The value of biphasic CT in the diagnosis of chronic obstructive pulmonary disease_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

WU Zhangli ^1,2 , WU Zhenchao ² , WANG Wenting ² , WU Nan ² , YANG Ping ^1,2 , LIANG Cuixia ⁴ , CHEN Deyan ⁴ , XU Jiaxuan ⁵ , ZHENG Jingping ⁵ , WANG Xiaohua ³ , HE Bei ^1,2 ,  SHEN Ning ^1,2

1. Institute of Medical Technology, Peking University Health Science Center, Beijing 100191, P. R. China;
2. Department of Respiratory and Critical Care Medicine, Peking University Third Hospital, Beijing 100191, P. R. China;
3. Department of Radiology, Peking University Third Hospital, Beijing 100191, P. R. China;
4. Neusoft Medical Systems Co., Ltd., Shenyang, Liaoning 110167, P. R. China;
5. State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The National Center for Respiratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510120, P. R. China;

Corresponding?author：

SHEN Ning, Email: shenning1972@126.com

Keywords：

Chronic obstructive pulmonary disease; principle component analysis; logistic regression; biphasic CT scan

DOI：

10.7507/1671-6205.202111022

Video：

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Objective To investigate the feasibility of diagnosis of potential chronic obstructive pulmonary disease (COPD) patients who cannot finish the pulmonary function test via biphasic CT scan. Methods Sixty-seven male individuals aged 43 to 74 (57.0±5.9) years were divided into a COPD group (n=26) and a control group (n=41). All individuals underwent biphasic quantitative CT scan for calculating the proportion of emphysema, functional small airway disease, and normal component of the whole lung and each lobe. Results Based on principle component analysis, two principal components “imaging feature function 1 and imaging feature function 2” were calculated and analyzed by logistic regression, which found that imaging feature function 1 was an independent risk factor of COPD (odds ratio=8.749, P<0.001), and imaging features function 1 could be used to assist the diagnosis of COPD (area under receiver operating characteristic curve=0.843, P<0.001). Conclusion Imaging features function 1 is an independent risk factor for COPD and can assist the diagnosis of COPD.

Citation： WU Zhangli, WU Zhenchao, WANG Wenting, WU Nan, YANG Ping, LIANG Cuixia, CHEN Deyan, XU Jiaxuan, ZHENG Jingping, WANG Xiaohua, HE Bei, SHEN Ning. The value of biphasic CT in the diagnosis of chronic obstructive pulmonary disease. Chinese Journal of Respiratory and Critical Care Medicine, 2022, 21(2): 77-83. doi: 10.7507/1671-6205.202111022 Copy

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2.	Galbán CJ, Han MK, Boes JL, et al. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med, 2012, 18(11): 1711-1715.
3.	趙凡惠, 王雷, 朱彥瑾, 等. 基于雙氣相配準定量CT在慢性阻塞性肺疾病影像學表型中的應用. 中國醫學影像學雜志, 2019, 27(11): 829-833.
4.	Vasilescu DM, Martinez FJ, Marchetti N, et al. Noninvasive imaging biomarker identifies small airway damage in severe chronic obstructive pulmonary disease. Am J Respir Crit Care Med, 2019, 200(5): 575-581.
5.	王雯婷, 王曉華, 賀蓓, 等. 基于吸呼雙相CT定量參數的慢性阻塞性肺疾病影像學表型研究. 中華醫學雜志, 2021, 101(28): 2242-2245.
6.	中華醫學會呼吸病學分會慢性阻塞性肺疾病學組, 中國醫師協會呼吸醫師分會慢性阻塞性肺疾病工作委員會. 慢性阻塞性肺疾病診治指南(2021年修訂版). 中華結核和呼吸雜志, 2021, 44(3): 170-205.
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8.	Cosio M, Ghezzo H, Hogg JC, et al. The relations between structural changes in small airways and pulmonary-function tests. N Engl J Med, 1978, 298(23): 1277-1281.
9.	Burgel PR, Bergeron A, De BJ, et al. Small airways diseases, excluding asthma and COPD: an overview. Eur Respir Rev, 2013, 22(128): 131-147.
10.	Parr DG, Stoel BC, Stolk J, et al. Validation of computed tomographic lung densitometry for monitoring emphysema in alpha1-antitrypsin deficiency. Thorax, 2006, 61(6): 485-490.
11.	Han MLK, Kazerooni EA, Lynch DA, et al. Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes. Radiology, 2011, 261(1): 274-282.
12.	Lim JU, Kim EK, Lim SY, et al. Mixed phenotype of emphysema and airway wall thickening is associated with frequent exacerbation in chronic obstructive pulmonary disease patients. Int J Chron Obstruct Pulmon Dis, 2019, 14: 3035-3042.
13.	Subramanian DR, Gupta S, Burggraf D, et al. Emphysema-and airway-dominant COPD phenotypes defined by standardised quantitative computed tomography. Eur Respir J, 2016, 48(1): 92-103.
14.	尤曉婷, 夏亭亭, 關玉寶, 等. 低劑量CT掃描及定量分析對慢性阻塞性肺疾病氣道病變的應用研究. 實用放射學雜志, 2016, 32(10): 1520-1524.
15.	Martinez CH, Diaz AA, Meldrum C, et al. Age and small airway imaging abnormalities in subjects with and without airflow obstruction in SPIROMICS. Am J Respir Crit Care Med, 2017, 195(4): 464-472.
16.	Pisi R, Aiello M, Frizzelli A, et al. Detection of small airway dysfunction in asymptomatic smokers with preserved spirometry: the value of the impulse oscillometry system. Int J Chron Obstruct Pulmon Dis, 2021, 16: 2585-2590.
17.	中華醫學會放射學分會質量管理與安全管理學組. CT輻射劑量診斷參考水平專家共識. 中華放射學雜志, 2017, 51(11): 817-822.

1. World Health Organization. The top 10 causes of death[EB/OL]. (2019-07-25). Available at: https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death.
2. Galbán CJ, Han MK, Boes JL, et al. Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression. Nat Med, 2012, 18(11): 1711-1715.
3. 趙凡惠, 王雷, 朱彥瑾, 等. 基于雙氣相配準定量CT在慢性阻塞性肺疾病影像學表型中的應用. 中國醫學影像學雜志, 2019, 27(11): 829-833.
4. Vasilescu DM, Martinez FJ, Marchetti N, et al. Noninvasive imaging biomarker identifies small airway damage in severe chronic obstructive pulmonary disease. Am J Respir Crit Care Med, 2019, 200(5): 575-581.
5. 王雯婷, 王曉華, 賀蓓, 等. 基于吸呼雙相CT定量參數的慢性阻塞性肺疾病影像學表型研究. 中華醫學雜志, 2021, 101(28): 2242-2245.
6. 中華醫學會呼吸病學分會慢性阻塞性肺疾病學組, 中國醫師協會呼吸醫師分會慢性阻塞性肺疾病工作委員會. 慢性阻塞性肺疾病診治指南(2021年修訂版). 中華結核和呼吸雜志, 2021, 44(3): 170-205.
7. McDonough JE, Yuan R, Suzuki M, et al. Small-airway obstruction and emphysema in chronic obstructive pulmonary disease. N Engl J Med, 2011, 365(17): 1567-1575.
8. Cosio M, Ghezzo H, Hogg JC, et al. The relations between structural changes in small airways and pulmonary-function tests. N Engl J Med, 1978, 298(23): 1277-1281.
9. Burgel PR, Bergeron A, De BJ, et al. Small airways diseases, excluding asthma and COPD: an overview. Eur Respir Rev, 2013, 22(128): 131-147.
10. Parr DG, Stoel BC, Stolk J, et al. Validation of computed tomographic lung densitometry for monitoring emphysema in alpha1-antitrypsin deficiency. Thorax, 2006, 61(6): 485-490.
11. Han MLK, Kazerooni EA, Lynch DA, et al. Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes. Radiology, 2011, 261(1): 274-282.
12. Lim JU, Kim EK, Lim SY, et al. Mixed phenotype of emphysema and airway wall thickening is associated with frequent exacerbation in chronic obstructive pulmonary disease patients. Int J Chron Obstruct Pulmon Dis, 2019, 14: 3035-3042.
13. Subramanian DR, Gupta S, Burggraf D, et al. Emphysema-and airway-dominant COPD phenotypes defined by standardised quantitative computed tomography. Eur Respir J, 2016, 48(1): 92-103.
14. 尤曉婷, 夏亭亭, 關玉寶, 等. 低劑量CT掃描及定量分析對慢性阻塞性肺疾病氣道病變的應用研究. 實用放射學雜志, 2016, 32(10): 1520-1524.
15. Martinez CH, Diaz AA, Meldrum C, et al. Age and small airway imaging abnormalities in subjects with and without airflow obstruction in SPIROMICS. Am J Respir Crit Care Med, 2017, 195(4): 464-472.
16. Pisi R, Aiello M, Frizzelli A, et al. Detection of small airway dysfunction in asymptomatic smokers with preserved spirometry: the value of the impulse oscillometry system. Int J Chron Obstruct Pulmon Dis, 2021, 16: 2585-2590.
17. 中華醫學會放射學分會質量管理與安全管理學組. CT輻射劑量診斷參考水平專家共識. 中華放射學雜志, 2017, 51(11): 817-822.

Chinese Journal of Respiratory and Critical Care Medicine

The value of biphasic CT in the diagnosis of chronic obstructive pulmonary disease

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