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One diffusion acquisition and different white matter models: How does microstructure change in human early development based on WMTI and NODDI?
Open accessAbstract
White matter microstructural changes during the first three years of healthy brain development are characterized using two different models developed for limited clinical diffusion data: White Matter Tract Integrity (WMTI) metrics from Diffusional Kurtosis Imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI). Both models reveal a non-linear increase in intra-axonal water fraction and in tortuosity of the extra-axonal space as a function of age, in the genu and splenium of the corpus callosum and the posterior limb of the internal capsule. The changes are consistent with expected behavior related to myelination and asynchrony of fiber development. The intra- and extracellular axial diffusivities as estimated with WMTI do not change appreciably in normal brain development. The quantitative differences in parameter estimates between models are examined and explained in the light of each model's assumptions and consequent biases, as highlighted in simulations. Finally, we discuss the feasibility of a model with fewer assumptions.
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“The pathology changes at different MS stages may also be attributed to the decoupling between intra-axonal and extra-axonal diffusivity, which may also affect the calculated NODDI metrics and need substantial investigation in further studies (Jelescu et al. 2015; Jelescu et al. 2016).”
From Neurite orientation dispersion and density imaging of mouse brain microstructure (2019) · cites this paper as Jelescu et al. 2015
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“In contrast, ODI in WM remains almost stable during the first two decades of life (Genc et al., 2017;Jelescu et al., 2015;Lynch et al., 2020;Mah et al., 2017).”
From NODDI in clinical research (2020) · cites this paper as Jelescu et al., 2015
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“The pathology changes at different MS stages may also be attributed to the decoupling between intra-axonal and extra-axonal diffusivity, which may also affect the calculated NODDI metrics and need substantial investigation in further studies (Jelescu et al. 2015; Jelescu et al. 2016).”
From Neurite orientation dispersion and density imaging of mouse brain microstructure (2019) · cites this paper as Jelescu et al. 2015
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“When applied to clinical studies, the use of different constraints sometimes yields results that agree in their relative trends (Huber et al., 2019;Jelescu et al., 2015;Kamiya et al., 2017), but such agreement is not always guaranteed and is not proof of validity.”
From NODDI in clinical research (2020) · cites this paper as Jelescu et al., 2015
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“In WM, NDI has a positive correlation with age, but the increase is non-linear and more rapid during early life (Dean et al., 2016;Jelescu et al., 2015;Lynch et al., 2020) (Fig. 9B).”
From NODDI in clinical research (2020) · cites this paper as Jelescu et al., 2015
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Cited by
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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
The development of brain white matter microstructure
Lebel, C., & Deoni, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.097 · Cited by 602
Quantifying brain microstructure with diffusion MRI: Theory and parameter estimation
Novikov, D. S., Fieremans, E., Jespersen, S. N., & Kiselev, V. G. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3998 · Cited by 581
Self-citationImaging brain microstructure with diffusion MRI: practicality and applications
Alexander, D. C., Dyrby, T. B., Nilsson, M., & Zhang, H. G. (2017) · NMR in Biomedicine · doi:10.1002/nbm.3841 · Cited by 456
Novikov, D. S., Kiselev, V. G., & Jespersen, S. N. (2018) · Magnetic Resonance in Medicine · doi:10.1002/mrm.27101 · Cited by 362
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Metadata
- Authors
- Jelescu, I. O., Veraart, J., Adisetiyo, V., Milla, S. S., Novikov, D. S., & Fieremans, E.
- Affiliations
- NYU Langone Health (US)
- Corresponding author
- Jelescu, Ileana O.
- ORCID
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2015-02
- Volume
- 107
- Pages
- 242-256
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC4300243
- OpenAlex
- W2005552408
- Cited by
- 202
- References
- 45
- Citations by year
- 2026: 2 · 2025: 13 · 2024: 11 · 2023: 13 · 2022: 14 · 2021: 18 · 2020: 27 · 2019: 21 · 2018: 29 · 2017: 27 · 2016: 15 · 2015: 12
- FWCI
- 14.08
- 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)
- Funders
- National Institutes of Health (R01-NS088040, R21-NS081230)
- Raymond and Beverly Sackler Laboratories for Convergence of Physical, Engineering, and Biomedical Sciences
- Alzheimer Drug Discovery Foundation
- Belgian Science Policy Office (P7/11)
- King Baudouin Foundation
- Belgian American Educational Foundation
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- white matter microstructure, early brain development, white matter tract integrity, NODDI, diffusion kurtosis imaging, corpus callosum, internal capsule, myelination, axial diffusivity, model bias, parameter estimation
- MeSH terms
- Aging, Axons, Computer Simulation, Corpus Callosum, Female, Humans, Infant, Infant, Newborn, Male, Models, Neurological, Myelin Sheath, Nerve Fibers, Myelinated, Neurites, Internal Capsule, Diffusion Magnetic Resonance Imaging, White Matter
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