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Articles Published Processes
6/18/2024 9:29:50 AM | Browse: 95 | Download: 520
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Received |
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2024-03-04 07:44 |
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Peer-Review Started |
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2024-03-04 07:44 |
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To Make the First Decision |
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Return for Revision |
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2024-04-13 02:42 |
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Revised |
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2024-04-17 13:12 |
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Second Decision |
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2024-04-23 02:48 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2024-04-23 08:49 |
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Articles in Press |
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2024-04-23 08:49 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2024-05-31 12:24 |
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Publish the Manuscript Online |
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2024-06-18 09:29 |
| ISSN |
2307-8960 (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) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
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 Cohort Study |
| Article Title |
Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Qing-Long Guan, Hai-Xiao Zhang, Jun-Peng Gu, Geng-Fei Cao and Wei-Xin Ren |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Wei-Xin Ren, MD, Chief Physician, Doctor, Doctor, Postdoc, Postdoctoral Fellow, Department of Interventional Radiology, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi 830011, Xinjiang Uygur Autonomous Region, China. rwx__1031@163.com |
| Key Words |
Magnetic resonance imaging; Radiomics; Deep learning; Progression-free survival; Transcatheter arterial chemoembolization; Hepatocellular carcinoma |
| Core Tip |
In this study, traditional radiomics and deep learning (DL) were used to model HCC in order to reflect the heterogeneity of tumors through voxel changes in images. The main purpose of this method is to extract the regions of interest features of the three-phase images of enhanced magnetic resonance imaging obtained before transarterial chemoembolization (TACE), construct the prediction model and nomogram through feature screening and least absolute shrinkage and selection operator regression, to construct a prediction model and nomogram to evaluate the clinical value of DL radiomics omics feature model and to predict progression-free survival after TACE. |
| Publish Date |
2024-06-18 09:29 |
| Citation |
<p>Guan QL, Zhang HX, Gu JP, Cao GF, Ren WX. Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization. <i>World J Clin Cases</i> 2024; 12(18): 3340-3350</p> |
| URL |
https://www.wjgnet.com/2307-8960/full/v12/i18/3340.htm |
| DOI |
https://dx.doi.org/10.12998/wjcc.v12.i18.3340 |
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