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. 2024 Jun;15(16):1305-1311.
doi: 10.1111/1759-7714.15306. Epub 2024 Apr 29.

Automated CT quantification of interstitial lung abnormality in patients with resectable stage I non-small cell lung cancer: Prognostic significance

Jae Ho Chung  1 , Jong Myung Park  2   3   4 , Do Hyung Kim  2   3   4
Affiliations

Automated CT quantification of interstitial lung abnormality in patients with resectable stage I non-small cell lung cancer: Prognostic significance

Jae Ho Chung et al. Thorac Cancer. 2024 Jun.

Abstract

Background: In patients with non-small cell lung cancer (NSCLC), interstitial lung abnormalities (ILA) have been linked to mortality and can be identified on computed tomography (CT) scans. In the present study we aimed to evaluate the predictive value of automatically quantified ILA based on the Fleischner Society definition in patients with stage I NSCLC.

Methods: We retrospectively reviewed 948 patients with pathological stage I NSCLC who underwent pulmonary resection between April 2009 and October 2022. A commercially available deep learning-based automated quantification program for ILA was used to evaluate the preoperative CT data. The Fleischner Society definition, quantitative results, and interdisciplinary discussion led to the division of patients into normal and ILA groups. The sum of the fibrotic and nonfibrotic ILA components constituted the total ILA component and more than 5%.

Results: Of the 948 patients with stage I NSCLC, 99 (10.4%) patients had ILA. Shorter overall survival and recurrence-free survival was associated with the presence of ILA. After controlling for confounding variables, the presence of ILA remained significant for increased risk of death (hazard ratio [HR] = 3.09; 95% confidence interval [CI]: 1.91-5.00; p < 0.001) and the presence of ILA remained significant for increased recurrence (HR = 1.96; 95% CI: 1.16-3.30; p = 0.012).

Conclusions: The automated CT quantification of ILA, based on the Fleischner Society definition, was significantly linked to poorer survival and recurrence in patients with stage I NSCLC.

Keywords: computed tomography; deep learning; interstitial lung abnormality; lung cancer.

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Conflict of interest statement

None of the authors has any conflicts of interest.

Figures

FIGURE 1
FIGURE 1
Overall survival (OS) of patients with and without interstitial lung abnormalities (ILA). The graph shows OS of patients without ILA using Kaplan–Meier estimate. Patients with ILA had significantly shorter OS than those without ILA (p < 0.0001).
FIGURE 2
FIGURE 2
Recurrence‐free survival (RFS) of patients with and without interstitial lung abnormalities (ILA). The graph shows overall disease‐free survival (DFS) of patients without ILA using Kaplan–Meier estimate. RFS was significantly shorter in patients with ILA than non‐ILA group (p = 0.021).
See this image and copyright information in PMC

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