The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Pediatric diffusion tensor imaging: Normal database and observation of the white matter maturation in early childhood
Open accessAbstract
Recent advances in diffusion tensor imaging (DTI) have made it possible to reveal white matter anatomy and to detect neurological abnormalities in children. However, the clinical use of this technique is hampered by the lack of a normal standard of reference. The goal of this study was to initiate the establishment of a database of DTI images in children, which can be used as a normal standard of reference for diagnosis of pediatric neurological abnormalities. Seven pediatric volunteers and 23 pediatric patients (age range: 0-54 months) referred for clinical MR examinations, but whose brains were shown to be normal, underwent anatomical and DTI acquisitions on a 1.5 T MR scanner. The white matter maturation, as observed on DTI color maps, was described and illustrated. Changes in diffusion fractional anisotropy (FA), average apparent diffusion constant (ADC(ave)), and T2-weighted (T2W) signal intensity were quantified in 12 locations to characterize the anatomical variability of the maturation process. Almost all prominent white matter tracts could be identified from birth, although their anisotropy was often low. The evolution of FA, shape, and size of the white matter tracts comprised generally three phases: rapid changes during the first 12 months; slow modifications during the second year; and relative stability after 24 months. The time courses of FA, ADC(ave), and T2W signal intensity confirmed our visual observations that maturation of the white matter and the normality of its architecture can be assessed with DTI in young children. The database is available online and is expected to foster the use of this promising technique in the diagnosis of pediatric pathologies.
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
Cites
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 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 · cited 2×
“High quality DTI data from pediatric brains are becoming more and more abundant (Huppi and Inder, 2001; Neil et al., 2002 ).”
BackgroundMethod
Cited by
The basics of brain development
Stiles, J., & Jernigan, T. L. (2010) · Neuropsychology Review · doi:10.1007/s11065-010-9148-4 · Cited by 2,009
Normal development of brain circuits
Tau, G. Z., & Peterson, B. S. (2010) · Neuropsychopharmacology · doi:10.1038/npp.2009.115 · Cited by 1,391
Microstructural maturation of the human brain from childhood to adulthood
Lebel, C., Walker, L., Leemans, A., Phillips, L., & Beaulieu, C. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.12.053 · Cited by 1,398
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
Diffusion tensor imaging of white matter tract evolution over the lifespan
Lebel, C., Gee, M., Camicioli, R., Wieler, M., Martin, W., & Beaulieu, C. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.11.094 · Cited by 1,100
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
Resting-state networks in the infant brain
Fransson, P., Skiöld, B., Horsch, S., Nordell, A., Blennow, M., Lagercrantz, H., & Åden, U. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0704380104 · Cited by 696
Wolff, J. J., Gu, H., Gerig, G., Elison, J. T., Styner, M., Gouttard, S., Botteron, K. N., Dager, S. R., Dawson, G., Estes, A. M., et al. (2012) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2011.11091447 · Cited by 671
The development of brain white matter microstructure
Lebel, C., & Deoni, S. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2017.12.097 · Cited by 602
The functional architecture of the infant brain as revealed by resting-state fMRI
Fransson, P., Åden, U., Blennow, M., & Lagercrantz, H. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq071 · Cited by 542
White matter development in adolescence: A DTI study
Asato, M. R., Terwilliger, R., Woo, J., & Luna, B. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp282 · Cited by 512
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
Ageing and brain white matter structure in 3,513 UK Biobank participants
Cox, S. R., Ritchie, S. J., Tucker-Drob, E. M., Liewald, D. C., Hagenaars, S. P., Davies, G., Wardlaw, J. M., Gale, C. R., Bastin, M. E., & Deary, I. J. (2016) · Nature Communications · doi:10.1038/ncomms13629 · Cited by 487
Deoni, S. C. L., Dean, D. C., O'Muircheartaigh, J., Dirks, H., & Jerskey, B. A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.07.037 · Cited by 390
Lebel, C., Treit, S., & Beaulieu, C. (2019) · NMR in Biomedicine · doi:10.1002/nbm.3778 · Cited by 379
Huang, 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
Self-citationAccelerated maturation of white matter in young children with autism: A high b value DWI study
Ben Bashat, D., Kronfeld-Duenias, V., Zachor, D. A., Ekstein, P. M., Hendler, T., Tarrasch, R., Even, A., Levy, Y., & Ben Sira, L. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.060 · Cited by 300
Assessing Executive Function in Preschoolers
Anderson, P. J., & Reidy, N. (2012) · Neuropsychology Review · doi:10.1007/s11065-012-9220-3 · Cited by 293
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
Changes in white matter microstructure during adolescence
Giorgio, A., Watkins, K. E., Douaud, G., James, A. C., James, S., De Stefano, N., Matthews, P. M., Smith, S. M., & Johansen-Berg, H. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.043 · Cited by 278
White matter development during adolescence as shown by diffusion MRI
Schmithorst, V. J., & Yuan, W. (2010) · Brain and Cognition · doi:10.1016/j.bandc.2009.06.005 · Cited by 249
Diffusion tensor imaging for understanding brain development in early life
Qiu, A., Mori, S., & Miller, M. I. (2015) · Annual Review of Psychology · doi:10.1146/annurev-psych-010814-015340 · Cited by 238
Self-citationLebel, C., Walton, M., Letourneau, N., Giesbrecht, G. F., Kaplan, B. J., & Dewey, D. (2016) · Biological Psychiatry · doi:10.1016/j.biopsych.2015.12.004 · Cited by 237
Krogsrud, S. K., Fjell, A. M., Tamnes, C. K., Grydeland, H., Mork, L., Due-Tønnessen, P., Bjørnerud, A., Sampaio-Baptista, C., Andersson, J., Johansen-Berg, H., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2015.09.017 · Cited by 190
Development of global cortical networks in early infancy
Homae, F., Watanabe, H., Otobe, T., Nakano, T., Go, T., Konishi, Y., & Taga, G. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.5618-09.2010 · Cited by 206
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
Age-related regional variations of the corpus callosum identified by diffusion tensor tractography
Lebel, C., Caverhill-Godkewitsch, S., & Beaulieu, C. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.03.072 · Cited by 209
Vértes, P. E., & Bullmore, E. T. (2015) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.12365 · Cited by 197
Rethinking schizophrenia in the context of normal neurodevelopment
Catts, V. S., Fung, S. J., Long, L. E., Joshi, D., Vercammen, A., Allen, K. M., Fillman, S. G., Rothmond, D. A., Sinclair, D., Tiwari, Y., et al. (2013) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2013.00060 · Cited by 206
Jelescu, I. O., Veraart, J., Adisetiyo, V., Milla, S. S., Novikov, D. S., & Fieremans, E. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.009 · Cited by 202
Collin, G., & van den Heuvel, M. P. (2013) · The Neuroscientist · doi:10.1177/1073858413503712 · Cited by 198
Donald, K. A., Eastman, E., Howells, F. M., Adnams, C., Riley, E. P., Woods, R. P., Narr, K. L., & Stein, D. J. (2015) · Acta Neuropsychiatrica · doi:10.1017/neu.2015.12 · Cited by 185
White matter development and early cognition in babies and toddlers
O'Muircheartaigh, J., Dean, D. C., Ginestet, C. E., Walker, L., Waskiewicz, N., Lehman, K., Dirks, H., Piryatinsky, I., & Deoni, S. C. L. (2014) · Human Brain Mapping · doi:10.1002/hbm.22488 · Cited by 183
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
Self-citationCASCIO, 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
Modeling healthy male white matter and myelin development: 3 through 60months of age
Dean, D. C., O'Muircheartaigh, J., Dirks, H., Waskiewicz, N., Lehman, K., Walker, L., Han, M., & Deoni, S. C. L. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.09.058 · Cited by 163
EEG functional connectivity is partially predicted by underlying white matter connectivity
Chu, C. J., Tanaka, N., Diaz, J., Edlow, B. L., Wu, O., Hämäläinen, M., Stufflebeam, S., Cash, S. S., & Kramer, M. A. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.033 · Cited by 135
Resting-state networks in awake five- to eight-year old children
de Bie, H. M. A., Boersma, M., Adriaanse, S., Veltman, D. J., Wink, A. M., Roosendaal, S. D., Barkhof, F., Stam, C. J., Oostrom, K. J., Delemarre‐van de Waal, H. A., et al. (2012) · Human Brain Mapping · doi:10.1002/hbm.21280 · Cited by 143
AAV gene therapy for Tay-Sachs disease
Flotte, T. R., Cataltepe, O., Puri, A., Batista, A. R., Moser, R., McKenna-Yasek, D., Douthwright, C., Gernoux, G., Blackwood, M., Mueller, C., et al. (2022) · Nature Medicine · doi:10.1038/s41591-021-01664-4 · Cited by 143
Global and regional white matter development in early childhood
Reynolds, J. E., Grohs, M. N., Dewey, D., & Lebel, C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.04.004 · Cited by 124
Douet, V., & Chang, L. (2015) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2014.00343 · Cited by 122
Billeci, L., Calderoni, S., Tosetti, M., Catani, M., & Muratori, F. (2012) · BMC Neurology · doi:10.1186/1471-2377-12-148 · Cited by 116
Khan, S., Vasung, L., Marami, B., Rollins, C. K., Afacan, O., Ortinau, C. M., Yang, E., Warfield, S. K., & Gholipour, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.030 · Cited by 115
Hasan, K. M., Kamali, A., Abid, H., Kramer, L. A., Fletcher, J. M., & Ewing-Cobbs, L. (2010) · Brain Structure and Function · doi:10.1007/s00429-009-0238-0 · Cited by 114
Associations between white matter microstructure and infants' working memory
Short, S. J., Elison, J. T., Goldman, B. D., Styner, M., Gu, H., Connelly, M., Maltbie, E., Woolson, S., Lin, W., Gerig, G., et al. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.021 · Cited by 105
Daniels, J. (2011) · Journal of Psychiatry & Neuroscience · doi:10.1503/jpn.100050 · Cited by 93
Lynch, K. M., Cabeen, R. P., Toga, A. W., & Clark, K. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116672 · Cited by 79
White Matter Injury in Newborns With Congenital Heart Disease: A Diffusion Tensor Imaging Study
Mulkey, S. B., Ou, X., Ramakrishnaiah, R. H., Glasier, C. M., Swearingen, C. J., Melguizo, M. S., Yap, V. L., Schmitz, M. L., & Bhutta, A. T. (2014) · Pediatric Neurology · doi:10.1016/j.pediatrneurol.2014.04.008 · Cited by 52
A penny for your thoughts: children’s inner speech and its neuro-development
Geva, S., & Fernyhough, C. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.01708 · Cited by 35
Multi-Tiered Analysis of Brain Injury in Neonates With Congenital Heart Disease
Mulkey, S. B., Swearingen, C. J., Melguizo, M. S., Schmitz, M. L., Ou, X., Ramakrishnaiah, R. H., Glasier, C. M., Bradley Schaefer, G., & Bhutta, A. T. (2013) · Pediatric Cardiology · doi:10.1007/s00246-013-0712-6 · Cited by 34
A tract-specific approach to assessing white matter in preterm infants
Pecheva, D., Yushkevich, P., Batalle, D., Hughes, E., Aljabar, P., Wurie, J., Hajnal, J. V., Edwards, A. D., Alexander, D. C., Counsell, S. J., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.04.057 · Cited by 33
Metadata
- Authors
- Hermoye, L., Saint-Martin, C., Cosnard, G., Lee, S.-K., Kim, J., Nassogne, M.-C., Menten, R., Clapuyt, P., Donohue, P. K., Hua, K., Wakana, S., Jiang, H., van Zijl, P. C. M., & Mori, S.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2006-01
- Volume
- 29
- Issue
- 2
- Pages
- 493-504
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W1973233713
- Cited by
- 425
- References
- 2
- FWCI
- 14.76
- Type
- journal article
- Language
- en
- Open access
- green
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.
