Evidence map›Paper›PMID 40321262›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Automated cervix biometry, volumetry and normative models for 3D motion-corrected T2-weighted 0.55-3T fetal MRI during 2nd and 3rd trimesters.

Alena U Uus, Agnieszka Glazewska-Hallin, Simi Bansal, Megan Hall, Charline Bradshaw, Jordina Aviles Verdera, Mary A Rutherford, Jana Hutter, Lisa Story

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Alena U UusBiomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Agnieszka Glazewska-HallinResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Simi BansalResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Megan HallResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Charline BradshawResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Jordina Aviles VerderaBiomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Mary A RutherfordResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Jana HutterBiomedical Computing Department, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
Lisa StoryResearch Department of Early Life Imaging,School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.

Funding

Structure and function of the placenta from implantation to delivery: a next generation MRI approachU01HD087202 · NICHD · KING'S COLLEGE LONDON · PI ALEXANDER, DANIEL, ALJABAR, PAUL · 2015 to 2015
$3.2M
NICHD NIH HHS U01 HD087202Wellcome Trust
6 · The paper itself

Abstract

Fetal MRI provides superior tissue contrast and true 3D spatial information however there is only a limited number of number of MRI studies investigating cervix during pregnancy. Furthermore, there are no clearly formalised protocols or automated methods for MRI cervical measurements. This work introduces the first deep learning pipeline for automated multi-layer segmentation and biometry for 3D T2w images of the pregnant cervix. Evaluation on 20 datasets from 0.55T and 3T acquisitions showed good performance in comparison to manual measurements. This solution could potentially minimise the need for manual editing, significantly reduce analysis time and address inter- and intra-observer bias. Next, we used the pipeline to process 270 normal term cases from 16 to 40 weeks gestational age (GA) range. The inlet diameter and length showed the strongest correlation with GA which is in agreement with the gradual remodeling and softening of the cervix prior to birth. We also generated 3D population-averaged atlases of the cervix that are publicly available online.

Identifiers

PMID40321262
PMCPMC12047906

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.