Evidence map›Paper›PMID 39966316›Full record

ArticleEuropean radiology experimental2025

Placental quantitative susceptibility mapping and T2* characteristics for predicting birth weight in healthy and high-risk pregnancies.

Morteza Pishghadam, Lylach Haizler-Cohen, Julius S Ngwa, Wu Yao, Kushal Kapse, Sara N Iqbal, Catherine Limperopoulos, Nickie N Andescavage

Abstract read
In one paragraph

Article in European radiology experimental, 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

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

8 authors.

Morteza Pishghadam *Developing Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
Lylach Haizler-Cohen *Division of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, DC, USA.
Julius S NgwaDeveloping Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
Wu YaoDeveloping Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
Kushal KapseDeveloping Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
Sara N IqbalDivision of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, MedStar Washington Hospital Center, Washington, DC, USA.
Catherine LimperopoulosDeveloping Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA.
Nickie N AndescavageDeveloping Brain Institute, Division of Diagnostic Imaging and Radiology, Children's National Hospital, Washington, DC, USA. nniforat@childrensnational.org.ORCID http://orcid.org/0000-0002-6812-7898

Funding

Antecedents of Impaired Brain Development in Fetuses with Heart DiseaseR01HL116585 · NHLBI · CHILDREN'S RESEARCH INSTITUTE · PI LIMPEROPOULOS, CATHERINE · 2013 to 2017
$3.8M
national institute of health NHLBI R01 HL116585-01NHLBI NIH HHS R01 HL116585
6 · The paper itself

Abstract

backgroundThe human placenta is critical in supporting fetal development, and placental dysfunction may compromise maternal-fetal health. Early detection of placental dysfunction remains challenging due to the lack of reliable biomarkers. This study compares placental quantitative susceptibility mapping and T2* values between healthy and high-risk pregnancies and investigates their association with maternal and fetal parameters and their ability to predict birth weight (BW).

methodsA total of 105 pregnant individuals were included: 68 healthy controls and 37 high-risk due to fetal growth restriction (FGR), chronic or gestational hypertension, and pre-eclampsia. Placental magnetic resonance imaging data were collected using a three-dimensional multi-echo radiofrequency-spoiled gradient-echo, and mean susceptibility and T2* values were calculated. To analyze associations and estimate BW, we employed linear regression and regression forest models.

resultsNo significant differences were found in susceptibility between high-risk pregnancies and controls (p = 0.928). T2* values were significantly lower in high-risk pregnancies (p = 0.013), particularly in pre-eclampsia and FGR, emerging as a predictor of BW. The regression forest model showed placental T2* as a promising mode for BW estimation.

conclusionOur findings underscore the potential of mean placental T2* as a more sensitive marker for detecting placental dysfunction in high-risk pregnancies than mean placental susceptibility. Moreover, the high-risk status emerged as a significant predictor of BW. These results call for further research with larger and more diverse populations to validate these findings and enhance prediction models for improved pregnancy management. RELEVANCE STATEMENT: This study highlights the potential of placental T2* magnetic resonance imaging measurements as reliable indicators for detecting placental dysfunction in high-risk pregnancies, aiding in improved prenatal care and birth weight prediction. KEY POINTS: Placental dysfunction in high-risk pregnancies is evaluated using MRI T2* values. Lower T2* values significantly correlate with pre-eclampsia and fetal growth restriction. T2* MRI may predict birth weight, enhancing prenatal care outcomes.

Indexed as

Birth WeightMagnetic Resonance ImagingPlacentaPregnancy, High-RiskAdultCase-Control StudiesFemaleFetal Growth RetardationHumansInfant, NewbornPre-EclampsiaPregnancyBirth weightFetal growth retardationMagnetic resonance imagingPlacentaPregnancy (high-risk)

Identifiers

PMID39966316
PMCPMC11836258

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.