Graph Neural Network Model for Prediction of Non-Small Cell Lung Cancer Lymph Node Metastasis Using Protein-Protein Interaction Network and ¹⁸F-FDG PET/CT Radiomics

The image texture features obtained from ^(18)F-fluorodeoxyglucose positron emission tomography/computed tomography (^(18)F-FDG PET/CT) images of non-small cell lung cancer (NSCLC) have revealed tumor heterogeneity. A combination of genomic data and radiomics may improve the prediction of tumor prognosis. This study aimed to predict NSCLC metastasis using a graph neural network (GNN) obtained by combining a protein-protein interaction (PPI) network based on gene expression data and image …