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Osteoporosis is more common in patients with COPD and in smokers. The aim of this study was to assess whether measures of emphysema and airway disease on computed tomography (CT) were associated with lower bone density or vertebral fractures in smokers with and without COPD. For this purpose, we included participants from the NELSON lung cancer screening trial. Bone density was measured as Hounsfield Units in the first lumbar vertebra, and vertebral fractures were assessed semiquantitatively. The 15th percentile method (Perc15) was used to assess emphysema, and the airway lumen perimeter (Pi10) was used for airway wall thickness. Expiratory/inspiratory-ratiomean lung density (E/I-ratioMLD) was used as a measure for air trapping and tracheal index to assess tracheal deformity. Linear regression models and logistic regression models were used to assess associations between CT biomarkers, bone density, and presence of fractures. Exactly 1,093 male participants were eligible for analysis. Lower Perc15 and higher E/I-ratioMLD were significantly associated with lower bone density (b=−1.27, P=0.02 and b=−0.37, P=0.02, respectively). Pi10 and tracheal index were not associated with bone density changes. CT-derived biomarkers were not associated with fracture prevalence. Bone density is lower with increasing extent of emphysema and small airway disease but is not associated with large airway disease and tracheal deformity. This may indicate the necessity to measure bone density early in smokers with emphysema and air trapping to prevent vertebral fractures.

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.

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RATIONALEThe role of the central pulmonary vasculature in chronic obstructive pulmonary disease (COPD) is not well understood. We investigated a central pulmonary arterial biomarker automatically extracted from computed tomography (CT) and its relation to airflow obstruction in COPD. METHODS Baseline inspiratory CT scans on a random selection of 40 subjects per GOLD stage including PRISm (preserved ratio impaired spirometry) and never smoker controls were selected from the COPDGene study, leading to a total data set of 280 subjects. Lung quantification software (LungQ, Thirona, Nijmegen, the Netherlands) was used to identify the lung fields and all central arterial branches from CT, defined as the segmental, sub-segmental, and sub-subsegmental arterial branches. The arterial diameter was calculated for each branch and averaged to compute the mean central arterial (MCA) diameter. Emphysema was defined as the percentage of low attenuation areas ≤ -950HU (LAA -950 ). CT derived total lung capacity (TLC CT ) was calculated from the extracted lung fields. Spirometry measurements were used to define airflow obstruction, including FEV 1 %-predicted and FEV 1 /FVC. Quality of life was defined by the SGRQ-score. Univariate Pearson's correlation was extracted between MCA and LAA -950 , FEV 1 %-predicted, FEV 1 /FVC, and SGRQ-score. Multiple linear regression analysis was performed to investigate the relative contribution of MCA for each of the spirometry and quality of life measurements. All models were adjusted for gender, age, weight, height, pack years, TLC CT , smoking status and LAA -950 . Results are expressed as coefficients, standard error (se), and p-values. RESULTS MCA had a significant (p<0.001) Pearson correlation with all investigated measurements ( r=0.32 for LAA -950 , r=-0.45 for FEV 1 %-predicted, r=-0.42 for FEV 1 /FVC, and r=0.34 for SGRQ-score). In the multiple regression analysis, MCA showed to be a significant independent predictor for FEV 1 %-predicted (B=-10.9, se=2.79, p<0.001), FEV 1 /FVC (B=-0.06, se=0.014, p<0.001), and SGRQ-score (B=-8.02, se=2.85, p=0.005). CONCLUSIONS Larger central arterial diameters in COPD were independently associated with worse spirometry and quality of life, even when adjusted for the extent of emphysema. Enlarged central pulmonary arteries may be an indication for pulmonary hypertension and could therefore be a clinically relevant CT derived marker.

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