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Articles in Press
9/11/2026 9:20:00 AM | Browse: 40 | Download: 5
| Category |
Radiology, Nuclear Medicine & Medical Imaging |
| Manuscript Type |
Retrospective Cohort Study |
| Article Title |
Artificial intelligence-driven body composition atlas for predicting clinical outcomes after transarterial chemoembolization in hepatocellular carcinoma: A multicenter study
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Yi Li, Jie Lou, Xiao-Na Fu, Yu-Sheng Guo, Shan-Shan Jiang, Qiu-Ping Liu, Kai Zhao, Ji-Jun Wu, Yu-Yang Wang, Yan-Jie Yang, Li-Xia Wang, Guo-Feng Zhou and Lian Yang |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Key Project of Hubei Provincial Natural Science Foundation |
No. 2023BCB014 |
| National Natural Science Foundation of China |
No. 82172034 and No. 82472058 |
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| Corresponding Author |
Lian Yang, Professor, Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1277 Jiefang Avenue, Wuhan 430022, Hubei Province, China. yanglian@hust.edu.cn |
| Key Words |
Hepatocellular carcinoma; Artificial intelligence; Transarterial chemoembolization; Body composition; Computed tomography |
| Core Tip |
This study developed an artificial intelligence-driven multidimensional body composition atlas for hepatocellular carcinoma patients undergoing transarterial chemoembolization. Automated multilevel computed tomography analysis identified skeletal muscle and visceral fat parameters that were independently associated with overall survival in male patients, whereas body mass index showed no consistent prognostic association. Exploratory histopathological and transcriptomic analyses suggested potential links between skeletal muscle status, tumor-inflammatory cell spatial features, immune-related pathways, and hypoxia-related biological programs, supporting the potential value of artificial intelligence-based body composition assessment for risk stratification. |
| Citation |
Li Y, Lou J, Fu XN, Guo YS, Jiang SS, Liu QP, Zhao K, Wu JJ, Wang YY, Yang YJ, Wang LX, Zhou GF, Yang L. Artificial intelligence-driven body composition atlas for predicting clinical outcomes after transarterial chemoembolization in hepatocellular carcinoma: A multicenter study. World J Gastroenterol 2026; In press
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| PDF |
123932-in-press.pdf
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Received |
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2026-06-03 06:46 |
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Peer-Review Started |
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2026-06-03 06:46 |
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First Decision by Editorial Office Director |
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Return for Revision |
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2026-07-02 10:04 |
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Revised |
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2026-07-14 14:54 |
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Publication Fee Transferred |
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2026-07-28 08:42 |
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Second Decision by Editor |
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2026-09-11 02:52 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-09-11 09:20 |
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Articles in Press |
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2026-09-11 09:20 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
