Catching pancreatic cancer early: Are we there yet?

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies worldwide, primarily due to its aggressive nature and the predominance of late-stage diagnoses. The 5-year survival rate remains dismal, often below 7 %, underscoring the urgent need for effective early detection strategies. Despite advancements in imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), and endoscopic ultrasound (EUS), population-wide screening remains impractical due to the disease's low incidence and lack of specific early biomarkers. Recent technological innovations, including artificial intelligence (AI)-driven imaging analysis and the discovery of circulating biomarkers have shown promising potential in improving early diagnosis and risk stratification. AI-enabled pancreas segmentation and radiomics further enhance the detection of subtle morphological changes that may be imperceptible to human naked eyes. However, these approaches remain largely investigational and require further validation, standardization, and clinical integration. This review summarizes current advances and ongoing challenges in early PDAC detection, emphasizing that despite promising developments, clinically effective early detection strategies are still lacking. Continued efforts to integrate multi-omics profiling, refine imaging technologies, and incorporate AI-assisted diagnostics into validated, risk-based screening models are essential to move toward earlier intervention and improved patient outcomes.