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. 2013 May 27;14(1):59.
doi: 10.1186/1465-9921-14-59.

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

Onno M Mets  1 , Michael Schmidt, Constantinus F Buckens, Martijn J Gondrie, Ivana Isgum, Matthijs Oudkerk, Rozemarijn Vliegenthart, Harry J de Koning, Carlijn M van der Aalst, Mathias Prokop, Jan-Willem J Lammers, Pieter Zanen, Firdaus A Mohamed Hoesein, Willem PthM Mali, Bram van Ginneken, Eva M van Rikxoort, Pim A de Jong
Affiliations

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

Onno M Mets et al. Respir Res. .

Abstract

Background: Beyond 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.

Methods: Prebronchodilator 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.

Results: Each 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.

Conclusion: Quantitatively 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.

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Figures

Figure 1
Figure 1
Illustration of the lung segmentation process and calculation of CT emphysema and CT air trapping. A = Axial inspiratory CT image; B = Axial expiratory CT image; C and D = Overlay showing the lung segmentation of the right (turquoise) and left (green) lung in an axial slice. The trachea and main bronchi are shown in blue; E = Overlay showing the lung segmentation in a coronal inspiratory CT image; F = Graph showing the attenuation histograms of both the inspiratory and expiratory CT. CT emphysema is calculated as the percentage of voxels below −950 HU. CT air trapping is calculated as the ratio of the expiratory to inspiratory mean lung density.
Figure 2
Figure 2
Illustration of the bronchial segmentation process and the calculation of CT bronchial wall thickness. The upper part of the figure shows the bronchial tree segmentation of the right and left lung, both separately and combined. The lower part shows a random selection of bronchial cross-sections obtained perpendicular to the bronchial lumen center line. In these bronchial cross-sections, the inner (yellow) and outer (orange) bronchial wall boundaries are shown; solid lines represent observed boundaries whereas dashed lines represent interpolated boundaries. From the observed bronchial wall boundaries the wall area is calculated. The line graph shows a schematic representation of a regression line (dashed line) through the bronchial measurements, from which the square root of wall area for a theoretical bronchial with 10 mm lumen perimeter (i.e. Pi10) was calculated (dotted lines).
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