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Lung cancer is currently the leading cause of cancer-related mortality worldwide, and the dominant histopathology is non-small cell lung cancer (NSCLC). Although many new targeted and immunomodulation therapies have emerged, not all patients are responsive to novel therapeutics. A more reliable and accurate risk stratification model to predict the treatment response and survival outcomes are still lacking. The 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) derived radiomics can be used to interrogate tumor biologies such as glycolytic activity and heterogeneity. It can, therefore, be used to predict treatment response and survival outcomes. Cancer genomics derived from gene sequencing can evaluate cancer's genetic alterations. It can be used to feature the genotype of the tumor. However, both tools have drawbacks; combining these two modalities may enable a more robu
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