Spatial imaging features derived from SUVmax location in resectable NSCLC are associated with tumor aggressiveness

Jiang, Zewen and Spielvogel, Clemens and Haberl, David and Yu, Josef and Krisch, Maximilian and Szakáll, Szabolcs and Molnár, Péter and Fillinger, János and Horváth, Lilla and Rényi-Vámos, Ferenc and Aigner, Clemens and Dome, Balazs and Lang, Christian and Megyesfalvi, Zsolt and Kenner, Lukas and Hacker, Marcus (2025) Spatial imaging features derived from SUVmax location in resectable NSCLC are associated with tumor aggressiveness. European Journal of Nuclear Medicine and Molecular Imaging. ISSN 1619-7070

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Abstract

Purpose Accurate non-invasive prediction of histopathologic invasiveness and recurrence risk remains a clinical challenge in resectable non-small cell lung cancer (NSCLC). We developed and validated the Edge Proximity Score (EPS), a novel [ 18F]FDG PET/CT-based spatial imaging feature that quantifies the displacement of SUVmax relative to the tumor centroid and perimeter, to assess tumor aggressiveness and predict progression-free survival (PFS). Methods This retrospective study included 244 NSCLC patients with preoperative [18F]FDG PET/CT. EPS was computed from normalized SUVmax-to-centroid and SUVmax-to-perimeter distances. A total of 115 PET radiomics features were extracted and standardized. Eight machine learning models (80:20 split) were trained to predict lymphovascular invasion (LVI), visceral pleural invasion (VPI), and spread through air spaces (STAS), with feature importance assessed using SHAP. Prognostic analysis was conducted using multivariable Cox regression. A survival prediction model incorporating EPS was externally validated in the TCIA cohort. RNA sequencing data from 76 TCIA patients were used for transcriptomic and immune profiling. Results EPS was significantly elevated in tumors with LVI, VPI, and STAS (P<0.001), consistently ranked among the top SHAP features, and was an independent predictor of PFS (HR=2.667, P=0.015). The EPS-based nomogram achieved AUCs of 0.67, 0.70, and 0.68 for predicting 1-, 3-, and 5-year PFS in the TCIA validation cohort. High EPS was associated with proliferative and metabolic gene signatures, whereas low EPS was linked to immune activation and neutrophil infiltration. Conclusion EPS is a biologically relevant, non-invasive imaging biomarker that may improve risk stratification in NSCLC.

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