Evidence map›Paper›PMID 42226136›Full record

ArticleBMC gastroenterology2026

Combining preoperative clinical and ultrasound radiomic features to predict the predominant component of combined hepatocellular carcinoma-cholangiocarcinoma.

Yuanping Yang, Weiming Liang, Jinshu Pang, Xiumei Bai, Rong Wen, Yuquan Wu, Jinbo Peng, Hong Yang, Yun He, Ruizhi Gao

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In one paragraph

Article in BMC gastroenterology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Yuanping Yang *Department of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Weiming Liang *School of Basic Medical Sciences, Guangxi Medical University, 22 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, China.
Jinshu PangDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Xiumei BaiDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Rong WenDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Yuquan WuDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Jinbo PengDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Hong YangDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China.
Yun HeDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China. heyun@stu.gxmu.edu.cn.
Ruizhi GaoDepartment of Medical Ultrasound, First Affiliated Hospital of Guangxi Medical University, 6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, China. 767785114@qq.com.

Funding

Guangxi Medical University Undergraduate Innovation and Entrepreneurship Training Program 202410598008the Clinical Research Climbing Project of The First Affiliated Hospital of Guangxi Medical University No.YYZS2020024
6 · The paper itself

Abstract

backgroundAs a rare subtype of primary liver cancer that contains both hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA) components, combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) is characterized by strong invasiveness and poor prognosis. The proportion of HCC and CCA components is closely related to the prognosis of patients. This study aimed to develop a combined model integrating preoperative ultrasound radiomic features and clinical data to non-invasively predict the predominant component in cHCC-CCA.

methodsThe study included 60 histopathologically confirmed cHCC-CCA patients, divided into high hepatocellular carcinoma percentage (HCC%) group (n = 33, HCC% > 50) and low HCC% group (n = 27, HCC% ≤ 50). A predominant component prediction model for cHCC-CCA was developed using radiomic features extracted from four distinct region of interest (ROI) to identify the optimal radiomic model: tumor alone (ROI

resultsThe model developed based on ROI

conclusionsCombination of ultrasound-based radiomics with tumor maximum diameter and total bilirubin levels holds significant value for the preoperative identification of HCC% in cHCC-CCA.

Indexed as

Bile Duct NeoplasmsCarcinoma, HepatocellularCholangiocarcinomaLiver NeoplasmsAgedFemaleHumansMaleMiddle AgedPredictive Value of TestsRadiomicsRetrospective StudiesUltrasonographyCombined hepatocellular carcinoma–cholangiocarcinomaPredominant componentRadiomicsUltrasound

Identifiers

PMID42226136
PMCPMC13435421

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