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Age-related changes of white matter association tracts in normal children throughout adulthood: a diffusion tensor tractography study

  • Paediatric Neuroradiology
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Abstract

Purpose

The aim of this study is to study the age, gender and lateral asymmetry-related white matter changes of long association tracts throughout late childhood and adolescence into adulthood using diffusion tensor tractography (DTT).

Methods

DTT was performed in 44 healthy subjects aged 7–45 years. Fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), Trace, density and volume were calculated for long association tracts, namely the inferior fronto-occipital fasciculus (IFOF), inferior longitudinal fasciculus (ILF), uncinate fasciculus, superior longitudinal fasciculus (SLF) and its arcuate fibres. FA and diffusivity indices were correlated as function of age using Pearson correlation test. Comparison between males and females, and comparison between both hemispheres among all participants were also performed. A p value less than .01 was considered significant.

Results

The majority of the examined tracts (SLF and IFOF of both hemispheres, and the arcuate fasciculus, uncinate fasciculus, and ILF of the left hemisphere) followed a common pattern of metric changes with age. This pattern was characterized by significant FA increase accompanied by reduction in RD, Trace without significant AD changes. The right arcuate fasciculus showed similar pattern but without significant FA changes. The right uncinate and right ILF fasciculus demonstrated significant reduction in RD, Trace and AD, with and without significant FA increase, respectively. Left hemispheric dominance regarding the FA and diffusivity indices was demonstrated in uncinate fasciculus with no significant gender-related differences.

Conclusion

Significant microstructural tract-specific maturation processes continue throughout late childhood into adulthood. These processes may represent stages in a cascade of age-related maturation in white matter microstructure.

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References

  1. Lebel C, Gee M, Camicioli R et al (2012) Diffusion tensor imaging of white matter tract evolution over the lifespan. NeuroImage 60:340–352

    Article  CAS  PubMed  Google Scholar 

  2. Jellison BJ, Field AS, Medow J et al (2004) Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. Am J Neuroradiol 25:356–369

    PubMed  Google Scholar 

  3. Casey BJ, Tottenham N, Liston C et al (2005) Imaging the developing brain: what have we learned about cognitive development? Trends Cogn Sci 9:104–110

    Article  CAS  PubMed  Google Scholar 

  4. Grossman AW, Churchill JD, McKinney BC et al (2003) Experience effects on brain development: possible contributions to psychopathology. J Child Psychol Psychiatry 44:33–63

    Article  PubMed  Google Scholar 

  5. Wolff JJ, Gu H, Gerig G et al (2012) Differences in white matter fiber tract development present from 6 to 24 months in infants with autism. Am J Psychiatry 169:589–600

    Article  PubMed  PubMed Central  Google Scholar 

  6. Meng JZ, Guo LW, Cheng H et al (2012) Correlation between cognitive function and the association fibers in patients with Alzheimer’s disease using diffusion tensor imaging. J Clin Neurosci 19(12):1659–1663

    Article  PubMed  Google Scholar 

  7. Giorgio A, Watkins KE, Douaud G et al (2008) Changes in white matter microstructure during adolescence. NeuroImage 39:52–61

    Article  CAS  PubMed  Google Scholar 

  8. Qiu D, Tan LH, Zhou K et al (2008) Diffusion tensor imaging of normal white matter maturation from late childhood to young adulthood: voxel-wise evaluation of mean diffusivity, fractional anisotropy, radial and axial diffusivities, and correlation with reading development. NeuroImage 41:223–232

    Article  PubMed  Google Scholar 

  9. Snook L, Plewes C, Beaulieu C (2007) Voxel based versus region of interest analysis in diffusion tensor imaging of neurodevelopment. NeuroImage 34:243–252

    Article  PubMed  Google Scholar 

  10. Muzik O, Chugani DC, Juhasz C et al (2000) Statistical parametric mapping: assessment of application in children. NeuroImage 12:538–549

    Article  CAS  PubMed  Google Scholar 

  11. Jones DK, Symms MR, Cercignani M et al (2005) The effect of filter size on VBM analyses of DT-MRI data. NeuroImage 26:546–554

    Article  PubMed  Google Scholar 

  12. Mori S, Kaufmann WE, Davatzikos C et al (2002) Imaging cortical association tracts in the human brain using diffusion-tensor-based axonal tracking. Magn Reson Med 47:215–223

    Article  PubMed  Google Scholar 

  13. Catani M, Howard RJ, Pajevic S et al (2002) Virtual in vivo interactive dissection of white matter fasciculi in the human brain. NeuroImage 17:77–94

    Article  PubMed  Google Scholar 

  14. Wakana S, Caprihan A, Panzenboeck MM et al (2007) Reproducibility of quantitative tractography methods applied to cerebral white matter. NeuroImage 36:630–644

    Article  PubMed  PubMed Central  Google Scholar 

  15. Berman JI, Mukherjee P, Partridge SC et al (2005) Quantitative diffusion tensor MRI fiber tractography of sensorimotor white matter development in premature infants. NeuroImage 27:862–871

    Article  PubMed  Google Scholar 

  16. Dubois J, Hertz-Pannier L, Dehaene-Lambertz G et al (2006) Assessment of the early organization and maturation of infants’ cerebral white matter fiber bundles: a feasibility study using quantitative diffusion tensor imaging and tractography. NeuroImage 30:1121–1132

    Article  CAS  PubMed  Google Scholar 

  17. Zacharia A, Zimine S, Lovblad KO (2006) Early assessment of brain maturation by MR imaging segmentation in neonates and premature infants. Am J Neuroradiol 27:972–977

    CAS  PubMed  Google Scholar 

  18. Giménez M, Miranda MJ, Born AP et al (2008) Accelerated cerebral white matter development in preterm infants: a voxel-based morphometry study with diffusion tensor MR imaging. NeuroImage 41:728–734

    Article  PubMed  Google Scholar 

  19. Moon WJ, Provenzale JM, Sarikaya B et al (2011) Diffusion-tensor imaging assessment of white matter maturation in childhood and adolescence. Am J Roentgenol 197:704–712

    Article  Google Scholar 

  20. Schmithorst VJ, Wilke M, Dardzinski BJ et al (2002) Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology 222:212–218

    Article  PubMed  PubMed Central  Google Scholar 

  21. Barnea-Goraly N, Menon V, Eckert M et al (2005) White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb Cortex 15:1848–1854

    Article  PubMed  Google Scholar 

  22. Eluvathingal TJ, Hasan KM, Kramer L et al (2007) Quantitative diffusion tensor tractography of association and projection fibers in normally developing children and adolescents. Cereb Cortex 17:2760–2768

    Article  PubMed  PubMed Central  Google Scholar 

  23. Snook L, Paulson LA, Roy D et al (2005) Diffusion tensor imaging of neurodevelopment in children and young adults. NeuroImage 26:1164–1173

    Article  PubMed  Google Scholar 

  24. Lebel C, Walker L, Leemans A et al (2008) Microstructural maturation of the human brain from childhood to adulthood. NeuroImage 40:1044–1055

    Article  CAS  PubMed  Google Scholar 

  25. Asato MR, Terwilliger R, Woo J et al (2010) White matter development in adolescence: a DTI study. Cereb Cortex 20:2122–2131

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Lebel C, Beaulieu C (2011) Longitudinal development of human brain wiring continues from childhood into adulthood. J Neurosci 31:10937–10947

    Article  CAS  PubMed  Google Scholar 

  27. Kumar R, Nguyen HD, Macey PM et al (2012) Regional brain axial and radial diffusivity changes during development. J Neurosci Res 90:346–355

    Article  CAS  PubMed  Google Scholar 

  28. Hasan KM, Kamali A, Abid H et al (2010) Quantification of the spatiotemporal microstructural organization of the human brain association, projection and commissural pathways across the lifespan using diffusion tensor tractography. Brain Struct Funct 214:361–373

    Article  PubMed  PubMed Central  Google Scholar 

  29. Jiang DTIH, van Zijl PC, Kim J et al (2006) DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Prog Biomed 81:106–116

    Article  Google Scholar 

  30. Song SK, Sun SW, Ramsbottom MJ et al (2002) Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage 17:1429–1436

    Article  PubMed  Google Scholar 

  31. Sun SW, Liang HF, Le TQ (2006) Differential sensitivity of in vivo and ex vivo diffusion tensor imaging to evolving optic nerve injury in mice with retinal ischemia. NeuroImage 32:1195–1204

    Article  PubMed  Google Scholar 

  32. Luna B, Garver KE, Urban TA et al (2004) Maturation of cognitive processes from late childhood to adulthood. Child Dev 75:1357–1372

    Article  PubMed  Google Scholar 

  33. Suzuki Y, Matsuzawa H, Kwee IL et al (2003) Absolute eigenvalue diffusion tensor analysis for human brain maturation. NMR Biomed 16:257–260

    Article  PubMed  Google Scholar 

  34. Dubois J, Dehaene-Lambertz G, Perrin M et al (2008) Asynchrony of the early maturation of white matter bundles in healthy infants: quantitative landmarks revealed noninvasively by diffusion tensor imaging. Hum Brain Mapp 29:14–27

    Article  PubMed  Google Scholar 

  35. Dubois J, Dehaene-Lambertz G, Kulikova S et al (2014) The early development of brain white matter: a review of imaging studies in fetuses, newborns and infants. Neuroscience 276:48–71

    Article  CAS  PubMed  Google Scholar 

  36. Qiu A, Sz M, Miller MI (2015) Diffusion tensor imaging for understanding brain development in early life. Annu Rev Psychol 66:853–876

    Article  PubMed  PubMed Central  Google Scholar 

  37. Mori S, Zhang J (2006) Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51:527–539

    Article  CAS  PubMed  Google Scholar 

  38. Bennett IJ, Madden DJ, Vaidya CJ et al (2010) Age-related differences in multiple measures of white matter integrity: a diffusion tensor imaging study of healthy aging. Hum Brain Mapp 31:378–390

    PubMed  PubMed Central  Google Scholar 

  39. Burzynska AZ, Preuschhof C, Backman L et al (2010) Age-related differences in white matter microstructure: region specific patterns of diffusivity. NeuroImage 49:2104–2112

    Article  CAS  PubMed  Google Scholar 

  40. Moll J, Zahn R, de Oliveira-Souza R et al (2005) Opinion: the neural basis of human moral cognition. Nat Rev Neurosci 6:799–809

    Article  CAS  PubMed  Google Scholar 

  41. Blakemore SJ, Choudhury S (2006) Development of the adolescent brain: implications for executive function and social cognition. J Child Psychol Psychiatry 47:296–312

    Article  PubMed  Google Scholar 

  42. Schmithorst VJ, Wilke M, Dardzinski BJ et al (2005) Cognitive functions correlate with white matter architecture in a normal pediatric population: a diffusion tensor MR imaging study. Hum Brain Mapp 26:139–147

    Article  PubMed  PubMed Central  Google Scholar 

  43. Salami M, Itami C, Tsumoto T, Kimura F (2003) Change of conduction velocity by regional myelination yields constant latency irrespective of distance between thalamus and cortex. Proc Natl Acad Sci U S A 100:6174–6179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Scholz J, Klein MC, Behrens TE, Johansen-Berg H (2009) Training induces changes in white-matter architecture. Nat Neurosci 12:1370–1371

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Wahl M, Li YO, Ng J et al (2010) Microstructural correlations of white matter tracts in the human brain. NeuroImage 51:534–541

    Article  Google Scholar 

  46. Wu Y, Sun D, Wang Y et al (2016) Subcomponents and connectivity of the inferior fronto-occipital fasciculus revealed by diffusion spectrum imaging fiber tracking. Front Neuroanat 10:88

    PubMed  PubMed Central  Google Scholar 

  47. Dick AS, Tremblay P (2012) Beyond the arcuate fasciculus: consensus and controversy in the connectional anatomy of language. Brain 135:3529–3550

    Article  PubMed  Google Scholar 

  48. Geier C, Luna B (2009) The maturation of incentive processing and cognitive control. Pharmacol Biochem Behav 93:212–221

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zhang J, Evans A, Hermoye L et al (2007) Evidence of slow maturation of the superior longitudinal fasciculus in early childhood by diffusion tensor imaging. NeuroImage 38:239–247

    Article  PubMed  PubMed Central  Google Scholar 

  50. Urger SE, De Bellis MD, Hooper S et al (2015) The superior longitudinal fasciculus in typically developing children and adolescents: diffusion tensor imaging and neuropsychological correlates. J Child Neurol 30:9–20

    Article  PubMed  Google Scholar 

  51. Park HJ, Westin CF, Kubicki M et al (2004) White matter hemisphere asymmetries in healthy subjects and in schizophrenia: a diffusion tensor MRI study. NeuroImage 23:213–223

    Article  PubMed  PubMed Central  Google Scholar 

  52. Rodrigo S, Oppenheim C, Chassoux F, Golestani N, Cointepas Y, Poupon C et al (2007) Uncinate fasciculus fiber tracking in mesial temporal lobe epilepsy: initial findings. Eur Radiol 17:1663–1668

    Article  CAS  PubMed  Google Scholar 

  53. Hasan KM, Iftikhar A, Kamali A et al (2009) Development and aging of the healthy human brain uncinate fasciculus across the lifespan using diffusion tensor tractography. Brain Res 18(1276):67–76

    Article  Google Scholar 

  54. Powell HW, Parker GJ, Alexander DC et al (2006) Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. NeuroImage 32:388–399

    Article  PubMed  Google Scholar 

  55. Agosta F, Henry RG, Migliaccio R et al (2010) Language networks in semantic dementia. Brain 133:286–299

    Article  PubMed  Google Scholar 

  56. Lo YC, Soong WT, Gau SSF et al (2011) The loss of asymmetry and reduced interhemispheric connectivity in adolescents with autism: a study using diffusion spectrum imaging tractography. Psychiatric Res 192:60–66

    Article  Google Scholar 

  57. Allen JS, Damasio H, Grabowski TJ et al (2003) Sexual dimorphism and asymmetries in the gray-white composition of the human cerebrum. NeuroImage 18:880–894

    Article  PubMed  Google Scholar 

  58. Shin YW, Kim DJ, Hyon T et al (2005) Sex differences in the human corpus callosum: diffusion tensor imaging study. Neuroreport 16:795–798

    Article  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank Prof. Dr. Moustafa El Houssinie, Professor of Public Health, Faculty of Medicine, Ain-Shams University, for the helpful discussions on statistical issues related to this paper.

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Authors and Affiliations

  1. Radiodiagnosis department, Faculty of medicine, Ain-Shams University, 9 Lotfi Elsayed St. Ain-Shams University Staff Buildings, Cairo, 11657, Egypt

    Shaimaa Abdelsattar Mohammad

  2. National Research Centre, Cairo, Egypt

    Neveen Hassan Nashaat

Authors
  1. Shaimaa Abdelsattar Mohammad
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  2. Neveen Hassan Nashaat
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Correspondence to Shaimaa Abdelsattar Mohammad.

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No funding was received for this study.

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The authors declare that they have no conflict of interest.

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All procedures performed in the studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

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Mohammad, S.A., Nashaat, N.H. Age-related changes of white matter association tracts in normal children throughout adulthood: a diffusion tensor tractography study. Neuroradiology 59, 715–724 (2017). https://doi.org/10.1007/s00234-017-1858-3

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  • DOI: https://doi.org/10.1007/s00234-017-1858-3

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