ReviewDevelopmental cognitive neuroscience2018
Processing of structural neuroimaging data in young children: Bridging the gap between current practice and state-of-the-art methods.
Review in Developmental cognitive neuroscience, 2018. 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 35 papers.
What it found
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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
35 citing papers in PubMed.
- Feasibility of Non-Sedate Magnetic Resonance Imaging for Children with Cerebral Palsy: Tolerance and Structural Analysis Considerations.Children (Basel, Switzerland) · 2026Article
- Agreement between FreeSurfer and CAT12 Cortical Thickness Measurements: A Discovery and a Replication Study in Children/Adolescents.Brain topography · 2026Article
- Observational
- The Development of Lateralized Brain Oscillations in Infants: Lessons From Autism.Developmental psychobiology · 2025Article
- A FastSurfer Database for Age-Specific Brain Volumes in Healthy Children: A Tool for Quantifying Localized and Global Brain Volume Alterations in Pediatric Patients.Brain and behavior · 2025Article
- Skull stripping tools in pediatric T2-weighted MRI scans: a retrospective evaluation of segmentation performance.Frontiers in neuroscience · 2025Article
- Article
- Quantification of myelination in children with attention-deficit/hyperactivity disorder: a comparative assessment with synthetic MRI and DTI.European child & adolescent psychiatry · 2024Article
- A deep learning model for brain segmentation across pediatric and adult populations.Scientific reports · 2024Article
- Deep learning-based, fully automated, pediatric brain segmentation.Scientific reports · 2024Article
- Structural brain correlates of non-verbal cognitive ability in 5-year-old children: Findings from the FinnBrain birth cohort study.Human brain mapping · 2023Article
- Greater maltreatment severity is associated with smaller brain volume with implication for intellectual ability in young children.Neurobiology of stress · 2023Article
- EEG functional connectivity analysis in the source space.Developmental cognitive neuroscience · 2022Article
- A diffeomorphic aging model for adult human brain from cross-sectional data.Scientific reports · 2022Article
- An Age-Specific Atlas for Delineation of White Matter Pathways in Children Aged 6-8 Years.Brain connectivity · 2022Article
- Clinical adaptation of synthetic MRI-based whole brain volume segmentation in children at 3 T: comparison with modified SPM segmentation methods.Neuroradiology · 2022Article
- Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors.Neuro-oncology · 2022Article
- Feasibility of FreeSurfer Processing for T1-Weighted Brain Images of 5-Year-Olds: Semiautomated Protocol of FinnBrain Neuroimaging Lab.Frontiers in neuroscience · 2022Article
- Structural brain dynamics across reading development: A longitudinal MRI study from kindergarten to grade 5.Human brain mapping · 2021Article
- How to capture developmental brain dynamics: gaps and solutions.NPJ science of learning · 2021Article
Corrections and comments
- Erratum issuedErratum.2020
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The structure of the brain is subject to very rapid developmental changes during early childhood. Pediatric studies based on Magnetic Resonance Imaging (MRI) over this age range have recently become more frequent, with the advantage of providing in vivo and non-invasive high-resolution images of the developing brain, toward understanding typical and atypical trajectories. However, it has also been demonstrated that application of currently standard MRI processing methods that have been developed with datasets from adults may not be appropriate for use with pediatric datasets. In this review, we examine the approaches currently used in MRI studies involving young children, including an overview of the rationale for new MRI processing methods that have been designed specifically for pediatric investigations. These methods are mainly related to the use of age-specific or 4D brain atlases, improved methods for quantifying and optimizing image quality, and provision for registration of developmental data obtained with longitudinal designs. The overall goal is to raise awareness of the existence of these methods and the possibilities for implementing them in developmental neuroimaging studies.
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Registered trials
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.