Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Jun 28, 2025; 17(6): 108247
Published online Jun 28, 2025. doi: 10.4329/wjr.v17.i6.108247
Clinical value and applicability of radiomics in differential diagnosis of dual-phenotype hepatocellular carcinoma and intrahepatic cholangiocarcinoma
Chen-Cai Zhang, Da Lu, Jun Yang, Ling Zhang, Xia-Feng Zeng, Xiang-Ming Fang, Cun-Geng Fan
Chen-Cai Zhang, Xiang-Ming Fang, Department of Radiology, The Affiliated Wuxi People’s Hospital of Nanjing Medical University, Wuxi Medical Center Nanjing Medical University, Wuxi People’s Hospital, Wuxi 214000, Jiangsu Province, China
Da Lu, China Railway Guangzhou Engineering Group Company Limited, Guangzhou 510515, Guangdong Province, China
Jun Yang, Department of Radiology, The Tenth Affiliated Hospital of Southern Medical University (Dongguan People’s Hospital), Dongguan 523003, Guangdong Province, China
Ling Zhang, Xia-Feng Zeng, Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou 510515, Guangdong Province, China
Cun-Geng Fan, Department of Medical Imaging Center, Ganzhou People's Hosptial, Ganzhou, 341000, Jiangxi Province, China
Co-first authors: Chen-Cai Zhang and Da Lu.
Co-corresponding authors: Xiang-Ming Fang and Cun-Geng Fan.
Author contributions: Zhang CC, Fang XM, and Fan CG performed concept learning and research design; Lu D, Zhang CC, and Zhang L performed data collection; Zhang CC, Fan CG, and Fang XM performed data analysis and interpretation; Zhang CC and Lu D drafted the manuscript; Yang J, Lu D, and Zeng XF conducted the statistical analysis; Zhang L, Fan CG, Fang XM, and Lu D critically revised the manuscript for important intellectual content; Lu D carried out material support; Yang J, Zeng XF, and Fang XM gave study guidance. There are two reasons for appointing Zhang CC and Lu D as co-first authors. First, Zhang CC and Lu D made equal substantial efforts throughout the research process and played an equally important role in the completion of the paper. Second, this study was completed collaboratively by experts in different fields, and the appointment of co-authors can reflect this characteristic. Therefore, we believe that it is reasonable to designate Zhang CC and Lu D as co-first authors. Fang XM and Fan CG played an equally important role in the early research design and subsequent revision of the paper, so they were appointed as co-corresponding authors of the article. All authors have read and approved the final manuscript.
Institutional review board statement: The study was reviewed and approved by the Nanfang Hospital of Southern Medical University Institutional Review Board.
Informed consent statement: This was a retrospective study approved by the Ethics Committee of Nanfang Hospital of Southern Medical University. Because the data were analyzed retrospectively and anonymously, the need to obtain informed consent from the patients was waived.
Conflict-of-interest statement: The authors declare that there are no financial interests, commercial affiliations, or other potential conflicts of interest that could have influenced the objectivity of this research.
Data sharing statement: The software used in this paper is publicly available at http://www.itksnap.org.
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: Cun-Geng Fan, Medical Imaging Center, Ganzhou People’s Hospital, Meiguan, Ganzhou 341000, Jiangxi Province, China. 3832472809@qq.com
Received: April 9, 2025
Revised: April 19, 2025
Accepted: May 26, 2025
Published online: June 28, 2025
Processing time: 78 Days and 23.6 Hours
Abstract
BACKGROUND

Dual-phenotype hepatocellular carcinoma (HCC) is a relatively new subtype of HCC. Studies have shown that in the context of chronic hepatitis, liver cirrhosis, and other liver conditions, some intrahepatic cholangiocarcinomas (ICCs) exhibit an enhancement pattern similar to that of HCC. Both dual-phenotype HCC (DPHCC) and ICC can express biliary markers, making imaging and pathology differentiation difficult. Currently, radiomics is widely used in the differentiation, clinical staging, and prognosis assessment of various diseases. Radiomics can effectively differentiate DPHCC and ICC preoperatively.

AIM

To evaluate the value of radiomics in the differential diagnosis of DPHCC and ICC and to validate its clinical applicability

METHODS

In this retrospective study, the data of 53 DPHCC patients and 124 ICC patients were collected retrospectively and randomly divided into training and testing sets at a ratio of 7: 3. After delineation of regions of interest and feature extraction and selection, radiomics models were constructed. Receiver operating characteristic curve analysis was conducted to calculate the area under the curve (AUC) for each model. The AUC values of radiologists with and without assistance from the model were also assessed.

RESULTS

In the training set, the AUC value of the radiomic model was the highest, and the combined model and the radiomic model had similar AUC (P > 0.05); the differences in the AUC values between the combined model and the clinical-sign model was statistically significant (P < 0.05). In the testing set, the AUC value of the combined model was the highest, and the differences in the AUC values between the combined model and the clinical-sign model was statistically significant (P < 0.05). With model assistance, the AUC values of Doctor D (10 years of experience in abdominal imaging diagnosis) and Doctor E (5 years of experience in abdominal imaging diagnosis) both increased.

CONCLUSION

Radiomics can differentiate DPHCC and ICC, and with assistance from the developed model, the accuracy of less experienced doctors in the differential diagnosis of these two diseases can be improved.

Keywords: Dual-phenotype hepatocellular carcinoma; Intrahepatic cholangiocarcinoma; Computer-aided diagnosis; Radiomics; Machine learning

Core Tip: In the present study, the clinical and imaging data of 53 dual-phenotype hepatocellular carcinoma (DPHCC) patients and 124 intrahepatic cholangiocarcinoma (ICC) patients were collected, the regions of interest were delineated slice by slice, and relevant information was extracted to construct a clinical-sign model, a radiomic model, and a combined model. Subsequently, the performance of the predictive models was evaluated to explore their clinical applicability. The study found that radiomics can effectively differentiate DPHCC and ICC preoperatively, and with assistance from the developed model, the accuracy of less experienced doctors in the differential diagnosis of these two diseases can be improved.