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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