Skeletal Muscle Adiposity and Lung Function Trajectory in the Severe Asthma Research Program.

Rationale: Extrapulmonary manifestations of asthma, including fatty infiltration in tissues, may reflect systemic inflammation and influence lung function and disease severity. Objectives: To determine if skeletal muscle adiposity predicts lung function trajectory in asthma. Methods: Adult SARP III (Severe Asthma Research Program III) participants with baseline computed tomography imaging and longitudinal postbronchodilator FEV1% predicted (median follow-up 5 years [1,132 person-years]) were evaluated. The mean of left and right paraspinous muscle density (PSMD) at the 12th thoracic vertebral body was calculated (Hounsfield units [HU]). Lower PSMD reflects higher muscle adiposity. We derived PSMD reference ranges from healthy control subjects without asthma. A linear multivariable mixed-effects model was constructed to evaluate associations of baseline PSMD and lung function trajectory stratified by sex. Measurements and Main Results: Participants included 219 with asthma (67% women; mean [SD] body mass index, 32.3 [8.8] kg/m2) and 37 control subjects (51% women; mean [SD] body mass index, 26.3 [4.7] kg/m2). Participants with asthma had lower adjusted PSMD than control subjects (42.2 vs. 55.8 HU; P < 0.001). In adjusted models, PSMD predicted lung function trajectory in women with asthma (ß = -0.47 Δ slope per 10-HU decrease; P = 0.03) but not men (ß = 0.11 Δ slope per 10-HU decrease; P = 0.77). The highest PSMD tertile predicted a 2.9% improvement whereas the lowest tertile predicted a 1.8% decline in FEV1% predicted among women with asthma over 5 years. Conclusions: Participants with asthma have lower PSMD, reflecting greater muscle fat infiltration. Baseline PSMD predicted lung function decline among women with asthma but not men. These data support an important role of metabolic dysfunction in lung function decline.

CT pectoralis muscle area is associated with DXA lean mass and correlates with emphysema progression in a tobacco-exposed cohort.

INTRODUCTION: Muscle loss is an important extrapulmonary manifestation of COPD. Dual energy X-ray absorptiometry (DXA) is the method of choice for body composition measurement but is not widely used for muscle mass evaluation. The pectoralis muscle area (PMA) is quantifiable by CT and predicts cross-sectional COPD-related morbidity. There are no studies that compare PMA with DXA measures or that evaluate longitudinal relationships between PMA and lung disease progression. METHODS: Participants from our longitudinal tobacco-exposed cohort had baseline and 6-year chest CT (n=259) and DXA (n=164) data. Emphysema was quantified by CT density histogram parenchymal scoring using the 15th percentile technique. Fat-free mass index (FFMI) and appendicular skeletal mass index (ASMI) were calculated from DXA measurements. Linear regression model relationships were reported using standardised coefficient (ß) with 95% CI. RESULTS: PMA was more strongly associated with DXA measures than with body mass index (BMI) in both cross-sectional (FFMI: ß=0.76 (95% CI 0.65 to 0.86), p<0.001; ASMI: ß=0.76 (95% CI 0.66 to 0.86), p<0.001; BMI: ß=0.36 (95% CI 0.25 to 0.47), p<0.001) and longitudinal (ΔFFMI: ß=0.43 (95% CI 0.28 to 0.57), p<0.001; ΔASMI: ß=0.42 (95% CI 0.27 to 0.57), p<0.001; ΔBMI: ß=0.34 (95% CI 0.22 to 0.46), p<0.001) models. Six-year change in PMA was associated with 6-year change in emphysema (ß=0.39 (95% CI 0.23 to 0.56), p<0.001) but not with 6-year change in airflow obstruction. CONCLUSIONS: PMA is an accessible measure of muscle mass and may serve as a useful clinical surrogate for assessing skeletal muscle loss in smokers. Decreased PMA correlated with emphysema progression but not lung function decline, suggesting a difference in the pathophysiology driving emphysema, airflow obstruction and comorbidity risk.

Quantitative CT Characteristics of Cluster Phenotypes in the Severe Asthma Research Program Cohorts.

Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4; P < .001). Lower whole-lung Jacobian and ADI values were associated with greater cluster severity. Compared to cluster 1, cluster 5 lung expansion was 31% smaller (Jacobian in SARP III cohort: 2.31 ± 0.6 vs 1.61 ± 0.3, respectively, P < .001) and 34% more isotropic (ADI in SARP III cohort: 0.40 ± 0.1 vs 0.61 ± 0.2, P < .001). Within-lung Jacobian and ADI SDs decreased as severity worsened (Jacobian SD in SARP III cohort: 0.90 ± 0.4 for cluster 1; 0.79 ± 0.3 for cluster 2; 0.62 ± 0.2 for cluster 3; 0.63 ± 0.2 for cluster 4; and 0.41 ± 0.2 for cluster 5; P < .001). Conclusion Quantitative CT assessments of the degree and intraindividual regional variability of lung expansion distinguished between well-established clinical phenotypes among participants with asthma from the Severe Asthma Research Program study. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Verschakelen in this issue.

Super U-Net: a modularized generalizable architecture.

Objective: To develop and validate a novel convolutional neural network (CNN) termed "Super U-Net" for medical image segmentation. Methods: Super U-Net integrates a dynamic receptive field module and a fusion upsampling module into the classical U-Net architecture. The model was developed and tested to segment retinal vessels, gastrointestinal (GI) polyps, skin lesions on several image types (i.e., fundus images, endoscopic images, dermoscopic images). We also trained and tested the traditional U-Net architecture, seven U-Net variants, and two non-U-Net segmentation architectures. K-fold cross-validation was used to evaluate performance. The performance metrics included Dice similarity coefficient (DSC), accuracy, positive predictive value (PPV), and sensitivity. Results: Super U-Net achieved average DSCs of 0.808±0.0210, 0.752±0.019, 0.804±0.239, and 0.877±0.135 for segmenting retinal vessels, pediatric retinal vessels, GI polyps, and skin lesions, respectively. The Super U-net consistently outperformed U-Net, seven U-Net variants, and two non-U-Net segmentation architectures (p < 0.05). Conclusion: Dynamic receptive fields and fusion upsampling can significantly improve image segmentation performance.

Elevated plasma level of Pentraxin 3 is associated with emphysema and mortality in smokers.

BACKGROUND: Pentraxin 3 (PTX3) influences innate immunity and inflammation, host defence, the complement cascade and angiogenesis. PTX3 expression in lung and blood of subjects with tobacco exposure, and its potential relationship with disease pattern and clinical outcome are poorly understood. METHODS: Using independent platforms and cohorts, we identified associations of PTX3 gene expression in lung tissue and plasma from current and former tobacco smokers (with and without chronic obstructive pulmonary disease, COPD) to disease phenotypes including quantitative CT determined emphysema, lung function, symptoms and survival. Two putative regulatory variants of the PTX3 gene were examined for association with COPD manifestations. The relationship between plasma PTX3 and hyaluronic acid levels was further examined. RESULTS: PTX3 gene expression in lung tissue was directly correlated with emphysema severity (p<0.0001). Circulating levels of PTX3 were inversely correlated with FEV1 (p=0.006), and positively associated with emphysema severity (p=0.004) and mortality (p=0.008). Two PTX3 gene regulatory variants were associated with a lower risk for emphysema and expiratory airflow obstruction, and plasma levels of PTX3 and hyaluronic acid were related. CONCLUSIONS: These data show strong and overlapping associations of lung and blood PTX3 levels, and PTX3 regulatory gene variants, with the severity of airflow obstruction, emphysema and mortality among smokers. These findings have potential implications regarding the pathogenesis of smoking-related lung diseases and warrant further exploration for the use of PTX3 as a predictive biomarker.

Gene coexpression networks reveal novel molecular endotypes in alpha-1 antitrypsin deficiency.

BACKGROUND: Alpha-1 antitrypsin deficiency (AATD) is a genetic condition that causes early onset pulmonary emphysema and airways obstruction. The complete mechanisms via which AATD causes lung disease are not fully understood. To improve our understanding of the pathogenesis of AATD, we investigated gene expression profiles of bronchoalveolar lavage (BAL) and peripheral blood mononuclear cells (PBMCs) in AATD individuals. METHODS: We performed RNA-Seq on RNA extracted from matched BAL and PBMC samples isolated from 89 subjects enrolled in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Subjects were stratified by genotype and augmentation therapy. Supervised and unsupervised differential gene expression analyses were performed using Weighted Gene Co-expression Network Analysis (WGCNA) to identify gene profiles associated with subjects' clinical variables. The genes in the most significant WGCNA module were used to cluster AATD individuals. Gene validation was performed by NanoString nCounter Gene Expression Assay. RESULT: We observed modest effects of AATD genotype and augmentation therapy on gene expression. When WGCNA was applied to BAL transcriptome, one gene module, ME31 (2312 genes), correlated with the highest number of clinical variables and was functionally enriched with numerous immune T-lymphocyte related pathways. This gene module identified two distinct clusters of AATD individuals with different disease severity and distinct PBMC gene expression patterns. CONCLUSIONS: We successfully identified novel clusters of AATD individuals where severity correlated with increased immune response independent of individuals' genotype and augmentation therapy. These findings may suggest the presence of previously unrecognised disease endotypes in AATD that associate with T-lymphocyte immunity and disease severity.

Transcriptomics of bronchoalveolar lavage cells identifies new molecular endotypes of sarcoidosis.

BACKGROUND: Sarcoidosis is a multisystem granulomatous disease of unknown origin with a variable and often unpredictable course and pattern of organ involvement. In this study we sought to identify specific bronchoalveolar lavage (BAL) cell gene expression patterns indicative of distinct disease phenotypic traits. METHODS: RNA sequencing by Ion Torrent Proton was performed on BAL cells obtained from 215 well-characterised patients with pulmonary sarcoidosis enrolled in the multicentre Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study. Weighted gene co-expression network analysis and nonparametric statistics were used to analyse genome-wide BAL transcriptome. Validation of results was performed using a microarray expression dataset of an independent sarcoidosis cohort (Freiburg, Germany; n=50). RESULTS: Our supervised analysis found associations between distinct transcriptional programmes and major pulmonary phenotypic manifestations of sarcoidosis including T-helper type 1 (Th1) and Th17 pathways associated with hilar lymphadenopathy, transforming growth factor-ß1 (TGFB1) and mechanistic target of rapamycin (MTOR) signalling with parenchymal involvement, and interleukin (IL)-7 and IL-2 with airway involvement. Our unsupervised analysis revealed gene modules that uncovered four potential sarcoidosis endotypes including hilar lymphadenopathy with increased acute T-cell immune response; extraocular organ involvement with PI3K activation pathways; chronic and multiorgan disease with increased immune response pathways; and multiorgan involvement, with increased IL-1 and IL-18 immune and inflammatory responses. We validated the occurrence of these endotypes using gene expression, pulmonary function tests and cell differentials from Freiburg. CONCLUSION: Taken together, our results identify BAL gene expression programmes that characterise major pulmonary sarcoidosis phenotypes and suggest the presence of distinct disease molecular endotypes.

Automated quantification of COVID-19 severity and progression using chest CT images.

OBJECTIVE: To develop and test computer software to detect, quantify, and monitor progression of pneumonia associated with COVID-19 using chest CT scans. METHODS: One hundred twenty chest CT scans from subjects with lung infiltrates were used for training deep learning algorithms to segment lung regions and vessels. Seventy-two serial scans from 24 COVID-19 subjects were used to develop and test algorithms to detect and quantify the presence and progression of infiltrates associated with COVID-19. The algorithm included (1) automated lung boundary and vessel segmentation, (2) registration of the lung boundary between serial scans, (3) computerized identification of the pneumonitis regions, and (4) assessment of disease progression. Agreement between radiologist manually delineated regions and computer-detected regions was assessed using the Dice coefficient. Serial scans were registered and used to generate a heatmap visualizing the change between scans. Two radiologists, using a five-point Likert scale, subjectively rated heatmap accuracy in representing progression. RESULTS: There was strong agreement between computer detection and the manual delineation of pneumonic regions with a Dice coefficient of 81% (CI 76-86%). In detecting large pneumonia regions (> 200 mm3), the algorithm had a sensitivity of 95% (CI 94-97%) and specificity of 84% (CI 81-86%). Radiologists rated 95% (CI 72 to 99) of heatmaps at least "acceptable" for representing disease progression. CONCLUSION: The preliminary results suggested the feasibility of using computer software to detect and quantify pneumonic regions associated with COVID-19 and to generate heatmaps that can be used to visualize and assess progression. KEY POINTS: • Both computer vision and deep learning technology were used to develop computer software to quantify the presence and progression of pneumonia associated with COVID-19 depicted on CT images. • The computer software was tested using both quantitative experiments and subjective assessment. • The computer software has the potential to assist in the detection of the pneumonic regions, monitor disease progression, and assess treatment efficacy related to COVID-19.

Feasibility of lung cancer prediction from low-dose CT scan and smoking factors using causal models.

INTRODUCTION: Low-dose CT (LDCT) is currently used in lung cancer screening of high-risk populations for early lung cancer diagnosis. However, 96% of individuals with detected nodules are false positives. METHODS: In order to develop an efficient early lung cancer predictor from clinical, demographic and LDCT features, we studied a total of 218 subjects with lung cancer or benign nodules. Probabilistic graphical models (PGMs) were used to integrate demographics, clinical data and LDCT features from 92 subjects (training cohort) from the Pittsburgh Lung Screening Study cohort. RESULTS: Learnt PGMs identified three variables directly (causally) linked to malignant nodules and the largest benign nodule and used them to build the Lung Cancer Causal Model (LCCM), which was validated in a separate cohort of 126 subjects. Nodule and vessel numbers and years since the subject quit smoking were sufficient to discriminate malignant from benign nodules. Comparison with existing predictors in the training and validation cohorts showed that (1) incorporating LDCT scan features greatly enhances predictive accuracy; and (2) LCCM improves cancer detection over existing methods, including the Brock parsimonious model (p<0.001). Notably, the number of surrounding vessels, a feature not previously used in predictive models, significantly improves predictive efficiency. Based on the validation cohort results, LCCM is able to identify 30% of the benign nodules without risk of misclassifying cancer nodules. DISCUSSION: LCCM shows promise as a lung cancer predictor as it is significantly improved over existing models. Validated in a larger, prospective study, it may help reduce unnecessary follow-up visits and procedures.

Loss of skin elasticity is associated with pulmonary emphysema, biomarkers of inflammation, and matrix metalloproteinase activity in smokers.

BACKGROUND: Elastin breakdown and the resultant loss of lung elastic recoil is a hallmark of pulmonary emphysema in susceptible individuals as a consequence of tobacco smoke exposure. Systemic alterations to the synthesis and degradation of elastin may be important to our understanding of disease phenotypes in chronic obstructive pulmonary disease. We investigated the association of skin elasticity with pulmonary emphysema, obstructive lung disease, and blood biomarkers of inflammation and tissue protease activity in tobacco-exposed individuals. METHODS: Two hundred and thirty-six Caucasian individuals were recruited into a sub-study of the University of Pittsburgh Specialized Center for Clinically Orientated Research in chronic obstructive pulmonary disease, a prospective cohort study of current and former smokers. The skin viscoelastic modulus (VE), a determinant of skin elasticity, was recorded from the volar forearm and facial wrinkling severity was determined using the Daniell scoring system. RESULTS: In a multiple regression analysis, reduced VE was significantly associated with cross-sectional measurement of airflow obstruction (FEV1/FVC) and emphysema quantified from computed tomography (CT) images, ß = 0.26, p = 0.001 and ß = 0.24, p = 0.001 respectively. In emphysema-susceptible individuals, elasticity-determined skin age was increased (median 4.6 years) compared to the chronological age of subjects without emphysema. Plasma biomarkers of inflammation (TNFR1, TNFR2, CRP, PTX3, and SAA) and matrix metalloproteinase activity (MMP1, TIMP1, TIMP2, and TIMP4) were inversely associated with skin elasticity. CONCLUSIONS: We report that an objective non-invasive determinant of skin elasticity is independently associated with measures of lung function, pulmonary emphysema, and biomarkers of inflammation and tissue proteolysis in tobacco-exposed individuals. Loss of skin elasticity is a novel observation that may link the common pathological processes that drive tissue elastolysis in the extracellular matrix of the skin and lung in emphysema-susceptible individuals.

Extreme Trait Whole-Genome Sequencing Identifies PTPRO as a Novel Candidate Gene in Emphysema with Severe Airflow Obstruction.

RATIONALE: Genetic association studies in chronic obstructive pulmonary disease have primarily tested for association with common variants, the results of which explain only a portion of disease heritability. Because rare variation is also likely to contribute to susceptibility, we used whole-genome sequencing of subjects with clinically extreme phenotypes to identify genomic regions enriched for rare variation contributing to chronic obstructive pulmonary disease susceptibility. OBJECTIVES: To identify regions of rare genetic variation contributing to emphysema with severe airflow obstruction. METHODS: We identified heavy smokers that were resistant (n = 65) or susceptible (n = 64) to emphysema with severe airflow obstruction in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We filtered whole-genome sequencing results to include only rare variants and conducted single variant tests, region-based tests across the genome, gene-based tests, and exome-wide tests. MEASUREMENTS AND MAIN RESULTS: We identified several suggestive associations with emphysema with severe airflow obstruction, including a suggestive association of all rare variation in a region within the gene ZNF816 (19q13.41; P = 4.5 × 10-6), and a suggestive association of nonsynonymous coding rare variation in the gene PTPRO (P = 4.0 × 10-5). Association of rs61754411, a rare nonsynonymous variant in PTPRO, with emphysema and obstruction was demonstrated in all non-Hispanic white individuals in the Pittsburgh Specialized Center of Clinically Oriented Research cohort. We found that cells containing this variant have decreased signaling in cellular pathways necessary for survival and proliferation. CONCLUSIONS: PTPRO is a novel candidate gene in emphysema with severe airflow obstruction, and rs61754411 is a previously unreported rare variant contributing to emphysema susceptibility. Other suggestive candidate genes, such as ZNF816, are of interest for future studies.

Mediastinal and Subcutaneous Chest Fat Are Differentially Associated with Emphysema Progression and Clinical Outcomes in Smokers.

BACKGROUND: Studies have demonstrated both positive and negative effects of obesity on clinical outcomes in chronic obstructive pulmonary disease (COPD). In other chronic diseases, fat location is differentially associated with disease outcomes; however, this relationship has not been well studied in COPD. OBJECTIVE: To determine if fat location explains the differential association of body mass index (BMI) with clinical outcome measures in smokers. METHODS: Baseline and 6-year chest computed tomography scans from 68 current and former smokers were used to quantify mediastinal and subcutaneous fat. The relationships of BMI, mediastinal fat, and subcutaneous fat with cross-sectional and 6-year changes in pulmonary function, incremental shuttle walk distance (ISWD), quantitative emphysema, and circulating interleukin-6 (IL-6) and C-reactive protein (CRP) levels were assessed using generalized linear models adjusted for clinically relevant covariates. RESULTS: Baseline subcutaneous fat was negatively associated with emphysema progression over 6 years (p < 0.01). BMI and mediastinal fat volume were inversely associated with baseline ISWD (p < 0.01 and p = 0.043, respectively) as well as 6-year change in ISWD (p = 0.020 and p = 0.028, respectively). IL-6 was directly associated with BMI and mediastinal fat (p < 0.01) and CRP was directly associated with BMI only (p = 0.033). CONCLUSIONS: Increased subcutaneous chest fat is associated with less emphysema progression over time in smokers, while increased mediastinal fat volume is associated with decreased walk distance and increased IL-6 levels. These findings suggest a complex interaction between fat, inflammation, and emphysema that should be considered when phenotyping patients with COPD and provide new evidence of an inverse association between emphysema progression and chest subcutaneous fat.

Airflow Limitation and Endothelial Dysfunction. Unrelated and Independent Predictors of Atherosclerosis.

RATIONALE: Lower FEV1 is associated with increased prevalence of atherosclerosis; however, causal mechanisms remain elusive. OBJECTIVES: To determine if systemic endothelial dysfunction mediates the association between reduced FEV1 and increased atherosclerosis. METHODS: Brachial artery endothelial function, pulmonary function, coronary artery calcium, and carotid plaque were assessed in 231 Pittsburgh SCCOR (Specialized Centers for Clinically Oriented Research) study participants; peripheral arterial endothelial function, pulmonary function, and coronary artery calcium were assessed in 328 HeartSCORE (Heart Strategies Concentrating on Risk Evaluation) study participants. MEASUREMENTS AND MAIN RESULTS: Lower FEV1 was independently associated with increased atherosclerosis in both cohorts (per 25% lower % predicted FEV1: odds ratio [OR], 1.76; 95% confidence interval [CI], 1.30-2.40; P < 0.001 for carotid plaque in SCCOR participants) (per 25% lower % predicted FEV1: OR, 1.35; 95% CI, 1.02-1.77; P = 0.03 for coronary artery calcium in HeartSCORE participants). Similarly, reduced endothelial function was independently associated with increased atherosclerosis in both cohorts (per SD lower endothelial function: OR, 1.30; 95% CI, 1.01-1.67; P = 0.04 for carotid plaque in SCCOR participants) (per SD lower endothelial function: OR, 1.38; 95% CI, 1.09-1.76; P = 0.008 and OR, 1.41; 95% CI, 1.07-1.86; P = 0.01 for coronary artery calcium in SCCOR and HeartSCORE participants, respectively). However, there was no association between endothelial dysfunction and FEV1, FEV1/FVC, low-attenuation area/visual emphysema, and diffusing capacity in SCCOR participants, and between endothelial dysfunction and FEV1 or FEV1/FVC in HeartSCORE participants (all P > 0.05). Adjusting the association between FEV1 and atherosclerosis for endothelial dysfunction had no impact. CONCLUSIONS: Endothelial dysfunction does not mediate the association between airflow limitation and atherosclerosis. Instead, airflow limitation and endothelial dysfunction seem to be unrelated and mutually independent predictors of atherosclerosis.

Adiposity influences airway wall thickness and the asthma phenotype of HIV-associated obstructive lung disease: a cross-sectional study.

BACKGROUND: Airflow obstruction, which encompasses several phenotypes, is common among HIV-infected individuals. Obesity and adipose-related inflammation are associated with both COPD (fixed airflow obstruction) and asthma (reversible airflow obstruction) in HIV-uninfected persons, but the relationship to airway inflammation and airflow obstruction in HIV-infected persons is unknown. The objective of this study was to determine if adiposity and adipose-associated inflammation are associated with airway obstruction phenotypes in HIV-infected persons. METHODS: We performed a cross-sectional analysis of 121 HIV-infected individuals assessed with pulmonary function testing, chest CT scans for measures of airway wall thickness (wall area percent [WA%]) and adipose tissue volumes (mediastinal and subcutaneous), as well as HIV- and adipose-related inflammatory markers. Participants were defined as COPD phenotype (post-bronchodilator FEV1/FVC < lower limit of normal) or asthma phenotype (doctor-diagnosed asthma or bronchodilator response). Pearson correlation coefficients were calculated between adipose measurements, WA%, and pulmonary function. Multivariable logistic and linear regression models were used to determine associations of airflow obstruction and airway remodeling (WA%) with adipose measurements and participant characteristics. RESULTS: Twenty-three (19 %) participants were classified as the COPD phenotype and 33 (27 %) were classified as the asthma phenotype. Body mass index (BMI) was similar between those with and without COPD, but higher in those with asthma compared to those without (mean [SD] 30.7 kg/m(2) [8.1] vs. 26.5 kg/m(2) [5.3], p = 0.008). WA% correlated with greater BMI (r = 0.55, p < 0.001) and volume of adipose tissue (subcutaneous, r = 0.40; p < 0.001; mediastinal, r = 0.25; p = 0.005). Multivariable regression found the COPD phenotype associated with greater age and pack-years smoking; the asthma phenotype with younger age, female gender, smoking history, and lower adiponectin levels; and greater WA% with greater BMI, younger age, higher soluble CD163, and higher CD4 counts. CONCLUSIONS: Adiposity and adipose-related inflammation are associated with an asthma phenotype, but not a COPD phenotype, of obstructive lung disease in HIV-infected persons. Airway wall thickness is associated with adiposity and inflammation. Adipose-related inflammation may play a role in HIV-associated asthma.

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma.

OBJECTIVE: We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification. METHODS: We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repeated-measures analysis of variance. RESULTS: Phantom measurements were more accurate when FOV decreased from 30 to 15 cm (P < 0.05). Decreasing FOV further to 10 cm did not significantly improve accuracy. Human airway measurements similarly decreased by decreasing FOV (P < 0.001). Percent changes in all measurements when reducing FOV from 30 to 15 cm were less than 3%. CONCLUSIONS: Airway measurements at 30-cm FOV are near the limits of CT resolution using a medium-smooth kernel. Reducing reconstructed FOV would minimally increase sensitivity to detect differences in airway dimensions.

C-X-C motif chemokine 13 (CXCL13) is a prognostic biomarker of idiopathic pulmonary fibrosis.

RATIONALE: C-X-C motif chemokine 13 (CXCL13) mediates B-cell trafficking and is increased, proportionately to disease activity, in many antibody-mediated syndromes. Dysregulated B cells have recently been implicated in idiopathic pulmonary fibrosis (IPF) pathogenesis. OBJECTIVES: To determine if CXCL13 is associated with IPF progression. METHODS: CXCL13 was measured in lungs by DNA microarray and immunohistochemistry, and in plasma by ELISA. MEASUREMENTS AND MAIN RESULTS: CXCL13 mRNA was threefold and eightfold greater in IPF lungs (n = 92) compared with chronic obstructive pulmonary disease (COPD) (n = 191) and normal (n = 108) specimens, respectively (P < 0.0001). IPF lungs also showed increased CXCL13 staining. Plasma CXCL13 concentrations (pg/ml) were greater in 95 patients with IPF (94 ± 8) than in 128 subjects with COPD (53 ± 9) and 57 normal subjects (35 ± 3) (P < 0.0001). Circulating CXCL13 levels were highest in patients with IPF with pulmonary artery hypertension (P = 0.01) or acute exacerbations (P = 0.002). Six-month survival of patients with IPF in the highest quartile of plasma CXCL13 was 65 ± 10% versus 93 ± 10% in the others (hazard ratio, 5.5; 95% confidence interval, 1.8-16.9; P = 0.0008). CXCL13 increases by more than 50% in IPF serial assays, irrespective of initial values, also presaged respiratory failure (hazard ratio, 7.2; 95% confidence interval, 1.3-40.0; P = 0.008). In contrast, CXCL13 clinical associations in subjects with COPD were limited to modest correlations with FEV1 (P = 0.05) and progression of radiographic emphysema (P = 0.05). CONCLUSIONS: CXCL13 is increased and is a prognostic biomarker in patients with IPF, and more so than in patients with COPD. This contrast indicates CXCL13 overexpressions are intrinsic to IPF, rather than an epiphenomenon of lung injury. The present data implicate CXCL13 and B cells in IPF pathogenesis, and support considerations for trials of specific B-cell-targeted therapies in patients with this intractable disease.

Contributors to diffusion impairment in HIV-infected persons.

Abnormal diffusing capacity is common in HIV-infected individuals, including never smokers. Aetiologies for diffusing capacity impairment in HIV are not understood, particularly in those without a history of cigarette smoking. Our study was a cross-sectional analysis of 158 HIV-infected individuals without acute respiratory symptoms or infection with the aim to determine associations between a diffusing capacity of the lung for carbon monoxide (D(LCO)) % predicted and participant demographics, pulmonary spirometric measures (forced expiratory volume in 1 s (FEV1) and FEV1/forced vital capacity), radiographic emphysema (fraction of lung voxels < -950 Hounsfield units), pulmonary vascular/cardiovascular disease (echocardiographic tricuspid regurgitant jet velocity, N-terminal pro-brain natriuretic peptide) and airway inflammation (induced sputum cell counts), stratified by history of smoking. The mean D(LCO) was 65.9% predicted, and 55 (34.8%) participants had a significantly reduced D(LCO) (<60% predicted). Lower D(LCO) % predicted in ever-smokers was associated with lower post-bronchodilator FEV1 % predicted (p<0.001) and greater radiographic emphysema (p=0.001). In never-smokers, mean±SD D(LCO) was 72.7±13.4% predicted, and D(LCO) correlated with post-bronchodilator FEV1 (p=0.02), sputum neutrophils (p=0.03) and sputum lymphocytes (p=0.009), but not radiographic emphysema. Airway obstruction, emphysema and inflammation influence D(LCO) in HIV. Never-smokers may have a unique phenotype of diffusing capacity impairment. The interaction of multiple factors may account for the pervasive nature of diffusing capacity impairment in HIV infection.

Graphical modeling of causal factors associated with the postoperative survival of esophageal cancer subjects.

PURPOSE: To clarify the causal relationship between factors contributing to the postoperative survival of patients with esophageal cancer. METHODS: A cohort of 195 patients who underwent surgery for esophageal cancer between 2008 and 2021 was used in the study. All patients had preoperative chest computed tomography (CT) and positron emission tomography-CT (PET-CT) scans prior to receiving any treatment. From these images, high throughput and quantitative radiomic features, tumor features, and various body composition features were automatically extracted. Causal relationships among these image features, patient demographics, and other clinicopathological variables were analyzed and visualized using a novel score-based directed graph called "Grouped Greedy Equivalence Search" (GGES) while taking prior knowledge into consideration. After supplementing and screening the causal variables, the intervention do-calculus adjustment (IDA) scores were calculated to determine the degree of impact of each variable on survival. Based on this IDA score, a GGES prediction formula was generated. Ten-fold cross-validation was used to assess the performance of the models. The prediction results were evaluated using the R-Squared Score (R2 score). RESULTS: The final causal graphical model was formed by two PET-based image variables, ten body composition variables, four pathological variables, four demographic variables, two tumor variables, and one radiological variable (Percentile 10). Intramuscular fat mass was found to have the most impact on overall survival month. Percentile 10 and overall TNM (T: tumor, N: nodes, M: metastasis) stage were identified as direct causes of overall survival (month). The GGES casual model outperformed GES in regression prediction (R2  = 0.251) (p < 0.05) and was able to avoid unreasonable causality that may contradict common sense. CONCLUSION: The GGES causal model can provide a reliable and straightforward representation of the intricate causal relationships among the variables that impact the postoperative survival of patients with esophageal cancer.

XRayWizard: Reconstructing 3-D lung surfaces from a single 2-D chest x-ray image via Vision Transformer.

BACKGROUND: Chest x-ray is widely utilized for the evaluation of pulmonary conditions due to its technical simplicity, cost-effectiveness, and portability. However, as a two-dimensional (2-D) imaging modality, chest x-ray images depict limited anatomical details and are challenging to interpret. PURPOSE: To validate the feasibility of reconstructing three-dimensional (3-D) lungs from a single 2-D chest x-ray image via Vision Transformer (ViT). METHODS: We created a cohort of 2525 paired chest x-ray images (scout images) and computed tomography (CT) acquired on different subjects and we randomly partitioned them as follows: (1) 1800 - training set, (2) 200 - validation set, and (3) 525 - testing set. The 3-D lung volumes segmented from the chest CT scans were used as the ground truth for supervised learning. We developed a novel model termed XRayWizard that employed ViT blocks to encode the 2-D chest x-ray image. The aim is to capture global information and establish long-range relationships, thereby improving the performance of 3-D reconstruction. Additionally, a pooling layer at the end of each transformer block was introduced to extract feature information. To produce smoother and more realistic 3-D models, a set of patch discriminators was incorporated. We also devised a novel method to incorporate subject demographics as an auxiliary input to further improve the accuracy of 3-D lung reconstruction. Dice coefficient and mean volume error were used as performance metrics as the agreement between the computerized results and the ground truth. RESULTS: In the absence of subject demographics, the mean Dice coefficient for the generated 3-D lung volumes achieved a value of 0.738 ± 0.091. When subject demographics were included as an auxiliary input, the mean Dice coefficient significantly improved to 0.769 ± 0.089 (p < 0.001), and the volume prediction error was reduced from 23.5 ± 2.7%. to 15.7 ± 2.9%. CONCLUSION: Our experiment demonstrated the feasibility of reconstructing 3-D lung volumes from 2-D chest x-ray images, and the inclusion of subject demographics as additional inputs can significantly improve the accuracy of 3-D lung volume reconstruction.

Assessment of lung volume collapsibility in chronic obstructive lung disease patients using CT.

OBJECTIVE: To investigate the collapsibility of the lung and individual lobes in patients with COPD during inspiration/expiration and assess the association of whole lung and lobar volume changes with pulmonary function tests (PFTs) and disease severity. METHODS: PFT measures used were RV/TLC%, FEV1% predicted, FVC, FEV1/FVC%, DLco% predicted and GOLD category. A total of 360 paired inspiratory and expiratory CT examinations acquired in 180 subjects were analysed. Automated computerised algorithms were used to compute individual lobe and total lung volumes. Lung volume collapsibility was assessed quantitatively using the simple difference between CT computed inspiration (I) and expiration (E) volumes (I-E), and a relative measure of volume changes, (I-E)/I. RESULTS: Mean absolute collapsibility (I-E) decreased in all lung lobes with increasing disease severity defined by GOLD classification. Relative collapsibility (I-E)/I showed a similar trend. Upper lobes had lower volume collapsibility across all GOLD categories and lower lobes collectively had the largest volume collapsibility. Whole lung and left lower lobe collapsibility measures tended to have the highest correlations with PFT measures. Collapsibility of lung lobes and whole lung was also negatively correlated with the degree of air trapping between expiration and inspiration, as measured by mean lung density. All measured associations were statistically significant (P < 0.01). CONCLUSION: Severity of COPD appears associated with increased collapsibility in the upper lobes, but change (decline) in collapsibility is faster in the lower lobes. KEY POINTS: • Inspiratory and expiratory computed tomography allows assessment of lung collapsibility • Lobe volume collapsibility is significantly correlated with measures of lung function. • As COPD severity increases, collapsibility of individual lung lobes decreases. • Upper lobes exhibit more severe disease, while lower lobes decline faster.