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Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation
BACKGROUND: Liver cirrhosis-acute decompensation (LC-AD) has rapid short-term disease progression and difficult early risk stratification. The purpose is to develop and validate a model based on dual-energy CT quantification of extracellular liver volume (ECV(IC-liver)) for predicting the occurrence...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050608/ https://www.ncbi.nlm.nih.gov/pubmed/36977956 http://dx.doi.org/10.1186/s13244-023-01393-x |
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author | Xu, Yuan Li, Yufeng Li, Shenglin Xue, Shouxiao Liu, Jianli |
author_facet | Xu, Yuan Li, Yufeng Li, Shenglin Xue, Shouxiao Liu, Jianli |
author_sort | Xu, Yuan |
collection | PubMed |
description | BACKGROUND: Liver cirrhosis-acute decompensation (LC-AD) has rapid short-term disease progression and difficult early risk stratification. The purpose is to develop and validate a model based on dual-energy CT quantification of extracellular liver volume (ECV(IC-liver)) for predicting the occurrence of acute-on-chronic liver failure (ACLF) within 90 days in patients with hepatitis B (HBV) LC-AD. METHODS: The retrospective study included patients with HBV LC-AD who underwent dual-energy CT scans of the liver from January 2018 to March 2022 and were randomized to training group (215 patients) and validation group (92 patients). The primary outcome was the need for readmission within 90 days due to ACLF. Based on the training group data, independent risk factors for disease progression in clinical and dual-energy CT parameters were identified and modeled by logistic regression analysis. Based on the training and validation groups data, receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCA) were used to verify the discrimination, calibration, and clinical validity of the nomogram. RESULTS: Chronic liver failure consortium-acute decompensation score (CLIF-C ADs) (p = 0.008) and ECV(IC-liver) (p < 0.001) were independent risk factors for ACLF within 90 days. The AUC of the model combined ECV(IC-liver) and CLIF-C ADs were 0.893 and 0.838 in the training and validation groups, respectively. The calibration curves show good agreement between predicted and actual risks. The DCA indicates that the model has good clinical application. CONCLUSION: The model combined ECV(IC-liver) and CLIF-C ADs can early predict the occurrence of ACLF within 90 days in HBV LC-AD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01393-x. |
format | Online Article Text |
id | pubmed-10050608 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-100506082023-03-30 Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation Xu, Yuan Li, Yufeng Li, Shenglin Xue, Shouxiao Liu, Jianli Insights Imaging Original Article BACKGROUND: Liver cirrhosis-acute decompensation (LC-AD) has rapid short-term disease progression and difficult early risk stratification. The purpose is to develop and validate a model based on dual-energy CT quantification of extracellular liver volume (ECV(IC-liver)) for predicting the occurrence of acute-on-chronic liver failure (ACLF) within 90 days in patients with hepatitis B (HBV) LC-AD. METHODS: The retrospective study included patients with HBV LC-AD who underwent dual-energy CT scans of the liver from January 2018 to March 2022 and were randomized to training group (215 patients) and validation group (92 patients). The primary outcome was the need for readmission within 90 days due to ACLF. Based on the training group data, independent risk factors for disease progression in clinical and dual-energy CT parameters were identified and modeled by logistic regression analysis. Based on the training and validation groups data, receiver operating characteristic (ROC) curves, calibration curves, and decision analysis curves (DCA) were used to verify the discrimination, calibration, and clinical validity of the nomogram. RESULTS: Chronic liver failure consortium-acute decompensation score (CLIF-C ADs) (p = 0.008) and ECV(IC-liver) (p < 0.001) were independent risk factors for ACLF within 90 days. The AUC of the model combined ECV(IC-liver) and CLIF-C ADs were 0.893 and 0.838 in the training and validation groups, respectively. The calibration curves show good agreement between predicted and actual risks. The DCA indicates that the model has good clinical application. CONCLUSION: The model combined ECV(IC-liver) and CLIF-C ADs can early predict the occurrence of ACLF within 90 days in HBV LC-AD patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-023-01393-x. Springer Vienna 2023-03-29 /pmc/articles/PMC10050608/ /pubmed/36977956 http://dx.doi.org/10.1186/s13244-023-01393-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Xu, Yuan Li, Yufeng Li, Shenglin Xue, Shouxiao Liu, Jianli Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title | Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title_full | Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title_fullStr | Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title_full_unstemmed | Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title_short | Dual-energy CT quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis B liver cirrhosis-acute decompensation |
title_sort | dual-energy ct quantification of extracellular liver volume predicts short-term disease progression in patients with hepatitis b liver cirrhosis-acute decompensation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10050608/ https://www.ncbi.nlm.nih.gov/pubmed/36977956 http://dx.doi.org/10.1186/s13244-023-01393-x |
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