ArticleBMC medical imaging2020
Association of gestational age with MRI-based biometrics of brain development in fetuses.
Article in BMC medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 24 citations in OpenAlex.
- MRI-based assessment of fetal brain gyrification: Reliability across two methods.Neuroimage. Reports · 2026Article
- An end-to-end pipeline for automated fetal brain segmentation and biometry from 3D SSFP MRI.Frontiers in neuroscience · 2026Article
- Late gestation MRI to assess maternal pelvimetry, fetal biometry and placental oxygenation: a retrospective pilot study.BMC pregnancy and childbirth · 2025Article
- Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imaging.Frontiers in neurology · 2024Article
- Automatic biometry of fetal brain MRIs using deep and machine learning techniques.Scientific reports · 2023Article
- Automatic Localization of the Pons and Vermis on Fetal Brain MR Imaging Using a U-Net Deep Learning Model.AJNR. American journal of neuroradiology · 2023Article
- Effect of magnet strength on fetal brain biometry - a single-center retrospective MRI-based cohort study.Neuroradiology · 2023Article
- Automatic Ventriculomegaly Detection in Fetal Brain MRI: A Step-by-Step Deep Learning Model for Novel 2D-3D Linear Measurements.Diagnostics (Basel, Switzerland) · 2023Article
- Attention-guided deep learning for gestational age prediction using fetal brain MRI.Scientific reports · 2022Article
- Reference biometry of foetal brain by prenatal MRI and the distribution of measurements in foetuses with ventricular septal defect.Annals of medicine · 2021Article
- Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study.Frontiers in pediatrics · 2021Article
- Systematic review and meta-analysis of MRI-based sex differences in the human fetal brain.Imaging neuroscience (Cambridge, Mass.)Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundReported date of last menstrual period and ultrasonography measurements are the most commonly used methods for determining gestational age in antenatal life. However, the mother cannot always determine the last menstrual period with certainty, and ultrasonography measurements are accurate only in the first trimester. We aimed to assess the ability of various biometric measurements on magnetic resonance imaging (MRI) in determining the accurate gestational age of an individual fetus in the second half of gestation.
methodsWe used MRI to scan a total of 637 fetuses ranging in age from 22 to 40 gestational weeks. We evaluated 9 standard fetal 2D biometric parameters, and regression models were fitted to assess normal fetal brain development. A stepwise linear regression model was constructed to predict gestational age, and measurement accuracy was determined in a held-out, unseen test sample (n = 49).
resultsA second-order polynomial regression model was found to be the best descriptor of biometric measures including brain bi-parietal diameter, head circumference, and fronto-occipital diameter in relation to normal fetal growth. Normal fetuses showed divergent growth patterns for the cerebrum and cerebellum, where the cerebrum undergoes rapid growth in the second trimester, while the cerebellum undergoes rapid growth in the third trimester. Moreover, a linear model based on biometrics of brain bi-parietal diameter, length of the corpus callosum, vermis area, transverse cerebellar diameter, and cerebellar area accurately predicted gestational age in the second and third trimesters (cross-validation R
conclusionsThese results support the use of MRI biometry charts to improve MRI evaluation of fetal growth and suggest that MRI biometry measurements offer a potential estimation model of fetal gestational age in the second half of gestation, which is vital to any assessment of pregnancy, fetal development, and neonatal care.
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