|本期目录/Table of Contents|

[1]罗洁君,管宇,范丽,等.慢性阻塞性肺疾病临床及影像学表型研究进展[J].中华肺部疾病杂志,2022,(06):900-903.[doi:10.3877/cma.j.issn.1674-6902.2022.06.038]
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慢性阻塞性肺疾病临床及影像学表型研究进展(PDF)

《中华肺部疾病杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2022年06期
页码:
900-903
栏目:
出版日期:
2022-12-20

文章信息/Info

Title:
-
作者:
罗洁君; 管宇; 范丽; 刘士远
200003 上海,海军军医大学第二附属医院放射诊断科
Author(s):
-
关键词:
肺疾病; 慢性阻塞性;  临床表型;  影像学表型
Keywords:
-
分类号:
R563
DOI:
10.3877/cma.j.issn.1674-6902.2022.06.038
摘要:
-
Abstract:
-

参考文献/References:

1 Corlateanu A, Mendez Y, Wang Y, et al. “Chronic obstructive pulmonary disease and phenotypes: a state-of-the-art.”[J]. Pulmonol, 2020, 26(2): 95-100.
2 Mekov E, Nu?ez A A-O, Sin D A-O, et al. Update on Asthma-COPD Overlap(ACO): A narrative review[J]. Int J Chronic Obstruct Pulmon Dis 2021 16: 1783-99.
3 Vestbo JD, Frcp. COPD: definition and phenotypes[J]. Clin Chest Med, 2014, 35(1): 1-6.
4 Hurst JR, Donaldson GC, Quint JK, et al. Temporal clustering of exacerbations in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 2009, 179(5): 369-374.
5 J?rgen Vestbo, Lisa D Edwards, Paul D Scanlon, et al. Changes in forced expiratory volume in 1 second over time in COPD[J]. New England J Med, 2011, 365(13): 1184-1192.
6 Leem AY, Park B, Kim YS, et al. Longitudinal decline in lung function: a community-based cohort study in Korea[J]. Sci Rep, 2019, 9(1): 13614.
7 Vasilis Nikolaou, Sebastiano Massaro, Wolfgang Garn, et al. Fast decliner phenotype of chronic obstructive pulmonary disease(COPD): applying machine learning for predicting lung function loss[J]. BMJ Open Respir Res, 2021, 8(1): e000980.
8 Masaru Suzuki, Hironi Makita, Satoshi Konno, et al. Annual change in FEV(1)in elderly 10-year survivors with established chronic obstructive pulmonary disease[J]. Sci Rep, 2019, 9(1): 2073.
9 Barbara Kuznar-Kaminska, Justyna Mikua-Pietrasik, Krzysztof Ksiazek, et al. Lung cancer in chronic obstructive pulmonary disease patients: importance of cellular senescence[J]. Pol Arch Intern Med, 2018, 128(7-8): 462-468.
10 Yasutaka Nakano, Jonathan C Wong, Pim A de Jong, et al. The prediction of small airway dimensions using computed tomography[J]. Am J Respir Crit Care Med, 2005, 171(2): 142-146.
11 Kitaoka H, Kijima T. What is “functional small airway disease” in inspiratory and expiratory CT images?[J]. Respir Investig, 2021, 59(1): 157-158.
12 Fujimoto K, Kitaguchi Y, Kubo K, et al. Clinical analysis of chronic obstructive pulmonary disease phenotypes classified using high-resolution computed tomography[J]. Respirol, 2006, 11(6): 731-740.
13 Lee JH, Lee YK, Kim EK, et al. Responses to inhaled long-acting beta-agonist and corticosteroid according to COPD subtype[J]. Respir Med, 2010, 104(4): 542-549.
14 Deepak R Subramanian, Sumit Gupta, Dorothe Burggraf, et al. Emphysema-and airway-dominant COPD phenotypes defined by standardised quantitative computed tomography[J]. Eur Respir J, 2016, 48(1): 92-103.
15 Jeong Uk Lim, Eun Kyung Kim, Seong Yong Lim, et al. Mixed phenotype of emphysema and airway wall thickening is associated with frequent exacerbation in chronic obstructive pulmonary disease patients[J]. Int J Chron Obstruct Pulmon Dis, 2019, 14: 3035-3042.
16 David A Lynch, John H M Austin, James C Hogg, et al. CT-definable subtypes of chronic obstructive pulmonary disease: A statement of the fleischner society[J]. Radiol, 2015, 277(1): 192-205.
17 Park J, Hobbs BD, Crapo JD, et al. Subtyping COPD by using visual and quantitative CT imaging features[J]. Chest, 2020, 157(1): 47-60.
18 Chauhan NS, Sood D, Takkar P, et al. Quantitative assessment of airway and parenchymal components of chronic obstructive pulmonary disease using thin-section helical computed tomography[J]. Pol J Radiol, 2019, 84: e54-e60.
19 Nambu A, Zach J, Schroeder J, et al. Quantitative computed tomography measurements to evaluate airway disease in chronic obstructive pulmonary disease: Relationship to physiological measurements, clinical index and visual assessment of airway disease[J]. Eur J Radiol, 2016, 85(11): 2144-2151.
20 Grydeland TB, Dirksen A, Coxson HO, et al. Quantitative computed tomography: emphysema and airway wall thickness by sex, age and smoking[J]. Eur Respir J, 2009, 34(4): 858-865.
21 Weikert T, Friebe L, Wilder-Smith A, et al. Automated quantification of airway wall thickness on chest CT using retina U-Nets-Performance evaluation and application to a large cohort of chest CTs of COPD patients[J]. Eur J Radiol, 2022, 155: 110460.
22 Jean-Paul Charbonnier, Esther Pompe, Camille Moore, et al. Airway wall thickening on CT: Relation to smoking status and severity of COPD[J]. Respir Med, 2019, 146: 36-41.
23 Alexander A Bankier, Cornelia Schaefer-Prokop, Viviane De Maertelaer, et al. Air trapping: comparison of standard-dose and simulated low-dose thin-section CT techniques[J]. Radiology, 2007, 242(3): 898-906.
24 Arakawa H, Webb WR. Air trapping on expiratory high-resolution CT scans in the absence of inspiratory scan abnormalities: correlation with pulmonary function tests and differential diagnosis[J]. AJR Am J Roentgenol, 1998, 170(5): 1349-1353.
25 Benjamin A Hoff, Esther Pompe, Stefanie Galbán, et al. CT-based local distribution metric improves characterization of COPD[J]. Sci Rep, 2017, 7(1): 2999.
26 Miranda Kirby, Youbing Yin, Juerg Tschirren, et al. A novel method of estimating small airway disease using inspiratory-to-expiratory computed tomography[J]. Respiration, 2017, 94(4): 336-345.
27 Bian Z, Charbonnier JP, Liu J, et al. Small airway segmentation in thoracic computed tomography scans: a machine learning approach[J]. Phys Med Biol, 2018, 63(15): 155024.
28 Antonio Garcia-Uceda, Raghavendra Selvan, Zaigham Saghir, et al. Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks[J]. Sci Rep, 2021, 11(1): 16001.
29 Ivan Dudurych, Antonio Garcia-Uceda, Zaigham Saghir, et al. Creating a training set for artificial intelligence from initial segmentations of airways[J]. Eur Radiol Exp, 2021, 5(1): 54.
30 Thibaut Capron, Arnaud Bourdin, Thierry Perez, et al. COPD beyond proximal bronchial obstruction: phenotyping and related tools at the bedside[J]. Eur Respir Rev, 2019, 28(152): 190010.
31 Gabor Kovacs, Alvar Agusti, Joan Albert Barberà, et al. Pulmonary vascular involvement in chronic obstructive pulmonary disease. Is there a pulmonary vascular phenotype?[J]. Am J Respir Crit Care Med, 2018, 198(8): 1000-1011.
32 陈 琰, 钱 频, 袁 琳, 等. 慢性阻塞性肺疾病肺外合并症的治疗现状和研究进展[J/CD]. 中华肺部疾病杂志(电子版), 2020, 13(1): 100-103.
33 John D Maclay, David A McAllister, Nicholas L Mills, et al. Vascular dysfunction in chronic obstructive pulmonary disease[J]. Am J Respir Crit Care Med, 2009, 180(6): 513-520.
34 Santos S, Peinado VI, Ramírez J, et al. Characterization of pulmonary vascular remodelling in smokers and patients with mild COPD[J]. Eur RespiratJ, 2002, 19(4): 632-638.
35 Marius M Hoeper, Joan Albert Barberà, Richard N Channick, et al. Diagnosis, assessment, and treatment of non-pulmonary arterial hypertension pulmonary hypertension[J]. J Am Coll Cardiol, 2009, 54(1 Suppl): S85-S96.
36 Seiichiro Sakao, Norbert F Voelkel, Koichiro Tatsumi. The vascular bed in COPD: pulmonary hypertension and pulmonary vascular alterations[J]. Eur Respir Rev, 2014, 23(133): 350-355.
37 Shin Matsuoka, George R Washko, Tsuneo Yamashiro, et al. Pulmonary hypertension and computed tomography measurement of small pulmonary vessels in severe emphysema[J]. Am J Respir Crit Care Med, 2010, 181(3): 218-225.
38 George R Washko, Pietro Nardelli, Samuel Y Ash, et al. Arterial vascular pruning, right ventricular size, and clinical outcomes in chronic obstructive pulmonary disease. A longitudinal observational study[J]. Am J Respir Crit Care Med, 2019, 200(4): 454-461.
39 Cho YH, Lee SM, Seo JB, et al. Quantitative assessment of pulmonary vascular alterations in chronic obstructive lung disease: Associations with pulmonary function test and survival in the KOLD cohort[J]. Eur J Radiol, 2018, 108: 276-282.
40 Sang Won Park, Myoung-Nam Lim, Woo Jin Kim, et al. Quantitative assessment the longitudinal changes of pulmonary vascular counts in chronic obstructive pulmonary disease[J]. Respir Res, 2022, 23(1): 29.
41 Vincent Tedjasaputra, Sean van Diepen, Devin B Phillips, et al. Pulmonary capillary blood volume response to exercise is diminished in mild chronic obstructive pulmonary disease[J]. Respir Med, 2018, 145: 57-65.
42 Katja Hueper, Jens Vogel-Claussen, Megha A Parikh, et al. Pulmonary microvascular blood flow in mild chronic obstructive pulmonary disease and emphysema. The MESA COPD study[J]. Am J Respir Crit Care Med, 2015, 192(5): 570-580.
43 David A Lynch, Camille M Moore, Carla Wilson, et al. CT-based visual classification of emphysema: Association with mortality in the COPDGene study[J]. Radiology, 2018, 288(3): 859-866.
44 Samuel Y Ash, Raúl San José Estépar, Sean B Fain, et al. Relationship between emphysema progression at CT and mortality in ever-smokers: results from the COPDGene and ECLIPSE cohorts[J]. Radiology, 2021, 299(1): 222-231.
45 黄宇婷, 刘 翱. 慢性阻塞性肺疾病患者影像学表型的临床治疗及疗效探究[J/CD]. 中华肺部疾病杂志(电子版), 2016, 9(1): 51-55.
46 Francesco Blasi, Luca Neri, Stefano Centanni, et al. Clinical characterization and treatment patterns for the frequent exacerbator phenotype in chronic obstructive pulmonary disease with severe or very severe airflow limitation[J]. J Chronic Obstruct Pulmon Dis, 2017, 14(1): 15-22.
47 Meilan K Han, Ella A Kazerooni, David A Lynch, et al. Chronic obstructive pulmonary disease exacerbations in the COPDGene study: associated radiologic phenotypes[J]. Radiology, 2011, 261(1): 274-282.
48 George R Washko, Pietro Nardelli, Samuel Y Ash, et al. Smaller left ventricle size at noncontrast CT is associated with lower mortality in COPDGene participants[J]. Radiology, 2020, 296(1): 208-215.

备注/Memo

备注/Memo:
基金项目: 国家自然科学基金重点项目(81930049)
国家自然科学基金面上项目(82171926、81871321)
通信作者: 刘士远, Email: cjr.liushiyuan@vip.163.com
更新日期/Last Update: 2022-12-20