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Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions by Bánk Keczer; Márton Benke; Tamás Marjai; Miklós Horváth; Pál Miheller; Ákos Szücs; László Harsányi; Attila Szijártó; István Hritz is a Medicine article available to read on EtoBox.

What is Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions about?

Endoscopic ultrasonography (EUS) is the most accurate imaging modality for the evaluation of different types of pancreatic cystic lesions. Our aim was to analyze EUS images of pancreatic cystic lesions using an image processing software. We specified the echogenicity of the lesions by measuring the gray value of pixels inside the selected areas. The images were divided into groups (serous cystic neoplasm /SCN/, intraductal papillary mucinous neoplasms and mucinous cystic neoplasms /Non-SCN/ and Pseudocyst) according to the pathology results of the lesions. Overall, 170 images were processed by the software: 81 in Non-SCN, 30 in SCN and 59 in Pseudocyst group. The mean gray value of the entire lesion in the Non-SCN group was significantly higher than in the SCN group (27.8 vs. 18.8; p < 0.0005). The area ratio in the SCN, Non-SCN and Pseudocyst groups was 57%, 39% and 61%, respectively; significantly lower in the Non-SCN group than in the SCN or Pseudocyst groups (p < 0.0005 and p < 0.0005, respectively). The lesion density was also significantly higher in the Non-SCN group compared to the SCN or Pseudocyst groups (4186.6/mm2 vs. 2833.8/mm2 vs. 2981.6/mm2; p < 0.0005 and p < 0.0005,

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Author

Bánk Keczer; Márton Benke; Tamás Marjai; Miklós Horváth; Pál Miheller; Ákos Szücs; László Harsányi; Attila Szijártó; István Hritz

Publisher

MDPI AG

Published

2022

Language

EN

Field

Medicine (Health Sciences)