The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.
Atlas-based analysis of neurodevelopment from infancy to adulthood using diffusion tensor imaging and applications for automated abnormality detection
Open accessAbstract
Quantification of normal brain maturation is a crucial step in understanding developmental abnormalities in brain anatomy and function. The aim of this study was to develop atlas-based tools for time-dependent quantitative image analysis, and to characterize the anatomical changes that occur from 2years of age to adulthood. We used large deformation diffeomorphic metric mapping to register diffusion tensor images of normal participants into the common coordinates and used a pre-segmented atlas to segment the entire brain into 176 structures. Both voxel- and atlas-based analyses reported a structure that showed distinctive changes in terms of its volume and diffusivity measures. In the white matter, fractional anisotropy (FA) linearly increased with age in logarithmic scale, while diffusivity indices, such as apparent diffusion coefficient (ADC), and axial and radial diffusivity, decreased at a different rate in several regions. The average, variability, and the time course of each measured parameter are incorporated into the atlas, which can be used for automated detection of developmental abnormalities. As a demonstration of future application studies, the brainstem anatomy of cerebral palsy patients was evaluated and the altered anatomy was delineated.
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“Diffusion values change much more gradually through later childhood and adolescence, with AD and RD decreasing and FA increasing. 34,35”
From Imaging structural and functional brain development in early childhood (2018) · cites this paper as [34]
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“Thus, differentiation of cognitive control networks is obtained through maturation of major white matter (WM) tracts, which is measurable by diffusion tensor imaging (DTI) (23–27), and therefore, gradually, an adult organization of cognitive control and self-regulation emerges.”
From Multimodal imaging of the self-regulating developing brain (2012) · cites this paper as [23]
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“This cortical “loss” has been described often (Gogtay et al., 2004;Shaw et al., 2008;Sowell et al., 2003), but the cortex shrinking while WM expands may indicate not only changes in volume (cortical shrink may be driven, at least in part, by a component of synaptic pruning, glial and vascular changes, and cell shrinka…”
BackgroundInfluentialBrain development during childhood and adolescence: a longitudinal MRI study
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A Voxel-Based Morphometric Study of Ageing in 465 Normal Adult Human Brains
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Diffusion tensor imaging of the brain
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Jones, D. K., Knösche, T. R., & Turner, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.06.081 · Cited by 2,402
Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood
Lebel, C., & Beaulieu, C. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5302-10.2011 · Cited by 1,193
Imaging structural and functional brain development in early childhood
Gilmore, J. H., Knickmeyer, R. C., & Gao, W. (2018) · Nature Reviews Neuroscience · doi:10.1038/nrn.2018.1 · Cited by 1,013
Dubois, J., Dehaene-Lambertz, G., Kulikova, S., Poupon, C., Hüppi, P. S., & Hertz-Pannier, L. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2013.12.044 · Cited by 851
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Cui, Z., Zhong, S., Xu, P., Yong He, A., & Gong, G. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00042 · Cited by 767
Metadata
- Authors
- Faria, A. V., Zhang, J., Oishi, K., Li, X., Jiang, H., Akhter, K., Hermoye, L., Lee, S.-K., Hoon, A., & Stashinko, E.
- Affiliations
- Johns Hopkins University (US)
- Kennedy Krieger Institute (US)
- UCLouvain (BE)
- Yonsei University (KR)
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2010-08-15
- Volume
- 52
- Issue
- 2
- Pages
- 415-428
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2886186
- OpenAlex
- W2025108982
- Cited by
- 180
- References
- 91
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 5 · 2023: 7 · 2022: 6 · 2021: 8 · 2020: 6 · 2019: 8 · 2018: 5 · 2017: 18 · 2016: 11 · 2015: 15 · 2014: 16 · 2013: 32 · 2012: 15
- FWCI
- 15.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
- Funders
- Johns Hopkins University
- National Institute on Aging (R01AG020012, AG 20012)
- National Institute of Neurological Disorders and Stroke (R01NS058299, F05NS059230)
- National Institute of Biomedical Imaging and Bioengineering (P41EB015909)
- National Center for Research Resources (RR 015241, P41RR015241, P41RR005959)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- brain maturation, brain development, diffusion tensor imaging, brain atlas, longitudinal brain development, fractional anisotropy, apparent diffusion coefficient, white matter maturation, brainstem anatomy, cerebral palsy, brain structure segmentation
- MeSH terms
- Adolescent, Adult, Atlases as Topic, Automation, Brain, Child, Child, Preschool, Diagnosis, Computer-Assisted, Diffusion, Female, Humans, Image Processing, Computer-Assisted, Male, Nerve Fibers, Myelinated, Organ Size, Time Factors, Linear Models, Anisotropy, Young Adult, Diffusion Tensor Imaging
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