A study published in BMC Cancer demonstrates that radiomic analysis of contrast-enhanced computed tomography (CECT) images combined with machine learning algorithms can predict perineural invasion (PNI) in pancreatic cancer preoperatively. PNI is a critical prognostic factor associated with poor patient outcomes. This non-invasive predictive method aids in treatment decision-making and could improve personalized therapeutic strategies for one of the most lethal digestive system malignancies. The integration of advanced imaging analytics marks a significant step toward precision oncology.