Wufei Chen,1,* Jing Zhu,2,3,* Jixiang Ni,2,3 Xiang Li,4 Yu Li,2,3 Wen Yin,2,3 Shan Zhu,2,3 Yang Xiao,2,3 Ying Wang,2,3 Hui Huang,2,3 Yi Hu2,3 

1Department of Radiology, Huadong Hospital Affiliated to Fudan University, Shanghai, 200040, People’s Republic of China; 2Department of Pulmonary and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 3Wuhan Clinical Research Center for Interventional Diagnosis and Treatment of Respiratory Diseases, Wuhan, Hubei, People’s Republic of China; 4Department of Radiology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China

*These authors contributed equally to this work

Correspondence: Yi Hu, Department of Pulmonary and Critical Care Medicine, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, 26 Shengli Street, Wuhan, 430014, People’s Republic of China, Tel +86-13995618974, Email huyi@zxhospital.com

Purpose: To explore the quantitative imaging phenotype differences for CT-defined subtypes classified by the Fleischner Society in patients with chronic obstructive pulmonary disease (COPD).
Patients and Methods: A total of 228 COPD patients who underwent non-enhanced chest CT screening from 2018 to 2024 were included. All patients were divided into type-A (Absent emphysema that no or mild emphysema, Goddard score ≤ 8, regardless of bronchial wall thickening), type-E (Emphysema that significant emphysema, Goddard score > 8, without bronchial wall thickening), and type-M (Mixed emphysema and bronchial wall thickening that both significant emphysema, Goddard score > 8, and bronchial wall thickening ≥ grade 1 in ≥ 1 lung lobe). Imaging phenotype parameters included lung airspace analysis (LAA) and LAA size analysis (LAASA) in emphysema, airway wall, lung vessels and interstitial lung disease (ILD) extracted by a COPD-specific analysis software were analysis among three groups.
Results: Quantitative assessment of emphysema among three image phenotypes showed significant differences in full emphysema and full emphysema ratio based on LAA among three groups (P < 0.05). The areas of consolidation, ground-glass opacity, and reticular patterns were significantly larger in type-M than the other two types (P < 0.05). Quantitative assessment of small airways disease and small vessel parameters found smaller lumen-volume and larger wall-volume in whole lung level in the emphysema phenotype of type-M (P < 0.05) were found in the small vessel count in distance of 6 mm and 9mm from the pleura were significant differences among three groups (P < 0.05). The multivariate logistic regression analysis showed that the higher proportion of full emphysema ratio and wall-volume, a proportion of smaller lumen-volume, and a more noticeable interstitial lung alterations were associated with type-M.
Conclusion: A quantitative CT evaluation can further delineate the imaging phenotypes characteristics thereby in guiding to early diagnosis, severity assessment, and therapeutic recommendations in COPD patients.

Keywords: chronic obstructive pulmonary disease, computed tomography, image phenotypes, quantitative analysis