Automated CT quantification of interstitial lung abnormality and interstitial lung disease according to the Fleischner Society in patients with resectable lung cancer: prognostic significance
- PMID: 37266656
- DOI: 10.1007/s00330-023-09783-x
Automated CT quantification of interstitial lung abnormality and interstitial lung disease according to the Fleischner Society in patients with resectable lung cancer: prognostic significance
Abstract
Objective: To assess the prognostic significance of automatically quantified interstitial lung abnormality (ILA) according to the definition by the Fleischner Society in patients with resectable non-small-cell lung cancer (NSCLC).
Methods: Patients who underwent lobectomy or pneumonectomy for NSCLC between January 2015 and December 2019 were retrospectively included. Preoperative CT scans were analyzed using the commercially available deep-learning-based automated quantification software for ILA. According to quantified results and the definition by the Fleischner Society and multidisciplinary discussion, patients were divided into normal, ILA, and interstitial lung disease (ILD) groups.
Results: Of the 1524 patients, 87 (5.7%) and 20 (1.3%) patients had ILA and ILD, respectively. Both ILA (HR, 1.81; 95% CI: 1.25-2.61; p = .002) and ILD (HR, 5.26; 95% CI: 2.99-9.24; p < .001) groups had poor recurrence-free survival (RFS). Overall survival (OS) decreased (HR 2.13 [95% CI: 1.27-3.58; p = .004] for the ILA group and 7.20 [95% CI: 3.80-13.62, p < .001] for the ILD group) as the disease severity increased. Both quantified fibrotic and non-fibrotic ILA components were associated with poor RFS (HR, 1.57; 95% CI: 1.12-2.21; p = .009; and HR, 1.11; 95% CI: 1.01-1.23; p = .03) and OS (HR, 1.59; 95% CI: 1.06-2.37; p = .02; and HR, 1.17; 95% CI: 1.03-1.33; and p = .01) in normal and ILA groups.
Conclusions: The automated CT quantification of ILA based on the definition by the Fleischner Society predicts outcomes of patients with resectable lung cancer based on the disease category and quantified fibrotic and non-fibrotic ILA components.
Clinical relevance statement: Quantitative CT assessment of ILA provides prognostic information for lung cancer patients after surgery, which can help in considering active surveillance for recurrence, especially in those with a larger extent of quantified ILA.
Key points: • Of the 1524 patients with resectable lung cancer, 1417 (93.0%) patients were categorized as normal, 87 (5.7%) as interstitial lung abnormality (ILA), and 20 (1.3%) as interstitial lung disease (ILD). • Both ILA and ILD groups were associated with poor recurrence-free survival (hazard ratio [HR], 1.81, p = .002; HR, 5.26, p < .001, respectively) and overall survival (HR, 2.13; p = .004; HR, 7.20; p < .001). • Both quantified fibrotic and non-fibrotic ILA components were associated with recurrence-free survival and overall survival in normal and ILA groups.
Keywords: Deep learning; Lung cancer; Lung disease, interstitial; Prognosis.
© 2023. The Author(s), under exclusive licence to European Society of Radiology.
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