Imaging Phenotypes Assessment by Using Quantitative Parameters for CT-Defined Subtypes of Chronic Obstructive Pulmonary Disease

Abstract

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.

Figure 1

Inspiratory LAA and LAAsize Analysis for a 69-year-old man who belonged to type-A. (A and D) LAA&LAAsize coronal pseudo-color image, The default threshold is −950 hounsfield Units (HU); (B) LAA three-dimensional image; (C and F) LAA&LAAsize Chart to show the volume, LAA% and D-slope. (E) LAA Size Log-Log to show the cluster diameter.

Figure 2

The predictive performance of LAA and Goddard score for type-M classification (0.616 vs 0.739, P=0.002).

Figure 3

Multivariate logistic regression analysis of quantitative phenotypes parameters.