Inverse association of plasma IL-13 and inflammatory chemokines with lung function impairment in stable COPD: a cross-sectional cohort study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome characterized by varying degrees of airflow limitation and diffusion impairment. There is increasing evidence to suggest that COPD is also characterized by systemic inflammation. The primary goal of this study was to identify soluble proteins in plasma that associate with the severity of airflow limitation in a COPD cohort with stable disease. A secondary goal was to assess whether unique markers associate with diffusion impairment, based on diffusion capacity of carbon monoxide (DLCO), independent of the forced expiratory volume in 1 second (FEV1). METHODS: A cross sectional study of 73 COPD subjects was performed in order to examine the association of 25 different plasma proteins with the severity of lung function impairment, as defined by the baseline measurements of the % predicted FEV1 and the % predicted DLCO. Plasma protein concentrations were assayed using multiplexed immunobead-based cytokine profiling. Associations between lung function and protein concentrations were adjusted for age, gender, pack years smoking history, current smoking, inhaled corticosteroid use, systemic corticosteroid use and statin use. RESULTS: Plasma concentrations of CCL2/monocyte chemoattractant protein-1 (CCL2/MCP-1), CCL4/macrophage inflammatory protein-1 beta (CCL4/MIP-1 beta), CCL11/eotaxin, and interleukin-13 (IL-13) were inversely associated with the % FEV1. Plasma concentrations of soluble Fas were associated with the % DLCO, whereas CXCL9/monokine induced by interferon-gamma (CXCL9/Mig), granulocyte- colony stimulating factor (G-CSF) and IL-13 showed inverse relationships with the % DLCO. CONCLUSION: Systemic inflammation in a COPD cohort is characterized by cytokines implicated in inflammatory cell recruitment and airway remodeling. Plasma concentrations of IL-13 and chemoattractants for monocytes, T lymphocytes, and eosinophils show associations with increasing severity of disease. Soluble Fas, G-CSF and CXCL9/Mig may be unique markers that associate with disease characterized by disproportionate abnormalities in DLCO independent of the FEV1.

Automated detection and quantitative assessment of pulmonary airways depicted on CT images.

We developed and tested a fully automated computerized scheme that identifies pulmonary airway sections depicted on computed tomography (CT) images and computes their sizes including the lumen and airway wall areas. The scheme includes four processing modules that (1) segment left and right lung areas, (2) identify airway locations, (3) segment airway walls from neighboring pixels, and (4) compute airway sizes. The scheme uses both a raster scanning and a labeling algorithm complemented by simple classification rules for region size and circularity to automatically search for and identify airway sections of interest. A profile tracking method is used to segment airway walls from neighboring pixels including those associated with dense tissue (i.e., pulmonary arteries) along scanning radial rays. A partial pixel membership method is used to compute airway size. The scheme was tested on ten randomly selected CT studies that included 26 sets of CT images acquired using both low and conventional dose CT examinations with one of four reconstruction algorithms (namely, "bone," "lung," "soft," and "standard" convolution kernels). Three image section thicknesses (1.25, 2.5, and 5 mm) were evaluated. The scheme detected a large number of quantifiable airway sections when the CT images were reconstructed using high spatial frequency convolution kernels. The detection results demonstrated a consistent trend for all test image sets in that as airway lumen size increases, on average the airway wall area increases as well and the wall area percentage decreases. The study suggested that CT images reconstructed using high spatial frequency convolution kernels and thin-section thickness were most amenable to automated detection, reasonable segmentation, and quantified assessment when the airways are close to being perpendicular to the CT image plane.