Onno M. Mets

Identification of chronic obstructive pulmonary disease in lung cancer screening computed tomographic scans.

CONTEXT Smoking is a major risk factor for both cancer and chronic obstructive pulmonary disease (COPD). Computed tomography (CT)-based lung cancer screening may provide an opportunity to detect additional individuals with COPD at an early stage. OBJECTIVE To determine whether low-dose lung cancer screening CT scans can be used to identify participants with COPD. DESIGN, SETTING, AND PATIENTS Single-center prospective cross-sectional study within an ongoing lung cancer screening trial. Prebronchodilator pulmonary function testing with inspiratory and expiratory CT on the same day was obtained from 1140 male participants between July 2007 and September 2008. Computed tomographic emphysema was defined as percentage of voxels less than -950 Hounsfield units (HU), and CT air trapping was defined as the expiratory:inspiratory ratio of mean lung density. Chronic obstructive pulmonary disease was defined as the ratio of forced expiratory volume in the first second to forced vital capacity (FEV(1)/FVC) of less than 70%. Logistic regression was used to develop a diagnostic prediction model for airflow limitation. MAIN OUTCOME MEASURES Diagnostic accuracy of COPD diagnosis using pulmonary function tests as the reference standard. RESULTS Four hundred thirty-seven participants (38%) had COPD according to lung function testing. A diagnostic model with CT emphysema, CT air trapping, body mass index, pack-years, and smoking status corrected for overoptimism (internal validation) yielded an area under the receiver operating characteristic curve of 0.83 (95% CI, 0.81-0.86). Using the point of optimal accuracy, the model identified 274 participants with COPD with 85 false-positives, a sensitivity of 63% (95% CI, 58%-67%), specificity of 88% (95% CI, 85%-90%), positive predictive value of 76% (95% CI, 72%-81%); and negative predictive value of 79% (95% CI, 76%-82%). The diagnostic model showed an area under the receiver operating characteristic curve of 0.87 (95% CI, 0.86-0.88) for participants with symptoms and 0.78 (95% CI, 0.76-0.80) for those without symptoms. CONCLUSION Among men who are current and former heavy smokers, low-dose inspiratory and expiratory CT scans obtained for lung cancer screening can identify participants with COPD, with a sensitivity of 63% and a specificity of 88%.

Quantitative Computed Tomography in COPD: Possibilities and Limitations

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease that is characterized by chronic airflow limitation. Unraveling of this heterogeneity is challenging but important, because it might enable more accurate diagnosis and treatment. Because spirometry cannot distinguish between the different contributing pathways of airflow limitation, and visual scoring is time-consuming and prone to observer variability, other techniques are sought to start this phenotyping process. Quantitative computed tomography (CT) is a promising technique, because current CT technology is able to quantify emphysema, air trapping, and large airway wall dimensions. This review focuses on CT quantification techniques of COPD disease components and their current status and role in phenotyping COPD.

Computed tomographic screening for lung cancer: an opportunity to evaluate other diseases

THE RESULTS OF THE NATIONAL LUNG SCREENING TRIAL (NLST) have led to renewed interest in lung cancer screening. The NLST demonstrated that lung cancer screening using computed tomography (CT) reduces lung cancer–specific mortality by more than 20% and overall mortality by 7%. Although the discussion about false-positive findings is unsettling and cost-effectiveness analysis and confirmation by other large randomized trials are still being awaited, guidelines have been released by major organizations in the United States recommending lung cancer screening for patients who meet the inclusion criteria of the NLST. The approach used in the NLST is based on low-dose non– contrast-enhanced chest CT scanning. As such, not only pulmonary nodules but a host of other imaging findings may be assessed as well, all of which are associated with increased morbidity and mortality. Because this assessment does not require additional scans but only systematic evaluation of data already acquired, it appears logical to extend evaluation to quantification of coronary calcium and signs of chronic obstructive pulmonary disease (COPD). Lung cancer screening therefore can evolve into chest screening, including 3 major diseases: lung cancer, cardiovascular disease, and COPD. That this is possible has been shown in several recent studies. In addition, the concept of comprehensive screening may be extended to osteoporosis and various other diseases that may be asymptomatic but can be detected by noncontrast CT. Coronary calcium scoring using electrocardiography (ECG)-synchronized CT has been shown to be an independent predictor of cardiovascular risk. However, lung cancer screening CT is not ECG-synchronized, resulting in suboptimal display of the coronary arteries due to motion artifacts. Nevertheless, although a nonsynchronized technique cannot exclude coronary heart disease, this approach is useful for demonstrating serious coronary heart disease. Recently, investigators from the Dutch-Belgian lung cancer screening trial and the Italian lung cancer screening trial showed that coronary calcium scoring can be performed using lung cancer screening CT, and results are highly predictive of cardiovascular events and overall mortality. Relative to individuals with no or minimal detected calcium, hazard ratios greater than 9 were seen for all-cause mortality in the highest quartile of coronary calcium scores. Appropriate treatment of patients at high risk for coronary heart disease has substantially reduced cardiovascular morbidity and mortality in the past decades. Therefore, the information derived from chest CT screening might help provide more appropriate care for asymptomatic individuals with an increased risk profile. Chronic obstructive pulmonary disease is characterized by chronic airflow limitation, caused by pulmonary emphysema, large airways disease, and inflammation with remodeling of the smallest conducting airways, each contributing in varying degrees. Clinical diagnosis of COPD is usually late in the course of the disease, when patients become symptomatic. Today, the disease components can be quantified automatically using automated CT analysis tools, and recently screening CT has been shown to be useful for detecting early stages of COPD. External validation is still needed, but adding other quantitative markers, such as airway wall dimensions, may enable even better diagnostic performance. These other CT markers may also help separate various phenotypes of COPD: predominant emphysema, involvement of the large bronchi, or small airways disease. Detection of early stages of the disease together with a better characterization may become an important step toward developing more tailored treatments based on disease phenotype. Moreover, the diagnosis of COPD or emphysema is associated with an increased incidence of lung cancer independent of cumulative smoking history, which suggests that stricter screening regimens may be warranted. Evaluation of other diseases visible on CT may be added to the evaluation of lung cancer in screening CT. Osteopenia/

The relationship between lung function impairment and quantitative computed tomography in chronic obstructive pulmonary disease.

AbstractObjectivesTo determine the relationship between lung function impairment and quantitative computed tomography (CT) measurements of air trapping and emphysema in a population of current and former heavy smokers with and without airflow limitation.MethodsIn 248 subjects (50 normal smokers; 50 mild obstruction; 50 moderate obstruction; 50 severe obstruction; 48 very severe obstruction) CT emphysema and CT air trapping were quantified on paired inspiratory and end-expiratory CT examinations using several available quantification methods. CT measurements were related to lung function (FEV1, FEV1/FVC, RV/TLC, Kco) by univariate and multivariate linear regression analysis.ResultsQuantitative CT measurements of emphysema and air trapping were strongly correlated to airflow limitation (univariate r-squared up to 0.72, p < 0.001). In multivariate analysis, the combination of CT emphysema and CT air trapping explained 68-83% of the variability in airflow limitation in subjects covering the total range of airflow limitation (p < 0.001).ConclusionsThe combination of quantitative CT air trapping and emphysema measurements is strongly associated with lung function impairment in current and former heavy smokers with a wide range of airflow limitation.Key Points• CT helps to automatically assess lung disease in heavy smokers • CT quantitatively measures emphysema and small airways disease in heavy smokers • CT air trapping and CT emphysema are associated with lung function impairment

Lung Cancer Screening CT-Based Prediction of Cardiovascular Events

OBJECTIVES The aim of this study was to derivate and validate a prediction model for cardiovascular events based on quantification of coronary and aortic calcium volume in lung cancer screening chest computed tomography (CT). BACKGROUND CT-based lung cancer screening in heavy smokers is a very timely topic. Given that the heavily smoking screening population is also at risk for cardiovascular disease, CT-based screening may provide the opportunity to additionally identify participants at high cardiovascular risk. METHODS Inspiratory screening CT of the chest was obtained in 3,648 screening participants. Next, smoking characteristics, patient demographics, and physician-diagnosed cardiovascular events were collected from 10 years before the screening CT (i.e., cardiovascular history) until 3 years after the screening CT (i.e., follow-up time). Cox proportional hazards analysis was used to derivate and validate a prediction model for cardiovascular risk. Age, smoking status, smoking history, and cardiovascular history, together with automatically quantified coronary and aortic calcium volume from the screening CT, were included as independent predictors. The primary outcome measure was the discriminatory value of the model. RESULTS Incident cardiovascular events occurred in 145 of 1,834 males (derivation cohort) and 118 of 1,725 males and 2 of 89 females (validation cohort). The model showed good discrimination in the validation cohort with a C-statistic of 0.71 (95% confidence interval: 0.67 to 0.76). When high risk was defined as a 3-year risk of 6% and higher, 589 of 1,725 males were regarded as high risk and 72 of 118 of all events were correctly predicted by the model. CONCLUSIONS Quantification of coronary and aortic calcium volumes in lung cancer screening CT images-information that is readily available-can be used to predict cardiovascular risk. Such an approach might prove useful in the reduction of cardiovascular morbidity and mortality and may enhance the cost-effectiveness of CT-based screening in heavy smokers.

Contribution of CT Quantified Emphysema, Air Trapping and Airway Wall Thickness on Pulmonary Function in Male Smokers With and Without COPD

Abstract Emphysema, airway wall thickening and air trapping are associated with chronic obstructive pulmonary disease (COPD). All three can be quantified by computed tomography (CT) of the chest. The goal of the current study is to determine the relative contribution of CT derived parameters on spirometry, lung volume and lung diffusion testing. Emphysema, airway wall thickening and air trapping were quantified automatically on CT in 1,138 male smokers with and without COPD. Emphysema was quantified by the percentage of voxels below –950 Hounsfield Units (HU), airway wall thickness by the square root of wall area for a theoretical airway with 10 mm lumen perimeter (Pi10) and air trapping by the ratio of mean lung density at expiration and inspiration (E/I-ratio). Spirometry, residual volume to total lung capacity (RV/TLC) and diffusion capacity (Kco) were obtained. Standardized regression coefficients (β) were used to analyze the relative contribution of CT changes to pulmonary function measures. The independent contribution of the three CT measures differed per lung function parameter. For the FEV1 airway wall thickness was the most contributing structural lung change (β = –0.46), while for the FEV1/FVC this was emphysema (β = –0.55). For the residual volume (RV) air trapping was most contributing (β = –0.35). Lung diffusion capacity was most influenced by emphysema (β = –0.42). In a cohort of smokers with and without COPD the effect of different CT changes varies per lung function measure and therefore emphysema, airway wall thickness and air trapping need to be taken in account.

Diagnosis of chronic obstructive pulmonary disease in lung cancer screening Computed Tomography scans: independent contribution of emphysema, air trapping and bronchial wall thickening

BackgroundBeyond lung cancer, screening CT contains additional information on other smoking related diseases (e.g. chronic obstructive pulmonary disease, COPD). Since pulmonary function testing is not regularly incorporated in lung cancer screening, imaging biomarkers for COPD are likely to provide important surrogate measures for disease evaluation. Therefore, this study aims to determine the independent diagnostic value of CT emphysema, CT air trapping and CT bronchial wall thickness for COPD in low-dose screening CT scans.MethodsPrebronchodilator spirometry and volumetric inspiratory and expiratory chest CT were obtained on the same day in 1140 male lung cancer screening participants. Emphysema, air trapping and bronchial wall thickness were automatically quantified in the CT scans. Logistic regression analysis was performed to derivate a model to diagnose COPD. The model was internally validated using bootstrapping techniques.ResultsEach of the three CT biomarkers independently contributed diagnostic value for COPD, additional to age, body mass index, smoking history and smoking status. The diagnostic model that included all three CT biomarkers had a sensitivity and specificity of 73.2% and 88.%, respectively. The positive and negative predictive value were 80.2% and 84.2%, respectively. Of all participants, 82.8% was assigned the correct status. The C-statistic was 0.87, and the Net Reclassification Index compared to a model without any CT biomarkers was 44.4%. However, the added value of the expiratory CT data was limited, with an increase in Net Reclassification Index of 4.5% compared to a model with only inspiratory CT data.ConclusionQuantitatively assessed CT emphysema, air trapping and bronchial wall thickness each contain independent diagnostic information for COPD, and these imaging biomarkers might prove useful in the absence of lung function testing and may influence lung cancer screening strategy. Inspiratory CT biomarkers alone may be sufficient to identify patients with COPD in lung cancer screening setting.

Toward automatic regional analysis of pulmonary function using inspiration and expiration thoracic CT

PURPOSE To analyze pulmonary function using a fully automatic technique which processes pairs of thoracic CT scans acquired at breath-hold inspiration and expiration, respectively. The following research objectives are identified to: (a) describe and systematically analyze the processing pipeline and its results; (b) verify that the quantitative, regional ventilation measurements acquired through CT are meaningful for pulmonary function analysis; (c) identify the most effective of the calculated measurements in predicting pulmonary function; and (d) demonstrate the potential of the system to deliver clinically important information not available through conventional spirometry. METHODS A pipeline of automatic segmentation and registration techniques is presented and demonstrated on a database of 216 subjects well distributed over the various stages of COPD (chronic obstructive pulmonary disorder). Lungs, fissures, airways, lobes, and vessels are automatically segmented in both scans and the expiration scan is registered with the inspiration scan using a fully automatic nonrigid registration algorithm. Segmentations and registrations are examined and scored by expert observers to analyze the accuracy of the automatic methods. Quantitative measures representing ventilation are computed at every image voxel and analyzed to provide information about pulmonary function, both globally and on a regional basis. These CT derived measurements are correlated with results from spirometry tests and used as features in a kNN classifier to assign COPD global initiative for obstructive lung disease (GOLD) stage. RESULTS The steps of anatomical segmentation (of lungs, lobes, and vessels) and registration in the workflow were shown to perform very well on an individual basis. All CT-derived measures were found to have good correlation with spirometry results, with several having correlation coefficients, r, in the range of 0.85-0.90. The best performing kNN classifier succeeded in classifying 67% of subjects into the correct COPD GOLD stage, with a further 29% assigned to a class neighboring the correct one. CONCLUSIONS Pulmonary function information can be obtained from thoracic CT scans using the automatic pipeline described in this work. This preliminary demonstration of the system already highlights a number of points of clinical importance such as the fact that an inspiration scan alone is not optimal for predicting pulmonary function. It also permits measurement of ventilation on a per lobe basis which reveals, for example, that the condition of the lower lobes contributes most to the pulmonary function of the subject. It is expected that this type of regional analysis will be instrumental in advancing the understanding of multiple pulmonary diseases in the future.

Normal range of emphysema and air trapping on CT in young men.

OBJECTIVE The purpose of our study was to assess the normal range of CT measures of emphysema and air trapping in young men with normal lung function. MATERIALS AND METHODS A cohort of 70 young men with high-normal spirometry and body plethysmography underwent paired inspiratory and expiratory CT. Visual and quantitative scores of emphysema and air trapping were obtained. On CT, emphysema was defined as the 15th percentile of the attenuation curve (Perc(15)), and as the percentage of inspiratory voxels below -950 (IN(-950)) and below -960 (IN(-960)) HU. On CT, air trapping was defined as the expiratory-to-inspiratory ratio of mean lung density (EI-ratio(MLD)), and the percentage of voxels below -856 HU in expiration (EXP(-856)). Means, medians, and upper limits of normal (ULN) are presented for the total population and for smokers and nonsmokers separately. RESULTS The mean age (± SD) of the subjects was 36.1 ± 9.3 years. Smoking history was limited (range, 0-11 pack-years). Spirometry was high normal, ranging from 113% to 160% of predicted for vital capacity (VC), and from 104% to 140% of predicted for forced expiratory volume in 1 second (FEV(1)). The ULN was 2.73% for IN(-950), 0.87% for IN(-960), -936 HU for Perc(15), 89.0% for EI-ratio(MLD), and 17.2% for EXP(-856).Visual CT scores showed minimal emphysema in eight (11%), > 5 lobules of air trapping in five (7%), and segmental air trapping in three (4%) subjects. CT measures were similar for never- and ever-smokers. CONCLUSION We report the normal range of CT values for young male subjects with normal lung function, which is important to define pulmonary disease.

Lung-RADS Category 4X: Does It Improve Prediction of Malignancy in Subsolid Nodules?

Purpose To evaluate the added value of Lung CT Screening Reporting and Data System (Lung-RADS) assessment category 4X over categories 3, 4A, and 4B for differentiating between benign and malignant subsolid nodules (SSNs). Materials and Methods SSNs on all baseline computed tomographic (CT) scans from the National Lung Cancer Trial that would have been classified as Lung-RADS category 3 or higher were identified, resulting in 374 SSNs for analysis. An experienced screening radiologist volumetrically segmented all solid cores and located all malignant SSNs visible on baseline scans. Six experienced chest radiologists independently determined which nodules to upgrade to category 4X, a recently introduced category for lesions that demonstrate additional features or imaging findings that increase the suspicion of malignancy. Malignancy rates of purely size-based categories and category 4X were compared. Furthermore, the false-positive rates of category 4X lesions were calculated and observer variability was assessed by using Fleiss κ statistics. Results The observers upgraded 15%-24% of the SSNs to category 4X. The malignancy rate for 4X nodules varied from 46% to 57% per observer and was substantially higher than the malignancy rates of categories 3, 4A, and 4B SSNs without observer intervention (9%, 19%, and 23%, respectively). On average, the false-positive rate for category 4X nodules was 7% for category 3 SSNs, 7% for category 4A SSNs, and 19% for category 4B SSNs. Of the falsely upgraded benign lesions, on average 27% were transient. The agreement among the observers was moderate, with an average κ value of 0.535 (95% confidence interval: 0.509, 0.561). Conclusion The inclusion of a 4X assessment category for lesions suspicious for malignancy in a nodule management tool is of added value and results in high malignancy rates in the hands of experienced radiologists. Proof of the transient character of category 4X lesions at short-term follow-up could avoid unnecessary invasive management.