Objective To establish and validate a voxel-based method for the quantitative detection of air trapping (AT),and to explore its diagnostic value by preliminarily apply this method in chronic obstructive pulmonary disease (COPD) patients.Methods From March 2015 to February 2016,fifty healthy young volunteers and eighteen COPD patients who underwent both end-inspiratory and end-expiratory CT were included from the Digital Lung Multi-center Study.The quantitative parameters of AT and emphysema were measured by both the voxel-based quantitative method and the conventional threshold method,respectively.All subjects underwent pulmonary function examination within 3 days after CT examination.For healthy volunteers,paired sample rank-sum test was used to compare the difference of quantitative parameters between voxel-based method and threshold method,Spearman rank correlation analysis was used to investigate the correlation between quantitative parameters of the two methods and pulmonary function.For COPD patients,the distribution and extent of AT and emphysema in patients with similar degree of pulmonary function (PFT) injury were observed.Results There were varying degrees of AT in the asymptomatic youth,with a median value of 5.70％ for the voxel-based method and with a median value of 7.96％ for the conventional threshold method,there was significant difference(Z=-4.015,P＜0.001).The correlation between AT and emphysema parameters of the voxel-based method and PFT parameters (r=-0.399 and-0.494,-0.335 and-0.439 separately,P＜0.05) were higher than that of the conventional threshold method,respectively (r=-0.357 and-0.453,-0.284 and-0.391,respectively;all P＜0.05).Furthermore,the voxel-based method can classify COPD patients with similar degree of pulmonary function injury into three subtypes:AT-dominant,emphysema-dominant,and mixed.Conclusions The voxel-based AT quantitative measurement method not only has high sensitivity and accuracy,but also provides imaging phenotype for the diagnosis of COPD and provides assistant decision-making for clinical management.