Characteristic features of pulmonary function test, CT volume analysis and MR perfusion imaging in COPD patients with different HRCT phenotypes-Reference-Cited by-同舟云学术

Characteristic features of pulmonary function test, CT volume analysis and MR perfusion imaging in COPD patients with different HRCT phenotypes

Published:2013-07-31 Issue:1 Volume:8 Page:45-54
ISSN:1752-6981
Container-title:The Clinical Respiratory Journal
language:en
Short-container-title:The Clinical Respiratory Journal

Author:

Fan Li¹,Xia Yi¹,Guan Yu¹,Zhang Tie-feng²,Liu Shi-yuan¹

Affiliation:

1. Department of Radiology; Changzheng Hospital of the Second Military Medical University; Shanghai China

2. Department of Respiration Medicine; Changzheng Hospital of the Second Military Medical University; Shanghai China

Publisher

Wiley

Subject

Genetics(clinical),Pulmonary and Respiratory Medicine,Immunology and Allergy

Reference21 articles.

1. Global Initiative for Chronic Obstructive Lung Disease Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease http://www.goldcopd.org/guidelines-global-strategy-for-diagnosis-management.html

2. Quantitative CT assessment of chronic obstructive pulmonary disease;Matsuoka;Radiographics,2010

3. Clinical analysis of chronic obstructive pulmonary disease phenotypes classified using high-resolution computed tomography;Fujimoto;Respirology,2006

4. Characterization of phenotypes based on severity of emphysema in chronic obstructive pulmonary disease;Makita;Thorax,2007

5. Characteristics of COPD phenotypes classified according to the findings of HRCT;Kitaguchi;Respir Med,2006

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