Endoscopic Ultrasound-Based Differentiation of Pancreatic Neuroendocrine Tumors and Pancreatic Duct Adenocarcinoma

Abstract

Endoscopic ultrasound (EUS) is one of the most critical imaging modalities for evaluating pancreatic masses, providing high-resolution visualization of the pancreas. This study aimed to assess the feasibility of digital image analysis (DIA) in differentiating pancreatic neuroendocrine neoplasms (PNEN) from pancreatic ductal adenocarcinoma (PDAC) in solid pancreatic tumors observed via EUS. A retrospective analysis was conducted on all solid pancreatic tumors examined by EUS procedures from 2018 to 2023, including cases with confirmed pathological diagnoses of PDAC and PNEN. Adobe Photoshop was used to perform DIA. The gray ratio, defined as the gray-scale ratio of the lesion to a selected background, was calculated to ensure consistency. Circularity was determined by the ratio of area to perimeter. Additionally, gray-scale standard deviations were extracted for further analysis. Three quantitative parameters from EUS images demonstrated potential for distinguishing PNEN from PDAC: circularity, gray ratio, and gray-scale standard deviation. Specifically, a circularity greater than 0.68, a gray ratio exceeding 0.40, and a gray-scale standard deviation below 12.44 were indicative of potential PNEN.