作者
Di Zhang,Yu Guan,Xiuxiu Zhou,Mingzi Zhang,Yu Pu,Pengchen Gu,益多朗 森下,Lu Yang,Jia Chen,Wenting Tu,Kunyao Huang,Jixin Hou,Yang Hua,Chi-Cheng Fu,Qu Fang,Chuan He,Shiyuan Liu,Li Fan
摘要
Purpose: To develop a novel method for calculating small airway resistance using computational fluid dynamics (CFD) based on CT data and evaluate its value to identify COPD. Patients and Methods: 24 subjects who underwent chest CT scans and pulmonary function tests between August 2020 and December 2020 were enrolled retrospectively. Subjects were divided into three groups: normal (10), high-risk (6), and COPD (8). The airway from the trachea down to the sixth generation of bronchioles was reconstructed by a 3D slicer. The small airway resistance (R SA ) and R SA as a percentage of total airway resistance (R SA %) were calculated by CFD combined with airway resistance and FEV 1 measured by pulmonary function test. A correlation analysis was conducted between R SA and pulmonary function parameters, including FEV 1 /FVC, FEV 1 % predicted, MEF50% predicted, MEF75% predicted and MMEF75/25% predicted. Results: The R SA and R SA % were significantly different among the three groups (p< 0.05) and related to FEV 1 /FVC (r = − 0.70, p < 0.001; r = − 0.67, p < 0.001), FEV 1 % predicted (r = − 0.60, p = 0.002; r = − 0.57, p = 0.004), MEF50% predicted (r = − 0.64, p = 0.001; r = − 0.64, p = 0.001), MEF75% predicted (r = − 0.71, p < 0.001; r = − 0.60, p = 0.002) and MMEF 75/25% predicted (r = − 0.64, p = 0.001; r = − 0.64, p = 0.001). Conclusion: Airway CFD is a valuable method for estimating the small airway resistance, where the derived R SA will aid in the early diagnosis of COPD. Keywords: COPD, small airway disease, CT, fluid dynamics