Noninvasive Assessment of Vascular Endothelial Growth Factor and Prognosis in Gastric Cancer Through Radiomic Features.

Introduction: Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide, with delayed diagnosis often limiting effective treatment options. This study introduces a novel, noninvasive radiomics-based approach using [18F] FDG PET/CT (fluorodeoxyglucose positron emission tomography/computed tomography) to predict vascular endothelial growth factor (VEGF) status and survival in patients with GC. The ability to noninvasively assess these parameters can significantly influence therapeutic decisions and outcomes.

Methods: We conducted a retrospective study involving patients diagnosed with GC, stratified into training, validation, and test groups. Each patient underwent a [18F] FDG PET/CT scan, and radiomic features were extracted using dedicated software. A Radiomics Score (RS) was calculated, serving as a predictor for VEGF status. Statistical analyses included logistic regression and Cox proportional hazards models to evaluate the predictive power of RS on survival outcomes.

Results: The developed radiomics model demonstrated high predictive accuracy, with the RS formula achieving an area under the receiver operating characteristic curve of 0.861 in the training cohort and 0.857 in the validation cohort for predicting VEGF status. The model also identified RS as an independent prognostic factor for survival, where higher RS values correlated with poorer survival rates.

Discussion: The findings underscore the potential of [18F] FDG PET/CT radiomics in transforming the management of GC by providing a noninvasive means to assess tumor aggressiveness and prognosis through VEGF status. This model could facilitate earlier and more tailored therapeutic interventions, potentially improving survival outcomes in a disease marked by typically late diagnosis and limited treatment success.