The DOI matches its Crossref record.
Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging.
Abstract
PURPOSE: To establish quantitative standards for the directionally averaged water apparent diffusion coefficient (D) and quantitative diffusion anisotropy (A sigma) of normal brains in newborns by using diffusion tensor magnetic resonance (MR) imaging. MATERIALS AND METHODS: Diffusion tensor MR imaging was performed during the first 36 hours of life in 22 newborns (gestational age range, 31-41 weeks). Values of D and A sigma were measured in regions of interest chosen in the cortical gray matter, centrum semiovale, caudate nuclei, lentiform nuclei, thalami, internal capsules, and cerebellar hemispheres. RESULTS: The D values in the gray and white matter in newborns are considerably higher than those in adults. There is a striking correlation between gestational age and D, with D decreasing as gestational age increases. The A sigma values in the white matter in newborns are lower than those in adults. Values of A sigma show statistically significant correlations with gestational age only in the white matter of the centrum semiovale, in which A sigma values increase sharply near term. CONCLUSION: The D values primarily reflect overall brain water content. The A sigma values are more sensitive to tissue microstructure (e.g., white matter packing and myelination). The D and A sigma images reveal information and not apparent on T1- and T2-weighted images.
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.
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
Cited by
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
Diffusion tensor imaging: Concepts and applications
Le Bihan, D., Mangin, J., Poupon, C., Clark, C. A., Pappata, S., Molko, N., & Chabriat, H. (2001) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.1076 · Cited by 3,547
Diffusion tensor imaging of the brain
Alexander, A. L., Lee, J. E., Lazar, M., & Field, A. S. (2007) · Neurotherapeutics · doi:10.1016/j.nurt.2007.05.011 · Cited by 2,747
Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water
Song, S.-K., Sun, S.-W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002) · NeuroImage · doi:10.1006/nimg.2002.1267 · Cited by 2,582
Principles of diffusion tensor imaging and its applications to basic neuroscience research
Mori, S., & Zhang, J. (2006) · Neuron · doi:10.1016/j.neuron.2006.08.012 · Cited by 1,708
Looking into the functional architecture of the brain with diffusion MRI.
Le Bihan, D. (2003) · Nature Reviews Neuroscience · doi:10.1038/nrn1119 · Cited by 1,571
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
Maturation of white matter in the human brain: A review of magnetic resonance studies.
Paus, T., Collins, D. L., Evans, A. C., Leonard, G., Pike, B., & Zijdenbos, A. (2001) · Brain Research Bulletin · doi:10.1016/s0361-9230(00)00434-2 · Cited by 863
White matter maturation reshapes structural connectivity in the late developing human brain
Hagmann, P., Sporns, O., Madan, N., Cammoun, L., Pienaar, R., Wedeen, V. J., Meuli, R., Thiran, J.-P., & Grant, P. E. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1009073107 · Cited by 700
Analysis of partial volume effects in diffusion‐tensor MRI
Alexander, A. L., Hasan, K. M., Lazar, M., Tsuruda, J. S., & Parker, D. L. (2001) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1105 · Cited by 695
Diffusion MRI at 25: exploring brain tissue structure and function
Le Bihan, D., & Johansen-Berg, H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.006 · Cited by 498
Normal aging in the central nervous system: Quantitative MR diffusion-tensor analysis
Abe, O., Aoki, S., Hayashi, N., Yamada, H., Kunimatsu, A., Mori, H., Yoshikawa, T., Okubo, T., & Ohtomo, K. (2002) · Neurobiology of Aging · doi:10.1016/s0197-4580(01)00318-9 · Cited by 420
The Neonatal Connectome During Preterm Brain Development
van den Heuvel, M. P., Kersbergen, K. J., de Reus, M. A., Keunen, K., Kahn, R. S., Groenendaal, F., de Vries, L. S., & Benders, M. J. N. L. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhu095 · Cited by 386
Diffusion tensor imaging of normal and injured developing human brain-a technical review
Neil, J., Miller, J., Mukherjee, P., & Hüppi, P. S. (2002) · NMR in Biomedicine · doi:10.1002/nbm.784 · Cited by 402
Self-citationHuang, H., Xue, R., Zhang, J., Ren, T., Richards, L. J., Yarowsky, P., Miller, M. I., & Mori, S. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.2769-08.2009 · Cited by 364
SANDI: a compartment‐based model for non‐invasive apparent soma and neurite imaging by diffusion MRI
Palombo, M., Ianus, A., Guerreri, M., Nunes, D., Alexander, D. C., Shemesh, N., & Zhang, H. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116835 · Cited by 349
Development of cortical microstructure in the preterm human brain
Ball, G., Srinivasan, L., Aljabar, P., Counsell, S. J., Durighel, G., Hajnal, J. V., Rutherford, M. A., & Edwards, A. D. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1301652110 · Cited by 331
Diffusion tensor imaging and aging—A review.
Moseley, M. (2002) · NMR in Biomedicine · doi:10.1002/nbm.785 · Cited by 302
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
Eluvathingal, T. J., Hasan, K. M., Kramer, L., Fletcher, J. M., & Ewing-Cobbs, L. (2007) · Cerebral Cortex · doi:10.1093/cercor/bhm003 · Cited by 288
Gender Differences in Human Brain: A Review
Zaidi, Z. F. (2010) · The Open Anatomy Journal · doi:10.2174/1877609401002010037 · Cited by 229
Quantitative tract-based white matter development from birth to age 2 years
Geng, X., Gouttard, S., Sharma, A., Gu, H., Styner, M., Lin, W., Gerig, G., & Gilmore, J. H. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.057 · Cited by 212
Faria, A. V., Zhang, J., Oishi, K., Li, X., Jiang, H., Akhter, K., Hermoye, L., Lee, S.-K., Hoon, A., & Stashinko, E. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.04.238 · Cited by 180
CASCIO, C. J., GERIG, G., & PIVEN, J. (2007) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1097/01.chi.0000246064.93200.e8 · Cited by 167
Callosal Contributions to Simultaneous Bimanual Finger Movements
Bonzano, L., Tacchino, A., Roccatagliata, L., Abbruzzese, G., Mancardi, G. L., & Bove, M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4076-07.2008 · Cited by 136
Structural network analysis of brain development in young preterm neonates
Brown, C. J., Miller, S. P., Booth, B. G., Andrews, S., Chau, V., Poskitt, K. J., & Hamarneh, G. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.07.030 · Cited by 103
Layer-specific diffusion weighted imaging in human primary visual cortex in vitro
Kleinnijenhuis, M., Zerbi, V., Küsters, B., Slump, C. H., Barth, M., & van Cappellen van Walsum, A.-M. (2013) · Cortex · doi:10.1016/j.cortex.2012.11.015 · Cited by 71
The Biological Basis of Diffusion Anisotropy
Beaulieu, C. (2014) · Diffusion MRI · doi:10.1016/b978-0-12-396460-1.00008-1 · Cited by 66
Smyser, C. D., Kidokoro, H., & Inder, T. E. (2012) · Journal of Paediatrics and Child Health · doi:10.1111/j.1440-1754.2012.02535.x · Cited by 61
White Matter Heritability Using Diffusion Tensor Imaging in Neonatal Brains
Geng, X., Prom-Wormley, E. C., Perez, J., Kubarych, T., Styner, M., Lin, W., Neale, M. C., & Gilmore, J. H. (2012) · Twin Research and Human Genetics · doi:10.1017/thg.2012.14 · Cited by 53
Karmacharya, S., Gagoski, B., Ning, L., Vyas, R., Cheng, H. H., Soul, J., Newberger, J. W., Shenton, M. E., Rathi, Y., & Grant, P. E. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2018.04.032 · Cited by 46
Krishnan, M. L., Wang, Z., Silver, M., Boardman, J. P., Ball, G., Counsell, S. J., Walley, A. J., Montana, G., & Edwards, A. D. (2016) · Brain and Behavior · doi:10.1002/brb3.434 · Cited by 28
Wang, X., Cuzon Carlson, V. C., Studholme, C., Newman, N., Ford, M. M., Grant, K. A., & Kroenke, C. D. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1919048117 · Cited by 31
Han, X., Maharjan, S., Chen, J., Zhao, Y., Qi, Y., White, L. E., Johnson, G. A., & Wang, N. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120734 · Cited by 15
High-resolution mri guided whole mouse brain neuronal cell type atlas using deep learning
Han, X., Hu, R., Liu, Z., Chen, J., Jafry, M., Song, H., Zhao, Y., Lin, M., White, L. E., Johnson, G. A., et al. (2026) · Communications Biology · doi:10.1038/s42003-026-10608-y
Metadata
- Authors
- Neil, J. J., Shiran, S. I., McKinstry, R. C., Schefft, G. L., Snyder, A. Z., Almli, C. R., Akbudak, E., Aronovitz, J. A., Miller, J. P., Lee, B. C., & Conturo, T. E.
- Venue
- Radiology
- Published
- 1998-10
- Volume
- 209
- Issue
- 1
- Pages
- 57-66
- ISSN
- 0033-8419 (ISSN-L)
- 1527-1315
- OpenAlex
- W1977678763
- Cited by
- 646
- References
- 0
- FWCI
- 17.82
- Type
- journal article
- Language
- en
- Open access
- closed
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
