Computed tomography (CT) is the modality of choice for imaging the airways. Volumetric data sets with isotropic spatial resolution based on multidetector thin-section CT with overlapping reconstruction should be used. Chronic obstructive pulmonary disease and asthma are the 2 most common disease entities that are defined by airflow obstruction. The morphologic correlates of airway changes are dilation of the lumen, thickening of the wall, visibility of small airways due to mucus or edema, air trapping, hypoxic vasoconstriction, and collapsibility. To assess air trapping, additional expiratory low-dose scans are recommended. In clinical routine, these findings are visually assessed and should be routinely reported. However, the interobserver variability is high, and there is a clear need for objective software-based measurements. The development of such tools is challenging, and they are just becoming available on a broader scale. Novel techniques based on dual-energy CT aim to measure iodine distribution maps to assess pulmonary perfusion as well as the distribution of inhaled xenon gas to assess the distribution and time course of pulmonary ventilation. However, these techniques are still being investigated in clinical studies. This review will provide an overview of CT for the diagnosis of chronic obstructive pulmonary disease and asthma, its role in phenotyping these diseases, and the measurement of disease severity and functional compromise.

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Rationale: Airway wall thickness (AWT) is affected by both environmental and genetic factors and is strongly associated with airflow limitation in smaller airways.Objectives: To investigate the genetic component of AWT.Methods: AWT was measured on low-dose computed tomography scans in male heavy smokers participating in a lung cancer screening study (n = 2,640). Genome-wide association studies on AWT were performed under an additive model using linear regression (adjusted for pack-years, lung volume), followed by metaanalysis. An independent cohort was used for validation of the most strongly associated single-nucleotide polymorphisms (SNPs). The functional relevance of significant SNPs was evaluated.