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The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma
OBJECTIVE: To establish and validate an MRI T2(∗)WI-based radiomics nomogram model and to discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICCA). METHODS: 174 patients were retrospectively collected, who were diagnosed with primary hepatic carcinoma by surgery or pun...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532145/ https://www.ncbi.nlm.nih.gov/pubmed/36203532 http://dx.doi.org/10.1155/2022/7099476 |
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author | Huang, Feng Liu, Xiaoyun Liu, Peng Xu, Dan Li, Zeda Lin, Huashan Xie, An |
author_facet | Huang, Feng Liu, Xiaoyun Liu, Peng Xu, Dan Li, Zeda Lin, Huashan Xie, An |
author_sort | Huang, Feng |
collection | PubMed |
description | OBJECTIVE: To establish and validate an MRI T2(∗)WI-based radiomics nomogram model and to discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICCA). METHODS: 174 patients were retrospectively collected, who were diagnosed with primary hepatic carcinoma by surgery or puncture pathology and received preoperative MRI scans including T2(∗)WI scans. There were 113 cases of HCC and 61 cases of mass-type ICCA. T2(∗)WI was used for feature extraction, the extent of the lesions was manually outlined at the largest lesions layer of the T2(∗)WI, and the feature dimension reduction was performed by the mRMR and LASSO to obtain the optimal feature set. The radiomics features and clinical risk factors were combined to establish the radiomics nomogram model. In both training and validation groups, calibration curves and ROC curves were applied to validate the efficacy of the established model. Finally, calibration curves were applied to assess the degree of fitting and DCA to assess the clinical utility of the established model. RESULTS: The radiomics model had the AUC of 0.90 (95% CI, 0.85–0.96) and 0.91 (95% CI, 0.83–0.99) in the training and validation groups, respectively; the AUC of the radiomics nomogram was 0.97 (95% CI, 0.94–0.99) in the training group and 0.95 (95% CI, 0.95–0.99) in the validation group. DCA suggested the clinical application value of the nomogram model. CONCLUSION: Radiomics nomogram model based on MRI T2(∗)WI scan without enhancement can be used to discriminate HCC from ICCA. |
format | Online Article Text |
id | pubmed-9532145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-95321452022-10-05 The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma Huang, Feng Liu, Xiaoyun Liu, Peng Xu, Dan Li, Zeda Lin, Huashan Xie, An Comput Math Methods Med Research Article OBJECTIVE: To establish and validate an MRI T2(∗)WI-based radiomics nomogram model and to discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma (ICCA). METHODS: 174 patients were retrospectively collected, who were diagnosed with primary hepatic carcinoma by surgery or puncture pathology and received preoperative MRI scans including T2(∗)WI scans. There were 113 cases of HCC and 61 cases of mass-type ICCA. T2(∗)WI was used for feature extraction, the extent of the lesions was manually outlined at the largest lesions layer of the T2(∗)WI, and the feature dimension reduction was performed by the mRMR and LASSO to obtain the optimal feature set. The radiomics features and clinical risk factors were combined to establish the radiomics nomogram model. In both training and validation groups, calibration curves and ROC curves were applied to validate the efficacy of the established model. Finally, calibration curves were applied to assess the degree of fitting and DCA to assess the clinical utility of the established model. RESULTS: The radiomics model had the AUC of 0.90 (95% CI, 0.85–0.96) and 0.91 (95% CI, 0.83–0.99) in the training and validation groups, respectively; the AUC of the radiomics nomogram was 0.97 (95% CI, 0.94–0.99) in the training group and 0.95 (95% CI, 0.95–0.99) in the validation group. DCA suggested the clinical application value of the nomogram model. CONCLUSION: Radiomics nomogram model based on MRI T2(∗)WI scan without enhancement can be used to discriminate HCC from ICCA. Hindawi 2022-09-27 /pmc/articles/PMC9532145/ /pubmed/36203532 http://dx.doi.org/10.1155/2022/7099476 Text en Copyright © 2022 Feng Huang et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Huang, Feng Liu, Xiaoyun Liu, Peng Xu, Dan Li, Zeda Lin, Huashan Xie, An The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title | The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title_full | The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title_fullStr | The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title_full_unstemmed | The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title_short | The Application Value of MRI T2(∗)WI Radiomics Nomogram in Discriminating Hepatocellular Carcinoma from Intrahepatic Cholangiocarcinoma |
title_sort | application value of mri t2(∗)wi radiomics nomogram in discriminating hepatocellular carcinoma from intrahepatic cholangiocarcinoma |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532145/ https://www.ncbi.nlm.nih.gov/pubmed/36203532 http://dx.doi.org/10.1155/2022/7099476 |
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