The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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
The cited source says what the claim attributes to it.
In the citing paper
“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
The cited source says what the claim attributes to it.
In the citing paper
“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
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Regression and time series model selection in small samples
HURVICH, C. M., & TSAI, C.-L. (1989) · Biometrika · doi:10.1093/biomet/76.2.297 · Cited by 6,586
The basis of anisotropic water diffusion in the nervous system—A technical review.
Beaulieu, C. (2002) · NMR in Biomedicine · doi:10.1002/nbm.782 · Cited by 4,628
Basser, P. J., & Pierpaoli, C. (1996) · Journal of Magnetic Resonance, Series B · doi:10.1006/jmrb.1996.0086 · Cited by 4,306
NODDI: Practical in vivo neurite orientation dispersion and density imaging of the human brain
Zhang, H., Schneider, T., Wheeler-Kingshott, C. A., & Alexander, D. C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.072 · Cited by 3,288
Characterization and propagation of uncertainty in diffusion-weighted MR imaging
Behrens, T. E. J., Woolrich, M. W., Jenkinson, M., Johansen‐Berg, H., Nunes, R. G., Clare, S., Matthews, P. M., Brady, J. M., & Smith, S. M. (2003) · Magnetic Resonance in Medicine · doi:10.1002/mrm.10609 · Cited by 3,038
Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H., & Kaczynski, K. (2005) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20508 · Cited by 2,488
Regional Development of the Brain in Early Life
(1968) · Archives of Disease in Childhood · doi:10.1136/adc.43.229.388 · Cited by 2,107
Wyatt, J. S., Delpy, D. T., Cope, M., Wray, S., & Reynolds, E. O. R. (1986) · The Lancet · doi:10.1016/s0140-6736(86)90467-8 · Cited by 875
Composite hindered and restricted model of diffusion (CHARMED) MR imaging of the human brain
Assaf, Y., & Basser, P. J. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.03.042 · Cited by 856
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
Axcaliber: A method for measuring axon diameter distribution from diffusion MRI
Assaf, Y., Blumenfeld‐Katzir, T., Yovel, Y., & Basser, P. J. (2008) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21577 · Cited by 849
Orientationally invariant indices of axon diameter and density from diffusion MRI
Alexander, D. C., Hubbard, P. L., Hall, M. G., Moore, E. A., Ptito, M., Parker, G. J. M., & Dyrby, T. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.05.043 · Cited by 683
The development of cerebral connections during the first 20–45 weeks’ gestation
Kostović, I., & Milošević, N. J. (2006) · Seminars in Fetal and Neonatal Medicine · doi:10.1016/j.siny.2006.07.001 · Cited by 568
White matter characterization with diffusional kurtosis imaging
Fieremans, E., Jensen, J. H., & Helpern, J. A. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.06.006 · Cited by 561
Self-citationTheoretical Model for Water Diffusion in Tissues
Szafer, A., Zhong, J., & Gore, J. C. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910330516 · Cited by 522
Benveniste, H., Hedlund, L. W., & Johnson, G. A. (1992) · Stroke · doi:10.1161/01.str.23.5.746 · Cited by 509
Veraart, J., Sijbers, J., Sunaert, S. G., Leemans, A., & Jeurissen, B. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.028 · Cited by 505
Self-citationAn analytical model of restricted diffusion in bovine optic nerve
Stanisz, G. J., Wright, G. A., Henkelman, R. M., & Szafer, A. (1997) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910370115 · Cited by 501
NUCLEAR MAGNETIC RESONANCE IMAGING OF THE BRAIN IN MULTIPLE SCLEROSIS
YOUNG, I. R., Hall, A. S., Pallis, C., Bydder, G. M., Legg, N. J., & Steiner, R. E. (1981) · The Lancet · doi:10.1016/s0140-6736(81)91273-3 · Cited by 471
Applications of diffusion‐weighted and diffusion tensor MRI to white matter diseases – a review
Horsfield, M. A., & Jones, D. K. (2002) · NMR in Biomedicine · doi:10.1002/nbm.787 · Cited by 468
Mukherjee, P., Miller, J. H., Shimony, J. S., Philip, J. V., Nehra, D., Snyder, A. Z., Conturo, T. E., Neil, J. J., & McKinstry, R. C. (2002) · PubMed Central · Cited by 445
Cytological and quantitative characteristics of four cerebral commissures in the rhesus monkey
LaMantia, A., & RAKIC, P. T. (1990) · The Journal of Comparative Neurology · doi:10.1002/cne.902910404 · Cited by 428
Hermoye, L., Saint‐Martin, C., Cosnard, G., Lee, S., Kim, J., Nassogne, M., Menten, R., Clapuyt, P. R. M., Donohue, P., Hua, K., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.08.017 · Cited by 422
Lu, H., Jensen, J. H., Ramani, A., & Helpern, J. A. (2006) · NMR in Biomedicine · doi:10.1002/nbm.1020 · Cited by 420
Modeling dendrite density from magnetic resonance diffusion measurements
Jespersen, S., Kroenke, C., Østergaard, L., Ackerman, J., & Yablonskiy, D. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.037 · Cited by 358
MRI of normal brain maturation.
Holland, B. A., Haas, D. K., Norman, D. M., Brant-Zawadzki, M. N., & Newton, T. H. (1986) · PubMed Central · Cited by 334
Dubois, J., Hertz‐Pannier, L., Dehaene‐Lambertz, G., Cointepas, Y., & Bihan, D. L. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.11.022 · Cited by 333
Jespersen, S. N., Bjarkam, C. R., Nyengaard, J. R., Chakravarty, M. M., Hansen, B., Vosegaard, T., Østergaard, L., Yablonskiy, D., Nielsen, N. C., & Vestergaard-Poulsen, P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.08.053 · Cited by 290
Duong, T. Q., Ackerman, J. J. H., Ying, H. S.-C., & Neil, J. J. (1998) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910400102 · Cited by 239
Monte Carlo study of a two‐compartment exchange model of diffusion
Fieremans, E., Novikov, D. S., Jensen, J. H., & Helpern, J. A. (2010) · NMR in Biomedicine · doi:10.1002/nbm.1577 · Cited by 234
Self-citationStroke Assessment With Diffusional Kurtosis Imaging
Hui, E. S. K., Fieremans, E., Jensen, J. H., Tabesh, A., Feng, W., Bonilha, L., Spampinato, M. V., Adams, R. J., & Helpern, J. A. (2012) · Stroke · doi:10.1161/strokeaha.112.657742 · Cited by 232
Self-citationOn the nature of the NAA diffusion attenuated MR signal in the central nervous system
Kroenke, C. D., Ackerman, J. J. H., & Yablonskiy, D. A. (2004) · Magnetic Resonance in Medicine · doi:10.1002/mrm.20260 · Cited by 170
Kunz, N., Zhang, H. G., Vasung, L., O’Brien, K., Assaf, Y., Lazeyras, F., Alexander, D. C., & Hüppi, P. S. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.057 · Cited by 160
Novel White Matter Tract Integrity Metrics Sensitive to Alzheimer Disease Progression
Fieremans, E., Benitez, A. M., Jensen, J. H., Falangola, M. F., Tabesh, A., Deardorff, R. L., Spampinato, M. V., Babb, J. S., Novikov, D. S., Ferris, S. H., et al. (2013) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3553 · Cited by 147
Self-citationStaining and embedding the whole mouse brain for electron microscopy
Mikula, S., Binding, J., & Denk, W. T. (2012) · Nature Methods · doi:10.1038/nmeth.2213 · Cited by 144
Benitez, A. M., Fieremans, E., Jensen, J. H., Falangola, M. F., Tabesh, A., Ferris, S. H., & Helpern, J. A. (2013) · NeuroImage Clinical · doi:10.1016/j.nicl.2013.11.001 · Cited by 134
Self-citationSimulation and experimental verification of the diffusion in an anisotropic fiber phantom
Fieremans, E., Deene, Y. D., Delputte, S., Ozdemir, M., D’Asseler, Y., Vlassenbroeck, J., Deblaere, K., Achten, E., & Lemahieu, I. A. (2007) · Journal of Magnetic Resonance · doi:10.1016/j.jmr.2007.10.014 · Cited by 132
Self-citationIs the “biexponential diffusion” biexponential?
Kiselev, V. G., & Il'yasov, K. A. (2007) · Magnetic Resonance in Medicine · doi:10.1002/mrm.21164 · Cited by 128
Ronen, I., Budde, M. D., Ercan, E., Annese, J., Techawiboonwong, A., & WEBB, A. G. (2013) · Brain Structure and Function · doi:10.1007/s00429-013-0600-0 · Cited by 96
Falangola, M. F., Guilfoyle, D. N., Tabesh, A., Hui, E. S., Nie, X., Jensen, J. H., Gerum, S. V., Hu, C., LaFrancois, J., Collins, H. R., et al. (2014) · NMR in Biomedicine · doi:10.1002/nbm.3140 · Cited by 96
Comprehensive framework for accurate diffusion MRI parameter estimation
Veraart, J., Rajan, J., Peeters, R. R., Leemans, A., Sunaert, S. G., & Sijbers, J. (2012) · Magnetic Resonance in Medicine · doi:10.1002/mrm.24529 · Cited by 95
Self-citationDiffusional kurtosis imaging of the developing brain
Paydar, A., Fieremans, E., Nwankwo, J. I., Lazar, M., Sheth, H. D., Adisetiyo, V., Helpern, J. A., Jensen, J. H., & Milla, S. S. (2014) · American Journal of Neuroradiology · doi:10.3174/ajnr.a3764 · Cited by 91
Self-citationColby, J. B., Horn, J. D. V., & Sowell, E. R. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.08.014 · Cited by 82
Motion correction and registration of high b‐value diffusion weighted images
Ben-Amitay, S., Jones, D. K., & Assaf, Y. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.23186 · Cited by 70
Ferizi, U., Schneider, T., Tariq, M., Wheeler‐Kingshott, C. A. M. G., Zhang, H. G., & Alexander, D. C. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-40811-3_10 · Cited by 17
Cited by
Sorted by citations
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
Self-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review