Quantitative Evaluation of Chronic Obstructive Pulmonary Disease and Risk Prediction of Acute Exacerbation by High-Resolution Computed Tomography

高分辨率计算机断层扫描对慢性阻塞性肺病的定量评估和急性加重的风险预测

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作者:Qifeng Hua, Guoping Chen, Yin Yang, Shaoyi Leng, Zhenzhen Zhao, Feng Bai, Xiaowei Hu, Liyan Qiu, Zhe Yu, Hongbin Zhang, Jiapei Shi, Qi Dai

Conclusions

HRCT imaging effectively classifies the severity of COPD, which combined with BMI, PFT, and serum PCT can predict the risk of AECOPD.

Methods

COPD patients were divided into mild (n = 18), moderate (n = 20), severe (n = 24), and extremely severe (n = 22) groups for performing high-resolution computed tomography (HRCT) and pulmonary function test. Serum procalcitonin (PCT) and high-sensitivity C-reactive protein (hs-CRP) were detected, and the occurrence rate of acute exacerbation COPD (AECOPD) was recorded during a 12-months follow-up period.

Objective

It is imperative to popularize the tertiary prevention of chronic obstructive pulmonary disease (COPD) and to improve the diagnosis and treatment.

Results

With an increase in the severity grade, the HRCT indexes, including emphysema index (EI), 1st and 15th percentile of inspiratory attenuation distribution (Perc1 and Perc15), ratio of expiratory/inspiratory mean lung density (MLDex/in) and lung volume (LVex/in), and ratio of the wall thickness to the outer diameter of the lumen (TDR), as well as percentage of the wall area to the total cross-sectional area (WA%) were increased with a decreased change in relative lung volume with attenuation values between -860 and -950 HU (RVC-860to -950) and lumen area (A i). These were correlated with the ratio of forced expiratory volume in 1 sec (FEV1) over forced vital capacity (FVC) (FEV1/FVC), the percentage of FEV1 the predicted value (FEV1%), and ratio of residual volume to total lung volume (RV/TLC). Body mass index, MLDex/in, FEV1%, FEV1/FVC, and PCT had a predictive value to AECOPD, with the combined AUC of 0.812. Conclusions: HRCT imaging effectively classifies the severity of COPD, which combined with BMI, PFT, and serum PCT can predict the risk of AECOPD.

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