Evidence map›Paper›PMID 41091155›Full record

ArticleInternational urogynecology journal2026

3D MRI Biomarkers for Predicting Pelvic Organ Prolapse Risk and Severity.

Huijun Bai, Lifan Shen, Xueyu Sun, Jiaxin Fu, Ping Liu, Chunlin Chen

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PubMed Full text at PMC Publisher
In one paragraph

Article in International urogynecology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Huijun BaiNanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Lifan ShenNanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Xueyu SunNanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Jiaxin FuNanfang Hospital, Southern Medical University, Guangzhou, 510515, China.
Ping LiuNanfang Hospital, Southern Medical University, Guangzhou, 510515, China. lpivy@126.com.
Chunlin ChenNanfang Hospital, Southern Medical University, Guangzhou, 510515, China. jieru@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo identify 3D MRI-derived biomarkers of the cardinal ligament (CL) and uterosacral ligament (USL) for pelvic organ prolapse (POP) risk and stress urinary incontinence (SUI), and to evaluate their correlations with prolapse severity.

methodsFemale patients undergoing pelvic MRI at *** Hospital (2021-2023) were grouped into POP and control cohorts. MRI data underwent 3D reconstruction (Mimics software) and modeling (Geomagic/Solidworks) to precisely measure ligament parameters.

resultsWomen with POP had longer postmenopausal intervals, and higher parity but similar age, Body Mass Index (BMI), Lean Body Mass (LBM) and Body Surface Area (BSA). CL volume, surface area, mass, and maximal thickness were significantly reduced in POP (all

conclusion3D MRI quantification of CL metrics (volume, area, mass) offers noninvasive biomarkers for POP and SUI risk prediction, unlike USL morphology. These markers improve pelvic floor failure understanding and enable early POP risk identification.

Indexed as

Imaging, Three-DimensionalLigamentsMagnetic Resonance ImagingPelvic Organ ProlapseUrinary Incontinence, StressAgedBiomarkersCase-Control StudiesFemaleHumansMiddle AgedPredictive Value of TestsRisk AssessmentSeverity of Illness IndexBiomarkers3D MRI morphometryCardinal ligamentImaging biomarkersPelvic organ prolapseUterosacral ligament

Identifiers

PMID41091155
PMCPMC13033027

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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 OpenQuestion graph.