This multicenter retrospective study aims to investigate the value of 18F-FDG PET/CT radiomics features in the preoperative precision staging, pathological typing, gene mutation status prediction, and prognostic risk stratification of patients with Non-Small Cell Lung Cancer (NSCLC). The study involves constructing and validating machine learning models to provide imaging-based evidence for individualized precision clinical decision-making.
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Diagnostic Performance for TNM Staging and Histological Subtyping
Timeframe: Baseline
Predictive Accuracy for EGFR Mutation Status
Timeframe: Baseline
Prognostic Value
Timeframe: From date of surgery up to 5 years