Brain white matter after pediatric mild traumatic brain injury: a diffusion tensor and neurite orientation and dispersion imaging study
preprint
OA: closed
CC-BY-NC-ND-4.0
Abstract
Background Pediatric mild traumatic brain injury (mTBI) affects millions of children annually. Diffusion tensor imaging (DTI) is sensitive to axonal injuries and white matter microstructure and has been used to characterize the brain changes associated with mild traumatic brain injury (mTBI). Neurite orientation dispersion and density imaging (NODDI) is a diffusion model that can provide additional insight beyond traditional DTI metrics, but has not been examined in pediatric mTBI. The goal of this study was to employ DTI and NODDI to gain added insight into white matter alterations in children with mTBI compared to children with mild orthopedic injury (OI). Methods Children (mTBI n=320, OI n=176) aged 8-16.99 years ( m 12.39 ± 2.32 years) were recruited from emergency departments at five hospitals across Canada and underwent 3T MRI on average 11 days post-injury. DTI and NODDI metrics were calculated for seven major white matter tracts and compared between groups using univariate analysis of covariance controlling for age, sex, and scanner type. False discovery rate (FDR) was used to correct for multiple comparisons. Results Univariate analysis revealed no significant group main effects or interactions in DTI or NODDI metrics. Fractional anisotropy and neurite density index in all tracts exhibited a significant positive association with age and mean diffusivity in all tracts exhibited a significant negative association with age in the whole sample. Conclusions Overall, there were no differences between mTBI and OI groups in brain white matter microstructure from either DTI or NODDI in the seven tracts. This indicates that mTBI is associated with relatively minor white matter differences, if any, at the post-acute stage. Brain differences may evolve at later stages of injury, so longitudinal studies with long-term follow-up are needed.
My notes (saved in your browser only)
Citation neighborhood (sparse)
Too few in-corpus citations on either side for a chart; here are the lists.
Cites (2)
References (63)
- Diffusion Tensor Model links to Neurite Orientation Dispersion and Density Imaging at high b-value in Cerebral Cortical Gray Matter via crossref
- The Evolution of White Matter Changes After Mild Traumatic Brain Injury: A DTI and NODDI Study via crossref
- doi:10.7759/cureus.3937 via crossref
- doi:10.1007/s11682-012-9156-5 via crossref
- doi:10.1016/j.pediatrneurol.2015.04.011 via crossref
- doi:10.1037/a0018112 via crossref
- doi:10.1007/s00701-005-0674-4 via crossref
- doi:10.1016/j.nicl.2013.12.009 via crossref
- doi:10.1097/htr.0b013e3181e52c2a via crossref
- doi:10.1089/neu.2018.6360 via crossref
- doi:10.1212/01.wnl.0000305961.68029.54 via crossref
- doi:10.3174/ajnr.a1806 via crossref
- doi:10.1016/j.pediatrneurol.2012.09.005 via crossref
- doi:10.1089/neu.2013.3269 via crossref
- doi:10.1523/jneurosci.3379-12.2012 via crossref
- doi:10.1111/j.1552-6569.2010.00537.x via crossref
- doi:10.1089/neu.2009.1110 via crossref
- doi:10.1002/hbm.21092 via crossref
- doi:10.1007/s11682-017-9752-5 via crossref
- doi:10.3389/fncir.2019.00028 via crossref
- doi:10.1002/hbm.24245 via crossref
- doi:10.1089/neu.2013.3213 via crossref
- doi:10.1016/j.neuroimage.2012.03.072 via crossref
- doi:10.1126/sciadv.aaz6892 via crossref
- doi:10.1002/hbm.24500 via crossref
- doi:10.1097/mcc.0b013e32808255dc via crossref
- doi:10.1159/000094151 via crossref
- doi:10.3389/fneur.2017.00685 via crossref
- doi:10.1136/bjsm.2009.058255 via crossref
- doi:10.1542/peds.2005-0994 via crossref
- doi:10.3390/brainsci7050046 via crossref
- doi:10.1136/bmjopen-2017-017012 via crossref
- doi:10.1097/pec.0000000000001360 via crossref
- doi:10.1016/s0140-6736(74)91639-0 via crossref
- doi:10.1097/00005373-198501000-00010 via crossref
- doi:10.1037/a0022580 via crossref
- doi:10.1097/00004583-199806000-00015 via crossref
- doi:10.1016/j.neuroimage.2014.05.044 via crossref
- doi:10.1016/j.neuroimage.2019.04.004 via crossref
- doi:10.2307/2346101 via crossref
- doi:10.3758/brm.41.4.1149 via crossref
- doi:10.1007/s00429-014-0947-x via crossref
- doi:10.1002/hbm.24706 via crossref
- doi:10.1371/journal.pone.0182340 via crossref
- doi:10.3389/fnhum.2021.616132 via crossref
- doi:10.3233/prm-150347 via crossref
- doi:10.1212/01.wnl.0000305961.68029.54 via crossref
- doi:10.1002/jnr.24142 via crossref
- doi:10.1148/radiol.14132512 via crossref
- doi:10.1002/hbm.23278 via crossref
- doi:10.1148/radiol.2015151388 via crossref
- doi:10.1016/j.nicl.2019.101842 via crossref
- doi:10.1212/wnl.0000000000004669 via crossref
- doi:10.1016/j.neuroimage.2017.01.023 via crossref
- doi:10.1002/hbm.23658 via crossref
- doi:10.1227/neu.0000000000000505 via crossref
- doi:10.3171/2016.11.peds16383 via crossref
- doi:10.1016/j.jpeds.2018.01.075 via crossref
- doi:10.1038/s41598-020-65948-4 via crossref
- doi:10.1016/j.nicl.2016.06.012 via crossref
- doi:10.1001/jama.2016.1203 via crossref
- doi:10.3174/ajnr.a5025 via crossref
- doi:10.1001/jamapediatrics.2018.3820 via crossref
Source provenance
- crossref
- last seen: 2026-07-13T06:45:35.931091+00:00
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-NC-ND-4.0