-value <0.0001]); 3-year C/D AUC (VAPORED [0.728] vs ADO [0.702; FDR p-value 0.017], BODE [0.704; FDR p-value 0.021], and updated BODE [0.703; FDR p-value 0.024]); integrated C/D AUC (VAPORED [0.723] vs ADO [0.698; FDR p-value 0.047], BODE [0.695; FDR p-value 0.024], and updated BODE [0.690; FDR p-value 0.021]). Finally, we developed a web tool to help clinicians calculate VAPORED mortality risk and compare it to ADO and BODE predictions.

Interpretation

Our work is an important step towards improving our identification of high-risk patients and generating hypotheses of potential biological mechanisms and social factors driving mortality in patients with COPD at the population level. The main limitation of our study is the fact that the analysed datasets consist of older people with extensive smoking history and limited racial diversity. Thus, the results are relevant to high-risk individuals or those diagnosed with COPD and the VAPORED score is validated for them.

Funding

This research was supported by NIH [NHLBI, NLM]. The COPDGene study is supported by the COPD Foundation, through grants from AstraZeneca, Bayer Pharmaceuticals, Boehringer Ingelheim, Genentech, GlaxoSmithKline, Novartis, Pfizer and Sunovion.

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.

A Multicenter Study of COPD and Cognitive Impairment: Unraveling the Interplay of Quantitative CT, Lung Function, HIF-1α, and Clinical Variables

Purpose

The exact link between cognitive impairment (CI) and chronic obstructive pulmonary disease (COPD) is still limited. Thus, we aim to find the relationship and interaction of quantitative CT (QCT), lung function, HIF-1α, and clinical factors with the development of CI among COPD patients.

Patients and Methods

A cross-sectional multicentre study was conducted from January 2022 to December 2023. We collected clinical data, spirometry, CT images, and venous blood samples from 114 COPD participants. Cognitive impairment assessment using the Montreal Cognitive Assessment Indonesian version (MoCA-Ina) with a cutoff value 26. The QCT analysis consists of lung density, airway wall thickness, pulmonary artery-to-aorta ratio (PA:A), and pectoralis muscles using 3D Slicer software. Serum HIF-1α analysis was performed using ELISA.

Results

We found significant differences between %LAA-950, age, COPD duration, BMI, FEV1 pp, and FEV1/FVC among GOLD grades I-IV. Only education duration was found to correlate with CI (r = 0.40; p < 0.001). We found no significant difference in HIF-1α among GOLD grades (p = 0.149) and no correlation between HIF-1α and CI (p = 0.105). From multiple linear regression, we observed that the MoCA-Ina score was influenced mainly by %LAA-950 (p = 0.02) and education duration (p = 0.01). The path analysis model showed both %LAA and education duration directly and indirectly through FEV1 pp contributing to CI.

Conclusion

We conclude that the utilization of QCT parameters is beneficial as it can identify abnormalities and contribute to the development of CI, indicating its potential utility in clinical decision-making. The MoCA-Ina score in COPD is mainly affected by %LAA-950 and education duration. Contrary to expectations, this study concludes that HIF-1α does not affect CI among COPD patients.

CT Chest Imaging Using Normalized Join-Count: Predicting Emphysema Progression in the CanCOLD Study

Background Pre-existing emphysema is recognized as an indicator of future worsening in patients with chronic obstructive pulmonary disease (COPD) when observed through CT imaging. However, it remains uncertain whether additional factors, such as the spatial compactness of CT emphysema, might also serve as predictors of disease progression. Purpose To evaluate the relationship between the compactness of CT emphysema voxels and emphysema progression. Materials and Methods This secondary analysis uses data from the prospective Canadian Cohort Obstructive Lung Disease (CanCOLD) study, examining CT images obtained in participants with and without COPD at baseline and a 3-year follow-up time point (November 2009 to November 2018). Measurements of forced expiratory volume in first second of expiration (FEV1) and diffusing capacity of lung for carbon monoxide (DLco) were collected. The normalized join-count (NJC) measurement from baseline CT images and lung density (LD) changes were analyzed. Emphysema progression was defined as an annualized LD change of less than half an SD below the mean of the participants without COPD with no smoking history. Multivariable linear and logistic regression models were used to assess the association between baseline CT NJC measurements and the annualized change in LD, FEV1, DLco, and emphysema progression versus nonprogression. Results A total of 524 participants (mean age, 66 years ± 10 [SD]; 293 male) (FEV1 percent predicted, 88% ± 19; FEV1/FVC, 67% ± 9; DLco percent predicted, 105% ± 25) were analyzed, 187 (36%) of whom had COPD. CT NJC was associated with the annualized change in LD (P < .001), FEV1 (P = .02), and DLco (P = .01). Additionally, CT NJC predicted emphysema progression versus nonprogression (odds ratio, 2.24; 95% CI: 1.37, 3.50; P < .001). Conclusion The spatial distribution, or "compactness," of CT emphysema voxels predicted emphysema progression in individuals with and without COPD. ClinicalTrials.gov Identifier: NCT00920348 © RSNA, 2024 Supplemental material is available for this article.

Computed tomography (CT) quantitative assessment of single lobe emphysema correlates with chronic obstructive pulmonary disease (COPD) severity: a cross-sectional study with retrospective data collection

Background

In the past, many researchers have studied the correlation between quantitative parameters of computed tomography (CT) and parameters of pulmonary function test (PFT) in patients with chronic obstructive pulmonary disease (COPD) with good results. Most of these studies have focused on the whole-lung level. In this study, we analyzed the biphasic CT lung volume parameters and the percentage of emphysema volume in different lobes of the lungs of patients with different grades of COPD and assessed their relationship with different lung function indices.

Methods

We retrospectively collected patients who underwent PFTs at The First Affiliated Hospital of Guangzhou Medical University from 1 July 2019 to 27 January 2020, and underwent chest respiratory dual-phase CT scans within 1 week, including 112 non-COPD patients and 297 COPD patients. We quantified the biphasic CT lung volume parameters and the percentage of emphysema volume in different lobes using a pulmonary image analysis tool. One-way analysis of variance (ANOVA) and Kruskal-Wallis H method were used to compare the quantitative CT parameters of each lung lobe in different groups. The correlation between quantitative CT parameters of different lung lobes and lung function indices was assessed using multiple linear regression.

Results

Among the 3 biphasic CT lung volume parameters, only volume change/inspiratory lung volume (∆LV/LVin) in the non-COPD control, mildly to moderately severe, and severe to extremely severe groups had statistical differences in each lobe level (all P<0.05). Correlation was significant between LVin and different lung function indices and between low attenuation areas percent below the threshold of -950 in the inspiratory phase [low attenuation area below -950 in the inspiratory phase (%LAA-950in)] and lung function indices in the left lower lobe (all P<0.05). There was statistically significant correlation between expiratory lung volume and ∆LV/LVin and lung function indices in the right lower lung (all P≤0.001). In the remaining lobes, LVin, expiratory lung volume, ∆LV/LVin, and %LAA-950in correlated with only some of the lung function indices.

Conclusions

The percentage of emphysema volume did not differ between lobes in the non-COPD control and severe to extremely severe COPD populations. LVin and %LAA-950in in the left upper lobe, expiratory lung volume and ∆LV/LVin in the right lower lobe were more reflective of the changes in lung function indices of the patients, whereas the correlation of the 3 biphasic CT lung volume parameters and the percentage of emphysema volume in the upper lobes of both lungs and the right middle lung with lung function indices was unclear.

The disruptive effects of COPD exacerbation-associated factors on epithelial repair responses

Introduction

Exacerbations of chronic obstructive pulmonary disease (COPD) increase mortality risk and can lead to accelerated loss of lung function. The increased inflammatory response during exacerbations contributes to worsening of airflow limitation, but whether it also impacts epithelial repair is unclear. Therefore, we studied the effect of the soluble factor micro-environment during COPD exacerbations on epithelial repair using an exacerbation cocktail (EC), composed of four factors that are increased in COPD lungs during exacerbations (IL-1β, IL-6, IL-8, TNF-α).

Methods

Mouse organoids (primary CD31-CD45-Epcam+ cells co-cultured with CCL206 fibroblasts) were used to study epithelial progenitor behavior. Mature epithelial cell responses were evaluated using mouse precision cut lung slices (PCLS). The expression of epithelial supportive factors was assessed in CCL206 fibroblasts and primary human lung fibroblasts.

Results

EC exposure increased the number and size of organoids formed, and upregulated Lamp3, Muc5ac and Muc5b expression in day 14 organoids. In PCLS, EC imparted no effect on epithelial marker expression. Pre-treatment of CCL206 fibroblasts with EC was sufficient to increase organoid formation. Additionally, the expression of Il33, Tgfa and Areg was increased in CCL206 fibroblasts from EC treated organoids, but these factors individually did not affect organoid formation or size. However, TGF-α downregulated Foxj1 expression and upregulated Aqp5 expression in day 14 organoids.

Conclusions

EC exposure stimulates organoid formation and growth, but it alters epithelial differentiation. EC changes the epithelial progenitor support function of fibroblasts which contributes to observed effects on epithelial progenitors.

Obstructive Sleep Apnea Effects on Chronic Airway Disease Exacerbations-Missed Opportunities for Improving Outcomes in Chronic Obstructive Pulmonary Disease and Asthma

In patients with chronic obstructive pulmonary disease (COPD) and asthma, exacerbations determine the natural history of both diseases. Patients with both respiratory diseases who suffer from obstructive sleep apnea (OSA) as a comorbidity (overlap syndromes) have a higher risk of exacerbations and hospitalization. In cases of OSA/COPD and OSA/asthma, continuous positive airway pressure treatment is indicated. Adequate adherence to therapy appears to reduce exacerbations and their severity, especially in OSA/COPD overlap. However, there is a lack of randomized trials that definitively demonstrate this evidence.

Polygenic and transcriptional risk scores identify chronic obstructive pulmonary disease subtypes

Rationale

Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear.

Objectives

Define high-risk COPD subtypes using both genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

Methods

We defined high-risk groups based on PRS and TRS quantiles by maximizing differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets. We tested multivariable associations of subgroups with clinical outcomes and compared protein-protein interaction networks and drug repurposing analyses between high-risk groups.

Measurements and Main Results

We examined two high-risk omics-defined groups in non-overlapping test sets (n=1,133 NHW COPDGene, n=299 African American (AA) COPDGene, n=468 ECLIPSE). We defined "High activity" (low PRS/high TRS) and "severe risk" (high PRS/high TRS) subgroups. Participants in both subgroups had lower body-mass index (BMI), lower lung function, and alterations in metabolic, growth, and immune signaling processes compared to a low-risk (low PRS, low TRS) reference subgroup. "High activity" but not "severe risk" participants had greater prospective FEV 1 decline (COPDGene: -51 mL/year; ECLIPSE: - 40 mL/year) and their proteomic profiles were enriched in gene sets perturbed by treatment with 5-lipoxygenase inhibitors and angiotensin-converting enzyme (ACE) inhibitors.

Conclusions

Concomitant use of polygenic and transcriptional risk scores identified clinical and molecular heterogeneity amongst high-risk individuals. Proteomic and drug repurposing analysis identified subtype-specific enrichment for therapies and suggest prior drug repurposing failures may be explained by patient selection.

Differential decline of lung function in COPD patients according to structural abnormality in chest CT

Background

Different progressions or prognoses of chronic obstructive pulmonary disease (COPD) have been reported according to structural abnormalities based on chest computed tomography (CT). This study aimed to investigate whether different structural abnormalities independently affect annual lung function changes and clinical prognosis in patients with COPD.

Methods

This longitudinal multicenter observational study was conducted using the KOCOSS cohort (NCT02800499) database in Korea from January 2012 to December 2019. For COPD patients with chest CT findings at baseline enrolment and longitudinal spirometric data, annual forced expiratory volume in 1 s (FEV1) decline rate (mL/year) and clinical outcomes were compared according to structural abnormalities, including emphysema, bronchiectasis (BE), and tuberculosis-destroyed lung (TDL). We estimated the adjusted annual FEV1 changes using a mixed-effect linear regression model.

Results

Among the enrolled 237 patients, 152 showed structural abnormalities. Emphysema, BE, and TDL were observed in 119 (78.3%), 28 (18.4%), and 27 (17.8%) patients, respectively. The annual decline in FEV1 was faster in COPD patients with structural abnormalities than those without (β = -70.6 mL/year, P-value = 0.039). BE/TDL-dominant or emphysema-dominant structural abnormality contributed to an accelerated annual FEV1 decline compared to no structural abnormality (BE/TDL-dominant, β = -103.7 mL/year, P-value = 0.043; emphysema-dominant, β = -84.1 mL/year, P-value = 0.018). Structural abnormalities made no significant differences in acute exacerbation rate and mortality.

Conclusion

The lung function decline rate in COPD differed according to structural abnormalities on CT. These findings may suggest that more focus should be placed on earlier intervention or regular follow-up with spirometry in COPD patients with BE or TDL on chest CT.

Association of Acute Respiratory Disease Events with Quantitative Interstitial Abnormality Progression at CT in Individuals with a History of Smoking

Background Acute respiratory disease (ARD) events are often thought to be airway-disease related, but some may be related to quantitative interstitial abnormalities (QIAs), which are subtle parenchymal abnormalities on CT scans associated with morbidity and mortality in individuals with a smoking history. Purpose To determine whether QIA progression at CT is associated with ARD and severe ARD events in individuals with a history of smoking. Materials and Methods This secondary analysis of a prospective study included individuals with a 10 pack-years or greater smoking history recruited from multiple centers between November 2007 and July 2017. QIA progression was assessed between baseline (visit 1) and 5-year follow-up (visit 2) chest CT scans. Episodes of ARD were defined as increased cough or dyspnea lasting 48 hours and requiring antibiotics or corticosteroids, whereas severe ARD episodes were those requiring an emergency room visit or hospitalization. Episodes were recorded via questionnaires completed every 3 to 6 months. Multivariable logistic regression and zero-inflated negative binomial regression models adjusted for comorbidities (eg, emphysema, small airway disease) were used to assess the association between QIA progression and episodes between visits 1 and 2 (intercurrent) and after visit 2 (subsequent). Results A total of 3972 participants (mean age at baseline, 60.7 years ± 8.6 [SD]; 2120 [53.4%] women) were included. Annual percentage QIA progression was associated with increased odds of one or more intercurrent (odds ratio [OR] = 1.29 [95% CI: 1.06, 1.56]; P = .01) and subsequent (OR = 1.26 [95% CI: 1.05, 1.52]; P = .02) severe ARD events. Participants in the highest quartile of QIA progression (≥1.2%) had more frequent intercurrent ARD (incidence rate ratio [IRR] = 1.46 [95% CI: 1.14, 1.86]; P = .003) and severe ARD (IRR = 1.79 [95% CI: 1.18, 2.73]; P = .006) events than those in the lowest quartile (≤-1.7%). Conclusion QIA progression was independently associated with higher odds of severe ARD events during and after radiographic progression, with higher frequency of intercurrent severe events in those with faster progression. Clinical trial registration no. NCT00608764 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Little in this issue.

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.

Predicting Postoperative Lung Function in Patients with Lung Cancer Using Imaging Biomarkers

There have been previous studies conducted to predict postoperative lung function with pulmonary function tests (PFTs). Computing tomography (CT) can quantitatively measure small airway walls' thickness, lung volume, pulmonary vessel volume, and emphysema area, which reflect the severity of respiratory diseases. These measurements are considered imaging biomarkers. This study aimed to predict postoperative lung function with imaging biomarkers. A retrospective analysis of 79 patients with lung cancer who had undergone lung surgery was completed. Postoperative lung function measured by forced expiratory volume in one second (FEV1) was defined as an outcome. Preoperative clinico-pathological parameters and imaging biomarkers representing airway walls' thickness, severity of emphysema, total lung volume, and pulmonary vessel volume were measured quantitatively in chest CT by an automated segmentation software, AVIEW COPD. Pi1 was defined as the first percentile along the histogram of lung attenuation that represents the degree of emphysema. Wafw was defined as the airway thickness, which was calculated by the full-width at half-maximum method. Logistic and linear regressions were used to assess these variables. If the actual postoperative FEV1 was higher than the postoperative FEV1 projected by a formula, the group was considered to be preserved. Among the 79 patients, 16 of the patients were grouped as a non-preserved group, and 63 of them were grouped as a preserved group. The patients in the preserved FEV1 group had a higher vessel volume than the non-preserved group. Pi1 and Wafw were independent predictors of postoperative lung function. Imaging biomarkers can be considered significant variables in predicting postoperative lung function in patients with lung cancer.

Evaluation of retrieval accuracy and visual similarity in content-based image retrieval of chest CT for obstructive lung disease

The aim of our study was to assess the performance of content-based image retrieval (CBIR) for similar chest computed tomography (CT) in obstructive lung disease. This retrospective study included patients with obstructive lung disease who underwent volumetric chest CT scans. The CBIR database included 600 chest CT scans from 541 patients. To assess the system performance, follow-up chest CT scans of 50 patients were evaluated as query cases, which showed the stability of the CT findings between baseline and follow-up chest CT, as confirmed by thoracic radiologists. The CBIR system retrieved the top five similar CT scans for each query case from the database by quantifying and comparing emphysema extent and size, airway wall thickness, and peripheral pulmonary vasculatures in descending order from the database. The rates of retrieval of the same pairs of query CT scans in the top 1-5 retrievals were assessed. Two expert chest radiologists evaluated the visual similarities between the query and retrieved CT scans using a five-point scale grading system. The rates of retrieving the same pairs of query CTs were 60.0% (30/50) and 68.0% (34/50) for top-three and top-five retrievals. Radiologists rated 64.8% (95% confidence interval 58.8-70.4) of the retrieved CT scans with a visual similarity score of four or five and at least one case scored five points in 74% (74/100) of all query cases. The proposed CBIR system for obstructive lung disease integrating quantitative CT measures demonstrated potential for retrieving chest CT scans with similar imaging phenotypes. Further refinement and validation in this field would be valuable.

Lung Structure and Risk of Sleep Apnea in SPIROMICS

Rationale

The SubPopulations and InteRmediate Outcome Measures in COPD Study (SPIROMICS) is a prospective cohort study that enrolled 2981 participants with the goal of identifying new chronic obstructive pulmonary disease (COPD) subgroups and intermediate markers of disease progression. Individuals with COPD and obstructive sleep apnea (OSA) experience impaired quality of life and more frequent exacerbations. COPD severity also associates with computed tomography scan-based emphysema and alterations in airway dimensions.

Objectives

The objective was to determine whether the combination of lung function and structure influences the risk of OSA among current and former smokers.

Methods

Using 2 OSA risk scores, the Berlin Sleep Questionnaire (BSQ), and the DOISNORE50 (Diseases, Observed apnea, Insomnia, Snoring, Neck circumference > 18 inches, Obesity with body mass index [BMI] > 32, R = are you male, Excessive daytime sleepiness, 50 = age ≥ 50) (DIS), 1767 current and former smokers were evaluated for an association of lung structure and function with OSA risk.

Measurements and Main Results

The study cohort's mean age was 63 years, BMI was 28 kg/m2, and forced expiratory volume in 1 second (FEV1) was 74.8% predicted. The majority were male (55%), White (77%), former smokers (59%), and had COPD (63%). A high-risk OSA score was reported in 36% and 61% using DIS and BSQ respectively. There was a 9% increased odds of a high-risk DIS score (odds ratio [OR]=1.09, 95% confidence interval [CI]:1.03-1.14) and nominally increased odds of a high-risk BSQ score for every 10% decrease in FEV1 %predicted (OR=1.04, 95%CI: 0.998-1.09). Lung function-OSA risk associations persisted after additionally adjusting for lung structure measurements (%emphysema, %air trapping, parametric response mapping for functional small airways disease, , mean segmental wall area, tracheal %wall area, dysanapsis) for DIS (OR=1.12, 95%CI:1.03-1.22) and BSQ (OR=1.09, 95%CI:1.01-1.18).

Conclusions

Lower lung function independently associates with having high risk for OSA in current and former smokers. Lung structural elements, especially dysanapsis, functional small airways disease, and tracheal %wall area strengthened the effects on OSA risk.

Machine learning slice-wise whole-lung CT emphysema score correlates with airway obstruction

OBJECTIVES

Quantitative CT imaging is an important emphysema biomarker, especially in smoking cohorts, but does not always correlate to radiologists' visual CT assessments. The objectives were to develop and validate a neural network-based slice-wise whole-lung emphysema score (SWES) for chest CT, to validate SWES on unseen CT data, and to compare SWES with a conventional quantitative CT method.

MATERIALS AND METHODS

Separate cohorts were used for algorithm development and validation. For validation, thin-slice CT stacks from 474 participants in the prospective cross-sectional Swedish CArdioPulmonary bioImage Study (SCAPIS) were included, 395 randomly selected and 79 from an emphysema cohort. Spirometry (FEV1/FVC) and radiologists' visual emphysema scores (sum-visual) obtained at inclusion in SCAPIS were used as reference tests. SWES was compared with a commercially available quantitative emphysema scoring method (LAV950) using Pearson's correlation coefficients and receiver operating characteristics (ROC) analysis.

RESULTS

SWES correlated more strongly with the visual scores than LAV950 (r = 0.78 vs. r = 0.41, p < 0.001). The area under the ROC curve for the prediction of airway obstruction was larger for SWES than for LAV950 (0.76 vs. 0.61, p = 0.007). SWES correlated more strongly with FEV1/FVC than either LAV950 or sum-visual in the full cohort (r =  - 0.69 vs. r =  - 0.49/r =  - 0.64, p < 0.001/p = 0.007), in the emphysema cohort (r =  - 0.77 vs. r =  - 0.69/r =  - 0.65, p = 0.03/p = 0.002), and in the random sample (r =  - 0.39 vs. r =  - 0.26/r =  - 0.25, p = 0.001/p = 0.007).

CONCLUSION

The slice-wise whole-lung emphysema score (SWES) correlates better than LAV950 with radiologists' visual emphysema scores and correlates better with airway obstruction than do LAV950 and radiologists' visual scores.

CLINICAL RELEVANCE STATEMENT

The slice-wise whole-lung emphysema score provides quantitative emphysema information for CT imaging that avoids the disadvantages of threshold-based scores and is correlated more strongly with reference tests than LAV950 and reader visual scores.

KEY POINTS

• A slice-wise whole-lung emphysema score (SWES) was developed to quantify emphysema in chest CT images. • SWES identified visual emphysema and spirometric airflow limitation significantly better than threshold-based score (LAV950). • SWES improved emphysema quantification in CT images, which is especially useful in large-scale research.

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

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

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

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

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.

Lung volumes differentiate the predominance of emphysema versus airway disease phenotype in early COPD: an observational study of the COPDGene cohort

Rationale

Lung volumes identify the "susceptible smokers" who progress to develop spirometric COPD. However, among susceptible smokers, development of spirometric COPD seems to be heterogeneous, suggesting the presence of different pathological mechanisms during early establishment of spirometric COPD. The objective of the present study was to determine the differential patterns of radiographic pathologies among susceptible smokers.

Methods

We categorised smokers with preserved spirometry (Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage 0) in the Genetic Epidemiology of COPD (COPDGene) cohort based on tertiles (low, intermediate and high) of lung volumes (either total lung capacity (TLC), functional residual capacity FRC or FRC/TLC) at baseline visit. We then examined the differential patterns of change in spirometry and the associated prevalence of computed tomography measured pathologies of emphysema and airway disease with those categories of lung volumes.

Results

The pattern of spirometric change differed when participants were categorised by TLC versus FRC/TLC: those in the high TLC tertile showed stable forced expiratory volume in 1 s (FEV1), but enlarging forced vital capacity (FVC), while those in the high FRC/TLC tertile showed decline in both FEV1 and FVC. When participants from the high TLC and high FRC/TLC tertiles were partitioned into mutually exclusive groups, compared to those with high TLC, those with high FRC/TLC had lesser emphysema, but greater air trapping, more self-reported respiratory symptoms and exacerbation episodes and higher likelihood of progressing to more severe spirometric disease (GOLD stages 2-4 versus GOLD stage 1).

Conclusions

Lung volumes identify distinct physiological and radiographic phenotypes in early disease among susceptible smokers and predict the rate of spirometric disease progression and the severity of symptoms in early COPD.

Quantifying the spatial clustering characteristics of radiographic emphysema explains variability in pulmonary function

Quantitative assessment of emphysema in CT scans has mostly focused on calculating the percentage of lung tissue that is deemed abnormal based on a density thresholding strategy. However, this overall measure of disease burden discards virtually all the spatial information encoded in the scan that is implicitly utilized in a visual assessment. This simplification is likely grouping heterogenous disease patterns and is potentially obscuring clinical phenotypes and variable disease outcomes. To overcome this, several methods that attempt to quantify heterogeneity in emphysema distribution have been proposed. Here, we compare three of those: one based on estimating a power law for the size distribution of contiguous emphysema clusters, a second that looks at the number of emphysema-to-emphysema voxel adjacencies, and a third that applies a parametric spatial point process model to the emphysema voxel locations. This was done using data from 587 individuals from Phase 1 of COPDGene that had an inspiratory CT scan and plasma protein abundance measurements. The associations between these imaging metrics and visual assessment with clinical measures (FEV[Formula: see text], FEV[Formula: see text]-FVC ratio, etc.) and plasma protein biomarker levels were evaluated using a variety of regression models. Our results showed that a selection of spatial measures had the ability to discern heterogeneous patterns among CTs that had similar emphysema burdens. The most informative quantitative measure, average cluster size from the point process model, showed much stronger associations with nearly every clinical outcome examined than existing CT-derived emphysema metrics and visual assessment. Moreover, approximately 75% more plasma biomarkers were found to be associated with an emphysema heterogeneity phenotype when accounting for spatial clustering measures than when they were excluded.

First Experience With a Whole-Body Spectral Photon-Counting CT Clinical Prototype

ABSTRACT

Spectral photon-counting computed tomography (SPCCT) technology holds great promise for becoming the next generation of computed tomography (CT) systems. Its technical characteristics have many advantages over conventional CT imaging. For example, SPCCT provides better spatial resolution, greater dose efficiency for ultra-low-dose and low-dose protocols, and tissue contrast superior to that of conventional CT. In addition, SPCCT takes advantage of several known approaches in the field of spectral CT imaging, such as virtual monochromatic imaging and material decomposition imaging. In addition, SPCCT takes advantage of a new approach in this field, known as K-edge imaging, which allows specific and quantitative imaging of a heavy atom-based contrast agent. Hence, the high potential of SPCCT systems supports their ongoing investigation in clinical research settings. In this review, we propose an overview of our clinical research experience of a whole-body SPCCT clinical prototype, to give an insight into the potential benefits for clinical human imaging on image quality, diagnostic confidence, and new approaches in spectral CT imaging.

CT airway remodelling and chronic cough

RATIONALE

Structural 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 sample sizes. Advanced CT imaging not only allows airway abnormalities to be quantified, but also to count the number of visible airways. The current study evaluates these airway abnormalities in CC and assesses the contribution of CC in addition to CT findings on the progression of airflow limitation, defined as a decline in forced expiratory volume in 1 s (FEV1) over time.

METHODS

A total of 1183 males and females aged ≥40 years with thoracic CT scans and valid spirometry from Canadian Obstructive Lung Disease, a Canadian multicentre, population-based study has been included in this analysis. Participants were stratified into 286 never-smokers, 297 ever-smokers with normal lung function and 600 with chronic obstructive pulmonary disease (COPD) of different severity grades. Imaging parameters analyses included total airway count (TAC), airway wall thickness, emphysema as well as parameters for functional small airway disease quantification.

RESULTS

Irrespective of COPD presence, CC was not related to specific airway and lung structure features. Independent of TAC and emphysema score, CC was highly associated with FEV1 decline over time in the entire study population, particularly in ever-smokers (p<0.0001).

CONCLUSION

The absence of specific structural CT features independently from COPD presence indicate that other underlying mechanisms are contributing to the symptomatology of CC. On top of derived CT parameters, CC seems to be independently associated with FEV1 decline.

TRIAL REGISTRATION NUMBER

NCT00920348.

Quantitative CT Evaluation of Emphysema Progression over 10 Years in the COPDGene Study

Background Long-term studies of chronic obstructive pulmonary disease (COPD) can evaluate emphysema progression. Adjustment for differences in equipment and scanning protocols of individual CT examinations have not been studied extensively. Purpose To evaluate emphysema progression in current and former smokers in the COPDGene cohort over three imaging points obtained at 5-year intervals accounting for individual CT parameters. Materials and Methods Current and former cigarette smokers enrolled between 2008 and 2011 from the COPDGene study were prospectively followed for 10 years between 2008 and 2020. Extent of emphysema as adjusted lung density (ALD) from quantitative CT was measured at baseline and at 5- and 10-year follow-up. Linear mixed models adjusted for CT technical characteristics were constructed to evaluate emphysema progression. Mean annual changes in ALD over consecutive 5-year study periods were estimated by smoking status and baseline emphysema. Results Of 8431 participants at baseline (mean age, 60 years ± 9 [SD]; 3905 female participants), 4913 were at 5-year follow-up and 1544 participants were at 10-year follow-up. There were 4134 (49%) participants who were current smokers, and 4449 (53%) participants had more than trace emphysema at baseline. Current smokers with more than trace emphysema showed the largest decline in ALD, with mean annual decreases of 1.4 g/L (95% CI: 1.2, 1.5) in the first 5 years and 0.9 g/L (95% CI: 0.7, 1.2) in the second 5 years. Accounting for CT noise, field of view, and scanner model improved model fit for estimation of emphysema progression (P < .001 by likelihood ratio test). Conclusion Evaluation at CT of emphysema progression in the COPDGene study showed that, during the span of 10 years, participants with pre-existing emphysema who continued smoking had the largest decline in ALD. Adjusting for CT equipment and protocol factors improved these longitudinal estimates. Clinical trial registration no. NCT00608764 © RSNA, 2023 Supplemental material is available for this article. See the editorial by Parraga and Kirby in this issue.

Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV1 decline: results from COPDGene and SPIROMICS

Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.

Accuracy of Nodule Volume and Airway Wall Thickness Measurement Using Low-Dose Chest CT on a Photon-Counting Detector CT Scanner

OBJECTIVES

A comparison of high-resolution photon-counting detector computed tomography (PCD-CT) versus energy-integrating detector (EID) CT via a phantom study using low-dose chest CT to evaluate nodule volume and airway wall thickness quantification.

MATERIALS AND METHODS

Twelve solid and ground-glass lung nodule phantoms with 3 diameters (5 mm, 8 mm, and 10 mm) and 2 shapes (spherical and star-shaped) and 12 airway tube phantoms (wall thicknesses, 0.27-1.54 mm) were placed in an anthropomorphic chest phantom. The phantom was scanned with EID-CT and PCD-CT at 5 dose levels (CTDI vol = 0.1-0.8 mGy at Sn-100 kV, 7.35 mGy at 120 kV). All images were iteratively reconstructed using matched kernels for EID-CT and medium-sharp kernel (MK) PCD-CT and an ultra-sharp kernel (USK) PCD-CT kernel, and image noise at each dose level was quantified. Nodule volumes were measured using semiautomated segmentation software, and the accuracy was expressed as the percentage error between segmented and reference volumes. Airway wall thicknesses were measured, and the root-mean-square error across all tubes was evaluated.

RESULTS

MK PCD-CT images had the lowest noise. At 0.1 mGy, the mean volume accuracy for the solid and ground-glass nodules was improved in USK PCD-CT (3.1% and 3.3% error) compared with MK PCD-CT (9.9% and 10.2% error) and EID-CT images (11.4% and 9.2% error), respectively. At 0.2 mGy and 0.8 mGy, the wall thickness root-mean-square error values were 0.42 mm and 0.41 mm for EID-CT, 0.54 mm and 0.49 mm for MK PCD-CT, and 0.23 mm and 0.16 mm for USK PCD-CT.

CONCLUSIONS

USK PCD-CT provided more accurate lung nodule volume and airway wall thickness quantification at lower radiation dose compared with MK PCD-CT and EID-CT.

Potential Role of Computed Tomography Volumetry in Size Matching in Lung Transplantation

BACKGROUND

Accumulated knowledge on the outcomes related to size mismatch in lung transplantation derives from predicted total lung capacity equations rather than individualized measurements of donors and recipients. The increasing availability of computed tomography (CT) makes it possible to measure the lung volumes of donors and recipients before transplantation. We hypothesize that CT-derived lung volumes predict a need for surgical graft reduction and primary graft dysfunction.

METHODS

Donors from the local organ procurement organization and recipients from our hospital from 2012 to 2018 were included if their CT exams were available. The CT lung volumes and plethysmography total lung capacity were measured and compared with predicted total lung capacity using Bland Altman methods. We used logistic regression to predict the need for surgical graft reduction and ordinal logistic regression to stratify the risk for primary graft dysfunction.

RESULTS

A total of 315 transplant candidates with 575 CT scans and 379 donors with 379 CT scans were included. The CT lung volumes closely approximated plethysmography lung volumes and differed from the predicted total lung capacity in transplant candidates. In donors, CT lung volumes systematically underestimated predicted total lung capacity. Ninety-four donors and recipients were matched and transplanted locally. Larger donor and smaller recipient lung volumes estimated by CT predicted a need for surgical graft reduction and were associated with higher primary graft dysfunction grade.

CONCLUSION

The CT lung volumes predicted the need for surgical graft reduction and primary graft dysfunction grade. Adding CT-derived lung volumes to the donor-recipient matching process may improve recipients' outcomes.

COPD: Providing the right treatment for the right patient at the right time

Chronic Obstructive Pulmonary Disease (COPD) is a common disease associated with significant morbidity and mortality that is both preventable and treatable. However, a major challenge in recognizing, preventing, and treating COPD is understanding its complexity. While COPD has historically been characterized as a disease defined by airflow limitation, we now understand it as a multi-component disease with many clinical phenotypes, systemic manifestations, and associated co-morbidities. Evidence is rapidly emerging in our understanding of the many factors that contribute to the pathogenesis of COPD and the identification of "early" or "pre-COPD" which should provide exciting opportunities for early treatment and disease modification. In addition to breakthroughs in our understanding of the origins of COPD, we are optimizing treatment strategies and delivery of care that are showing impressive benefits in patient-centered outcomes and healthcare utilization. This special issue of Respiratory Medicine, "COPD: Providing the Right Treatment for the Right Patient at the Right Time" is a summary of the proceedings of a conference held in Stresa, Italy in April 2022 that brought together international experts to discuss emerging evidence in COPD and Pulmonary Rehabilitation in honor of a distinguished friend and colleague, Claudio Ferdinando Donor (1948-2021). Claudio was a true pioneer in the field of pulmonary rehabilitation and the comprehensive care of individuals with COPD. He held numerous leadership roles in in the field, provide editorial stewardship of several respiratory journals, authored numerous papers, statement and guidelines in COPD and Pulmonary Rehabilitation, and provided mentorship to many in our field. Claudio's most impressive talent was his ability to organize spectacular conferences and symposia that highlighted cutting edge science and clinical medicine. It is in this spirit that this conference was conceived and planned. These proceedings are divided into 4 sections which highlight crucial areas in the field of COPD: (1) New concepts in COPD pathogenesis; (2) Enhancing outcomes in COPD; (3) Non-pharmacologic management of COPD; and (4) Optimizing delivery of care for COPD. These presentations summarize the newest evidence in the field and capture lively discussion on the exciting future of treating this prevalent and impactful disease. We thank each of the authors for their participation and applaud their efforts toward pushing the envelope in our understanding of COPD and optimizing care for these patients. We believe that this edition is a most fitting tribute to a dear colleague and friend and will prove useful to students, clinicians, and researchers as they continually strive to provide the right treatment for the right patient at the right time. It has been our pleasure and a distinct honor to serve as editors and oversee such wonderful scholarly work.

Comparative Study of Systemic Inflammatory Markers in Clinical Phenotypes of Chronic Obstructive Pulmonary Disease

Background

Chronic Obstructive Pulmonary Disease (COPD) is an inflammatory pulmonary disorder with systemic inflammatory manifestations. This study aims to identify the profile of systemic inflammatory markers in the different phenotypes of COPD to help predict the disease and identify suitable treatment options.

Materials and Methods

A prospective observational study was conducted on 92 patients with COPD admitted to Victoria Hospital, Bangalore between August 2021 to December 2021. Levels of C-reactive protein (CRP), Serum Creatinine, Erythrocyte Sedimentation Rate (ESR), Absolute Lymphocyte Count (ALC), Absolute Eosinophil Count (AEC), and Lactate Dehydrogenase (LDH) were measured within 48 hours of presentation.

Results

Significantly higher levels of CRP were found in frequent exacerbator emphysema and chronic bronchitis phenotypes (p=0.001). The frequent exacerbator emphysema phenotype had significantly higher levels of LDH (p=0.001) and serum creatinine (p=0.001). Not surprisingly, absolute eosinophil counts were significantly raised in the overlap COPD-Asthma phenotype (p=0.001).

Conclusion

Raised serum CRP levels in the frequent exacerbator phenotypes of emphysema and chronic bronchitis suggest a possible inflammatory response to an infective etiology. Raised LDH levels in frequent exacerbator emphysema phenotype could signify underlying lung parenchymal destruction. Systemic inflammation and oxidative stress can lead to skeletal muscle injury and atrophy in COPD patients. This may explain the raised serum creatinine levels in frequent exacerbator emphysema phenotype. Eosinophilia seen in Overlap COPD-Asthma phenotype is suggestive of type 2 inflammation of the airways with better response to steroids.

Diffusing Capacity and Mortality in Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) mortality risk is often estimated using the BODE (body mass index, obstruction, dyspnea, exercise capacity) index, including body mass index, forced expiratory volume in 1 second, dyspnea score, and 6-minute walk distance. Diffusing capacity of the lung for carbon monoxide (DlCO) is a potential predictor of mortality that reflects physiology distinct from that in the BODE index. Objectives: This study evaluated DlCO as a predictor of mortality using participants from the COPDGene study. Methods: We performed time-to-event analyses of individuals with COPD (former or current smokers with forced expiratory volume in 1 second/forced vital capacity < 0.7) and DlCO measurements from the COPDGene phase 2 visit. Cox proportional hazard methods were used to model survival, adjusting for age, sex, pack-years, smoking status, BODE index, computed tomography (CT) percent emphysema (low attenuation areas below -950 Hounsfield units), CT airway wall thickness, and history of cardiovascular or kidney diseases. C statistics for models with DlCO and BODE scores were used to compare discriminative accuracy. Results: Of 2,329 participants, 393 (16.8%) died during the follow-up period (median = 4.9 yr). In adjusted analyses, for every 10% decrease in DlCO percent predicted, mortality increased by 28% (hazard ratio = 1.28; 95% confidence interval, 1.17-1.41, P < 0.001). When compared with other clinical predictors, DlCO percent predicted performed similarly to BODE (C statistic DlCO = 0.68; BODE = 0.70), and the addition of DlCO to BODE improved its discriminative accuracy (C statistic = 0.71). Conclusions: Diffusing capacity, a measure of gas transfer, strongly predicted all-cause mortality in individuals with COPD, independent of BODE index and CT evidence of emphysema and airway wall thickness. These findings support inclusion of DlCO in prognostic models for COPD.

Standardized airway wall thickness Pi10 from routine CT scans of COPD patients as imaging biomarker for disease severity, lung function decline, and mortality

BACKGROUND

Chest computed tomography (CT) is increasingly used for phenotyping and monitoring of patients with COPD. The aim of this work was to evaluate the association of Pi10 as a measure of standardized airway wall thickness on CT with exacerbations, mortality, and response to triple therapy.

METHODS

Patients of GOLD grades 1-4 of the COSYCONET cohort with prospective CT scans were included. Pi10 was automatically computed and analyzed for its relationship to COPD severity, comorbidities, lung function, respiratory therapy, and mortality over a 6-year period, using univariate and multivariate comparisons.

RESULTS

We included n = 433 patients (61%male). Pi10 was dependent on both GOLD grades 1-4 (p = 0.009) and GOLD groups A-D (p = 0.008); it was particularly elevated in group D, and ROC analysis yielded a cut-off of 0.26 cm. Higher Pi10 was associated to lower FEV₁ % predicted and higher RV/TLC, moreover the annual changes of lung function parameters (p < 0.05), as well as to an airway-dominated phenotype and a history of myocardial infarction (p = 0.001). These associations were confirmed in multivariate analyses. Pi10 was lower in patients receiving triple therapy, in particular in patients of GOLD groups C and D. Pi10 was also a significant predictor for mortality (p = 0.006), even after including multiple other predictors.

CONCLUSION

In summary, Pi10 was found to be predictive for the course of the disease in COPD, in particular mortality. The fact that Pi10 was lower in patients with severe COPD receiving triple therapy might hint toward additional effects of this functional therapy on airway remodeling.

REGISTRATION

ClinicalTrials.gov, Identifier: NCT01245933.

Greek Guidelines for the Management of COPD, a Proposal of a Holistic Approach Based on the needs of the Greek Community

Despite that COPD remains one of the most common respiratory diseases worldwide, it can be managed effectively with certain treatments and, more importantly, be prevented by the early implementation of various measures. The pathology and pathophysiology of this disease continue to be studied, with new pharmacological and invasive therapies emerging. In this consensus paper, the Working Group of the Hellenic Thoracic Society aimed to consolidate the up-to-date information and new advances in the treatment of COPD. Local and international data on its prevalence are presented, with revised strategies on the diagnostic approach and the evaluation of risk assessment and disease severity classification. Emphasis is placed on the management and therapy of patients with COPD, covering both common principles, specialized modalities, and algorithms to distinguish between home care and the need for hospitalization. Although pharmacological treatment is commonly recognized in COPD, an integrative approach of pulmonary rehabilitation, physical activity, patient education, and self-assessment should be encountered for a comprehensive treatment, prevention of exacerbations, and increased quality of life in patients.

Evaluation of the Effect of COVID-19 Vaccination on Exacerbations of Chronic Obstructive Pulmonary Disease: A Single-Center Study

BACKGROUND AND AIM

 Vaccinations have been one of the main approaches to reducing mortality and exacerbations caused by infectious agents in chronic obstructive pulmonary disease (COPD). Among viral pathogens, coronaviruses have been described to play a role. This study aims to investigate the role of coronavirus disease 2019 (COVID-19) vaccination on exacerbation reduction in patients with COPD.

METHODS

Patients diagnosed with COPD prior to the study date were considered the study population. Exacerbations of COPD before and after the COVID-19 vaccination were recorded. Patients with influenza and/or pneumococcal vaccination were excluded from the study due to their known role in reducing exacerbations of COPD.

RESULTS

The study included 152 patients with a mean age of 67.5 ± 9.7 years. Most patients were classified under Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages 2 and 3. In fully vaccinated patients, COPD exacerbation was observed to be higher than in those without full vaccination (70.5% vs. 55.3%, respectively). Total risk status and vaccination status, however, were seen to be in a positive correlation, with higher risk and complete vaccination status presenting with a higher count of COPD exacerbation.

CONCLUSION

Although it is known that the administration of COVID-19 vaccines in patients in risk groups reduces the risk of disease, there is no study showing a positive effect on COPD exacerbations alone. In our study, it was observed that only the COVID-19 vaccine was ineffective in attacks without influenza and pneumococcal vaccines.

Unsupervised Learning Identifies Computed Tomographic Measurements as Primary Drivers of Progression, Exacerbation, and Mortality in Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome with phenotypic manifestations that tend to be distributed along a continuum. Unsupervised machine learning based on broad selection of imaging and clinical phenotypes may be used to identify primary variables that define disease axes and stratify patients with COPD. Objectives: To identify primary variables driving COPD heterogeneity using principal component analysis and to define disease axes and assess the prognostic value of these axes across three outcomes: progression, exacerbation, and mortality. Methods: We included 7,331 patients between 39 and 85 years old, of whom 40.3% were Black and 45.8% were female smokers with a mean of 44.6 pack-years, from the COPDGene (Genetic Epidemiology of COPD) phase I cohort (2008-2011) in our analysis. Out of a total of 916 phenotypes, 147 continuous clinical, spirometric, and computed tomography (CT) features were selected. For each principal component (PC), we computed a PC score based on feature weights. We used PC score distributions to define disease axes along which we divided the patients into quartiles. To assess the prognostic value of these axes, we applied logistic regression analyses to estimate 5-year (n = 4,159) and 10-year (n = 1,487) odds of progression. Cox regression and Kaplan-Meier analyses were performed to estimate 5-year and 10-year risk of exacerbation (n = 6,532) and all-cause mortality (n = 7,331). Results: The first PC, accounting for 43.7% of variance, was defined by CT measures of air trapping and emphysema. The second PC, accounting for 13.7% of variance, was defined by spirometric and CT measures of vital capacity and lung volume. The third PC, accounting for 7.9% of the variance, was defined by CT measures of lung mass, airway thickening, and body habitus. Stratification of patients across each disease axis revealed up to 3.2-fold (95% confidence interval [CI] 2.4, 4.3) greater odds of 5-year progression, 5.4-fold (95% CI 4.6, 6.3) greater risk of 5-year exacerbation, and 5.0-fold (95% CI 4.2, 6.0) greater risk of 10-year mortality between the highest and lowest quartiles. Conclusions: Unsupervised learning analysis of the COPDGene cohort reveals that CT measurements may bolster patient stratification along the continuum of COPD phenotypes. Each of the disease axes also individually demonstrate prognostic potential, predictive of future forced expiratory volume in 1 second decline, exacerbation, and mortality.

Effect of timing of bronchodilator therapy initiation on exacerbations in patients with chronic obstructive pulmonary disease: a retrospective cohort study

Background

The benefit of prompt vs delayed treatment initiation with inhaled long-acting bronchodilators in reducing exacerbations in chronic obstructive pulmonary disease (COPD) is unclear. This study aimed to investigate if long-acting bronchodilator therapy initiation within 30 days of COPD diagnosis reduces exacerbation risk in patients with COPD.

Methods

This was a retrospective cohort study of patients with COPD based on claims and electronic medical records data extracted from the Real World Data database. The index date (day 0) was the date of the first confirmed inpatient or outpatient COPD diagnosis between January 1, 2005, and December 31, 2018. Patients with COPD without an asthma diagnosis and aged ≥ 40 years at the index date were included. Patients who initiated inhaled long-acting bronchodilator therapy within the first 30 days (day 0 to day 29) were categorized into the “prompt therapy” group and the rest into the “delayed therapy” group. Time from day 30 post-diagnosis to the first exacerbation and annual exacerbation rate (AER) were evaluated for the overall population and those stratified by COPD phenotype, including chronic bronchitis (CB) and emphysema.

Results

Compared with the delayed therapy group (n = 1516), time to first exacerbation was prolonged (hazard ratio 0.78; 95% confidence interval [CI] [0.70, 0.87]) and annual rates of moderate or severe exacerbations were lower (rate ratio 0.74; 95% CI [0.65, 0.84]) in the prompt therapy group (n = 1466). Similarly, time to first exacerbation was prolonged and AERs were lower in the prompt therapy group in the subgroups of patients with CB or emphysema.

Conclusions

This is the first study to demonstrate a prolonged time to first exacerbation upon initiation of long-acting bronchodilators within 30 days of COPD diagnosis. A beneficial effect was also observed in patients with CB and emphysema. Our data support advising patients to initiate long-acting bronchodilators soon after COPD diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12931-022-02184-6.

Reduction of Emphysema Severity by Human Umbilical Cord-Derived Mesenchymal Stem Cells in Mice

Chronic obstructive pulmonary disease (COPD) is a major cause of morbidity and mortality in chronic lung disease patients throughout the world. Mesenchymal stem cells (MSCs) have been shown to regulate immunomodulatory, anti-inflammatory, and regenerative responses. However, the effects of human-umbilical-cord-derived mesenchymal stem cells (hUC-MSCs) on the lung pathophysiology of COPD remain unclear. We aimed to investigate the role of hUC-MSCs in emphysema severity and Yes-associated protein (Yap) phosphorylation (p-Yap) in a porcine-pancreatic-elastase (PPE)-induced emphysema model. We observed that the emphysema percentages (normalized to the total lung volume) measured by chest computed tomography (CT) and exercise oxygen desaturation were significantly reduced by hUC-MSCs at 107 cells/kg body weight (BW) via intravenous administration in emphysematous mice (p < 0.05). Consistently, the emphysema index, as assessed by the mean linear intercept (MLI), significantly decreased with hUC-MSC administration at 3 × 106 and 107 cells/kg BW (p < 0.05). Changes in the lymphocytes, monocytes, and splenic cluster of differentiation 4-positive (CD4+) lymphocytes by PPE were significantly reversed by hUC-MSC administration in emphysematous mice (p < 0.05). An increasing neutrophil/lymphocyte ratio was reduced by hUC-MSCs at 3 × 106 and 107 cells/kg BW (p < 0.05). The higher levels of tumor necrosis factor (TNF)-α, keratinocyte chemoattractant (KC), and lactate dehydrogenase (LDH) in bronchoalveolar lavage fluid (BALF) were significantly decreased by hUC-MSC administration (p < 0.05). A decreasing p-Yap/Yap ratio in type II alveolar epithelial cells (AECII) of mice with PPE-induced emphysema was significantly increased by hUC-MSCs (p < 0.05). In conclusion, the administration of hUC-MSCs improved multiple pathophysiological features of mice with PPE-induced emphysema. The effectiveness of the treatment of pulmonary emphysema with hUC-MSCs provides an essential and significant foundation for future clinical studies of MSCs in COPD patients.

Mechanisms Linking COPD to Type 1 and 2 Diabetes Mellitus: Is There a Relationship between Diabetes and COPD?

Chronic obstructive pulmonary disease (COPD) patients frequently suffer from multiple comorbidities, resulting in poor outcomes for these patients. Diabetes is observed at a higher frequency in COPD patients than in the general population. Both type 1 and 2 diabetes mellitus are associated with pulmonary complications, and similar therapeutic strategies are proposed to treat these conditions. Epidemiological studies and disease models have increased our knowledge of these clinical associations. Several recent genome-wide association studies have identified positive genetic correlations between lung function and obesity, possibly due to alterations in genes linked to cell proliferation; embryo, skeletal, and tissue development; and regulation of gene expression. These studies suggest that genetic predisposition, in addition to weight gain, can influence lung function. Cigarette smoke exposure can also influence the differential methylation of CpG sites in genes linked to diabetes and COPD, and smoke-related single nucleotide polymorphisms are associated with resting heart rate and coronary artery disease. Despite the vast literature on clinical disease association, little direct mechanistic evidence is currently available demonstrating that either disease influences the progression of the other, but common pharmacological approaches could slow the progression of these diseases. Here, we review the clinical and scientific literature to discuss whether mechanisms beyond preexisting conditions, lifestyle, and weight gain contribute to the development of COPD associated with diabetes. Specifically, we outline environmental and genetic confounders linked with these diseases.

Quantitative CT Lung Imaging and Machine Learning Improves Prediction of Emergency Room Visits and Hospitalizations in COPD

RATIONALE

Predicting increased risk of future healthcare utilization in chronic obstructive pulmonary disease (COPD) patients is an important goal for improving patient management.

OBJECTIVE

Our objective was to determine the importance of computed tomography (CT) lung imaging measurements relative to other demographic and clinical measurements for predicting future health services use with machine learning in COPD.

MATERIALS AND METHODS

In this retrospective study, lung function measurements and chest CT images were acquired from Canadian Cohort of Obstructive Lung Disease study participants from 2010 to 2017 (https://clinicaltrials.gov, NCT00920348). Up to two follow-up visits (1.5- and 3-year follow-up) were performed and participants were asked for details related to healthcare utilization. Healthcare utilization was defined as any COPD hospitalization or emergency room visit due to respiratory problems in the 12 months prior to the follow-up visits. CT analysis was performed (VIDA Diagnostics Inc.); a total of 108 CT quantitative emphysema, airway and vascular measurements were investigated. A hybrid feature selection method with support vector machine classifier was used to predict healthcare utilization. Performance was determined using accuracy, F1-measure and area under the receiver operating characteristic curve (AUC) and Matthews's correlation coefficient (MC).

RESULTS

Of the 527 COPD participants evaluated, 179 (35%) used healthcare services at follow-up. There were no significant differences between the participants with or without healthcare utilization at follow-up for age (p = 0.50), sex (p = 0.44), BMI (p = 0.05) or pack-years (p = 0.76). The accuracy for predicting subsequent healthcare utilization was 80% ± 3% (F1-measure = 74%, AUC = 0.80, MC = 0.6) when all measurements were considered, 76% ± 6% (F1-measure = 72%, AUC = 0.77, MC = 0.55) for CT measurements alone and 65% ± 5% (F1-measure = 60%, AUC = 0.67, MC = 0.34) for demographic and lung function measurements alone.

CONCLUSION

The combination of CT lung imaging and conventional measurements leads to greater prediction accuracy of subsequent health services use than conventional measurements alone, and may provide needed prognostic information for patients suffering from COPD.

Computational lung modelling in respiratory medicine

Computational modelling of the lungs is an active field of study that integrates computational advances with lung biophysics, biomechanics, physiology and medical imaging to promote individualized diagnosis, prognosis and therapy evaluation in lung diseases. The complex and hierarchical architecture of the lung offers a rich, but also challenging, research area demanding a cross-scale understanding of lung mechanics and advanced computational tools to effectively model lung biomechanics in both health and disease. Various approaches have been proposed to study different aspects of respiration, ranging from compartmental to discrete micromechanical and continuum representations of the lungs. This article reviews several developments in computational lung modelling and how they are integrated with preclinical and clinical data. We begin with a description of lung anatomy and how different tissue components across multiple length scales affect lung mechanics at the organ level. We then review common physiological and imaging data acquisition methods used to inform modelling efforts. Building on these reviews, we next present a selection of model-based paradigms that integrate data acquisitions with modelling to understand, simulate and predict lung dynamics in health and disease. Finally, we highlight possible future directions where computational modelling can improve our understanding of the structure-function relationship in the lung.

Bronchiectasis in Low-Dose CT Screening for Lung Cancer

Background Bronchiectasis is associated with loss of lung function, substantial use of health care resources, and increased morbidity and mortality in people with cardiopulmonary diseases. Purpose To assess the frequency and severity of bronchiectasis and related clinical findings of participants in a low-dose CT (LDCT) screening program. Materials and Methods The Early Lung and Cardiac Action Program (ELCAP) bronchiectasis score (range, 0-42; higher values indicate more severe bronchiectasis) was developed to facilitate bronchiectasis assessment. This quantitative scoring system screened participants based on accumulated knowledge and improved CT imaging capabilities. Secondary review of LDCT studies from smokers aged 40-90 years was performed when they were initially enrolled in the prospective Mount Sinai ELCAP screening study between 2010 and 2019. Medical records were reviewed to identify associated respiratory symptoms and acute respiratory events during the 2 years after LDCT. Logistic regression analysis was performed to examine factors associated with bronchiectasis. Results LDCT studies of 2191 screening participants (mean age, 65 years ± 9; 1140 [52%] women) were obtained, and bronchiectasis was identified in 504 (23%) participants. Median ELCAP bronchiectasis score was 12 (interquartile range, 9-16). Bronchiectasis was most common in the lower lobes for all participants, and lower lobe prevalence was greater with higher ELCAP score (eg, 91% prevalence with an ELCAP score of 16-42). In the fourth quartile, however, midlung involvement was higher compared with lower lung involvement (128 of 131 participants [98%] vs 122 of 131 participants [93%]). Bronchiectasis was more frequent with greater age (odds ratio [OR] = 2.0 per decade; 95% CI: 1.7, 2.4); being a former smoker (OR = 1.33; 95% CI: 1.01, 1.73); and having self-reported chronic obstructive pulmonary disease (OR = 1.38; 95% CI: 1.02, 1.88), an elevated hemidiaphragm (OR = 4; 95% CI: 2, 11), or consolidation (OR = 5; 95% CI: 3, 11). It was less frequent in overweight (OR = 0.7; 95% CI: 0.5, 0.9) or obese (OR = 0.6; 95% CI: 0.4, 0.8) participants. Two years after baseline LDCT, respiratory symptoms, acute respiratory events, and respiratory events that required hospitalization were more frequent with increasing severity of the ELCAP bronchiectasis score (P < .005 for all trends). Conclusion Prevalence of bronchiectasis in smokers undergoing low-dose CT screening was high, and respiratory symptoms and acute events were more frequent with increasing severity of the Early Lung and Cardiac Action Program Bronchiectasis score. © RSNA, 2022 See also the editorial by Verschakelen in this issue.

Physiological Impairments on Respiratory Oscillometry and Future Exacerbations in Chronic Obstructive Pulmonary Disease Patients without a History of Frequent Exacerbations

Respiratory oscillometry allows measuring respiratory resistance and reactance during tidal breathing and may predict exacerbations in patients with chronic obstructive pulmonary disease (COPD). While the Global Initiative for Chronic Obstructive Lung Disease (GOLD) advocates the ABCD classification tool to determine therapeutic approach based on symptom and exacerbation history, we hypothesized that in addition to spirometry, respiratory oscillometry complemented the ABCD tool to identify patients with a high risk of exacerbations. This study enrolled male outpatients with stable COPD who were prospectively followed-up over 5 years after completing mMRC scale and COPD assessment test (CAT) questionnaires, post-bronchodilator spirometry and respiratory oscillometry to measure resistance, reactance, and resonant frequency (Fres), and emphysema quantitation on computed tomography. Total 134 patients were classified into the GOLD A, B, C, and D groups (n = 48, 71, 5, and 9) based on symptoms on mMRC and CAT and a history of exacerbations in the previous year. In univariable analysis, higher Fres was associated with an increased risk of exacerbation more strongly than other respiratory oscillometry indices. Fres was closely associated with forced expiratory volume in 1 sec (FEV₁). In multivariable Cox-proportional hazard models of the GOLD A and B groups, either lower FEV₁ group or higher Fres group was associated with a shorter time to the first exacerbation independent of the GOLD group (A vs B) and emphysema severity. Adding respiratory oscillometry to the ABCD tool may be useful for risk estimation of future exacerbations in COPD patients without frequent exacerbation history.

Blood miRNAs Are Linked to Frequent Asthma Exacerbations in Childhood Asthma and Adult COPD

MicroRNAs have been independently associated with asthma and COPD; however, it is unclear if microRNA associations will overlap when evaluating retrospective acute exacerbations. Objective: We hypothesized that peripheral blood microRNAs would be associated with retrospective acute asthma exacerbations in a pediatric asthma cohort and that such associations may also be relevant to acute COPD exacerbations. Methods: We conducted small-RNA sequencing on 374 whole-blood samples from children with asthma ages 6-14 years who participated in the Genetics of Asthma in Costa Rica Study (GACRS) and 450 current and former adult smokers with and without COPD who participated in the COPDGene study. Measurements and Main Results: After QC, we had 351 samples and 649 microRNAs for Differential Expression (DE) analysis between the frequent (n = 183) and no or infrequent exacerbation (n = 168) groups in GACRS. Fifteen upregulated miRs had odds ratios (OR) between 1.22 and 1.59 for a doubling of miR counts, while five downregulated miRs had ORs between 0.57 and 0.8. These were assessed for generalization in COPDGene, where three of the upregulated miRs (miR-532-3p, miR-296-5p, and miR-766-3p) and two of the downregulated miRs (miR-7-5p and miR-451b) replicated. Pathway enrichment analysis showed MAPK and PI3K-Akt signaling pathways were strongly enriched for target genes of DE miRNAs and miRNAs generalizing to COPD exacerbations, as well as infection response pathways to various pathogens. Conclusion: miRs (451b; 7-5p; 532-3p; 296-5p and 766-3p) associated with both childhood asthma and adult COPD exacerbations may play a vital role in airflow obstruction and exacerbations and point to shared genomic regulatory machinery underlying exacerbations in both diseases.

Head-to-head Comparison of Qualitative Radiologist Assessment With Automated Quantitative Computed Tomography Analysis for Bronchiolitis Obliterans Syndrome After Hematopoietic Cell Transplantation

PURPOSE

Computed tomography (CT) findings of bronchiolitis obliterans syndrome (BOS) can be nonspecific and variable. This study aims to measure the incremental value of automated quantitative lung CT analysis to clinical CT interpretation. A head-to-head comparison of quantitative CT lung density analysis by parametric response mapping (PRM) with qualitative radiologist performance in BOS diagnosis was performed.

MATERIALS AND METHODS

Inspiratory and end-expiratory CTs of 65 patients referred to a post-bone marrow transplant lung graft-versus-host-disease clinic were reviewed by 3 thoracic radiologists for the presence of mosaic attenuation, centrilobular opacities, airways dilation, and bronchial wall thickening. Radiologists' majority consensus diagnosis of BOS was compared with automated PRM air trapping quantification and to the gold-standard diagnosis of BOS as per National Institutes of Health (NIH) consensus criteria.

RESULTS

Using a previously established threshold of 28% air trapping on PRM, the diagnostic performance for BOS was as follows: sensitivity 56% and specificity 94% (area under the receiver operator curve [AUC]=0.75). Radiologist review of inspiratory CT images alone resulted in a sensitivity of 80% and a specificity of 69% (AUC=0.74). When radiologists assessed both inspiratory and end-expiratory CT images in combination, the sensitivity was 92% and the specificity was 59% (AUC=0.75). The highest performance was observed when the quantitative PRM report was reviewed alongside inspiratory and end-expiratory CT images, with a sensitivity of 92% and a specificity of 73% (AUC=0.83).

CONCLUSIONS

In the CT diagnosis of BOS, qualitative expert radiologist interpretation was noninferior to quantitative PRM. The highest level of diagnostic performance was achieved by the combination of quantitative PRM measurements with qualitative image feature assessments.

Pulmonary functional MRI: Detecting the structure-function pathologies that drive asthma symptoms and quality of life

Pulmonary functional MRI (PfMRI) using inhaled hyperpolarized, radiation-free gases (such as ³ He and ¹²⁹ Xe) provides a way to directly visualize inhaled gas distribution and ventilation defects (or ventilation heterogeneity) in real time with high spatial (~mm³ ) resolution. Both gases enable quantitative measurement of terminal airway morphology, while ¹²⁹ Xe uniquely enables imaging the transfer of inhaled gas across the alveolar-capillary tissue barrier to the red blood cells. In patients with asthma, PfMRI abnormalities have been shown to reflect airway smooth muscle dysfunction, airway inflammation and remodelling, luminal occlusions and airway pruning. The method is rapid (8-15 s), cost-effective (~$300/scan) and very well tolerated in patients, even in those who are very young or very ill, because unlike computed tomography (CT), positron emission tomography and single-photon emission CT, there is no ionizing radiation and the examination takes only a few seconds. However, PfMRI is not without limitations, which include the requirement of complex image analysis, specialized equipment and additional training and quality control. We provide an overview of the three main applications of hyperpolarized noble gas MRI in asthma research including: (1) inhaled gas distribution or ventilation imaging, (2) alveolar microstructure and finally (3) gas transfer into the alveolar-capillary tissue space and from the tissue barrier into red blood cells in the pulmonary microvasculature. We highlight the evidence that supports a deeper understanding of the mechanisms of asthma worsening over time and the pathologies responsible for symptoms and disease control. We conclude with a summary of approaches that have the potential for integration into clinical workflows and that may be used to guide personalized treatment planning.

Kernel Conversion for Robust Quantitative Measurements of Archived Chest Computed Tomography Using Deep Learning-Based Image-to-Image Translation

Chest computed tomography (CT) is used to screen for lung cancer and evaluate pulmonary and extra-pulmonary abnormalities such as emphysema and coronary artery calcification, particularly in smokers. In real-world practice, lung abnormalities are visually assessed using high-contrast thin-slice images which are generated from raw scan data using sharp reconstruction kernels with the sacrifice of increased image noise. In contrast, accurate CT quantification requires low-contrast thin-slice images with low noise, which are generated using soft reconstruction kernels. However, only sharp-kernel thin-slice images are archived in many medical facilities due to limited data storage space. This study aimed to establish deep neural network (DNN) models to convert sharp-kernel images to soft-kernel-like images with a final goal to reuse historical chest CT images for robust quantitative measurements, particularly in completed previous longitudinal studies. By using pairs of sharp-kernel (input) and soft-kernel (ground-truth) images from 30 patients with chronic obstructive pulmonary disease (COPD), DNN models were trained. Then, the accuracy of kernel conversion based on the established DNN models was evaluated using CT from independent 30 smokers with and without COPD. Consequently, differences in CT values between new images converted from sharp-kernel images using the established DNN models and ground-truth soft-kernel images were comparable with the inter-scans variability derived from repeated phantom scans (6 times), showing that the conversion error was the same level as the measurement error of the CT device. Moreover, the Dice coefficients to quantify the similarity between low attenuation voxels on given images and the ground-truth soft-kernel images were significantly higher on the DNN-converted images than the Gaussian-filtered, median-filtered, and sharp-kernel images (p < 0.001). There were good agreements in quantitative measurements of emphysema, intramuscular adipose tissue, and coronary artery calcification between the converted and the ground-truth soft-kernel images. These findings demonstrate the validity of the new DNN model for kernel conversion and the clinical applicability of soft-kernel-like images converted from archived sharp-kernel images in previous clinical studies. The presented method to evaluate the validity of the established DNN model using repeated scans of phantom could be applied to various deep learning-based image conversions for robust quantitative evaluation.

Clinical Utility of the Electrocardiographic P-Wave Axis in Patients with Chronic Obstructive Pulmonary Disease

BACKGROUND

The vertical P-wave axis on electrocardiography (ECG) is a useful criterion for screening patients with chronic obstructive pulmonary disease (COPD). This study aimed to investigate the clinical characteristics of patients with COPD with a vertical P-wave axis as they have not yet been elucidated.

METHODS

Keio University and its affiliated hospitals conducted an observational COPD cohort study over 3 years. We analyzed 201 patients using ECG and chest computed tomography.

RESULTS

The severity of airflow limitation was higher in patients with a P-wave axis >75° than in those with a P-wave axis ≤75°. Patients with a P-wave axis >75° exhibited significantly higher total COPD assessment test scores and increased St. George's Respiratory Questionnaire total, activity, and impact scores than those with a P-wave axis ≤75°. The incidence of exacerbations over 1 and 3 years was significantly higher in patients with a P-wave axis >75° than in those with a P-wave axis ≤75°. The optimal cutoff for the P-wave axis for a percentage of the predicted forced expiratory volume in 1 s <50% and future exacerbations over 3 years was 70° (the areas under the curve [AUC]: 0.788; sensitivity: 65.3%; specificity: 78.3%) and 79° (AUC: 0.642; sensitivity: 36.7%; specificity: 92.6%). The ratio of the low attenuation area was also significantly higher in patients with a P-wave axis >75° than in those with a P-wave axis ≤75°. However, the ratio of the airway wall area did not differ between the 2 groups.

CONCLUSIONS

Patients with COPD with a vertical P-wave axis exhibited severe airflow limitation and emphysema, a worse health status, and more frequent exacerbation than patients without a vertical P-wave. Detection of the vertical P-wave axis by ECG is beneficial for the management of patients with COPD.

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

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