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Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology

Portal hypertension secondary to liver cirrhosis may cause a number of life-threatening complications. The rupture of gastroesophageal varices is associated with a high mortality rate of 15–30%. Hepatic venous pressure gradient (HVPG) is an accurate reflection of disease severity, however this can o...

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Autores principales: Tseng, Yujen, Ma, Lili, Luo, Tiancheng, Zeng, Xiaoqing, Li, Na, Wei, Yichao, Zhou, Ji, Li, Feng, Chen, Shiyao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841049/
https://www.ncbi.nlm.nih.gov/pubmed/29545851
http://dx.doi.org/10.3892/etm.2018.5816
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author Tseng, Yujen
Ma, Lili
Luo, Tiancheng
Zeng, Xiaoqing
Li, Na
Wei, Yichao
Zhou, Ji
Li, Feng
Chen, Shiyao
author_facet Tseng, Yujen
Ma, Lili
Luo, Tiancheng
Zeng, Xiaoqing
Li, Na
Wei, Yichao
Zhou, Ji
Li, Feng
Chen, Shiyao
author_sort Tseng, Yujen
collection PubMed
description Portal hypertension secondary to liver cirrhosis may cause a number of life-threatening complications. The rupture of gastroesophageal varices is associated with a high mortality rate of 15–30%. Hepatic venous pressure gradient (HVPG) is an accurate reflection of disease severity, however this can only be assessed via an invasive interventional procedure. The aim of the present study was to explore a non-invasive method based on 3D computed tomography (CT) volume rendering technology to accurately predict HVPG. A total of 77 patients diagnosed with liver cirrhosis underwent HVPG examination in the present study and the appropriate clinical and radiological data were retrospectively reviewed. A 3D liver and spleen volume rendering was constructed for volume measurements. All non-invasive parameters were tested using univariate analysis and the resulting variables that were statistically significant (P<0.20) were used in the multivariate linear regression model. The HVPG predictive model was as follows: HVPG = 18.726 - 0.324 (albumin) + 1.57 (aminotransferase-to-platelet ratio index) + 0.004 (liver volume) (multivariate regression analysis, P=0.006). The corresponding area under receiver operating characteristic curve to identify clinically significant portal hypertension defined as HVPG ≥10 mmHg was 0.810 (95% confidence interval; 0.705–0.891), with an optimal cut-off value of 12.84, yielding a sensitivity of 80.36% a specificity of 76.19%. The results of the present study indicate that 3D CT volume rendering technology may have the potential to be used for non-invasive prediction of HVPG.
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spelling pubmed-58410492018-03-15 Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology Tseng, Yujen Ma, Lili Luo, Tiancheng Zeng, Xiaoqing Li, Na Wei, Yichao Zhou, Ji Li, Feng Chen, Shiyao Exp Ther Med Articles Portal hypertension secondary to liver cirrhosis may cause a number of life-threatening complications. The rupture of gastroesophageal varices is associated with a high mortality rate of 15–30%. Hepatic venous pressure gradient (HVPG) is an accurate reflection of disease severity, however this can only be assessed via an invasive interventional procedure. The aim of the present study was to explore a non-invasive method based on 3D computed tomography (CT) volume rendering technology to accurately predict HVPG. A total of 77 patients diagnosed with liver cirrhosis underwent HVPG examination in the present study and the appropriate clinical and radiological data were retrospectively reviewed. A 3D liver and spleen volume rendering was constructed for volume measurements. All non-invasive parameters were tested using univariate analysis and the resulting variables that were statistically significant (P<0.20) were used in the multivariate linear regression model. The HVPG predictive model was as follows: HVPG = 18.726 - 0.324 (albumin) + 1.57 (aminotransferase-to-platelet ratio index) + 0.004 (liver volume) (multivariate regression analysis, P=0.006). The corresponding area under receiver operating characteristic curve to identify clinically significant portal hypertension defined as HVPG ≥10 mmHg was 0.810 (95% confidence interval; 0.705–0.891), with an optimal cut-off value of 12.84, yielding a sensitivity of 80.36% a specificity of 76.19%. The results of the present study indicate that 3D CT volume rendering technology may have the potential to be used for non-invasive prediction of HVPG. D.A. Spandidos 2018-04 2018-01-30 /pmc/articles/PMC5841049/ /pubmed/29545851 http://dx.doi.org/10.3892/etm.2018.5816 Text en Copyright: © Tseng et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.
spellingShingle Articles
Tseng, Yujen
Ma, Lili
Luo, Tiancheng
Zeng, Xiaoqing
Li, Na
Wei, Yichao
Zhou, Ji
Li, Feng
Chen, Shiyao
Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title_full Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title_fullStr Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title_full_unstemmed Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title_short Non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
title_sort non-invasive predictive model for hepatic venous pressure gradient based on a 3-dimensional computed tomography volume rendering technology
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841049/
https://www.ncbi.nlm.nih.gov/pubmed/29545851
http://dx.doi.org/10.3892/etm.2018.5816
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