Evidence map›Paper›PMID 42707680›Full record

ArticleTheranostics2026

Mapping endometrial vascular functional gradients using depth-derived ultrasound localization microscopy (D-ULM) for early stratification of postinjury fibrotic remodeling and therapeutic guidance.

Xiaowen Liang, Le Gao, Zhili Guo, Meng Du, Yue Pan, Yixiang Lian, Yu Qiang, Haijun Luo, Ying Zhang, Xiaoyan Kui and 3 more

Abstract read
In one paragraph

Article in Theranostics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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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

13 authors.

Xiaowen LiangSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Le GaoUniversity of Chinese Academy of Sciences, Beijing, 101408, China.
Zhili GuoKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.
Meng DuKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.
Yue PanShenzhen key laboratory of ultrasound imaging and therapy, State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Yixiang LianDepartment of Pathology, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.
Yu QiangShenzhen key laboratory of ultrasound imaging and therapy, State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Haijun LuoDepartment of Pathology, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.
Ying ZhangKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.
Xiaoyan KuiSchool of Computer Science and Engineering, Central South University, Changsha, 410083, China.
Hairong ZhengShenzhen key laboratory of ultrasound imaging and therapy, State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Weibao QiuShenzhen key laboratory of ultrasound imaging and therapy, State Key Laboratory of Biomedical Imaging Science and System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Zhiyi ChenKey Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, 410004, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale: Endometrial injury exhibits significant clinical heterogeneity in fibrotic outcomes. Recovery of microvascular perfusion is central to prognosis, while the depth of injury is an important factor influencing regenerative capacity. However, current clinical imaging techniques are limited by diffraction, resulting in insufficient resolution to reliably depict depth-dependent microvascular architecture of the endometrium, with consequent difficulty in evaluating injury depth or in making early prognostic distinctions. Methods: A depth-derived ultrasound localization microscopy (D-ULM) approach is introduced to capture depth-dependent microvascular features in the endometrium. First, we established a normal depth reference band from healthy rats to provide a physiological baseline for identifying pathological vascular changes. Next, in an endometrial injury rat model, we applied unsupervised clustering of early D-ULM features to identify microcirculation phenotypes. Subsequently, we evaluated the correlation between D-ULM features, D-ULM clusters, and late-stage fibrosis area as well as immunofluorescence markers of hypoxia and inflammation, with a view to tying early microvascular changes to eventual recovery or to fibrotic remodeling. Results: In healthy rats, depth-profile curves revealed a distinct transition zone between the deep and superficial layers, enabling the delineation of a quantifiable functional boundary of the endometrial microvasculature. Based on this depth-dependent layering, normal reference intervals were established for the seven D-ULM features. Among these, the reference interval for the vascular distribution center (com_depth_vessel) was 0.371-0.481. In injured cohort, unsupervised hierarchical clustering of day-3 D-ULM features identified three phenotypes: regenerative (Reg), inflammatory hyperperfusion (IH), and irreversible destruction (ID). The day-14 fibrosis area differed significantly among the phenotypes ( Conclusions: D-ULM enables depth-resolved imaging of endometrial microvascular functional gradients in a noninvasive manner. This approach provides an imaging framework for early stratification of injury phenotypes, and may guide personalized preventive strategies for patients at risk of postinjury fibrosis.

Indexed as

EndometriumMicroscopy, AcousticAnimalsDisease Models, AnimalFemaleFibrosisMicrocirculationMicrovesselsRatsRats, Sprague-DawleyUltrasonographydepth-derived featureendometrial injuryhierarchical clusteringmicrovasculatureultrasound localization microscopy

Identifiers

PMID42707680
PMCPMC13549232

What Socratic holds

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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.