| ISSN |
1948-5204 (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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
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| Permissions |
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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 |
Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma
|
| Manuscript Source |
Invited Manuscript |
| All Author List |
Shuai Ren, Li-Chao Qian, Ying-Ying Cao, Marcus J Daniels, Li-Na Song, Ying Tian and Zhong-Qiu Wang |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science foundation of China |
82202135, 82371919, 82372017, 82171925 |
| China Postdoctoral Science Foundation |
2023M741808 |
| 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 |
| Nanjing Postdoctoral Science Foundation, Natural Science Foundation of Nanjing University of Chinese Medicine |
XZR2023036, XZR2021050 |
| Medical Imaging Artificial Intelligence Special Research Fund Project, Nanjing Medical Association Radiology Branch, Project of National Clinical Research Base of Traditional Chinese Medicine in Jiangsu Province, China |
JD2023SZ16 |
|
| Corresponding Author |
Zhong-Qiu Wang, MD, PhD, Deputy Director, 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. zhongqiuwang0815@163.com |
| Key Words |
Pancreatic ductal adenocarcinoma; Radiomics; Computed tomography; American Joint Committee on Cancer staging |
| Core Tip |
Pancreatic ductal adenocarcinoma (PDAC) remains the deadliest of the common cancers, with little change in patient survival in the past several decades. One of the biggest challenges of the management of PDAC that physicians often encounter is that the early detection in high-risk individuals and the early diagnosis of patients with suspected symptoms. Precise staging of PDAC is vital not only in making treatment decisions, but also in evaluating prognosis. Radiomics, the generation of minable high throughput data through conversion of digital computed tomography (CT) or magnetic resonance imaging, allows obtaining additional insight into pancreatic tissue heterogeneity. The aim of our study was to investigate a radiomics approach for potential differentiation of early- from late-stage PDAC. In conclusion, our study demonstrated that the radiomics model based on CT could serve as a promising non-invasive method in differential diagnosis between early and late stage PDAC. Large-scale prospective cohort studies, preferably multi-center, to validate the potential value of the radiomics diagnostic approach in differentiating early from late stage PDAC are in order. |
| Publish Date |
2024-04-11 02:23 |
| Citation |
Ren S, Qian LC, Cao YY, Daniels MJ, Song LN, Tian Y, Wang ZQ. Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma. World J Gastrointest Oncol 2024; 16(4): 1256-1267 |
| URL |
https://www.wjgnet.com/1948-5204/full/v16/i4/1256.ht |
| DOI |
https://dx.doi.org/10.4251/wjgo.v16.i4.1256 |
