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Background: Despite clinical implications, the pathogenesis of mucus plugging in asthma, chronic obstructive pulmonary disease (COPD), and asthma-COPD overlap (ACO) remains unclear. We hypothesized that distinct airway microbiomes might affect mucus plugging differently among ACO, asthma, and COPD and among different extents of airway eosinophilic inflammation. Methods: The sputum microbiome, sputum cell differential count, and mucus plug score on computed tomography were cross-sectionally evaluated in patients with chronic airflow limitation. Results: Patients with ACO, asthma, or COPD were enrolled (n = 56, 10, and 25). Higher mucus plug scores were associated with a greater relative abundance of the phylum Proteobacteria (rho = 0.29) only in patients with ACO and a greater relative abundance of the phylum Actinobacteria (rho = 0.46) only in patients with COPD. In multivariable models including only patients with ACO, the presence of mucus plugs was associated with a greater relative abundance of the phylum Proteobacteria and the genus Haemophilus, independent of smoking status, airflow limitation, and emphysema severity. Moreover, the mucus score was associated with a greater relative abundance of the genus Streptococcus (rho = 0.46) in patients with a high sputum eosinophil count (n = 22) and with that of the genus Haemophilus (rho = 0.46) in those with a moderate sputum eosinophil count (n = 26). Conclusions: The associations between mucus plugging and the microbiome in ACO differed from those in COPD and asthma. Greater relative abundances of the phylum Proteobacteria and genus Haemophilus may be involved in mucus plugging in patients with ACO and moderate airway eosinophilic inflammation.

Abstract Background Cutis laxa constitutes a diverse group of connective tissue diseases, both inherited and acquired, characterized by loose skin and varying systemic involvement, including pulmonary lesions. While cutis laxa has been linked to conditions like emphysema, asthma, and bronchiectasis, the specific pathological and radiological characteristics underlying pulmonary complications related to cutis laxa remain unclear. Case presentation A 36-year-old woman, diagnosed with cutis laxa at birth, presented to our outpatient clinic with severe obstructive ventilatory impairment, evident in pulmonary function tests (expiratory volume in one second (FEV1)/forced vital capacity (FVC): 34.85%; %residual volume [RV]: 186.5%; %total lung capacity [TLC]: 129.2%). Pulmonary function tests also indicated small airway disease (%FEF50%, 7.9%; %FEF75%, 5.7%; and %FEF25–75%, 6.8%). Computed tomography (CT) revealed the lack of normal increase in lung attenuation on expiratory CT scan, with no discernible emphysematous changes. Exome sequencing was performed to confirm the association between the pulmonary lesions and cutis laxa, revealing a frameshift variant in exon 30 of the elastin gene (ELN). Further analysis employing a parametric response map revealed a longitudinal increase in the percentage of functional small airway disease (fSAD) from 37.84% to 46.61% over the 8-year follow-up, despite the absence of overt changes in CT findings, specifically the lack of normal increase in lung attenuation on expiratory CT scan. Over the same follow-up interval, there was a modest reduction of 25.6 mL/year in FEV1 coupled with a significant increase in %RV. Pulmonary function test metrics, reflective of small airway disease, exhibited a continual decline; specifically, %FEF50%, %FEF75%, and %FEF25–75% diminished from 7.9% to 7.0%, 5.7% to 4.6%, and 6.8% to 5.4%, respectively. Conclusions This case highlighted an instance of autosomal dominant cutis laxa arising from a frameshift variant in exon 30 of ELN, accompanied by small airway disease. Comprehensive investigation, utilizing quantitative CT analysis, revealed a longitudinal increase in fSAD percentage with a mild reduction in FEV1. These findings indicate that elastin deficiency may not only diminish elastic fibers in the skin but also be implicated in small airway disease by impacting components of the extracellular matrix in the lungs.

Background: Associations of fractional exhaled nitric oxide (FeNO) with airway wall remodeling and mucus plugs remain to be explored in smokers and nonsmokers with asthma. Ultra-high-resolution computed tomography (U-HRCT), which allows accurate structural quantification of airways >1 mm in diameter, was used in this study to examine whether higher FeNO was associated with thicker walls of the 3rd to 6th generation airways and mucus plugging in patients with asthma. Methods: The retrospective analyses included consecutive former smokers and nonsmokers with asthma who underwent U-HRCT in a hospital. The ratio of wall area to summed lumen and wall area was calculated as the wall area percent (WA%). Mucus plugging was visually scored. Results: Ninety-seven patients with asthma (including 59 former smokers) were classified into low (35 ppb) FeNO groups (n = 24, 26, and 47). In analysis including all patients and subanalysis including nonsmokers or former smokers, WA% in the 6th generation airways was consistently higher in the high FeNO group than in the low FeNO group, whereas WA% in the 3rd to 5th generation airways was not. In multivariable models, WA% in the 6th generation airways and the rate of mucus plugging were higher in the high FeNO group than in the low FeNO group after adjusting for age, sex, body mass index, smoking status, lung volume, and allergic rhinitis presence. Conclusions: Higher FeNO may reflect the inflammation and remodeling of relatively peripheral airways in asthma in both former smokers and nonsmokers.

Abstract Background Interstitial lung abnormalities (ILAs) on CT may affect the clinical outcomes in patients with chronic obstructive pulmonary disease (COPD), but their quantification remains unestablished. This study examined whether artificial intelligence (AI)-based segmentation could be applied to identify ILAs using two COPD cohorts. Methods ILAs were diagnosed visually based on the Fleischner Society definition. Using an AI-based method, ground-glass opacities, reticulations, and honeycombing were segmented, and their volumes were summed to obtain the percentage ratio of interstitial lung disease-associated volume to total lung volume (ILDvol%). The optimal ILDvol% threshold for ILA detection was determined in cross-sectional data of the discovery and validation cohorts. The 5-year longitudinal changes in ILDvol% were calculated in discovery cohort patients who underwent baseline and follow-up CT scans. Results ILAs were found in 32 (14%) and 15 (10%) patients with COPD in the discovery (n = 234) and validation (n = 153) cohorts, respectively. ILDvol% was higher in patients with ILAs than in those without ILA in both cohorts. The optimal ILDvol% threshold in the discovery cohort was 1.203%, and good sensitivity and specificity (93.3% and 76.3%) were confirmed in the validation cohort. 124 patients took follow-up CT scan during 5 ± 1 years. 8 out of 124 patients (7%) developed ILAs. In a multivariable model, an increase in ILDvol% was associated with ILA development after adjusting for age, sex, BMI, and smoking exposure. Conclusion AI-based CT quantification of ILDvol% may be a reproducible method for identifying and monitoring ILAs in patients with COPD.

Background: Deteriorated sinusitis and increased adiposity relative to muscle mass may affect quality of life in patients with asthma. However, whether these effects are observed regardless of intrapulmonary pathology is unknown. Objectives: We evaluated the correlation of the cross-sectional ratio of abdominal visceral fat (VF) to erector spinae muscle (ESM) and sinus findings based on Lund-Mackey scoring system (LMS) on computed tomography (CT) with the impaired score of the Asthma Quality of Life Questionnaire (AQLQ), regardless of airway and parenchymal disease, in patients with asthma. Methods: We recruited participants from the Hokkaido-based severe asthma cohort who had completed AQLQ and CT examination at the entry. The participants were divided into high (highest) and low (other quartiles) groups on the bases of the extrapulmonary indices. Multivariate analysis examined the association of VF/ESM for the adiposity-to-muscle ratio and LMS with AQLQ after adjusting for the airway fractal dimension for airway index and percentage of low attenuation volume to lung volume for parenchymal index. Results: No significant differences were observed in VF/ESM and LMS in terms of sex. The AQLQ score in the high VF/ESM group and high LMS group was lower than those in low VF/ESM group and low LMS group (63 male and 100 female subjects). High VF/ESM (estimate [95% confidence interval] (−0.43 [−0.61, −0.25]) and high LMS scores (−0.22 [−0.41, −0.03]) were associated with low AQLQ scores when adjusted for age, body mass index, smoking status, blood eosinophil count, and intrapulmonary CT indices. Conclusions: Increased VF relative to ESM mass and high LMS may deteriorate asthma-related quality of life, regardless of presence of intrapulmonary disease.

Objective This study aimed to investigate the utility of CT quantification of lung volume for predicting critical outcomes in COVID-19 patients.Methods This retrospective cohort study included 1200 hospitalised patients with COVID-19 from 4 hospitals. Lung fields were extracted using artificial intelligence-based segmentation, and the percentage of the predicted (%pred) total lung volume (TLC (%pred)) was calculated. The incidence of critical outcomes and posthospitalisation complications was compared between patients with low and high CT lung volumes classified based on the median percentage of predicted TLCct (n=600 for each). Prognostic factors for residual lung volume loss were investigated in 208 patients with COVID-19 via a follow-up CT after 3 months.Results The incidence of critical outcomes was higher in the low TLCct (%pred) group than in the high TLCct (%pred) group (14.2% vs 3.3%, p

Abstract Background The substantial heterogeneity of clinical presentations in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pneumonia still requires robust chest computed tomography analysis to identify high-risk patients. While extension of ground-glass opacity and consolidation from peripheral to central lung fields on chest computed tomography (CT) might be associated with severely ill conditions, quantification of the central-peripheral distribution of ground glass opacity and consolidation in assessments of SARS-CoV-2 pneumonia remains unestablished. This study aimed to examine whether the central-peripheral distributions of ground glass opacity and consolidation were associated with severe outcomes in patients with SARS-CoV-2 pneumonia independent of the whole-lung extents of these abnormal shadows. Methods This multicenter retrospective cohort included hospitalized patients with SARS-CoV-2 pneumonia between January 2020 and August 2021. An artificial intelligence-based image analysis technology was used to segment abnormal shadows, including ground glass opacity and consolidation. The area ratio of ground glass opacity and consolidation to the whole lung (GGO%, CON%) and the ratio of ground glass opacity and consolidation areas in the central lungs to those in the peripheral lungs (GGO(C/P)) and (CON(C/P)) were automatically calculated. Severe outcome was defined as in-hospital death or requirement for endotracheal intubation. Results Of 512 enrolled patients, the severe outcome was observed in 77 patients. GGO% and CON% were higher in patients with severe outcomes than in those without. Multivariable logistic models showed that GGO(C/P), but not CON(C/P), was associated with the severe outcome independent of age, sex, comorbidities, GGO%, and CON%. Conclusion In addition to GGO% and CON% in the whole lung, the higher the ratio of ground glass opacity in the central regions to that in the peripheral regions was, the more severe the outcomes in patients with SARS-CoV-2 pneumonia were. The proposed method might be useful to reproducibly quantify the extension of ground glass opacity from peripheral to central lungs and to estimate prognosis.

Abstract Background Computed tomography (CT) imaging and artificial intelligence (AI)-based analyses have aided in the diagnosis and prediction of the severity of COVID-19. However, the potential of AI-based CT quantification of pneumonia in assessing patients with COVID-19 has not yet been fully explored. This study aimed to investigate the potential of AI-based CT quantification of COVID-19 pneumonia to predict the critical outcomes and clinical characteristics of patients with residual lung lesions. Methods This retrospective cohort study included 1,200 hospitalized patients with COVID-19 from four hospitals. The incidence of critical outcomes (requiring the support of high-flow oxygen or invasive mechanical ventilation or death) and complications during hospitalization (bacterial infection, renal failure, heart failure, thromboembolism, and liver dysfunction) was compared between the groups of pneumonia with high/low-percentage lung lesions, based on AI-based CT quantification. Additionally, 198 patients underwent CT scans 3 months after admission to analyze prognostic factors for residual lung lesions. Results The pneumonia group with a high percentage of lung lesions (N = 400) had a higher incidence of critical outcomes and complications during hospitalization than the low percentage group (N = 800). Multivariable analysis demonstrated that AI-based CT quantification of pneumonia was independently associated with critical outcomes (adjusted odds ratio [aOR] 10.5, 95% confidence interval [CI] 5.59–19.7), as well as with oxygen requirement (aOR 6.35, 95% CI 4.60–8.76), IMV requirement (aOR 7.73, 95% CI 2.52–23.7), and mortality rate (aOR 6.46, 95% CI 1.87–22.3). Among patients with follow-up CT scans (N = 198), the multivariable analysis revealed that the pneumonia group with a high percentage of lung lesions on admission (aOR 4.74, 95% CI 2.36–9.52), older age (aOR 2.53, 95% CI 1.16–5.51), female sex (aOR 2.41, 95% CI 1.13–5.11), and medical history of hypertension (aOR 2.22, 95% CI 1.09–4.50) independently predicted persistent residual lung lesions. Conclusions AI-based CT quantification of pneumonia provides valuable information beyond qualitative evaluation by physicians, enabling the prediction of critical outcomes and residual lung lesions in patients with COVID-19.

Abstract Background Interstitial lung abnormalities (ILAs) are subtle or mild parenchymal abnormalities observed in more than 5% of the lungs on computed tomography (CT) scans in patients in whom interstitial lung disease was not previously clinically suspected and is considered. ILA is considered to be partly undeveloped stages of idiopathic pulmonary fibrosis (IPF) or progressive pulmonary fibrosis (PPF). This study aims to clarify the frequency of subsequent IPF or PPF diagnosis, the natural course from the preclinical status of the diseases, and the course after commencing treatment. Methods This is an ongoing, prospective, multicentre observational cohort study of patients with ILA referred from general health screening facilities with more than 70,000 annual attendances. Up to 500 participants will be enrolled annually over 3 years, with 5-year assessments every six months. Treatment intervention including anti-fibrotic agents will be introduced in disease progression cases. The primary outcome is the frequency of subsequent IPF or PPF diagnoses. Additionally, secondary and further endpoints are associated with the efficacy of early therapeutic interventions in cases involving disease progression, including quantitative assessment by artificial intelligence. Discussion This is the first prospective, multicentre, observational study to clarify (i) the aetiological data of patients with ILA from the largest general health check-up population, (ii) the natural course of IPF or PPF from the asymptomatic stage, and (iii) the effects and outcomes of early therapeutic intervention including anti-fibrotic agents for progressive cases of ILA. The results of this study could significantly impact the clinical practice and treatment strategy for progressive fibrosing interstitial lung diseases. Trial registration number UMIN000045149.

Background: The physiological importance of mucus plugs in computed tomography (CT) imaging is being increasingly recognized. However, whether airway inflammation and smoking affect the association between mucus plugs and clinical–physiological outcomes in asthma remains to be elucidated. The objective of this study is to examine how airway inflammation and/or smoking affect the correlation of CT-based mucus plug scores with exacerbation frequency and airflow limitation indices in asthma. Methods: A total of 168 patients with asthma who underwent chest CT and sputum evaluation were enrolled and classified in eosinophilic asthma (EA; n = 103) and non-eosinophilic asthma (NEA; n = 65) groups based on sputum eosinophil percentage (cut-off: 3%). The mucus plug score was defined as the number of lung segments with mucus plugs seen on CT. Results: More mucus plugs were detected on CT scans in the EA group than in the NEA group, regardless of smoking status. Mucus plug score and exacerbation frequency during one year after enrollment were significantly associated in the EA group but not in the NEA group after adjusting for demographics, blood eosinophil count, and fractional exhaled nitric oxide. Mucus plug score was associated with percentage of predicted forced expiratory volume in 1 s in non-smoking individuals in the EA and NEA group and in smoking individuals in the EA group but not in the NEA group after adjusting for demographics. Conclusions: The association of mucus plug score with exacerbation frequency and reduced lung function may vary due to airway inflammatory profile and smoking status in asthma.

Introduction Airway eosinophilic inflammation is a pathological feature in a subgroup of patients with COPD and in some smokers with a high COPD risk. Although blood eosinophil count is used to define eosinophilic COPD, the association between blood eosinophil count and airway eosinophilic inflammation remains controversial. This cross-sectional study tested this association in smokers with and without COPD while considering potential confounders, such as smoking status and comorbidities. Methods Lung specimens were obtained from smokers with and without COPD and non-COPD never-smokers undergoing lung lobectomy. Those with any asthma history were excluded. The infiltration of eosinophils into the small airway wall was quantified on histological sections stained with major basic protein (MBP). Results The number of airway MBP-positive cells was greater in smokers (n=60) than in never-smokers (n=14). Smokers with and without COPD (n=30 each) exhibited significant associations between blood eosinophil count and airway MBP-positive cells (ρ=0.45 and 0.71). When smokers were divided into the high and low airway MBP groups based on their median value, blood eosinophil count was higher in the high-MBP group, with no difference in age, smoking status, comorbidities, emphysema or coronary artery calcification on computed tomography, and inhaled corticosteroid (ICS) use. The association between greater blood eosinophil count and the high-MBP group was confirmed in multivariable models adjusted for smoking status, airflow limitation and ICS use. Conclusion The blood eosinophil count may reflect eosinophilic inflammation in the small airways in smokers with and without COPD.

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.

Objectives This study aimed to identify and investigate changes in the mortality of patients with chronic obstructive pulmonary disease (COPD) at the same institute from the 1990s to the 2000s. We hypothesised that the improvement in long-term mortality of COPD was achieved due to the development of pharmacological and non-pharmacological treatments.Design This study was a retrospective analysis of two observational prospective cohort studies. One study enrolled subjects from 1995 to 1997 (the 1990s), and the other enrolled subjects from 2005 to 2009 (the 2000s).Setting Two studies from a single centre, which was the same university hospital in Japan.Participants Patients with stable COPD.Primary and secondary outcome measures We analysed all-cause mortality data from the pooled database. Subanalyses were conducted by stratifying subjects into two groups according to airflow limitation severity as severe/very severe (per cent predicted value of forced expiratory volume in 1 s (%FEV1)

Background: The mechanism of high transfer coefficients of the lungs for carbon monoxide (Kco) in non-smokers with asthma is explained by the redistribution of blood flow to the area with preserved ventilation, to match the ventilation perfusion.Objectives: To examine whether ventilation heterogeneity, assessed by pulmonary function tests, is associated with computed tomography (CT)-based vascular indices and Kco in patients with asthma.Methods: Participants were enrolled from the Hokkaido-based Investigative Cohort Analysis for Refractory Asthma (Hi-CARAT) study that included a prospective asthmatic cohort. Pulmonary function tests including Kco, using single breath methods; total lung capacity (TLC), using multiple breath methods; and CT, were performed on the same day. The ratio of the lung volume assessed using single breath methods (alveolar volume; VA) to that using multiple breath methods (TLC) was calculated as an index of ventilation heterogeneity. The volume of the pulmonary small vessels

Abstract In patients with chronic obstructive pulmonary disease (COPD), emphysema, airway disease, and extrapulmonary comorbidities may cause various symptoms and impair physical activity. To investigate the relative associations of pulmonary and extrapulmonary manifestations with physical activity in symptomatic patients, this study enrolled 193 patients with COPD who underwent chest inspiratory/expiratory CT and completed COPD assessment test (CAT) and the Life-Space Assessment (LSA) questionnaires to evaluate symptom and physical activity. In symptomatic patients (CAT ≥ 10, n = 100), emphysema on inspiratory CT and air-trapping on expiratory CT were more severe and height-adjusted cross-sectional areas of pectoralis muscles (PM index) and adjacent subcutaneous adipose tissue (SAT index) on inspiratory CT were smaller in those with impaired physical activity (LSA

Abstract Background Ventilatory management of respiratory failure with pneumomediastinum/subcutaneous emphysema is not established. Herein, we report a case of severe COVID-19 pneumonia with extensive pneumomediastinum/subcutaneous emphysema, rescued by thorough lung-protective ventilatory management after applying the VV-ECMO. Case presentation A 68-year-old male with no medical history was admitted to a local hospital and diagnosed with COVID-19 pneumonia. His pulmonary parameters worsened during invasive ventilation due to the development of pneumomediastinum/subcutaneous emphysema, and then he was transferred to our hospital. On arrival, we immediately decided to apply VV-ECMO and switch to ultraprotective ventilation. After maintaining the initial ventilation with a neuromuscular blocking agent for 2 days, we gradually increased PEEP while limiting PIP to 25 cmH2O. The patient was weaned off VV-ECMO on day 10; he was transferred to the medical ward after extubation. Conclusions Lung-protective ventilatory management should be performed thoroughly during VV-ECMO in severe COVID-19 pneumonia with pneumomediastinum/subcutaneous emphysema.

Abstract Remdesivir, a prodrug of the nucleoside analog GS‐441524, plays a key role in the treatment of coronavirus disease 2019 (COVID‐19). However, owing to limited information on clinical trials and inexperienced clinical use, there is a lack of pharmacokinetic (PK) data in patients with COVID‐19 with special characteristics. In this study, we aimed to measure serum GS‐441524 concentrations and develop a population PK (PopPK) model. Remdesivir was administered at a 200 mg loading dose on the first day followed by 100 mg from day 2, based on the package insert, in patients with an estimated glomerular filtration rate (eGFR) greater than or equal to 30 ml/min. In total, 190 concentrations from 37 Japanese patients were used in the analysis. The GS‐441524 trough concentrations were significantly higher in the eGFR less than 60 ml/min group than in the eGFR greater than or equal to 60 ml/min group. Extracorporeal membrane oxygenation in four patients hardly affected the total body clearance (CL) and volume of distribution (Vd) of GS‐441524. A one‐compartment model described serum GS‐441524 concentration data. The CL and Vd of GS‐441524 were significantly affected by eGFR readjusted by individual body surface area and age, respectively. Simulations proposed a dose regimen of 200 mg on day 1 followed by 100 mg once every 2 days from day 2 in patients with an eGFR of 30 ml/min or less. In conclusion, we successfully established a PopPK model of GS‐441524 using retrospectively obtained serum GS‐441524 concentrations in Japanese patients with COVID‐19, which would be helpful for optimal individualized therapy of remdesivir.

Abstract The discriminative power of CURB-65 for mortality in community-acquired pneumonia (CAP) is suspected to decrease with age. However, a useful prognostic prediction model for older patients with CAP has not been established. This study aimed to develop and validate a new scoring system for predicting mortality in older patients with CAP. We recruited two prospective cohorts including patients aged ≥ 65 years and hospitalized with CAP. In the derivation (n = 872) and validation cohorts (n = 1,158), the average age was 82.0 and 80.6 years and the 30-day mortality rate was 7.6% (n = 66) and 7.4% (n = 86), respectively. A new scoring system was developed based on factors associated with 30-day mortality, identified by multivariate analysis in the derivation cohort. This scoring system named CHUBA comprised five variables: confusion, hypoxemia (SpO2 ≤ 90% or PaO2 ≤ 60 mmHg), blood urea nitrogen ≥ 30 mg/dL, bedridden state, and serum albumin level ≤ 3.0 g/dL. With regard to 30-day mortality, the area under the receiver operating characteristic curve for CURB-65 and CHUBA was 0.672 (95% confidence interval, 0.607–0.732) and 0.809 (95% confidence interval, 0.751–0.856; P

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.

Centrilobular emphysema (CLE) and paraseptal emphysema (PSE) are observed in smokers with preserved ratio impaired spirometry (PRISm, defined as the ratio of forced expiratory volume in 1 s (FEV1) to forced vital capacity (FVC) ≥0.7 and FEV1

Introduction Despite the poor prognosis for nursing home acquired pneumonia (NHAP), a useful prognostic factor is lacking. We evaluated protein C (PC) activity as a predictor of in-hospital death in patients with NHAP and community-acquired pneumonia (CAP). Methods This prospective, observational study included all patients hospitalized with pneumonia between July 2007 and December 2012 in a single hospital. We measured PC activity at admission and investigated whether it was different between survivors and non-survivors. We also examined whether PC activity < 55% was a predictor for in-hospital death of pneumonia by logistic regression analysis with CURB-65 items (confusion, blood urea >20 mg/dL, respiratory rate >30/min, and blood pressure 65). When it was a useful prognostic factor for pneumonia, we combined PC activity with the existing prognostic scores, the pneumonia severity index (PSI) and CURB-65, and analyzed its additional effect by comparing the areas under the receiver operating characteristic curves (AUCs) of the modified and original scores. Results Participants comprised 75 NHAP and 315 CAP patients. PC activity was lower among non-survivors than among survivors in NHAP and all-pneumonia (CAP+NHAP). PC activity Conclusions PC activity was useful for predicting in-hospital death of pneumonia, especially in NHAP, and became more useful when combined with the PSI or CURB-65.

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.

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