Association between acute respiratory disease events and the MUC5B promoter polymorphism in smokers

A single-nucleotide polymorphism (rs35705950) in the mucin 5B (MUC5B) gene promoter is associated with pulmonary fibrosis and interstitial features on chest CT but may also have beneficial effects. In non-Hispanic whites in the COPDGene cohort with interstitial features (n=454), the MUC5B promoter polymorphism was associated with a 61% lower odds of a prospectively reported acute respiratory disease event (P=0.001), a longer time-to-first event (HR=0.57; P=0.006) and 40% fewer events (P=0.016). The MUC5B promoter polymorphism may have a beneficial effect on the risk of acute respiratory disease events in smokers with interstitial CT features.

Significance of Low-Attenuation Cluster Analysis on Quantitative CT in the Evaluation of Chronic Obstructive Pulmonary Disease

Objective

To assess clinical feasibility of low-attenuation cluster analysis in evaluation of chronic obstructive pulmonary disease (COPD).

Materials and Methods

Subjects were 199 current and former cigarette smokers that underwent CT for quantification of COPD and had physiological measurements. Quantitative CT (QCT) measurements included low-attenuation area percent (LAA%) (voxels ≤ -950 Hounsfield unit [HU]), and two-dimensional (2D) and three-dimensional D values of cluster analysis at three different thresholds of CT value (-856, -910, and -950 HU). Correlation coefficients between QCT measurements and physiological indices were calculated. Multivariable analyses for percentage of predicted forced expiratory volume at one second (%FEV1) was performed including sex, age, body mass index, LAA%, and D value had the highest correlation coefficient with %FEV1 as independent variables. These analyses were conducted in subjects including those with mild COPD (global initiative of chronic obstructive lung disease stage = 0-II).

Results

LAA% had a higher correlation coefficient (-0.549, p < 0.001) with %FEV1 than D values in subjects while 2D D_-910HU (-0.350, p < 0.001) revealed slightly higher correlation coefficient than LAA% (-0.343, p < 0.001) in subjects with mild COPD. Multivariable analyses revealed that LAA% and 2D D value_-910HU were significant independent predictors of %FEV1 in subjects and that only 2D D value_-910HU revealed a marginal p value (0.05) among independent variables in subjects with mild COPD.

Conclusion

Low-attenuation cluster analysis provides incremental information regarding physiologic severity of COPD, independent of LAA%, especially with mild COPD.

CT measurements of central pulmonary vasculature as predictors of severe exacerbation in COPD

To identify a predictive value for the exacerbation status of chronic obstructive pulmonary disease (COPD) subjects, we evaluated the relationship between pulmonary vascular measurements on chest CT and severe COPD exacerbation.Six hundred three subjects enrolled in the COPDGene population were included and divided into nonexacerbator (n = 313) and severe exacerbator (n = 290) groups, based on whether they had an emergency room visit and/or hospitalization for COPD exacerbation. We measured the diameter of the main pulmonary artery (MPA) and ascending aorta (AA) at 2 different sites of the MPA (the tubular midportion and bifurcation) on both axial images and multiplanar reconstructions. Using multiple logistic regression analyses, we evaluated the relationship between each CT-measured pulmonary vasculature and exacerbation status.Axial and multiplanar MPA to AA diameter ratios (PA:AA ratios) at the tubular midportion and the axial PA:AA ratios at the bifurcation indicated significant association with severe exacerbation. The strongest association was found with the axial PA:mean AA ratio at the bifurcation (adjusted odds ratio [OR] = 12.53, 95% confidence interval [CI] = 2.35-66.74, P = .003) and the axial PA:major AA ratio at the tubular midportion (adjusted OR = 10.72, 95% CI = 1.99-57.86, P = .006). No differences were observed in the MPA diameter. Receiver operating characteristic analysis of these variables indicates that they may serve as a good predictive value for severe exacerbation (area under the curve, 0.77-0.78). The range of cut-off value for PA:AA ratio was 0.8 to 0.87.CT-measured PA:AA ratios at either the bifurcation or the tubular site, measured either on axial or multiplanar images, are useful for identification of the risk of severe exacerbation, and consequently can be helpful in guiding the management of COPD. Although CT measurement was used at the level of pulmonary bifurcation in previous studies, we suggest that future studies should monitor the tubular site of the MPA for maximum diagnostic value of CT in pulmonary hypertension or severe COPD exacerbation, as the tubular site of the MPA remains relatively constant on CT images.

Asthma Is a Risk Factor for Respiratory Exacerbations Without Increased Rate of Lung Function Decline: Five-Year Follow-up in Adult Smokers From the COPDGene Study

BACKGROUND

Previous investigations in adult smokers from the COPDGene Study have shown that early-life respiratory disease is associated with reduced lung function, COPD, and airway thickening. Using 5-year follow-up data, we assessed disease progression in subjects who had experienced early-life respiratory disease. We hypothesized that there are alternative pathways to reaching reduced FEV₁ and that subjects who had childhood pneumonia, childhood asthma, or asthma-COPD overlap (ACO) would have less lung function decline than subjects without these conditions.

METHODS

Subjects returning for 5-year follow-up were assessed. Childhood pneumonia was defined by self-reported pneumonia at < 16 years. Childhood asthma was defined as self-reported asthma diagnosed by a health professional at < 16 years. ACO was defined as subjects with COPD who self-reported asthma diagnosed by a health-professional at ≤ 40 years. Smokers with and those without these early-life respiratory diseases were compared on measures of disease progression.

RESULTS

Follow-up data from 4,915 subjects were examined, including 407 subjects who had childhood pneumonia, 323 subjects who had childhood asthma, and 242 subjects with ACO. History of childhood asthma or ACO was associated with an increased exacerbation frequency (childhood asthma, P < .001; ACO, P = .006) and odds of severe exacerbations (childhood asthma, OR, 1.41; ACO, OR, 1.42). History of childhood pneumonia was associated with increased exacerbations in subjects with COPD (absolute difference [β], 0.17; P = .04). None of these early-life respiratory diseases were associated with an increased rate of lung function decline or progression on CT scans.

CONCLUSIONS

Subjects who had early-life asthma are at increased risk of developing COPD and of having more active disease with more frequent and severe respiratory exacerbations without an increased rate of lung function decline over a 5-year period.

TRIAL REGISTRY

ClinicalTrials.gov; No. NCT00608764; https://clinicaltrials.gov.

An Ensemble Method for Classifying Regional Disease Patterns of Diffuse Interstitial Lung Disease Using HRCT Images from Different Vendors

We propose the use of ensemble classifiers to overcome inter-scanner variations in the differentiation of regional disease patterns in high-resolution computed tomography (HRCT) images of diffuse interstitial lung disease patients obtained from different scanners. A total of 600 rectangular 20 × 20-pixel regions of interest (ROIs) on HRCT images obtained from two different scanners (GE and Siemens) and the whole lung area of 92 HRCT images were classified as one of six regional pulmonary disease patterns by two expert radiologists. Textual and shape features were extracted from each ROI and the whole lung parenchyma. For automatic classification, individual and ensemble classifiers were trained and tested with the ROI dataset. We designed the following three experimental sets: an intra-scanner study in which the training and test sets were from the same scanner, an integrated scanner study in which the data from the two scanners were merged, and an inter-scanner study in which the training and test sets were acquired from different scanners. In the ROI-based classification, the ensemble classifiers showed better (p < 0.001) accuracy (89.73%, SD = 0.43) than the individual classifiers (88.38%, SD = 0.31) in the integrated scanner test. The ensemble classifiers also showed partial improvements in the intra- and inter-scanner tests. In the whole lung classification experiment, the quantification accuracies of the ensemble classifiers with integrated training (49.57%) were higher (p < 0.001) than the individual classifiers (48.19%). Furthermore, the ensemble classifiers also showed better performance in both the intra- and inter-scanner experiments. We concluded that the ensemble classifiers provide better performance when using integrated scanner images.

Transfer Learning for Multicenter Classification of Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is a lung disease that can be quantified using chest computed tomography scans. Recent studies have shown that COPD can be automatically diagnosed using weakly supervised learning of intensity and texture distributions. However, up till now such classifiers have only been evaluated on scans from a single domain, and it is unclear whether they would generalize across domains, such as different scanners or scanning protocols. To address this problem, we investigate classification of COPD in a multicenter dataset with a total of 803 scans from three different centers, four different scanners, with heterogenous subject distributions. Our method is based on Gaussian texture features, and a weighted logistic classifier, which increases the weights of samples similar to the test data. We show that Gaussian texture features outperform intensity features previously used in multicenter classification tasks. We also show that a weighting strategy based on a classifier that is trained to discriminate between scans from different domains can further improve the results. To encourage further research into transfer learning methods for the classification of COPD, upon acceptance of this paper we will release two feature datasets used in this study on http://bigr.nl/research/projects/copd.

Pulmonary fibrosis: tissue characterization using late-enhanced MRI compared with unenhanced anatomic high-resolution CT

PURPOSE

We aimed to prospectively evaluate anatomic chest computed tomography (CT) with tissue characterization late gadolinium-enhanced magnetic resonance imaging (MRI) in the evaluation of pulmonary fibrosis (PF).

METHODS

Twenty patients with idiopathic pulmonary fibrosis (IPF) and twelve control patients underwent late-enhanced MRI and high-resolution CT. Tissue characterization of PF was depicted using a segmented inversion-recovery turbo low-angle shot MRI sequence. Pulmonary arterial blood pool nulling was achieved by nulling main pulmonary artery signal. Images were read in random order by a blinded reader for presence and extent of overall PF (reticulation and honeycombing) at five anatomic levels. Overall extent of IPF was estimated to the nearest 5% as well as an evaluation of the ratios of IPF made up of reticulation and honeycombing. Overall grade of severity was dependent on the extent of reticulation and honeycombing.

RESULTS

No control patient exhibited contrast enhancement on lung late-enhanced MRI. All IPF patients were identified with late-enhanced MRI. Mean signal intensity of the late-enhanced fibrotic lung was 31.8±10.6 vs. 10.5±1.6 for normal lung regions, P < 0.001, resulting in a percent elevation in signal intensity from PF of 204.8%±90.6 compared with the signal intensity of normal lung. The mean contrast-to-noise ratio was 22.8±10.7. Late-enhanced MRI correlated significantly with chest CT for the extent of PF (R=0.78, P = 0.001) but not for reticulation, honeycombing, or coarseness of reticulation or honeycombing.

CONCLUSION

Tissue characterization of IPF is possible using inversion recovery sequence thoracic MRI.

American Thoracic Society/National Heart, Lung, and Blood Institute Asthma-Chronic Obstructive Pulmonary Disease Overlap Workshop Report

Asthma and chronic obstructive pulmonary disease (COPD) are highly prevalent chronic obstructive lung diseases with an associated high burden of disease. Asthma, which is often allergic in origin, frequently begins in infancy or childhood with variable airflow obstruction and intermittent wheezing, cough, and dyspnea. Patients with COPD, in contrast, are usually current or former smokers who present after the age of 40 years with symptoms (often persistent) including dyspnea and a productive cough. On the basis of age and smoking history, it is often easy to distinguish between asthma and COPD. However, some patients have features compatible with both diseases. Because clinical studies typically exclude these patients, their underlying disease mechanisms and appropriate treatment remain largely uncertain. To explore the status of and opportunities for research in this area, the NHLBI, in partnership with the American Thoracic Society, convened a workshop of investigators in San Francisco, California on May 14, 2016. At the workshop, current understanding of asthma-COPD overlap was discussed among clinicians, pathologists, radiologists, epidemiologists, and investigators with expertise in asthma and COPD. They considered knowledge gaps in our understanding of asthma-COPD overlap and identified strategies and research priorities that will advance its understanding. This report summarizes those discussions.

The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers

RATIONALE AND OBJECTIVES

Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers.

MATERIALS AND METHODS

An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities.

RESULTS

The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89.

CONCLUSIONS

In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity.

Idiopathic Pulmonary Fibrosis: The Association between the Adaptive Multiple Features Method and Fibrosis Outcomes

RATIONALE

Adaptive multiple features method (AMFM) lung texture analysis software recognizes high-resolution computed tomography (HRCT) patterns.

OBJECTIVES

To evaluate AMFM and visual quantification of HRCT patterns and their relationship with disease progression in idiopathic pulmonary fibrosis.

METHODS

Patients with idiopathic pulmonary fibrosis in a clinical trial of prednisone, azathioprine, and N-acetylcysteine underwent HRCT at study start and finish. Proportion of lung occupied by ground glass, ground glass-reticular (GGR), honeycombing, emphysema, and normal lung densities were measured by AMFM and three radiologists, documenting baseline disease extent and postbaseline change. Disease progression includes composite mortality, hospitalization, and 10% FVC decline.

MEASUREMENTS AND MAIN RESULTS

Agreement between visual and AMFM measurements was moderate for GGR (Pearson's correlation r = 0.60, P < 0.0001; mean difference = -0.03 with 95% limits of agreement of -0.19 to 0.14). Baseline extent of GGR was independently associated with disease progression when adjusting for baseline Gender-Age-Physiology stage and smoking status (hazard ratio per 10% visual GGR increase = 1.98, 95% confidence interval [CI] = 1.20-3.28, P = 0.008; and hazard ratio per 10% AMFM GGR increase = 1.36, 95% CI = 1.01-1.84, P = 0.04). Postbaseline visual and AMFM GGR trajectories were correlated with postbaseline FVC trajectory (r = -0.30, 95% CI = -0.46 to -0.11, P = 0.002; and r = -0.25, 95% CI = -0.42 to -0.06, P = 0.01, respectively).

CONCLUSIONS

More extensive baseline visual and AMFM fibrosis (as measured by GGR densities) is independently associated with elevated hazard for disease progression. Postbaseline change in AMFM-measured and visually measured GGR densities are modestly correlated with change in FVC. AMFM-measured fibrosis is an automated adjunct to existing prognostic markers and may allow for study enrichment with subjects at increased disease progression risk.

Association between Functional Small Airway Disease and FEV1 Decline in Chronic Obstructive Pulmonary Disease

RATIONALE

The small conducting airways are the major site of airflow obstruction in chronic obstructive pulmonary disease and may precede emphysema development.

OBJECTIVES

We hypothesized a novel computed tomography (CT) biomarker of small airway disease predicts FEV1 decline.

METHODS

We analyzed 1,508 current and former smokers from COPDGene with linear regression to assess predictors of change in FEV1 (ml/yr) over 5 years. Separate models for subjects without and with airflow obstruction were generated using baseline clinical and physiologic predictors in addition to two novel CT metrics created by parametric response mapping (PRM), a technique pairing inspiratory and expiratory CT images to define emphysema (PRM(emph)) and functional small airways disease (PRM(fSAD)), a measure of nonemphysematous air trapping.

MEASUREMENTS AND MAIN RESULTS

Mean (SD) rate of FEV1 decline in ml/yr for GOLD (Global Initiative for Chronic Obstructive Lung Disease) 0-4 was as follows: 41.8 (47.7), 53.8 (57.1), 45.6 (61.1), 31.6 (43.6), and 5.1 (35.8), respectively (trend test for grades 1-4; P < 0.001). In multivariable linear regression, for participants without airflow obstruction, PRM(fSAD) but not PRM(emph) was associated with FEV1 decline (P < 0.001). In GOLD 1-4 participants, both PRM(fSAD) and PRM(emph) were associated with FEV1 decline (P < 0.001 and P = 0.001, respectively). Based on the model, the proportional contribution of the two CT metrics to FEV1 decline, relative to each other, was 87% versus 13% and 68% versus 32% for PRM(fSAD) and PRM(emph) in GOLD 1/2 and 3/4, respectively.

CONCLUSIONS

CT-assessed functional small airway disease and emphysema are associated with FEV1 decline, but the association with functional small airway disease has greatest importance in mild-to-moderate stage chronic obstructive pulmonary disease where the rate of FEV1 decline is the greatest. Clinical trial registered with www.clinicaltrials.gov (NCT 00608764).

Computed tomography quantification of tracheal abnormalities in COPD and their influence on airflow limitation

PURPOSE

To present a method to automatically quantify tracheal morphology changes during breathing and investigate its contribution to airflow impairment when adding CT measures of emphysema, airway wall thickness, air trapping and ventilation.

METHODS

Because tracheal abnormalities often occur localized, a method is presented that automatically determines the most abnormal trachea section based on automatically computed sagittal and coronal lengths. In this most abnormal section, trachea morphology is encoded using four equiangular rays from the center of the trachea and the normalized lengths of these rays are used as features in a classification scheme. Consequently, trachea measurements are used as input for classification into GOLD stages in addition to emphysema, air trapping and ventilation. A database of 200 subjects distributed across all GOLD stages is used to evaluate the classification with a k nearest neighbour algorithm. Performance is assessed in two experimental settings: (a) when only inspiratory scans are taken; (b) when both inspiratory and expiratory scans are available.

RESULTS

Given only an inspiratory CT scan, measuring tracheal shape provides complementary information only to emphysema measurements. The best performing set in the inspiratory setting was a combination of emphysema and bronchial measurements. The best performing feature set in the inspiratory-expiratory setting includes measurements of emphysema, ventilation, air trapping, and trachea. Inspiratory and inspiratory-expiratory settings showed similar performance.

CONCLUSIONS

The fully automated system presented in this study provides information on trachea shape at inspiratory and expiratory CT. Addition of tracheal morphology features improves the ability of emphysema and air trapping CT-derived measurements to classify COPD patients into GOLD stages and may be relevant when investigating different aspects of COPD.

Clinical and Genetic Associations of Objectively Identified Interstitial Changes in Smokers

BACKGROUND

Smoking-related lung injury may manifest on CT scans as both emphysema and interstitial changes. We have developed an automated method to quantify interstitial changes and hypothesized that this measurement would be associated with lung function, quality of life, mortality, and a mucin 5B (MUC5B) polymorphism.

METHODS

Using CT scans from the Genetic Epidemiology of COPD Study, we objectively labeled lung parenchyma as a tissue subtype. We calculated the percentage of the lung occupied by interstitial subtypes.

RESULTS

A total of 8,345 participants had clinical and CT scanning data available. A 5% absolute increase in interstitial changes was associated with an absolute decrease in FVC % predicted of 2.47% (P < .001) and a 1.36-point higher St. George's Respiratory Questionnaire score (P < .001). Among the 6,827 participants with mortality data, a 5% increase in interstitial changes was associated with a 29% increased risk of death (P < .001). These associations were present in a subgroup without visually defined interstitial lung abnormalities, as well as in those with normal spirometric test results, and in those without chronic respiratory symptoms. In non-Hispanic whites, for each copy of the minor allele of the MUC5B promoter polymorphism, there was a 0.64% (P < .001) absolute increase in the percentage of lung with interstitial changes.

CONCLUSIONS

Objective interstitial changes on CT scans were associated with impaired lung function, worse quality of life, increased mortality, and more copies of a MUC5B promoter polymorphism, suggesting that these changes may be a marker of susceptibility to smoking-related lung injury, detectable even in those who are healthy by other measures.

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ² tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ² tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. ^© RSNA, 2017.

Ventricular Geometry From Non-contrast Non-ECG-gated CT Scans: An Imaging Marker of Cardiopulmonary Disease in Smokers

RATIONALE AND OBJECTIVES

Imaging-based assessment of cardiovascular structure and function provides clinically relevant information in smokers. Non-cardiac-gated thoracic computed tomographic (CT) scanning is increasingly leveraged for clinical care and lung cancer screening. We sought to determine if more comprehensive measures of ventricular geometry could be obtained from CT using an atlas-based surface model of the heart.

MATERIALS AND METHODS

Subcohorts of 24 subjects with cardiac magnetic resonance imaging (MRI) and 262 subjects with echocardiography were identified from COPDGene, a longitudinal observational study of smokers. A surface model of the heart was manually initialized, and then automatically optimized to fit the epicardium for each CT. Estimates of right and left ventricular (RV and LV) volume and free-wall curvature were then calculated and compared to structural and functional metrics obtained from MRI and echocardiograms.

RESULTS

CT measures of RV dimension and curvature correlated with similar measures obtained using MRI. RV and LV volume obtained from CT inversely correlated with echocardiogram-based estimates of RV systolic pressure using tricuspid regurgitation jet velocity and LV ejection fraction respectively. Patients with evidence of RV or LV dysfunction on echocardiogram had larger RV and LV dimensions on CT. Logistic regression models based on demographics and ventricular measures from CT had an area under the curve of >0.7 for the prediction of elevated right ventricular systolic pressure and ventricular failure.

CONCLUSIONS

These data suggest that non-cardiac-gated, non-contrast-enhanced thoracic CT scanning may provide insight into cardiac structure and function in smokers.

Computed tomographic findings in subjects who died from respiratory disease in the National Lung Screening Trial

We evaluated the prevalence of significant lung abnormalities on computed tomography (CT) in patients who died from a respiratory illness other than lung cancer in the National Lung Screening Trial (NLST).

In this retrospective case–control study, NLST participants in the CT arm who died of respiratory illness other than lung cancer were matched for age, sex, pack-years and smoking status to a surviving control. A chest radiologist and a radiology resident blinded to the outcome independently scored baseline CT scans visually and qualitatively for the presence of emphysema, airway wall thickening and fibrotic lung disease. The prevalence of CT abnormalities was compared between cases and controls by using chi-squared tests.

In total, 167 participants died from a respiratory cause other than lung cancer. The prevalence of severe emphysema, airway wall thickening and fibrotic lung disease were 28.7% versus 4.8%, 26.9% versus 13.2% and 18.6% versus 0.5% in cases and controls, respectively. Radiological findings were significantly more prevalent in deaths compared with controls (all p<0.001).

CT-diagnosed severe emphysema, airway wall thickening and fibrosis were much more common in NLST participants who died from respiratory disease, and CT may provide an additional means of identifying these diseases.

Lung Mass in Smokers

RATIONALE AND OBJECTIVE

Emphysema is characterized by airspace dilation, inflammation, and irregular deposition of elastin and collagen in the interstitium. Computed tomographic studies have reported that lung mass (LM) may be increased in smokers, a finding attributed to inflammatory and parenchymal remodeling processes observed on histopathology. We sought to examine the epidemiologic and clinical associations of LM in smokers.

MATERIALS AND METHODS

Baseline epidemiologic, clinical, and computed tomography (CT) data (n = 8156) from smokers enrolled into the COPDGene Study were analyzed. LM was calculated from the CT scan. Changes in lung function at 5 years' follow-up were available from 1623 subjects. Regression analysis was performed to assess for associations of LM with forced expiratory volume in 1 second (FEV₁) and FEV₁ decline.

RESULTS

Subjects with Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 chronic obstructive pulmonary disease had greater LM than either smokers with normal lung function or those with GOLD 2-4 chronic obstructive pulmonary disease (P < 0.001 for both comparisons). LM was predictive of the rate of the decline in FEV₁ (decline per 100 g, -4.7 ± 1.7 mL/y, P = 0.006).

CONCLUSIONS

Our cross-sectional data suggest the presence of a biphasic radiological remodeling process in smokers: the presence of such nonlinearity must be accounted for in longitudinal computed tomographic studies. Baseline LM predicts the decline in lung function.

High resolution computed tomography pattern of usual interstitial pneumonia in rheumatoid arthritis-associated interstitial lung disease: Relationship to survival

PURPOSE

Interstitial lung disease is a common extra-articular manifestation of rheumatoid arthritis (RA-ILD) and is associated with significant morbidity and mortality. However, limited data exist regarding predictors of mortality. We sought to examine the prognostic value of the high-resolution computed tomography (HRCT) patterns in patients with RA-ILD.

MATERIALS AND METHODS

RA-ILD patients with HRCT patterns of usual interstitial pneumonia (UIP) or nonspecific interstitial pneumonia (NSIP) were identified among a longitudinal cohort of individuals evaluated at National Jewish Health. A total of 158 subjects were included in the study. For each subject, the earliest available HRCT was reviewed independently by two expert thoracic radiologists blinded to clinical data. HRCT patterns were classified as demonstrating definite UIP, possible UIP, or NSIP. Kaplan-Meier curves were generated and survival was compared among the three patterns using a log rank test for trend.

RESULTS

One hundred subjects (63%) had HRCT findings classified as definite UIP, 23 (15%) as possible UIP and 35 (22%) as NSIP. No difference in survival was seen between subjects with definite UIP versus those with possible UIP. The combined group of subjects with either definite- or possible UIP had significantly worse survival than those with NSIP (log-rank p = 0.03).

CONCLUSIONS

In patients with RA-ILD, patients with either definite UIP or possible UIP have equally poor survival when compared to those with an NSIP pattern.

Standardizing CT lung density measure across scanner manufacturers

PURPOSE

Computed Tomography (CT) imaging of the lung, reported in Hounsfield Units (HU), can be parameterized as a quantitative image biomarker for the diagnosis and monitoring of lung density changes due to emphysema, a type of chronic obstructive pulmonary disease (COPD). CT lung density metrics are global measurements based on lung CT number histograms, and are typically a quantity specifying either the percentage of voxels with CT numbers below a threshold, or a single CT number below which a fixed relative lung volume, nth percentile, falls. To reduce variability in the density metrics specified by CT attenuation, the Quantitative Imaging Biomarkers Alliance (QIBA) Lung Density Committee has organized efforts to conduct phantom studies in a variety of scanner models to establish a baseline for assessing the variations in patient studies that can be attributed to scanner calibration and measurement uncertainty.

METHODS

Data were obtained from a phantom study on CT scanners from four manufacturers with several protocols at various tube potential voltage (kVp) and exposure settings. Free from biological variation, these phantom studies provide an assessment of the accuracy and precision of the density metrics across platforms solely due to machine calibration and uncertainty of the reference materials. The phantom used in this study has three foam density references in the lung density region, which, after calibration against a suite of Standard Reference Materials (SRM) foams with certified physical density, establishes a HU-electron density relationship for each machine-protocol. We devised a 5-step calibration procedure combined with a simplified physical model that enabled the standardization of the CT numbers reported across a total of 22 scanner-protocol settings to a single energy (chosen at 80 keV). A standard deviation was calculated for overall CT numbers for each density, as well as by scanner and other variables, as a measure of the variability, before and after the standardization. In addition, a linear mixed-effects model was used to assess the heterogeneity across scanners, and the 95% confidence interval of the mean CT number was evaluated before and after the standardization.

RESULTS

We show that after applying the standardization procedures to the phantom data, the instrumental reproducibility of the CT density measurement of the reference foams improved by more than 65%, as measured by the standard deviation of the overall mean CT number. Using the lung foam that did not participate in the calibration as a test case, a mixed effects model analysis shows that the 95% confidence intervals are [-862.0 HU, -851.3 HU] before standardization, and [-859.0 HU, -853.7 HU] after standardization to 80 keV. This is in general agreement with the expected CT number value at 80 keV of -855.9 HU with 95% CI of [-857.4 HU, -854.5 HU] based on the calibration and the uncertainty in the SRM certified density.

CONCLUSIONS

This study provides a quantitative assessment of the variations expected in CT lung density measures attributed to non-biological sources such as scanner calibration and scanner x-ray spectrum and filtration. By removing scanner-protocol dependence from the measured CT numbers, higher accuracy and reproducibility of quantitative CT measures were attainable. The standardization procedures developed in study may be explored for possible application in CT lung density clinical data.