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Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid

Differentiation between mucinous and non-mucinous pancreatic cysts is exceedingly important and challenging, particularly as the former bears malignant transformation potential. Pancreatic cyst fluid (PCF)-based diagnostics, including analyses of biochemical markers, as well as cytology, has shown i...

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Autores principales: Khamaysi, Iyad, Abu Ammar, Aiman, Vasilyev, Gleb, Arinstein, Arkadii, Chowers, Yehuda, Zussman, Eyal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372360/
https://www.ncbi.nlm.nih.gov/pubmed/28358122
http://dx.doi.org/10.1038/srep45589
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author Khamaysi, Iyad
Abu Ammar, Aiman
Vasilyev, Gleb
Arinstein, Arkadii
Chowers, Yehuda
Zussman, Eyal
author_facet Khamaysi, Iyad
Abu Ammar, Aiman
Vasilyev, Gleb
Arinstein, Arkadii
Chowers, Yehuda
Zussman, Eyal
author_sort Khamaysi, Iyad
collection PubMed
description Differentiation between mucinous and non-mucinous pancreatic cysts is exceedingly important and challenging, particularly as the former bears malignant transformation potential. Pancreatic cyst fluid (PCF)-based diagnostics, including analyses of biochemical markers, as well as cytology, has shown inadequate accuracy. Herein, a preliminary single-center study of 22 PCF samples, collected by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA), assessed the rheological behavior of PCF and its correlation with lesion type. The dependence of PCF shear viscosity on shear rate was found to follow a power law and could be fitted using Ostwald–de Waele model. Three types of flow curves were identified, where two types correlated with non-mucinous cysts, differing by their power law exponent, and the third type corresponding to mucinous cysts. Viscosity measured at a high shear rate was shown to serve as an accurate and independent marker distinguishing between mucinous and non-mucinous cysts, with an optimal cutoff value of η(c) = 1.3 cP The accuracy of this novel technique proved superior to string-sign, cytology, carcinoembryonic antigen, and amylase assessments. Moreover, the combined predictive value of η(c) and patient age provided for sensitivity and specificity of 100% and 95.5%, respectively. This simple and rapid diagnostic tool can be immediately implemented after EUS-FNA sampling.
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spelling pubmed-53723602017-03-31 Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid Khamaysi, Iyad Abu Ammar, Aiman Vasilyev, Gleb Arinstein, Arkadii Chowers, Yehuda Zussman, Eyal Sci Rep Article Differentiation between mucinous and non-mucinous pancreatic cysts is exceedingly important and challenging, particularly as the former bears malignant transformation potential. Pancreatic cyst fluid (PCF)-based diagnostics, including analyses of biochemical markers, as well as cytology, has shown inadequate accuracy. Herein, a preliminary single-center study of 22 PCF samples, collected by endoscopic ultrasound-guided fine needle aspiration (EUS-FNA), assessed the rheological behavior of PCF and its correlation with lesion type. The dependence of PCF shear viscosity on shear rate was found to follow a power law and could be fitted using Ostwald–de Waele model. Three types of flow curves were identified, where two types correlated with non-mucinous cysts, differing by their power law exponent, and the third type corresponding to mucinous cysts. Viscosity measured at a high shear rate was shown to serve as an accurate and independent marker distinguishing between mucinous and non-mucinous cysts, with an optimal cutoff value of η(c) = 1.3 cP The accuracy of this novel technique proved superior to string-sign, cytology, carcinoembryonic antigen, and amylase assessments. Moreover, the combined predictive value of η(c) and patient age provided for sensitivity and specificity of 100% and 95.5%, respectively. This simple and rapid diagnostic tool can be immediately implemented after EUS-FNA sampling. Nature Publishing Group 2017-03-30 /pmc/articles/PMC5372360/ /pubmed/28358122 http://dx.doi.org/10.1038/srep45589 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Khamaysi, Iyad
Abu Ammar, Aiman
Vasilyev, Gleb
Arinstein, Arkadii
Chowers, Yehuda
Zussman, Eyal
Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title_full Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title_fullStr Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title_full_unstemmed Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title_short Differentiation of Pancreatic Cyst Types by Analysis of Rheological Behavior of Pancreatic Cyst Fluid
title_sort differentiation of pancreatic cyst types by analysis of rheological behavior of pancreatic cyst fluid
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372360/
https://www.ncbi.nlm.nih.gov/pubmed/28358122
http://dx.doi.org/10.1038/srep45589
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