ArticleInternational journal of chronic obstructive pulmonary disease2019
Clinical features of three-dimensional computed tomography-based radiologic phenotypes of chronic obstructive pulmonary disease.
Article in International journal of chronic obstructive pulmonary disease, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Chest CT in the evaluation of chronic obstructive pulmonary disease: recommendations of Asian Society of Thoracic Radiology.The British journal of radiology · 2026Guideline
- 3D CT-Based quantification of airway structural changes during asthma exacerbations: a retrospective observational study.BMC pulmonary medicine · 2026Observational
- Changes in lung function in children after pneumonia: a multicenter study.Italian journal of pediatrics · 2025Article
- The utility of quantitative computed tomography in cohort studies of chronic obstructive pulmonary disease: a narrative review.Journal of thoracic disease · 2023Review
- Phenotype of Chronic Obstructive Pulmonary Disease Based on Computed Tomography-Defined Underlying Pathology.Tuberculosis and respiratory diseases · 2022Review
- Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.PloS one · 2020Article
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Authors and funding
13 authors.
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Abstract
Purpose: The diagnosis and severity of chronic obstructive pulmonary disease (COPD) are defined by airflow limitation using spirometry. However, COPD has diverse clinical features, and several phenotypes based on non-spirometric data have been investigated. To identify novel phenotypes of COPD using radiologic data obtained by three-dimensional computed tomography (3D-CT). Patients and methods: The inner luminal area and wall thickness of third- to sixth-generation bronchi and the percentage of the low-attenuation area (less than -950 HU) of the lungs were measured using 3D-CT in patients with COPD. Using the radiologic data, hierarchical clustering was performed. Respiratory reactance and resistance were measured to evaluate functional differences among the clusters. Results: Four clusters were identified among 167 patients with COPD: Cluster I, mild emphysema with severe airway changes, severe airflow limitation, and high exacerbation risk; Cluster II, mild emphysema with moderate airway changes, mild airflow limitation, and mild dyspnea; Cluster III, severe emphysema with moderate airway changes, severe airflow limitation, and increased dyspnea; and Cluster IV, moderate emphysema with mild airway changes, mild airflow limitation, low exacerbation risk, and mild dyspnea. Cluster I had the highest respiratory resistance among the four clusters. Clusters I and III had higher respiratory reactance than Clusters II and IV. Conclusions: The 3D-CT-based radiologic phenotypes were associated with the clinical features of COPD. Measurement of respiratory resistance and reactance may help to identify phenotypic differences.
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