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Pediatric Radiology

, Volume 47, Issue 13, pp 1809–1816 | Cite as

Long-term effects of radiation therapy on white matter of the corpus callosum: a diffusion tensor imaging study in children

  • Monwabisi Makola
  • M. Douglas Ris
  • E. Mark Mahone
  • Keith Owen Yeates
  • Kim M. CecilEmail author
Original Article

Abstract

Background

Despite improving survival rates, children are at risk for long-term cognitive and behavioral difficulties following the diagnosis and treatment of a brain tumor. Surgery, chemotherapy and radiation therapy have all been shown to impact the developing brain, especially the white matter.

Objective

The purpose of this study was to determine the long-term effects of radiation therapy on white matter integrity, as measured by diffusion tensor imaging, in pediatric brain tumor patients 2 years after the end of radiation treatment, while controlling for surgical interventions.

Materials and methods

We evaluated diffusion tensor imaging performed at two time points: a baseline 3 to 12 months after surgery and a follow-up approximately 2 years later in pediatric brain tumor patients. A region of interest analysis was performed within three regions of the corpus callosum. Diffusion tensor metrics were determined for participants (n=22) who underwent surgical tumor resection and radiation therapy and demographically matched with participants (n=22) who received surgical tumor resection only.

Results

Analysis revealed that 2 years after treatment, the radiation treated group exhibited significantly lower fractional anisotropy and significantly higher radial diffusivity within the body of the corpus callosum compared to the group that did not receive radiation.

Conclusion

The findings indicate that pediatric brain tumor patients treated with radiation therapy may be at greater risk of experiencing long-term damage to the body of the corpus callosum than those treated with surgery alone.

Keywords

Brain Brain tumor Children Corpus callosum Diffusion tensor imaging Magnetic resonance imaging Radiation White matter 

Notes

Acknowledgements

Funding to support this work came from the National Institutes of Health grant numbers R01 CA112182, R01 ES027724 and the Intellectual & Development Disabilities Research Center, at Kennedy Krieger Institute, grant number U54 HD079123.

Compliance with ethical standards

Conflicts of interest

None

References

  1. 1.
    Patel S, Bhatnagar A, Wear C et al (2014) Are pediatric brain tumors on the rise in the USA? Significant incidence and survival findings from the SEER database analysis. Childs Nerv Syst 30:147–154CrossRefPubMedGoogle Scholar
  2. 2.
    Ostrom QT, Gittleman H, Fulop J et al (2015) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the united states in 2008-2012. Neuro Oncol 17(Suppl 4):iv1-iv62Google Scholar
  3. 3.
    Greene-Schloesser D, Moore E, Robbins ME (2013) Molecular pathways: radiation-induced cognitive impairment. Clin Cancer Res 19:2294–2300CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Conklin HM, Ashford JM, Di Pinto M et al (2013) Computerized assessment of cognitive late effects among adolescent brain tumor survivors. J Neuro-Oncol 113:333–340CrossRefGoogle Scholar
  5. 5.
    Lee YW, Cho HJ, Lee WH, Sonntag WE (2012) Whole brain radiation-induced cognitive impairment: pathophysiological mechanisms and therapeutic targets. Biomol Ther 20:357–370CrossRefGoogle Scholar
  6. 6.
    Palmer SL, Armstrong C, Onar-Thomas A et al (2013) Processing speed, attention, and working memory after treatment for medulloblastoma: an international, prospective, and longitudinal study. J Clin Oncol 31:3494–3500CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Mulhern RK, Palmer SL, Reddick WE et al (2001) Risks of young age for selected neurocognitive deficits in medulloblastoma are associated with white matter loss. J Clin Oncol 19:472–479CrossRefPubMedGoogle Scholar
  8. 8.
    Mulhern RK, Merchant TE, Gajjar A et al (2004) Late neurocognitive sequelae in survivors of brain tumours in childhood. Lancet Oncol 5:399–408CrossRefPubMedGoogle Scholar
  9. 9.
    Dietrich J, Monje M, Wefel J, Meyers C (2008) Clinical patterns and biological correlates of cognitive dysfunction associated with cancer therapy. Oncologist 13:1285–1295CrossRefPubMedGoogle Scholar
  10. 10.
    Mulhern RK, Palmer SL, Merchant TE et al (2005) Neurocognitive consequences of risk-adapted therapy for childhood medulloblastoma. J Clin Oncol 23:5511–5519CrossRefPubMedGoogle Scholar
  11. 11.
    Ris MD, Packer R, Goldwein J et al (2001) Intellectual outcome after reduced-dose radiation therapy plus adjuvant chemotherapy for medulloblastoma: a Children's cancer group study. J Clin Oncol 19:3470–3476CrossRefPubMedGoogle Scholar
  12. 12.
    Price RE, Langford LA, Jackson EF et al (2001) Radiation-induced morphologic changes in the rhesus monkey (Macaca Mulatta) brain. J Med Primatol 30:81–87CrossRefPubMedGoogle Scholar
  13. 13.
    Vogel FS, Hoak CG, Sloper JC, Haymaker W (1958) The induction of acute morphological changes in the central nervous system and pituitary body of macaque monkeys by cobalt60 (gamma) radiation. J Neuropathol Exp Neurol 17:138–150CrossRefPubMedGoogle Scholar
  14. 14.
    Burns TC, Awad AJ, Li MD, Grant GA (2016) Radiation-induced brain injury: low-hanging fruit for neuroregeneration. Neurosurg Focus 40:E3CrossRefPubMedGoogle Scholar
  15. 15.
    Ishii A, Dutta R, Wark GM et al (2009) Human myelin proteome and comparative analysis with mouse myelin. Proc Natl Acad Sci U S A 106:14605–14610CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Panagiotakos G, Alshamy G, Chan B et al (2007) Long-term impact of radiation on the stem cell and oligodendrocyte precursors in the brain. PLoS One 2:e588CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Schultheiss TE, Stephens LC (1992) The pathogenesis of radiation myelopathy: widening the circle. Int J Radiat Oncol Biol Phys 23:1089–1091 discussion 1093-1084CrossRefPubMedGoogle Scholar
  18. 18.
    Nagesh V, Tsien CI, Chenevert TL et al (2008) Radiation-induced changes in normal-appearing white matter in patients with cerebral tumors: a diffusion tensor imaging study. Int J Radiat Oncol Biol Phys 70:1002–1010CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Rueckriegel SM, Driever PH, Blankenburg F et al (2010) Differences in supratentorial damage of white matter in pediatric survivors of posterior fossa tumors with and without adjuvant treatment as detected by magnetic resonance diffusion tensor imaging. Int J Radiat Oncol Biol Phys 76:859–866CrossRefPubMedGoogle Scholar
  20. 20.
    Chapman CH, Nagesh V, Sundgren PC et al (2012) Diffusion tensor imaging of normal-appearing white matter as biomarker for radiation-induced late delayed cognitive decline. Int J Radiat Oncol Biol Phys 82:2033–2040CrossRefPubMedGoogle Scholar
  21. 21.
    Jiang H, van Zijl PC, Kim J et al (2006) DTIStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Prog Biomed 81:106–116CrossRefGoogle Scholar
  22. 22.
    Systat Software I (2014) SigmaPlot for windows. Systat Software, Inc., San JoseGoogle Scholar
  23. 23.
    Soares JM, Marques P, Alves V, Sousa N (2013) A hitchhiker's guide to diffusion tensor imaging. Front Neurosci 7:31CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Wozniak JR, Krach L, Ward E et al (2007) Neurocognitive and neuroimaging correlates of pediatric traumatic brain injury: a diffusion tensor imaging (DTI) study. Arch Clin Neuropsych 22:555–568CrossRefGoogle Scholar
  25. 25.
    Le Bihan D, Mangin JF, Poupon C et al (2001) Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 13:534–546CrossRefPubMedGoogle Scholar
  26. 26.
    Basser PJ, Pierpaoli C (1996) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 111:209–219CrossRefPubMedGoogle Scholar
  27. 27.
    Basser PJ (1995) Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed 8:333–344CrossRefPubMedGoogle Scholar
  28. 28.
    Basser PJ, Pajevic S, Pierpaoli C et al (2000) In vivo fiber tractography using DT-MRI data. Magn Reson Med 44:625–632CrossRefPubMedGoogle Scholar
  29. 29.
    Xue R, van Zijl PC, Crain BJ et al (1999) In vivo three-dimensional reconstruction of rat brain axonal projections by diffusion tensor imaging. Magn Reson Med 42:1123–1127CrossRefPubMedGoogle Scholar
  30. 30.
    Qiu D, Kwong DLW, Chan GCF et al (2007) Diffusion tensor magnetic resonance imaging finding of discrepant fractional anisotropy between the frontal and parietal lobes after whole-brain irradiation in childhood medulloblastoma survivors: reflection of regional white matter radiosensitivity? Int J Radiat Oncol Biol Phys 69:846–851CrossRefPubMedGoogle Scholar
  31. 31.
    Khong PL, Kwong DLW, Chan GCF et al (2003) Diffusion-tensor imaging for the detection and quantification of treatment-induced white matter injury in children with medulloblastoma: a pilot study. AJNR Am J Neuroradiol 24:734–740PubMedGoogle Scholar
  32. 32.
    Uh J, Merchant TE, Li Y et al (2015) Effects of surgery and proton therapy on cerebral white matter of craniopharyngioma patients. Int J Radiat Oncol Biol Phys 93:64–71CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Hope TR, Vardal J, Bjornerud A et al (2015) Serial diffusion tensor imaging for early detection of radiation-induced injuries to normal-appearing white matter in high-grade glioma patients. J Magn Reson Imaging 41:414–423CrossRefPubMedGoogle Scholar
  34. 34.
    de Blank PM, Berman JI, Fisher MJ (2016) Systemic chemotherapy and white matter integrity in tracts associated with cognition among children with neurofibromatosis type 1. Pediatr Blood Cancer 63:818–824CrossRefPubMedGoogle Scholar
  35. 35.
    Borghesani PR, Madhyastha TM, Aylward EH et al (2013) The association between higher order abilities, processing speed, and age are variably mediated by white matter integrity during typical aging. Neuropsychologia 51:1435–1444CrossRefPubMedGoogle Scholar
  36. 36.
    Genova HM, DeLuca J, Chiaravalloti N, Wylie G (2013) The relationship between executive functioning, processing speed, and white matter integrity in multiple sclerosis. J Clin Exp Neuropsychol 35:631–641CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Kerchner GA, Racine CA, Hale S et al (2012) Cognitive processing speed in older adults: relationship with white matter integrity. PLoS One 7:e50425CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Kourtidou P, McCauley SR, Bigler ED et al (2013) Centrum semiovale and corpus callosum integrity in relation to information processing speed in patients with severe traumatic brain injury. J Head Trauma Rehabil 28:433–441CrossRefPubMedGoogle Scholar
  39. 39.
    Ferrer E, Whitaker KJ, Steele JS et al (2013) White matter maturation supports the development of reasoning ability through its influence on processing speed. Dev Sci 16:941–951PubMedPubMedCentralGoogle Scholar
  40. 40.
    Alexander AL, Hasan KM, Lazar M et al (2001) Analysis of partial volume effects in diffusion-tensor MRI. Magn Reson Med 45:770–780CrossRefPubMedGoogle Scholar
  41. 41.
    Frank LR (2001) Anisotropy in high angular resolution diffusion-weighted MRI. Magn Reson Med 45:935–939CrossRefPubMedGoogle Scholar
  42. 42.
    Oouchi H, Yamada K, Sakai K et al (2007) Diffusion anisotropy measurement of brain white matter is affected by voxel size: underestimation occurs in areas with crossing fibers. AJNR Am J Neuroradiol 28:1102–1106CrossRefPubMedGoogle Scholar
  43. 43.
    Pfefferbaum A, Sullivan EV (2003) Increased brain white matter diffusivity in normal adult aging: relationship to anisotropy and partial voluming. Magn Reson Med 49:953–961CrossRefPubMedGoogle Scholar
  44. 44.
    Yuan W, Mangano FT, Air EL et al (2009) Anisotropic diffusion properties in infants with hydrocephalus: a diffusion tensor imaging study. AJNR Am J Neuroradiol 30:1792–1798CrossRefPubMedGoogle Scholar
  45. 45.
    Patel SK, Yuan W, Mangano FT (2017) Advanced neuroimaging techniques in pediatric hydrocephalus. Pediatr Neurosurg. doi: 10.1159/000454717
  46. 46.
    Siasios I, Kapsalaki EZ, Fountas KN et al (2016) The role of diffusion tensor imaging and fractional anisotropy in the evaluation of patients with idiopathic normal pressure hydrocephalus: a literature review. Neurosurg Focus 41:E12CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • Monwabisi Makola
    • 1
  • M. Douglas Ris
    • 2
  • E. Mark Mahone
    • 3
    • 4
  • Keith Owen Yeates
    • 5
  • Kim M. Cecil
    • 6
    • 7
    • 8
    • 9
    • 10
    Email author
  1. 1.College of MedicineUniversity of CincinnatiCincinnatiUSA
  2. 2.Department of Pediatrics, Baylor College of MedicineTexas Children’s HospitalHoustonUSA
  3. 3.Department of NeuropsychologyKennedy Krieger InstituteBaltimoreUSA
  4. 4.Department of Psychiatry & Behavioral SciencesJohns Hopkins University School of MedicineBaltimoreUSA
  5. 5.Department of Psychology, Alberta Children’s Hospital Research Institute, Hotchkiss Brain InstituteUniversity of CalgaryCalgaryCanada
  6. 6.Imaging Research Center, Cincinnati Children’s Hospital Medical CenterCincinnatiUSA
  7. 7.Department of RadiologyUniversity of Cincinnati College of MedicineCincinnatiUSA
  8. 8.Department of PediatricsUniversity of Cincinnati College of MedicineCincinnatiUSA
  9. 9. Neuroscience Graduate ProgramUniversity of Cincinnati College of MedicineCincinnatiUSA
  10. 10.Department of Environmental HealthUniversity of Cincinnati College of MedicineCincinnatiUSA

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