| ISSN |
1949-8470 (online) |
| 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/ |
| Copyright |
The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved. |
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For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Radiology, Nuclear Medicine & Medical Imaging |
| Manuscript Type |
Retrospective Study |
| Article Title |
Developing and validating a computed tomography radiomics strategy to predict lymph node metastasis in pancreatic cancer
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Shuai Ren, Bin Qin, Marcus J Daniels, Liang Zeng, Ying Tian and Zhong-Qiu Wang |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China (General Program) |
82202135, 82371919, 82372017, 82171925 |
| China Postdoctoral Science Foundation |
2023M741808 |
| Young Elite Scientists Sponsorship Program by China Association of Chinese Medicine |
2024-QNRC2-B16 |
| Young Elite Scientists Sponsorship Program by Jiangsu Association for Science and Technology |
JSTJ-2023-WJ027 |
| Foundation of Excellent Young Doctor of Jiangsu Province Hospital of Chinese Medicine |
2023QB0112 |
| Project funded by Nanjing Postdoctoral Science Foundation, Natural Science Foundation of Nanjing University of Chinese Medicine |
XZR2023036 |
| Jiangsu Provincial Key research and development program |
BE2023789 |
|
| Corresponding Author |
Zhong-Qiu Wang, Deputy Director, Head, MD, Professor, Department of Radiology, Jiangsu Province Hospital of Chinese Medicine, The Affiliated Hospital of Nanjing University of Chinese Medicine, Zhongqiu Wang, Department of Radiology, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, China.
Email: <email>zhongqiuwang@njucm.edu.cn</email>, Nanjing 210029, Jiangsu Province, China. zhongqiuwang@njucm.edu.cn |
| Key Words |
Computed tomography; Radiomics; Lymph node metastasis; Pancreatic cancer; Model construction |
| Core Tip |
A preoperative computed tomography (CT)-based radiomics model demonstrates high accuracy in predicting lymph node metastasis (LNM) in pancreatic cancer (PC), providing a non-invasive tool to guide personalized treatment. LNM significantly impacts prognosis (5-year survival: < 10% with LNM vs 40% without) and therapeutic decisions (e.g., surgery vs neoadjuvant therapy). Conventional CT, based on size and morphology, often misses subtle metastases. This study extracted 792 quantitative features from arterial and venous-phase CT scans of 168 PC patients. Using machine learning (Minimum Redundancy Maximum Relevance and Least Absolute Shrinkage and Selection Operator), 15 key features were identified, resulting in a Radscore model with an area under the curve of 0.86–0.94, sensitivity up to 91.7%, and 100% specificity in validation. 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 NAC for high-risk patients, optimizing outcomes. Prospective validation is needed for broader adoption. |
| Publish Date |
2025-08-28 08:34 |
| Citation |
<p>Ren S, Qin B, Daniels MJ, Zeng L, Tian Y, Wang ZQ. Developing and validating a computed tomography radiomics strategy to predict lymph node metastasis in pancreatic cancer. <i>World J Radiol</i> 2025; 17(8): 109373</p> |
| URL |
https://www.wjgnet.com/1949-8470/full/v17/i8/109373.htm |
| DOI |
https://dx.doi.org/10.4329/wjr.v17.i8.109373 |
