Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Aug 28, 2025; 17(8): 109373
Published online Aug 28, 2025. doi: 10.4329/wjr.v17.i8.109373
Developing and validating a computed tomography radiomics strategy to predict lymph node metastasis in pancreatic cancer
Shuai Ren, Bin Qin, Marcus J Daniels, Liang Zeng, Ying Tian, Zhong-Qiu Wang
Shuai Ren, Bin Qin, Liang Zeng, Ying Tian, Zhong-Qiu Wang, Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, Jiangsu Province, China
Marcus J Daniels, Department of Radiology, NYU Langone Health, New York, NY 10016, United States
Author contributions: Ren S, Qin B, and Wang ZQ designed the research study; Ren S, Tian Y, and Zeng L performed the research; Ren S, Qin B, and Zeng L analyzed the data. Ren S wrote the manuscript; Daniels MJ and Wang ZQ revised the manuscript; all authors read and approved the final manuscript.
Supported by National Natural Science foundation of China, No. 82202135, No. 82371919, No. 82372017, and No. 82171925; China Postdoctoral Science Foundation, No. 2023M741808; Young Elite Scientists Sponsorship Program by China Association of Chinese Medicine, No. 2024-QNRC2-B16; Jiangsu Provincial Key Research and Development Program, No. BE2023789; Young Elite Scientists Sponsorship Program by Jiangsu Association for Science and Technology, No. JSTJ-2023-WJ027; Project funded by Nanjing Postdoctoral Science Foundation, Natural Science Foundation of Nanjing University of Chinese Medicine, No. XZR2023036; and Foundation of Excellent Young Doctor of Jiangsu Province Hospital of Chinese Medicine, No. 2023QB0112.
Institutional review board statement: The study was reviewed and approved by the Ethics Committee of Affiliated Hospital of Nanjing University of Chinese Medicine.
Informed consent statement: Informed consent statement was waived due to the retrospective nature of the study.
Conflict-of-interest statement: All the authors report having no relevant conflicts of interest for this article.
Data sharing statement: Patient imaging data contain sensitive patient information and cannot be released publicly due to the legal and ethical restrictions imposed by the institutional ethics committee. Data is available upon reasonable request from the following e-mail address: zhongqiuwang@njucm.edu.cn.
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: Zhong-Qiu Wang, MD, Deputy Director, Head, Professor, Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, No. 155 Hanzhong Road, Nanjing 210029, Jiangsu Province, China. zhongqiuwang@njucm.edu.cn
Received: May 12, 2025
Revised: May 21, 2025
Accepted: July 22, 2025
Published online: August 28, 2025
Processing time: 112 Days and 0.9 Hours
Core Tip

Core Tip: A preoperative computed tomography-based radiomics model demonstrates high accuracy in predicting lymph node metastasis (LNM) in pancreatic cancer, providing a non-invasive tool to guide personalized treatment. Unlike traditional imaging, radiomics detects microstructural patterns invisible to the human eye, enhancing LNM detection irrespective of phase (arterial vs portal). Clinically, this model could refine preoperative staging, identify candidates for curative surgery, or prioritize neoadjuvant chemotherapy for high-risk patients, optimizing outcomes. Prospective validation is needed for broader adoption.