WCLC 2025 - Posters & ePosters-P2.06.01 Prognostic Value of a Combined Model Using CT and PET/CT Parameters for Predicting STAS in Stage I Lung Adenocarcinoma

P2.06.01 Prognostic Value of a Combined Model Using CT and PET/CT Parameters for Predicting STAS in Stage I Lung Adenocarcinoma

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This study investigated the prognostic value of combining CT and PET/CT imaging parameters to predict spread through air spaces (STAS) and recurrence risk in stage I lung adenocarcinoma. STAS is a pathological feature linked to poorer outcomes and higher recurrence. Researchers retrospectively analyzed 453 patients who underwent curative resection and assessed two imaging biomarkers: consolidation-to-tumor ratio (CTR) from chest CT and tumor-to-liver ratio (TLR) from PET-CT for their ability to predict STAS.<br /><br />Key findings include that STAS was present in 20.3% of patients and correlated with higher tumor stage, aggressive histology (grade 3), and lymphovascular invasion. STAS positivity was independently associated with worse disease-free survival (DFS). ROC analysis showed CTR (AUC=0.745) and TLR (AUC=0.641) moderately predicted STAS, with optimal cutoffs identified.<br /><br />An imaging-based risk model integrating CTR and TLR stratified patients into four groups with differing DFS outcomes. Patients with high TLR and either high or low CTR had significantly increased recurrence risk compared to low-risk groups, validated by multivariate analysis adjusting for clinical variables. Furthermore, higher imaging-based risk scores correlated with adverse pathological factors beyond STAS, including poor tumor differentiation and lymphovascular invasion.<br /><br />In conclusion, preoperative CT and PET-CT parameters can predict STAS and identify high-risk stage I lung adenocarcinoma patients. The combined imaging-based model effectively stratifies recurrence risk, potentially guiding personalized treatment decisions such as intensified adjuvant therapy for those at greatest risk. This approach may improve management and outcomes in early-stage lung cancer by augmenting current pathological assessment with non-invasive imaging biomarkers.

Asset Subtitle

Kyongmin Beck

Meta Tag

Speaker Kyongmin Beck

Topic Pathology and Biomarkers

Keywords

lung adenocarcinoma

stage I lung cancer

spread through air spaces

STAS

CT imaging

PET/CT imaging

consolidation-to-tumor ratio

tumor-to-liver ratio

recurrence risk prediction

imaging-based risk model