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Changes in brain microstructure during infancy and childhood using clinical feasible ADC-maps

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Abstract

Purpose

The purpose of this study was to examine age-related changes in apparent diffusion coefficient (ADC) during infancy and childhood using routine MRI data.

Methods

A total of 112 investigations of patients aged 0 to 17.2 years showing a normal degree of myelination and no signal abnormalities on conventional MRI were retrospectively selected from our pool of pediatric MRI examinations at 1.5T. ADC maps based on our routinely included axial diffusion weighted sequence were created from the scanner. ADC values were measured in 35 different brain regions investigating normal age-related changes during the maturation of the human brain in infancy and childhood using clinical feasible sequences at 1.5T.

Results

The relationship between ADC values and age in infancy and childhood can be described as an exponential function. With increasing age, the ADC values decrease significantly in all brain regions, especially during the first 2 years of life. Except in the peritrigonal white matter, no significant differences were found between both hemispheres. Between 0 and 2 years of life, no significant gender differences were detected.

Conclusions

Using ADC maps based on a routinely performed axial diffusion weighted sequence, it was possible first to describe the relationship between ADC values and age in infancy and childhood as exponential function in the whole brain and second to determine normative age-related ADC values in multiple brain regions.

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References

  1. Autti T, Raininko R, Vanhanen SL, Kallio M, Santavuori P (1994) MRI of the normal brain from early childhood to middle age. II. Age dependence of signal intensity changes on T2-weighted images. Neuroradiology 36:649–651

    Article  CAS  PubMed  Google Scholar 

  2. Coats JS, Freeberg A, Pajela EG, Obenaus A, Ashwal S (2009) Meta-analysis of apparent diffusion coefficients in the newborn brain. Pediatr Neurol 41:263–274. doi:10.1016/j.pediatrneurol.2009.04.013

    Article  PubMed  Google Scholar 

  3. Dubois J, Hertz-Pannier L, Dehaene-Lambertz G, Cointepas Y, Le Bihan D (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. doi:10.1016/j.neuroimage.2005.11.022

    Article  CAS  PubMed  Google Scholar 

  4. Engelbrecht V, Scherer A, Rassek M, Witsack HJ, Modder U (2002) Diffusion-weighted MR imaging in the brain in children: findings in the normal brain and in the brain with white matter diseases. Radiology 222:410–418. doi:10.1148/radiol.2222010492

    Article  PubMed  Google Scholar 

  5. Han R, Huang L, Sun Z, Zhang D, Chen X, Yang X, Cao Z (2015) Assessment of apparent diffusion coefficient of normal fetal brain development from gestational age week 24 up to term age: a preliminary study. Fetal Diagn Ther 37:102–107. doi:10.1159/000363650

    Article  PubMed  Google Scholar 

  6. Helenius J, Soinne L, Perkio J, Salonen O, Kangasmaki A, Kaste M, Carano RA, Aronen HJ, Tatlisumak T (2002) Diffusion-weighted MR imaging in normal human brains in various age groups. AJNR Am J Neuroradiol 23:194–199

    PubMed  Google Scholar 

  7. Holland BA, Haas DK, Norman D, Brant-Zawadzki M, Newton TH (1986) MRI of normal brain maturation. AJNR Am J Neuroradiol 7:201–208

    CAS  PubMed  Google Scholar 

  8. Huppi PS, Maier SE, Peled S, Zientara GP, Barnes PD, Jolesz FA, Volpe JJ (1998) Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging. Pediatr Res 44:584–590. doi:10.1203/00006450-199810000-00019

    Article  CAS  PubMed  Google Scholar 

  9. Jones RA, Palasis S, Grattan-Smith JD (2003) The evolution of the apparent diffusion coefficient in the pediatric brain at low and high diffusion weightings. Journal of magnetic resonance imaging : JMRI 18:665–674. doi:10.1002/jmri.10413

    Article  PubMed  Google Scholar 

  10. Kehrer M, Blumenstock G, Ehehalt S, Goelz R, Poets C, Schoning M (2005) Development of cerebral blood flow volume in preterm neonates during the first two weeks of life. Pediatr Res 58:927–930. doi:10.1203/01.pdr.0000182579.52820.c3

    Article  PubMed  Google Scholar 

  11. Le Bihan D (2013) Apparent diffusion coefficient and beyond: what diffusion MR imaging can tell us about tissue structure. Radiology 268:318–322. doi:10.1148/radiol.13130420

    Article  PubMed  Google Scholar 

  12. Le Bihan D, Johansen-Berg H (2012) Diffusion MRI at 25: exploring brain tissue structure and function. NeuroImage 61:324–341. doi:10.1016/j.neuroimage.2011.11.006

    Article  PubMed  Google Scholar 

  13. Miller SP, Vigneron DB, Henry RG, Bohland MA, Ceppi-Cozzio C, Hoffman C, Newton N, Partridge JC, Ferriero DM, Barkovich AJ (2002) Serial quantitative diffusion tensor MRI of the premature brain: development in newborns with and without injury. Journal of magnetic resonance imaging : JMRI 16:621–632. doi:10.1002/jmri.10205

    Article  PubMed  Google Scholar 

  14. Mukherjee P, Miller JH, Shimony JS, Conturo TE, Lee BC, Almli CR, McKinstry RC (2001) Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. Radiology 221:349–358. doi:10.1148/radiol.2212001702

    Article  CAS  PubMed  Google Scholar 

  15. Neil JJ, Shiran SI, McKinstry RC, Schefft GL, Snyder AZ, Almli CR, Akbudak E, Aronovitz JA, Miller JP, Lee BC, Conturo TE (1998) Normal brain in human newborns: apparent diffusion coefficient and diffusion anisotropy measured by using diffusion tensor MR imaging. Radiology 209:57–66. doi:10.1148/radiology.209.1.9769812

    Article  CAS  PubMed  Google Scholar 

  16. Nossin-Manor R, Card D, Raybaud C, Taylor MJ, Sled JG (2015) Cerebral maturation in the early preterm period-a magnetization transfer and diffusion tensor imaging study using voxel-based analysis. NeuroImage 112:30–42. doi:10.1016/j.neuroimage.2015.02.051

    Article  PubMed  Google Scholar 

  17. Partridge SC, Mukherjee P, Henry RG, Miller SP, Berman JI, Jin H, Lu Y, Glenn OA, Ferriero DM, Barkovich AJ, Vigneron DB (2004) Diffusion tensor imaging: serial quantitation of white matter tract maturity in premature newborns. NeuroImage 22:1302–1314. doi:10.1016/j.neuroimage.2004.02.038

    Article  PubMed  Google Scholar 

  18. Paus T, Collins DL, Evans AC, Leonard G, Pike B, Zijdenbos A (2001) Maturation of white matter in the human brain: a review of magnetic resonance studies. Brain Res Bull 54:255–266

    Article  CAS  PubMed  Google Scholar 

  19. Sakuma H, Nomura Y, Takeda K, Tagami T, Nakagawa T, Tamagawa Y, Ishii Y, Tsukamoto T (1991) Adult and neonatal human brain: diffusional anisotropy and myelination with diffusion-weighted MR imaging. Radiology 180:229–233. doi:10.1148/radiology.180.1.2052700

    Article  CAS  PubMed  Google Scholar 

  20. Schneider JF, Confort-Gouny S, Le Fur Y, Viout P, Bennathan M, Chapon F, Fogliarini C, Cozzone P, Girard N (2007) Diffusion-weighted imaging in normal fetal brain maturation. Eur Radiol 17:2422–2429. doi:10.1007/s00330-007-0634-x

    Article  CAS  PubMed  Google Scholar 

  21. Watanabe M, Sakai O, Ozonoff A, Kussman S, Jara H (2013) Age-related apparent diffusion coefficient changes in the normal brain. Radiology 266:575–582. doi:10.1148/radiol.12112420

    Article  PubMed  Google Scholar 

  22. Yakovlev P, Lecours A (1967) The myelogenetic cycles of regional maturation of the brain. In: Minkowski A (ed) Regional development of the brain in early life. Blackwell Scientific, Oxford, pp 3–70

    Google Scholar 

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Correspondence to Eva Bültmann.

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No funding was received.

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The authors declare that they have no conflict of interest.

Ethical approval

This retrospective study was approved by the local institutional review board. All procedures performed in studies involving human participants were in accordance with 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: for this type of study, formal consent is not required.

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Bültmann, E., Mußgnug, H.J., Zapf, A. et al. Changes in brain microstructure during infancy and childhood using clinical feasible ADC-maps. Childs Nerv Syst 33, 735–745 (2017). https://doi.org/10.1007/s00381-017-3391-4

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  • DOI: https://doi.org/10.1007/s00381-017-3391-4

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