Evidence map›Paper›PMID 42591258›Full record

ArticleFrontiers in physiology2026

Quantitative assessment of fetal lung development using MRI-based radiomics: a comparative analysis of 3D and 2D approaches with external validation.

Yaoxi Jiang, Pan Xiao, Song Peng, Weidong Fang

Abstract read
In one paragraph

Article in Frontiers in physiology, 2026. 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

4 authors.

Yaoxi Jiang *Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Pan Xiao *Department of Oncology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Song PengDepartment of Radiology, Chongqing Health Center for Women and Children, Women and Children's Hospital of Chongqing Medical University, Chongqing, China.
Weidong FangDepartment of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Fetal lung development is a critical determinant of neonatal health. This study aimed to externally validate and compare the performance of 3D versus 2D MRI radiomics models in quantifying fetal lung development. Gestational age estimation was utilized as a quantitative surrogate marker for this assessment in a large multi-institutional cohort with an independent test set. Methods: To compare 2D versus 3D radiomics, we analyzed 292 fetal MRI scans using T2-weighted coronal images. The cohort comprised an original dataset (n=252) and an independent test set (n=40) from two institutions, with gestational ages ranging from 28 to 38 Results: Features extracted from 3D ROIs exhibited superior performance for gestational age estimation, achieving Pearson correlation coefficients (r) of 0.904 (SVR) and 0.902 (PLSR) in the original dataset, and 0.846 (SVR) and 0.861 (PLSR) in the independent test set. In contrast, 2D ROI-based models showed significantly lower accuracy. The median ICCs for the correspondence between 2D and 3D radiomic measurements were 0.379 (IQR: 0.179-0.554; range: 0.010-0.880) in the original dataset and 0.247 (IQR: 0.060-0.384; range: -0.024-0.721) in the test set. Conclusion: This study demonstrates that 3D MRI radiomics features outperform 2D features for gestational age estimation, serving as a quantitative surrogate for fetal lung development. These findings underscore the clinical potential of 3D radiomics in non-invasive prenatal assessment. Future studies incorporating larger cohorts and standardized imaging protocols are encouraged to further enhance the model's robustness and clinical utility.

Indexed as

external validationfetal lung developmentmagnetic resonance imagingprenatal diagnosisradiomics

Identifiers

PMID42591258
PMCPMC13461516

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.