Perspectives in transvaginal sonography for the diagnosis of adenomyosis

Adenomyosis is a common gynecological condition affecting women of reproductive age, posing significant diagnostic challenges due to its diverse clinical presentations. This extended opinion study critically reviews the diagnostic methods for adenomyosis, with a focus on transvaginal sonography (TVS), a widely used non-invasive imaging technique. The study evaluates the effectiveness, limitations, and clinical applicability of TVS, while exploring the role of histopathological confirmation when non-invasive methods are insufficient. Advancements in TVS, including three-dimensional ultrasound and color Doppler, have enhanced diagnostic precision, particularly in assessing uterine morphology and blood flow. Additionally, artificial intelligence integration offers potential to further optimize diagnostic accuracy and efficiency. While histopathological examination remains the gold standard, its use is often impractical in patients who do not undergo hysterectomy. This study provides a comprehensive overview of the current status of TVS in diagnosing adenomyosis, analyzing its accuracy, strengths, and limitations across diverse patient populations. Results suggest that TVS is a reliable diagnostic tool, though its accuracy improves when combined with magnetic resonance imaging, especially in complex cases. Ongoing research is needed to refine TVS capabilities and identify non-invasive alternatives to histopathological confirmation, improving accessibility and diagnostic efficiency.

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Publication Details

Journal
Frontiers in Medicine
Published
2025-06-19
DOI
https://doi.org/10.3389/fmed.2025.1533648
Citations
3
Primary Topic
Endometriosis Research and Treatment
Type
article
Field-Weighted Citation Impact
5.09
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article

Perspectives in transvaginal sonography for the diagnosis of adenomyosis

Xu Yun, Xiaohua Yang, Meimei Liu, Xin An et al.
3 citations
Frontiers in Medicine
Endometriosis Research and Treatment
5.09
article

Perspectives in transvaginal sonography for the diagnosis of adenomyosis

Xu Yun, Xiaohua Yang, Meimei Liu, Xin An, Xiaohui Lei, Jun Zhang, Jian Zhao
article en
3 citations

Abstract

Adenomyosis is a common gynecological condition affecting women of reproductive age, posing significant diagnostic challenges due to its diverse clinical presentations. This extended opinion study critically reviews the diagnostic methods for adenomyosis, with a focus on transvaginal sonography (TVS), a widely used non-invasive imaging technique. The study evaluates the effectiveness, limitations, and clinical applicability of TVS, while exploring the role of histopathological confirmation when non-invasive methods are insufficient. Advancements in TVS, including three-dimensional ultrasound and color Doppler, have enhanced diagnostic precision, particularly in assessing uterine morphology and blood flow. Additionally, artificial intelligence integration offers potential to further optimize diagnostic accuracy and efficiency. While histopathological examination remains the gold standard, its use is often impractical in patients who do not undergo hysterectomy. This study provides a comprehensive overview of the current status of TVS in diagnosing adenomyosis, analyzing its accuracy, strengths, and limitations across diverse patient populations. Results suggest that TVS is a reliable diagnostic tool, though its accuracy improves when combined with magnetic resonance imaging, especially in complex cases. Ongoing research is needed to refine TVS capabilities and identify non-invasive alternatives to histopathological confirmation, improving accessibility and diagnostic efficiency.

Frontiers in MedicineVol. 12
Northwest Women's and Children's Hospital (CN), Xiamen Chang Gung Hospital (CN), Xi'an Chest Hospital (CN)
Good health and well-being
Openalex Percentile: Top 5%
Endometriosis Research and Treatment
5.09
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Perspectives in transvaginal sonography for the diagnosis of adenomyosis — Xu Yun, Xiaohua Yang, et al. · Frontiers in Medicine (2025) | TGRS Research Map | TGRS