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Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound
AIM: To develop a contrast-enhanced ultrasound (CEUS) predictive model for distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) in high-risk patients. METHODS: This retrospective study consisted of 88 consecutive high-risk patients with ICC and 88 high-risk patien...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127655/ https://www.ncbi.nlm.nih.gov/pubmed/30197484 http://dx.doi.org/10.3748/wjg.v24.i33.3786 |
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author | Chen, Li-Da Ruan, Si-Min Liang, Jin-Yu Yang, Zheng Shen, Shun-Li Huang, Yang Li, Wei Wang, Zhu Xie, Xiao-Yan Lu, Ming-De Kuang, Ming Wang, Wei |
author_facet | Chen, Li-Da Ruan, Si-Min Liang, Jin-Yu Yang, Zheng Shen, Shun-Li Huang, Yang Li, Wei Wang, Zhu Xie, Xiao-Yan Lu, Ming-De Kuang, Ming Wang, Wei |
author_sort | Chen, Li-Da |
collection | PubMed |
description | AIM: To develop a contrast-enhanced ultrasound (CEUS) predictive model for distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) in high-risk patients. METHODS: This retrospective study consisted of 88 consecutive high-risk patients with ICC and 88 high-risk patients with HCC selected by propensity score matching between May 2004 and July 2016. Patients were assigned to two groups, namely, a training set and validation set, at a 1:1 ratio. A CEUS score for diagnosing ICC was generated based on significant CEUS features. Then, a nomogram based on the CEUS score was developed, integrating the clinical data. The performance of the nomogram was then validated and compared with that of the LR-M of the CEUS Liver Imaging Reporting and Data System (LI-RADS). RESULTS: The most useful CEUS features for ICC were as follows: rim enhancement (64.5%), early washout (91.9%), intratumoral vein (58.1%), obscure boundary of intratumoral non-enhanced area (64.5%), and marked washout (61.3%, all P < 0.05). In the validation set, the area under the curve (AUC) of the CEUS score (AUC = 0.953) for differentiation between ICC and HCC was improved compared to the LI-RADS (AUC = 0.742) (P < 0.001). When clinical data were added, the CEUS score nomogram was superior to the LI-RADS nomogram (AUC: 0.973 vs 0.916, P = 0.036, Net Reclassification Improvement: 0.077, Integrated Discrimination Index: 0.152). Subgroup analysis demonstrated that the CEUS score model was notably improved compared to the LI-RADS in tumors smaller than 5.0 cm (P < 0.05) but not improved in tumors smaller than 3.0 cm (P > 0.05). CONCLUSION: The CEUS predictive model for differentiation between ICC and HCC in high-risk patients had improved discrimination and clinical usefulness compared to the CEUS LI-RADS. |
format | Online Article Text |
id | pubmed-6127655 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-61276552018-09-07 Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound Chen, Li-Da Ruan, Si-Min Liang, Jin-Yu Yang, Zheng Shen, Shun-Li Huang, Yang Li, Wei Wang, Zhu Xie, Xiao-Yan Lu, Ming-De Kuang, Ming Wang, Wei World J Gastroenterol Retrospective Study AIM: To develop a contrast-enhanced ultrasound (CEUS) predictive model for distinguishing intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) in high-risk patients. METHODS: This retrospective study consisted of 88 consecutive high-risk patients with ICC and 88 high-risk patients with HCC selected by propensity score matching between May 2004 and July 2016. Patients were assigned to two groups, namely, a training set and validation set, at a 1:1 ratio. A CEUS score for diagnosing ICC was generated based on significant CEUS features. Then, a nomogram based on the CEUS score was developed, integrating the clinical data. The performance of the nomogram was then validated and compared with that of the LR-M of the CEUS Liver Imaging Reporting and Data System (LI-RADS). RESULTS: The most useful CEUS features for ICC were as follows: rim enhancement (64.5%), early washout (91.9%), intratumoral vein (58.1%), obscure boundary of intratumoral non-enhanced area (64.5%), and marked washout (61.3%, all P < 0.05). In the validation set, the area under the curve (AUC) of the CEUS score (AUC = 0.953) for differentiation between ICC and HCC was improved compared to the LI-RADS (AUC = 0.742) (P < 0.001). When clinical data were added, the CEUS score nomogram was superior to the LI-RADS nomogram (AUC: 0.973 vs 0.916, P = 0.036, Net Reclassification Improvement: 0.077, Integrated Discrimination Index: 0.152). Subgroup analysis demonstrated that the CEUS score model was notably improved compared to the LI-RADS in tumors smaller than 5.0 cm (P < 0.05) but not improved in tumors smaller than 3.0 cm (P > 0.05). CONCLUSION: The CEUS predictive model for differentiation between ICC and HCC in high-risk patients had improved discrimination and clinical usefulness compared to the CEUS LI-RADS. Baishideng Publishing Group Inc 2018-09-07 2018-09-07 /pmc/articles/PMC6127655/ /pubmed/30197484 http://dx.doi.org/10.3748/wjg.v24.i33.3786 Text en ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Retrospective Study Chen, Li-Da Ruan, Si-Min Liang, Jin-Yu Yang, Zheng Shen, Shun-Li Huang, Yang Li, Wei Wang, Zhu Xie, Xiao-Yan Lu, Ming-De Kuang, Ming Wang, Wei Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title | Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title_full | Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title_fullStr | Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title_full_unstemmed | Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title_short | Differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: A predictive model using contrast-enhanced ultrasound |
title_sort | differentiation of intrahepatic cholangiocarcinoma from hepatocellular carcinoma in high-risk patients: a predictive model using contrast-enhanced ultrasound |
topic | Retrospective Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6127655/ https://www.ncbi.nlm.nih.gov/pubmed/30197484 http://dx.doi.org/10.3748/wjg.v24.i33.3786 |
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