| 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: 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 |
Gastroenterology & Hepatology |
| Manuscript Type |
Observational Study |
| Article Title |
Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Xiao-Nan Yin, Zi-Hao Wang, Li Zou, Cai-Wei Yang, Chao-Yong Shen, Bai-Ke Liu, Yuan Yin, Xi-Jiao Liu and Bo Zhang |
| ORCID |
|
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China Program Grant |
No. 82203108 |
| China Postdoctoral Science Foundation |
No. 2022M722275 |
| Beijing Bethune Charitable Foundation |
No. WCJZL202105 |
| Beijing Xisike Clinical Oncology Research Foundation |
No. Y-zai2021/zd-0185 |
|
| Corresponding Author |
Xi-Jiao Liu, PhD, Doctor, Doctor, Department of Radiology, West China Hospital, Sichuan University, No. 37 Guoxue Lane, Wuhou District, Chengdu 610041, Sichuan Province, China. bless_jiao@163.com |
| Key Words |
Gastrointestinal stromal tumor; Radiomics; Gene mutation; Computed tomography; Model |
| Core Tip |
In this study, we developed and validated a radiomics model to predict the genotypes of gastric gastrointestinal stromal tumors (GISTs) using contrast-enhanced computed tomography images. Our findings demonstrated that the radiomics model exhibited a satisfactory performance in distinguishing gastric GISTs with KIT exon 11 mutations and GISTs with KIT exon 11 codons 557-558 deletions. Among the different models evaluated, the combined modelCT sign + rad + clinic demonstrated the highest predictive accuracy. This model holds promise as an effective and noninvasive approach to guide personalized treatment decisions prior to surgery. |
| Publish Date |
2024-04-11 02:23 |
| Citation |
Yin XN, Wang ZH, Zou L, Yang CW, Shen CY, Liu BK, Yin Y, Liu XJ, Zhang B. Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor. World J Gastrointest Oncol 2024; 16(4): 1296-1308 |
| URL |
https://www.wjgnet.com/1948-5204/full/v16/i4/1296.htm |
| DOI |
https://dx.doi.org/10.4251/wjgo.v16.i4.1296 |
