4.6 Review

Computed tomography-identified phenotypes of small airway obstructions in chronic obstructive pulmonary disease

期刊

CHINESE MEDICAL JOURNAL
卷 134, 期 17, 页码 2025-2036

出版社

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/CM9.0000000000001724

关键词

Chronic obstructive pulmonary disease; Small airway obstruction; Computed tomography; Phenotype; Pulmonary function test

资金

  1. National Key Research and Development Program of China [2018YFC1313602]
  2. Major International (Regional) Joint Research Project [81820108001]
  3. National Natural Science Foundation of China [81670029]
  4. Jiangsu Key Principal Investigator of Medicine [ZDRCA2016018]
  5. Project 333 for Cultivation of Young and Middle-aged Leading Talents [BRA2019078]
  6. Jiangsu Key Program of Social Development [BE2015651]
  7. Nanjing Key Project of Science and Technology [2019060002]
  8. Xuzhou Administration of Science and Technology [KC20082]

向作者/读者索取更多资源

This review highlights the role and importance of CT in identifying different phenotypes of COPD, emphasizing the accuracy of small airway CT phenotypes in reflecting disease severity and aiding in improving prognosis. Additionally, it discusses the application of CT in clinical, epidemiologic, and genetic investigations related to COPD.
Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease characteristic of small airway inflammation, obstruction, and emphysema. It is well known that spirometry alone cannot differentiate each separate component. Computed tomography (CT) is widely used to determine the extent of emphysema and small airway involvement in COPD. Compared with the pulmonary function test, small airway CT phenotypes can accurately reflect disease severity in patients with COPD, which is conducive to improving the prognosis of this disease. CT measurement of central airway morphology has been applied in clinical, epidemiologic, and genetic investigations as an inference of the presence and severity of small airway disease. This review will focus on presenting the current knowledge and methodologies in chest CT that aid in identifying discrete COPD phenotypes.

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