# Association of automated quantified emphysema and interstitial lung abnormality with survival in non-small cell lung cancer

## TL;DR

This study shows that AI-measured lung abnormalities are linked to survival rates in non-small cell lung cancer patients.

## Contribution

AI quantification of emphysema and ILA improves survival prediction beyond traditional staging in NSCLC.

## Key findings

- Whole emphysema and ILA severity are independent prognostic factors for NSCLC survival.
- AI-quantified emphysema and ILA outperform TNM staging in predicting patient outcomes.
- Regional emphysema and ILA severity do not show significant prognostic value.

## Abstract

To investigate the prognostic value of artificial intelligence (AI) quantified emphysema and interstitial lung abnormality (ILA) in patients with non-small cell lung cancer (NSCLC).

This retrospective study used AI to quantify emphysema and ILA in patients diagnosed with NSCLC between January 2015 and December 2017. Associations between AI-quantified emphysema and ILA severity and overall survival (OS) were evaluated using Cox proportional hazards models. The ability of AI-quantified emphysema and ILA severity to predict OS was explored via concordance index (C-index) and area under the time-dependent receiver operating characteristic curve (AUC). Furthermore, exploratory OS analyses were performed on subgroups stratified by chronic obstructive pulmonary disease status, treatment type, and tumor-node-metastasis (TNM) staging.

Of 1675 patients, 830 (49.6%) survived, and 845 (50.4%) died. Whole emphysema (mild: HR, 1.66 [95% CI: 1.26, 2.18]; p < 0.001; more than mild: HR, 2.55 [95% CI: 1.88, 3.48]; p < 0.001) and ILA (equivocal ILA: HR, 1.63 [95% CI: 1.15, 2.32]; p = 0.006; definite ILA: HR, 2.33 [95% CI: 1.61, 3.35]; p < 0.001) severity were independent prognostic factors for NSCLC, while regional emphysema and regional ILA severity were not. The model combining AI-quantified whole emphysema severity and ILA severity outperformed the TNM staging-only model in predicting NSCLC patient outcome (C-index, 0.80 vs. 0.75; AUC, 0.90 vs. 0.85).

Increased AI-quantified whole emphysema and ILA severity were associated with worse OS in NSCLC. The model combining AI-quantified emphysema and ILA showed improved performance for predicting patient survival versus TNM staging alone.

AI-quantified emphysema and ILA severity are associated with NSCLC patient outcome and can provide information complementary to TNM staging for predicting NSCLC patient survival and promoting the development of individualized management strategies.

The study explores artificial intelligence (AI) quantified emphysema and interstitial lung abnormality (ILA) severity in non-small cell lung cancer (NSCLC) prognosis.The AI-quantified whole emphysema severity and ILA severity were independent prognostic factors for NSCLC patient outcome, while regional emphysema and regional ILA severity were not.AI-quantified emphysema and ILA severity may help predict the survival of NSCLC patients and help clinicians make informed treatment decisions.

The study explores artificial intelligence (AI) quantified emphysema and interstitial lung abnormality (ILA) severity in non-small cell lung cancer (NSCLC) prognosis.

The AI-quantified whole emphysema severity and ILA severity were independent prognostic factors for NSCLC patient outcome, while regional emphysema and regional ILA severity were not.

AI-quantified emphysema and ILA severity may help predict the survival of NSCLC patients and help clinicians make informed treatment decisions.