超声内镜下胰腺神经内分泌肿瘤与胰管腺癌的鉴别。

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES
Danjie Shen, Can Yao, Ke Chen, Yunwei Sun, Xiaojuan Li, Junpei Zhang
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引用次数: 0

摘要

内镜超声(EUS)是评估胰腺肿块最关键的成像方式之一,提供胰腺的高分辨率可视化。本研究旨在评估数字图像分析(DIA)在通过EUS观察的实体胰腺肿瘤中鉴别胰腺神经内分泌肿瘤(PNEN)和胰腺导管腺癌(PDAC)的可行性。回顾性分析2018 - 2023年EUS检查的所有实体胰腺肿瘤,包括病理诊断为PDAC和PNEN的病例。使用Adobe Photoshop执行DIA。计算灰度比,定义为病变与选定背景的灰度比,以确保一致性。圆度是由面积与周长之比决定的。此外,提取灰度标准差进行进一步分析。EUS图像中的三个定量参数显示了区分PNEN和PDAC的潜力:圆度、灰度比和灰度标准差。圆度大于0.68、灰度比大于0.40、灰度标准差小于12.44为潜在PNEN。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Endoscopic Ultrasound-Based Differentiation of Pancreatic Neuroendocrine Tumors and Pancreatic Duct Adenocarcinoma.

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.

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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
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.
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