Cargando…
Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions
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...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498186/ https://www.ncbi.nlm.nih.gov/pubmed/36140506 http://dx.doi.org/10.3390/diagnostics12092105 |
_version_ | 1784794694931185664 |
---|---|
author | Keczer, Bánk Benke, Márton Marjai, Tamás Horváth, Miklós Miheller, Pál Szücs, Ákos Harsányi, László Szijártó, Attila Hritz, István |
author_facet | Keczer, Bánk Benke, Márton Marjai, Tamás Horváth, Miklós Miheller, Pál Szücs, Ákos Harsányi, László Szijártó, Attila Hritz, István |
author_sort | Keczer, Bánk |
collection | PubMed |
description | 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/mm(2) vs. 2833.8/mm(2) vs. 2981.6/mm(2); p < 0.0005 and p < 0.0005, respectively). The EUS image analysis process may have the potential to be a diagnostic tool for the evaluation and differentiation of pancreatic cystic lesions. |
format | Online Article Text |
id | pubmed-9498186 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-94981862022-09-23 Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions Keczer, Bánk Benke, Márton Marjai, Tamás Horváth, Miklós Miheller, Pál Szücs, Ákos Harsányi, László Szijártó, Attila Hritz, István Diagnostics (Basel) Article 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/mm(2) vs. 2833.8/mm(2) vs. 2981.6/mm(2); p < 0.0005 and p < 0.0005, respectively). The EUS image analysis process may have the potential to be a diagnostic tool for the evaluation and differentiation of pancreatic cystic lesions. MDPI 2022-08-30 /pmc/articles/PMC9498186/ /pubmed/36140506 http://dx.doi.org/10.3390/diagnostics12092105 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Keczer, Bánk Benke, Márton Marjai, Tamás Horváth, Miklós Miheller, Pál Szücs, Ákos Harsányi, László Szijártó, Attila Hritz, István Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title | Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title_full | Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title_fullStr | Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title_full_unstemmed | Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title_short | Quantitative Software Analysis of Endoscopic Ultrasound Images of Pancreatic Cystic Lesions |
title_sort | quantitative software analysis of endoscopic ultrasound images of pancreatic cystic lesions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498186/ https://www.ncbi.nlm.nih.gov/pubmed/36140506 http://dx.doi.org/10.3390/diagnostics12092105 |
work_keys_str_mv | AT keczerbank quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT benkemarton quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT marjaitamas quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT horvathmiklos quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT mihellerpal quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT szucsakos quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT harsanyilaszlo quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT szijartoattila quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions AT hritzistvan quantitativesoftwareanalysisofendoscopicultrasoundimagesofpancreaticcysticlesions |