Abstract
OBJECTIVE: Lung cancer and pulmonary emphysema share common risk factors and pathophysiological pathways. Emerging evidence suggests that emphysema morphology, rather than emphysema burden, may influence lung cancer histology. This study evaluated the association between computed tomography (CT)-defined emphysema characteristics and histological subtypes of lung cancer. MATERIAL AND METHODS: A retrospective observational cohort study was conducted that included 144 patients with histologically confirmed lung cancer who underwent diagnostic thoracic CT between January 2020 and June 2024 at Dr. Saiful Anwar General Hospital in Indonesia. Emphysema morphology was visually classified as centrilobular emphysema (CLE), paraseptal emphysema, or mixed, and emphysema volume was quantified using 3D Slicer software. Associations with histological subtypes were analyzed using bivariate analyses and multivariate logistic regression, adjusted for age, sex, tumor size, and tumor location. Model performance was assessed using receiver operating characteristic analysis. RESULTS: Adenocarcinoma (ADC) was the most common subtype (65.3%). Emphysema was present in 37.5% of patients and occurred more frequently in non-ADC subtypes. Emphysema morphology was significantly associated with histological subtype (P < 0.001). Multivariate analysis identified CLE as an independent predictor of ADC (adjusted odds ratio: 8.5; 95% confidence interval: 1.24–57.9; P = 0.029), and CLE remained significant after adjustment for tumor size and tumor location. The model demonstrated excellent discrimination (area under the curve: 0.89). Emphysema volume did not differ significantly between groups (P = 0.339). CONCLUSION: CT-defined CLE is independently associated with lung ADC, whereas emphysema volume is not predictive of lung ADC. Emphysema morphology may serve as a non-invasive imaging biomarker to support histological risk stratification when tissue diagnosis is limited.
| Original language | English |
|---|---|
| Pages (from-to) | 103-108 |
| Number of pages | 6 |
| Journal | Thoracic Research and Practice |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Mar 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- adenocarcinoma
- biomarker
- CT scan
- emphysema morphology
- Lung cancer
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