Danjie Shen, Can Yao, Ke Chen, Yunwei Sun, Xiaojuan Li, Junpei Zhang
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引用次数: 0
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.
期刊介绍:
JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.