Abstract
BACKGROUND: Pancreatic neoplasms are associated with high morbidity and mortality, largely due to late diagnosis and challenges in accurate staging. Multiphasic computed tomography (CT) is a critical imaging tool for evaluating pancreatic masses offering detailed information on lesion characterization and surgical resectability. Precise radiological assessment is vital for treatment planning, and correlating imaging findings with histopathology improves diagnostic efficiency. METHODS: This prospective study was conducted on 50 patients with clinically suspected pancreatic neoplasms who underwent multiphasic CT imaging. Non-contrast, late arterial (pancreatic phase), and portal venous phase images were acquired following standardized contrast-enhanced CT protocols. Lesions were evaluated for size, morphology, enhancement patterns, vascular involvement, and local invasion. Resectability was assessed according to the Dutch Pancreatic Cancer Group (DPCG) criteria. Imaging findings were correlated with the final histopathological diagnosis to determine diagnostic sensitivity and specificity. RESULTS: In the vast majority of cases, 43 out of 50 (86%) were diagnosed as adenocarcinoma. Other diagnoses, such as mucinous cystadenoma, solid pseudo-papillary epithelial neoplasm (SPEN), and neuroendocrine tumor, were very uncommon, each making up 4% of the total cases. Multiphasic CT showed excellent sensitivity and specificity of 100% and 85.7%, respectively, in diagnosing pancreatic neoplasms. Out of 50 cases, 16 cases were found to be resectable, 10 cases were borderline resectable, and 24 cases were non-resectable, out of which 15 cases showed distant metastasis. CONCLUSION: Multiphasic CT is a highly accurate, non-invasive modality for the evaluation and characterization of pancreatic masses. It demonstrates a strong correlation with histopathological findings, reliably assesses vascular involvement, and predicts resectability according to DPCG criteria. Therefore, early and accurate CT-based evaluation is critical for optimal treatment planning and improving patient outcomes.