One diffusion acquisition and different white matter models: How does microstructure change in human early development based on WMTI and NODDI?
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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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Pathology changes at different MS stages may be attributed to decoupling between intra-axonal and extra-axonal diffusivity.
“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
Theory §§2.2–2.3 say NODDI fixes intra- and extra-axonal diffusivities to the same value, although they may vary with pathology; §2.2 also warns that this assumption can bias NODDI parameters. The paper studies normal early development, not different stages of multiple sclerosis, and does not show that a diffusivity difference accounts for pathology changes across those stages. Page numbers were not available in our copy. (LLM, conf=0.85)
Experimental — accuracy not yet measuredODI in WM remains almost stable during the first two decades of life.
“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
The Results (§4.1) state that NODDI showed no trend in orientation dispersion with age across the three white-matter regions studied. However, the subjects were aged only 1 day to 2 years and 9 months (§3.1.1), so this paper does not establish stability throughout the first two decades of life. (LLM, conf=0.88)
Experimental — accuracy not yet measuredDecoupling between intra-axonal and extra-axonal diffusivity may affect calculated NODDI metrics.
“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
When applied to clinical studies, use of different constraints sometimes yields results that agree in relative trends, but such agreement is not always guaranteed and is not proof of validity.
“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
In WM, NDI has a positive correlation with age, but the increase is non-linear and more rapid during early life.
“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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“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.”
BackgroundMethodInfluentialDelineation of early brain development from fetuses to infants with diffusion MRI and beyond
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- 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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