Clinical features of three-dimensional computed tomography-based radiologic phenotypes of chronic obstructive pulmonary disease
Received 1 March 2019
Accepted for publication 30 May 2019
Published 24 June 2019 Volume 2019:14 Pages 1333—1342
Checked for plagiarism Yes
Review by Single-blind
Peer reviewers approved by Dr Melinda Thomas
Peer reviewer comments 2
Editor who approved publication: Dr Richard Russell
Masato Karayama,1 Naoki Inui,1,2 Hideki Yasui,1 Masato Kono,1 Hironao Hozumi,1 Yuzo Suzuki,1 Kazuki Furuhashi,1 Dai Hashimoto,1 Noriyuki Enomoto,1 Tomoyuki Fujisawa,1 Yutaro Nakamura,1 Hiroshi Watanabe,2 Takafumi Suda1
1Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan; 2Department of Clinical Pharmacology and Therapeutics, Hamamatsu University School of Medicine, Hamamatsu 431-3192, Japan
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.
Keywords: airway, chronic obstructive pulmonary disease, clustering analysis, emphysema, phenotype, three-dimensional computed tomography
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