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Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis

INTRODUCTION: Considering the narrow window of surgery, early diagnosis of liver cancer is still a fundamental issue to explore. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICCA) are considered as two different types of liver cancer because of their distinct pathogenesis, pat...

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Autores principales: Xu, Xiaoliang, Mao, Yingfan, Tang, Yanqiu, Liu, Yang, Xue, Cailin, Yue, Qi, Liu, Qiaoyu, Wang, Jincheng, Yin, Yin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8885247/
https://www.ncbi.nlm.nih.gov/pubmed/35237341
http://dx.doi.org/10.1155/2022/5334095
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author Xu, Xiaoliang
Mao, Yingfan
Tang, Yanqiu
Liu, Yang
Xue, Cailin
Yue, Qi
Liu, Qiaoyu
Wang, Jincheng
Yin, Yin
author_facet Xu, Xiaoliang
Mao, Yingfan
Tang, Yanqiu
Liu, Yang
Xue, Cailin
Yue, Qi
Liu, Qiaoyu
Wang, Jincheng
Yin, Yin
author_sort Xu, Xiaoliang
collection PubMed
description INTRODUCTION: Considering the narrow window of surgery, early diagnosis of liver cancer is still a fundamental issue to explore. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICCA) are considered as two different types of liver cancer because of their distinct pathogenesis, pathological features, prognosis, and responses to adjuvant therapies. Qualitative analysis of image is not enough to make a discrimination of liver cancer, especially early-stage HCC or ICCA. METHODS: This retrospective study developed a radiomic-based model in a training cohort of 122 patients. Radiomic features were extracted from computed tomography (CT) scans. Feature selection was operated with the least absolute shrinkage and operator (LASSO) logistic method. The support vector machine (SVM) was selected to build a model. An internal validation was conducted in 89 patients. RESULTS: In the training set, the AUC of the evaluation of the radiomics was 0.855 higher than for radiologists at 0.689. In the valuation cohorts, the AUC of the evaluation was 0.847 and the validation was 0.659, which indicated that the established model has a significantly better performance in distinguishing the HCC from ICCA. CONCLUSION: We developed a radiomic diagnosis model based on CT image that can quickly distinguish HCC from ICCA, which may facilitate the differential diagnosis of HCC and ICCA in the future.
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spelling pubmed-88852472022-03-01 Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis Xu, Xiaoliang Mao, Yingfan Tang, Yanqiu Liu, Yang Xue, Cailin Yue, Qi Liu, Qiaoyu Wang, Jincheng Yin, Yin Comput Math Methods Med Research Article INTRODUCTION: Considering the narrow window of surgery, early diagnosis of liver cancer is still a fundamental issue to explore. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICCA) are considered as two different types of liver cancer because of their distinct pathogenesis, pathological features, prognosis, and responses to adjuvant therapies. Qualitative analysis of image is not enough to make a discrimination of liver cancer, especially early-stage HCC or ICCA. METHODS: This retrospective study developed a radiomic-based model in a training cohort of 122 patients. Radiomic features were extracted from computed tomography (CT) scans. Feature selection was operated with the least absolute shrinkage and operator (LASSO) logistic method. The support vector machine (SVM) was selected to build a model. An internal validation was conducted in 89 patients. RESULTS: In the training set, the AUC of the evaluation of the radiomics was 0.855 higher than for radiologists at 0.689. In the valuation cohorts, the AUC of the evaluation was 0.847 and the validation was 0.659, which indicated that the established model has a significantly better performance in distinguishing the HCC from ICCA. CONCLUSION: We developed a radiomic diagnosis model based on CT image that can quickly distinguish HCC from ICCA, which may facilitate the differential diagnosis of HCC and ICCA in the future. Hindawi 2022-02-21 /pmc/articles/PMC8885247/ /pubmed/35237341 http://dx.doi.org/10.1155/2022/5334095 Text en Copyright © 2022 Xiaoliang Xu 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
Xu, Xiaoliang
Mao, Yingfan
Tang, Yanqiu
Liu, Yang
Xue, Cailin
Yue, Qi
Liu, Qiaoyu
Wang, Jincheng
Yin, Yin
Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title_full Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title_fullStr Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title_full_unstemmed Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title_short Classification of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on Radiomic Analysis
title_sort classification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma based on radiomic analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8885247/
https://www.ncbi.nlm.nih.gov/pubmed/35237341
http://dx.doi.org/10.1155/2022/5334095
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