Subject(s)
Lung , Respiratory Physiological Phenomena , Humans , Respiratory Function Tests , Lung/physiopathologyABSTRACT
Despite advances in the pathophysiology of chronic obstructive pulmonary disease (COPD), there is a distinct lack of biochemical markers to aid clinical management. Microvesicles (MVs) have been implicated in the pathophysiology of inflammatory diseases including COPD, but their association to COPD disease severity remains unknown. We analyzed different MV populations in plasma and bronchoalveolar lavage fluid (BALF) taken from 62 patients with mild to very severe COPD (51% male; mean age: 65.9 yr). These patients underwent comprehensive clinical evaluation (symptom scores, lung function, and exercise testing), and the capacity of MVs to be clinical markers of disease severity was assessed. We successfully identified various MV subtype populations within BALF [leukocyte, polymorphonuclear leukocyte (PMN; i.e., neutrophil), monocyte, epithelial, and platelet MVs] and plasma (leukocyte, PMN, monocyte, and endothelial MVs) and compared each MV population to disease severity. BALF neutrophil MVs were the only population to significantly correlate with the clinical evaluation scores including forced expiratory volume in 1 s, modified Medical Research Council dyspnea score, 6-min walk test, hyperinflation, and gas transfer. BALF neutrophil MVs, but not neutrophil cell numbers, also strongly correlated with BODE index. We have undertaken, for the first time, a comprehensive evaluation of MV profiles within BALF/plasma of COPD patients. We demonstrate that BALF levels of neutrophil-derived MVs are unique in correlating with a number of key functional and clinically relevant disease severity indexes. Our results show the potential of BALF neutrophil MVs for a COPD biomarker that tightly links a key pathophysiological mechanism of COPD (intra-alveolar neutrophil activation) with clinical severity/outcome.
Subject(s)
Bronchoalveolar Lavage Fluid/chemistry , Cell-Derived Microparticles/pathology , Neutrophils/pathology , Pulmonary Alveoli/pathology , Pulmonary Disease, Chronic Obstructive/pathology , Severity of Illness Index , Aged , Cell-Derived Microparticles/metabolism , Cytokines/metabolism , Female , Forced Expiratory Volume , Humans , Male , Neutrophils/metabolism , Pulmonary Alveoli/metabolism , Pulmonary Disease, Chronic Obstructive/etiology , Pulmonary Disease, Chronic Obstructive/metabolism , Respiratory Function TestsABSTRACT
BACKGROUND: Recent advances in bronchoscopic lung volume reduction offer new therapies for patients with emphysema and hyperinflation. Pulmonary lobe segmentation with quantification of lobar volumes and emphysema severity plays a pivotal role in treatment planning and post-interventional assessment. Computed tomography (CT)-derived lobar volumes could reflect more accurate regional changes in pulmonary function. OBJECTIVES: The aim of our study is to validate the reliability of an in-house CT Lung Segmentation software (LungSeg; the Hamlyn Centre, Imperial College London, UK) for lung lobar volume and emphysema quantification for chronic obstructive pulmonary disease (COPD) patients. METHODS: A total of 108 CT scans from subjects who participated in an endobronchial coil treatment trial were included. Lobar volume and emphysema quantification were performed using the LungSeg and Syngo CT Pulmo 3D package (Siemens Healthcare GmbH, Germany). The inter-user reliability of the LungSeg program was investigated. Correlation coefficients and Bland-Altman analyses were used to quantify the inter-software variability. The agreement between CT volume analysis and plethysmography analysis was also examined. RESULTS: The high intraclass correlation coefficients (mean ICC = 0.98) of the lobar volumes and emphysema indices measured by LungSeg suggest its excellent reproducibility. The LungSeg and Syngo program have good correlation (rho ≥0.94) and agreement for both lobar volume (median difference = 94 mL and LOAnp = 214.6 mL) and emphysema index (median difference ≤1.5% and LOAnp ≤2.03%) calculations. CT analysis provides a higher estimation of total lung capacity (TLCCT) than body plethysmography (TLCpleth), while there is a fair agreement on residual volume (RVCT) by LungSeg as compared with body plethysmography (RVpleth). CONCLUSIONS: CT-derived lobar volume and emphysema quantification using the LungSeg program is efficient and reliable in allowing lobar volume assessment. LungSeg has low inter-user variability and agrees better with plethysmography for COPD assessment in our study.