Evidence map›Paper›PMID 41209275›Full record

ArticleQuantitative imaging in medicine and surgery2025

Microvascular flow imaging for detection of endometrial malignancy: comparison with color Doppler imaging.

Ying Wang, Man Zhang, Junyan Cao, Manli Wu, Changyan Liang, Xin Lin, Huiyu Huang, Ying Chen, Shuangyu Wu, Minhong Zou and 5 more

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Ying Wang *Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Man Zhang *Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Junyan Cao *Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Manli WuDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Changyan LiangDepartment of Gynecology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xin LinDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Huiyu HuangDepartment of Gynecology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Ying ChenDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Shuangyu WuDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Minhong ZouDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Qiaoyuan WangDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Zhijuan ZhengDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yongjiang MaoDepartment of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Yu Zhang *Department of Gynecology, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
Xinling Zhang *Department of Ultrasound, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.ORCID https://orcid.org/0000-0002-7021-3533

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Comprehensive sonographic evaluation of pre- and postmenopausal women with abnormal uterine bleeding is essential for accurate diagnosis and the optimization of curative outcomes for endometrial malignancy. Microvascular flow imaging (MVFI), a state-of-the-art Doppler technique, enables high-resolution, noninvasive mapping of tumor-specific neovascularity that critically drives the initiation, growth, and progression of endometrial malignancy. This study aimed to compare the diagnostic performance of MVFI with that of conventional color Doppler imaging (CDI) for detecting endometrial malignancy using histopathology as the reference standard. Methods: From June 2023 to October 2024, 283 females with abnormal uterine bleeding over the age of 40 years were enrolled in this prospective single-center study. Transvaginal grayscale ultrasound imaging was performed with a HERA W10 system (Samsung Medison Co., Ltd.), with standardized documentation of endometrial features. Endometrial vascularity was subsequently evaluated through tandem CDI and MVFI assessments. Two senior radiologists independently assessed endometrial vascularity using International Endometrial Tumor Analysis (IETA) consensus criteria with a 4-point scale. Intra- and interobserver agreement were evaluated through sequential and reversed-order interpretations. All imaging results were validated against histopathological outcomes as the reference standard. Diagnostic performance was evaluated for (I) MVFI and CDI individually and for (II) integrated models combining vascular detection techniques with grayscale features for endometrial malignancy detection. Results: With histological outcomes used as the reference standards, there were 32 malignant and 251 nonmalignant endometrial specimens. MVFI yielded significantly higher vascular scores than did CDI (median score: 2 Conclusions: MVFI demonstrated significantly higher diagnostic performance than did CDI for the detection of endometrial malignancy; MVFI is thus a promising adjunctive technique for precisely diagnosing endometrial malignancy in females with abnormal uterine bleeding.

Indexed as

color Doppler imaging (CDI)diagnosisendometrial malignancyMicrovascular flow imaging (MVFI)ultrasonography

Identifiers

PMID41209275
PMCPMC12591921

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.