Abstract: Objective To investigate the imaging characteristics and differences among pancreatic serous cystic neoplasm (SCN) subtypes and their pathological basis, aiming to improve preoperative diagnostic accuracy. Methods Imaging and pathological data of 65 patients with pathologically confirmed pancreatic SCN were analyzed retrospectively. The lesions were categorized into four subtypes based on morphological features: macrocystic, microcystic, mixed, and solid. Computed tomography/magnetic resonance imaging (CT/MRI) imaging features of each subtype were compared and correlated with histopathological findings. Results No statistically significant differences were observed among the age, lesion location, clinical manifestations, or comorbidities of subtypes (P > 0.05). Significant differences were observed in lesion density and enhancement patterns (P < 0.05). All SCN exhibited hyperintensity on T2-weighted imaging, absence of communication with the pancreatic duct, and no metastatic signs. In addition, other shared imaging features included lobulated contours and multicystic structures, with internal calcifications (on CT) being a specific but less frequent finding (28.3%). Macrocystic SCN lacked central scars, while microcystic and mixed subtypes displayed higher MRI detection rates of central fibrous scars (63.2%). Solid-type SCN were smaller in size, demonstrating marked homogeneous enhancement. Pathological analysis revealed: macrocystic SCN had thin stroma and sparse vasculature between cysts; microcystic SCN were rich in fibrous scar tissue; mixed-type combined features of both; solid-type SCN were characterized by high vascular density and dense fibrous stroma, with microcystic structures undetectable by conventional imaging. Conclusion Each pancreatic SCN subtype exhibited characteristic imaging features, and these imaging findings correlate well with pathological characteristics. A thorough understanding of their pathological basis, combined with multimodal imaging techniques, can significantly enhance the accuracy of imaging diagnosis.