| 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. |
| 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 |
Systematic Reviews |
| Article Title |
Advances in ultrasound-based imaging for the diagnosis of endometrial cancer
|
| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Mohamad Tlais, Hussein Hamze, Ali Hteit, Karim Haddad, Issam El Fassih, Issa Zalzali, Sally Mahmoud, Sabine Karaki and Diana Jabbour |
| ORCID |
|
| Funding Agency and Grant Number |
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| Corresponding Author |
Mohamad Tlais, MD, Department of Radiology, University of Balamand, Dekweneh, Beirut 0000, Lebanon. mmtlaiss22@gmail.com |
| Key Words |
Endometrial cancer; Transvaginal ultrasound; Three-dimensional ultrasound; Contrast-enhanced ultrasound; Elastography; Artificial intelligence |
| Core Tip |
This study provides a comprehensive review of evolving ultrasound (US)-based imaging techniques in the diagnosis of endometrial cancer (EC), emphasizing their clinical and technological advancements. It highlights the integration of three-dimensional US, contrast-enhanced US, elastography, and artificial intelligence (AI) to improve diagnostic precision, staging accuracy, and patient stratification. By comparing these modalities with magnetic resonance imaging and incorporating radiomics-based models, the review demonstrates how US, particularly when AI-enhanced, offers a cost-effective, accessible, and accurate alternative for early EC detection and management in diverse clinical settings. |
| Publish Date |
2025-09-26 10:05 |
| Citation |
<p>Tlais M, Hamze H, Hteit A, Haddad K, El Fassih I, Zalzali I, Mahmoud S, Karaki S, Jabbour D. Advances in ultrasound-based imaging for the diagnosis of endometrial cancer. <i>World J Radiol</i> 2025; 17(9): 111493</p> |
| URL |
https://www.wjgnet.com/1949-8470/full/v17/i9/111493.htm |
| DOI |
https://dx.doi.org/10.4329/wjr.v17.i9.111493 |
