ArticleNeuroinformatics2023
Geometric Reliability of Super-Resolution Reconstructed Images from Clinical Fetal MRI in the Second Trimester.
Article in Neuroinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers, 1 of them a synthesis that pooled it.
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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.
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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.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Fetal brain MRI atlases and datasets: A review.NeuroImage · 2024Pooled it
- What you see is not always what you get-MRI-based ganglionic eminence volumetry challenges subjective assessment in CNS anomalies.European radiology · 2026Article
- MRI-based assessment of fetal brain gyrification: Reliability across two methods.Neuroimage. Reports · 2026Article
- Prenatal Volume in the Bilateral Superior Temporal Gyrus Associates With Children's Expressive Vocabulary at 24-36 Months.Developmental science · 2026Article
- MRI-based spatio-temporal atlas of ganglionic eminence.European radiology experimental · 2026Article
- Advances in automated fetal brain MRI segmentation and biometry: Insights from the FeTA 2024 challenge.Medical image analysis · 2026Article
- Evaluating reliability of automated quantitative brain morphometry from fetal T2-weighted MRI.Frontiers in neuroscience · 2026Article
- Biometry and volumetry in multi-centric fetal brain magnetic resonance imaging: assessing the bias of super-resolution reconstruction.Pediatric radiology · 2025Article
- Assessment of fetal corpus callosum biometry by 3D super-resolution reconstructed T2-weighted magnetic resonance imaging.Frontiers in neurology · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Fetal Magnetic Resonance Imaging (MRI) is an important noninvasive diagnostic tool to characterize the central nervous system (CNS) development, significantly contributing to pregnancy management. In clinical practice, fetal MRI of the brain includes the acquisition of fast anatomical sequences over different planes on which several biometric measurements are manually extracted. Recently, modern toolkits use the acquired two-dimensional (2D) images to reconstruct a Super-Resolution (SR) isotropic volume of the brain, enabling three-dimensional (3D) analysis of the fetal CNS.We analyzed 17 fetal MR exams performed in the second trimester, including orthogonal T2-weighted (T2w) Turbo Spin Echo (TSE) and balanced Fast Field Echo (b-FFE) sequences. For each subject and type of sequence, three distinct high-resolution volumes were reconstructed via NiftyMIC, MIALSRTK, and SVRTK toolkits. Fifteen biometric measurements were assessed both on the acquired 2D images and SR reconstructed volumes, and compared using Passing-Bablok regression, Bland-Altman plot analysis, and statistical tests.Results indicate that NiftyMIC and MIALSRTK provide reliable SR reconstructed volumes, suitable for biometric assessments. NiftyMIC also improves the operator intraclass correlation coefficient on the quantitative biometric measures with respect to the acquired 2D images. In addition, TSE sequences lead to more robust fetal brain reconstructions against intensity artifacts compared to b-FFE sequences, despite the latter exhibiting more defined anatomical details.Our findings strengthen the adoption of automatic toolkits for fetal brain reconstructions to perform biometry evaluations of fetal brain development over common clinical MR at an early pregnancy stage.
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