Machine learning-driven PET-CT and clinical pathology model for predicting mediastinal lymph node metastasis in non-small cell lung cancer: a retrospective cohort study

Combining PET-CT imaging features of primary tumors and lymph nodes with clinical and pathological data shows promise for accurately predicting MLNM in NSCLC. The TLPC model offers a non-invasive method for identifying lymph node metastasis, supporting personalized treatment strategies. However, since PET-CT was performed selectively rather than routinely acquired, external validation across diverse clinical settings is warranted to confirm model generalizability.