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 diagnosis of endometrial cancer. World J Radiol 2025; 17(9): 111493 [PMID: 41025054 DOI: 10.4329/wjr.v17.i9.111493]
Corresponding Author of This Article
Mohamad Tlais, MD, Department of Radiology, University of Balamand, Dekweneh, Beirut 0000, Lebanon. mmtlaiss22@gmail.com
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Systematic Reviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/
World J Radiol. Sep 28, 2025; 17(9): 111493 Published online Sep 28, 2025. doi: 10.4329/wjr.v17.i9.111493
Advances in ultrasound-based imaging for diagnosis of endometrial cancer
Mohamad Tlais, Hussein Hamze, Ali Hteit, Karim Haddad, Issam El Fassih, Issa Zalzali, Sally Mahmoud, Sabine Karaki, Diana Jabbour
Mohamad Tlais, Hussein Hamze, Ali Hteit, Karim Haddad, Issam El Fassih, Sally Mahmoud, Sabine Karaki, Department of Radiology, University of Balamand, Beirut 0000, Lebanon
Issa Zalzali, Department of Internal Medicine, Faculty of Medicine, Beirut Arab University, Beirut 0000, Lebanon
Diana Jabbour, Department of Radiology, Lebanese University, Beirut 0000, Lebanon
Author contributions: Tlais M and Hamze H contributed to the conception and design of the manuscript; Hteit A, Haddad K, and Mahmoud S conducted the literature review; El Fassih I and Karaki S provided critical revisions and guidance on the ultrasound imaging sections; Zalzali I and Jabbour D contributed to the radiological interpretation and contextual relevance of clinical applications; all authors participated in drafting and revising the manuscript, and approved the final version.
Conflict-of-interest statement: The authors declare that there is no conflict of interest related to this manuscript.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
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/
Corresponding author: Mohamad Tlais, MD, Department of Radiology, University of Balamand, Dekweneh, Beirut 0000, Lebanon. mmtlaiss22@gmail.com
Received: July 1, 2025 Revised: July 28, 2025 Accepted: August 20, 2025 Published online: September 28, 2025 Processing time: 87 Days and 18.2 Hours
Abstract
BACKGROUND
Endometrial cancer (EC) is the most common gynecological malignancy in high-income countries, with incidence rates rising globally. Early and accurate diagnosis is essential for improving outcomes. Transvaginal ultrasound (TVUS) remains a cost-effective first-line tool, and emerging techniques such as three-dimensional (3D) ultrasound (US), contrast-enhanced US (CEUS), elastography, and artificial intelligence (AI)-enhanced imaging may further improve diagnostic performance.
AIM
To systematically review recent advances in US-based imaging techniques for the diagnosis and staging of EC, and to compare their performance with magnetic resonance imaging (MRI).
METHODS
A systematic search of PubMed, Scopus, Web of Science, and Google Scholar was performed to identify studies published between January 2010 and March 2025. Eligible studies evaluated TVUS, 3D-US, CEUS, elastography, or AI-enhanced US in EC diagnosis and staging. Methodological quality was assessed using the QUADAS-2 tool. Sensitivity, specificity, and area under the curve (AUC) were extracted where available, with narrative synthesis due to heterogeneity.
RESULTS
Forty-one studies met the inclusion criteria. TVUS demonstrated high sensitivity (76%–96%) but moderate specificity (61%–86%), while MRI achieved higher specificity (84%–95%) and superior staging accuracy. 3D-US yielded accuracy comparable to MRI in selected early-stage cases. CEUS and elastography enhanced tissue characterization, and AI-enhanced US achieved pooled AUCs up to 0.91 for risk prediction and lesion segmentation. Variability in performance was noted across modalities due to patient demographics, equipment differences, and operator experience.
CONCLUSION
TVUS remains a highly sensitive initial screening tool, with MRI preferred for definitive staging. 3D-US, CEUS, elastography, and AI-enhanced techniques show promise as complementary or alternative approaches, particularly in low-resource settings. Standardization, multicenter validation, and integration of multi-modal imaging are needed to optimize diagnostic pathways for EC.
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.
