Qi X, Zhao FY. Value of radiomics models in precision diagnosis of dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma. World J Radiol 2025; 17(11): 114193 [DOI: 10.4329/wjr.v17.i11.114193]
Corresponding Author of This Article
Fei-Yu Zhao, PhD, Department of Radiation Oncology, The Fifth Medical Center of Chinese PLA General Hospital, No. 8 East Main Street, Fengtai District, Beijing 100071, China. 1029279130@qq.com
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Radiology, Nuclear Medicine & Medical Imaging
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Letter to the Editor
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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. See: http://creativecommons.org/licenses/by-nc/4.0/
Nov 28, 2025 (publication date) through Nov 27, 2025
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World Journal of Radiology
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1949-8470
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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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Qi X, Zhao FY. Value of radiomics models in precision diagnosis of dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma. World J Radiol 2025; 17(11): 114193 [DOI: 10.4329/wjr.v17.i11.114193]
World J Radiol. Nov 28, 2025; 17(11): 114193 Published online Nov 28, 2025. doi: 10.4329/wjr.v17.i11.114193
Value of radiomics models in precision diagnosis of dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma
Xu Qi, Fei-Yu Zhao
Xu Qi, Department of Radiology, Peking Union Medical College Hospital, Beijing 100730, China
Fei-Yu Zhao, Department of Radiation Oncology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing 100071, China
Author contributions: Qi X and Zhao FY contributed to manuscript writing, provided ideas for the draft, and revised the article.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Fei-Yu Zhao, PhD, Department of Radiation Oncology, The Fifth Medical Center of Chinese PLA General Hospital, No. 8 East Main Street, Fengtai District, Beijing 100071, China. 1029279130@qq.com
Received: September 17, 2025 Revised: October 3, 2025 Accepted: November 4, 2025 Published online: November 28, 2025 Processing time: 75 Days and 0.3 Hours
Abstract
In the clinical diagnosis and treatment of liver tumors, the differential diagnosis between dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma has long been a challenging problem for clinicians. These two types of tumors not only exhibit overlapping pathological features but also have significantly different treatment strategies and prognoses. Misdiagnosis can directly affect patients' quality of life. Recently, a study published by Zhang et al has brought groundbreaking insights into this dilemma. Radiomics technology has demonstrated remarkable value in the differential diagnosis of these two diseases, opening up a new path for the precise diagnosis and treatment of liver tumors.
Core Tip: A recent study published by Zhang et al focuses on exploring the practical value of radiomics in ahcieving the differential diagnosis between dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Its constructed combined model, with an area under the receiver operating characteristic curve of 0.892, can effectively boost diagnostic accuracy and provide significant assistance to less-experienced radiologists in clinical practice. However, the study still faces limitations of single-center data and small sample size, and future research thus needs to carry out multi-center studies and promote multi-omics fusion to address these issues.
