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Cited by 62Effects of Radiation ExposureCancer-related cognitive impairment studiesGlioma Diagnosis and Treatment

White and Gray Matter Abnormalities After Cranial Radiation in Children and Mice

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Nieman, Brian J., de Guzman, A. Elizabeth, Gazdzinski, Lisa M., Lerch, Jason P., Chakravarty, M. Mallar, Pipitone, Jon, Strother, Douglas, Fryer, Chris +6 more·2015·International Journal of Radiation Oncology*Biology*Physics
DOI 10.1016/j.ijrobp.2015.07.2293
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Abstract

PURPOSE: Pediatric patients treated with cranial radiation are at high risk of developing lasting cognitive impairments. We sought to identify anatomical changes in both gray matter (GM) and white matter (WM) in radiation-treated patients and in mice, in which the effect of radiation can be isolated from other factors, the time course of anatomical change can be established, and the effect of treatment age can be more fully characterized. Anatomical results were compared between species. METHODS AND MATERIALS: Patients were imaged with T1-weighted magnetic resonance imaging (MRI) after radiation treatment. Nineteen radiation-treated patients were divided into groups of 7 years of age and younger (7-) and 8 years and older (8+) and were compared to 41 controls. C57BL6 mice were treated with radiation (n=52) or sham treated (n=52) between postnatal days 16 and 36 and then assessed with in vivo and/or ex vivo MRI. In both cases, measurements of WM and GM volume, cortical thickness, area and volume, and hippocampal volume were compared between groups. RESULTS: WM volume was significantly decreased following treatment in 7- and 8+ treatment groups. GM volume was unchanged overall, but cortical thickness was slightly increased in the 7- group. Results in mice mostly mirrored these changes and provided a time course of change, showing early volume loss and normal growth. Hippocampal volume showed a decreasing trend with age in patients, an effect not observed in the mouse hippocampus but present in the olfactory bulb. CONCLUSIONS: Changes in mice treated with cranial radiation are similar to those in humans, including significant WM and GM alterations. Because mice did not receive any other treatment, the similarity across species supports the expectation that radiation is causative and suggests mice provide a representative model for studying impaired brain development after cranial radiation and testing novel treatments.

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  • In a study on the adverse impact of cranial irradiation on brain structure, brain changes in radiation-treated cancer survivors were very similar to those observed in radiation-treated mice.

    “In a study on the adverse impact of cranial irradiation on brain structure, we showed that brain changes in radiation‐treated cancer survivors were very similar to those observed in radiation‐treated mice (Nieman et al., 2015), highlighting the potential of using mice as a representative model.”

    From Brain structure, working memory and response inhibition in childhood leukemia survivors (2017) · cites this paper as Nieman et al., 2015

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Research works printed but not linked: 47

  1. Ris MD, Packer R, Goldwein J, et al. Intellectual outcome after reduced-dose radiation therapy plus adjuvant chemotherapy for me- dulloblastoma: A Children's Cancer Group study. J Clin Oncol 2001; 19:3470-3476.
  2. Mitby PA, Robison LL, Whitton JA, et al. Utilization of special education services and educational attainment among long-term survivors of childhood cancer: A report from the Childhood Cancer Survivor Study. Cancer 2003;97:1115-1126.
  3. Nathan PC, Patel SK, Dilley K, et al. Guidelines for identification of, advocacy for, and intervention in neurocognitive problems in survi- vors of childhood cancer: A report from the Children's Oncology Group. Arch Pediatr Adolesc Med 2007;161:798-806.
  4. Anderson DM, Rennie KM, Ziegler RS, et al. Medical and neuro- cognitive late effects among survivors of childhood central nervous system tumors. Cancer 2001;92:2709-2719.
  5. Schultz KA, Ness KK, Whitton J, et al. Behavioral and social out- comes in adolescent survivors of childhood cancer: A report from the childhood cancer survivor study. J Clin Oncol 2007;25:3649-3656.
  6. Palmer SL, Goloubeva O, Reddick WE, et al. Patterns of intellectual development among survivors of pediatric medulloblastoma: A lon- gitudinal analysis. J Clin Oncol 2001;19:2302-2308.
  7. Meyers CA, Smith JA, Bezjak A, et al. Neurocognitive function and progression in patients with brain metastases treated with whole- brain radiation and motexafin gadolinium: Results of a randomized phase III trial. J Clin Oncol 2004;22:157-165.
  8. Spiegler BJ, Bouffet E, Greenberg ML, et al. Change in neuro- cognitive functioning after treatment with cranial radiation in childhood. J Clin Oncol 2004;22:706-713.
  9. Ellenberg L, Liu Q, Gioia G, et al. Neurocognitive status in long-term survivors of childhood CNS malignancies: A report from the Childhood Cancer Survivor Study. Neuropsychology 2009;23:705- 717.
  10. Mulhern RK, Reddick WE, Palmer SL, et al. Neurocognitive deficits in medulloblastoma survivors and white matter loss. Ann Neurol 1999;46:834-841.
  11. Rueckriegel SM, Driever PH, Blankenburg F, et al. 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 2010;76:859-866.
  12. Riggs L, Bouffet E, Laughlin S, et al. Changes to memory structures in children treated for posterior fossa tumors. J Int Neuropsychol Soc 2014;20:168-180.
  13. Reddick WE, White HA, Glass JO, et al. Developmental model relating white matter volume to neurocognitive deficits in pediatric brain tumor survivors. Cancer 2003;97:2512-2519.
  14. Khong PL, Leung LH, Fung AS, et al. White matter anisotropy in post-treatment childhood cancer survivors: Preliminary evidence of association with neurocognitive function. J Clin Oncol 2006;24: 884-890.
  15. Mabbott DJ, Noseworthy MD, Bouffet E, et al. Diffusion tensor imaging of white matter after cranial radiation in children for me- dulloblastoma: correlation with IQ. Neuro Oncol 2006;8:244-252.
  16. Landier W, Bhatia S. Cancer survivorship: A pediatric perspective. Oncologist 2008;13:1181-1192.
  17. Rola R, Raber J, Rizk A, et al. Radiation-induced impairment of hippocampal neurogenesis is associated with cognitive deficits in young mice. Exp Neurol 2004;188:316-330.
  18. Rao AA, Ye H, Decker PA, et al. Therapeutic doses of cranial irra- diation induce hippocampus-dependent cognitive deficits in young mice. J Neurooncol 2011;105:191-198.
  19. Karlsson N, Kalm M, Nilsson MK, et al. Learning and activity after irradiation of the young mouse brain analyzed in adulthood using unbiased monitoring in a home cage environment. Radiat Res 2011; 175:336-346.
  20. Nieman BJ, Lerch JP, Bock NA, et al. Mouse behavioral mutants have neuroimaging abnormalities. Hum Brain Mapp 2007;28:567- 575.
  21. Gazdzinski LM, Cormier K, Lu FG, et al. Radiation-induced alterations in mouse brain development characterized by magnetic resonance imaging. Int J Radiat Oncol Biol Phys 2012;84:e631- e638.
  22. de Guzman AE, Gazdzinski LM, Alsop RJ, et al. Treatment age, dose and sex determine neuroanatomical outcome in irradiated juvenile mice. Radiat Res 2015;183:541-549.
  23. Grill J, Renaux VK, Bulteau C, et al. Long-term intellectual outcome in children with posterior fossa tumors according to radiation doses and volumes. Int J Radiat Oncol Biol Phys 1999;45:137-145.
  24. Law N, Bouffet E, Laughlin S, et al. Cerebello-thalamo-cerebral connections in pediatric brain tumor patients: impact on working memory. Neuroimage 2011;56:2238-2248.
  25. Law N, Greenberg M, Bouffet E, et al. Clinical and neuroanatomical predictors of cerebellar mutism syndrome. Neuro Oncol 2012;14: 1294-1303.
  26. Zijdenbos AP, Forghani R, Evans AC. Automatic "pipeline" analysis of 3-D MRI data for clinical trials: Application to multiple sclerosis. IEEE Trans Med Imaging 2002;21:1280-1291.
  27. Collins DL, Neelin P, Peters TM, et al. Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 1994;18:192-205.
  28. Sled JG, Zijdenbos AP, Evans AC. A nonparametric method for automatic correction of intensity nonuniformity in MRI data. IEEE Trans Med Imaging 1998;17:87-97.
  29. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 2001;20:45-57.
  30. Kim JS, Singh V, Lee JK, et al. Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification. Neuroimage 2005;27: 210-221.
  31. Lyttelton O, Boucher M, Robbins S, et al. An unbiased iterative group registration template for cortical surface analysis. Neuroimage 2007;34:1535-1544.
  32. Lerch JP, Evans AC. Cortical thickness analysis examined through power analysis and a population simulation. Neuroimage 2005;24: 163-173.
  33. Chakravarty MM, Steadman P, van Eede MC, et al. Performing label- fusion-based segmentation using multiple automatically generated templates. Hum Brain Mapp 2013;34:2635-2654.
  34. Winterburn JL, Pruessner JC, Chavez S, et al. A novel in vivo atlas of human hippocampal subfields using high-resolution 3 T magnetic resonance imaging. Neuroimage 2013;74:254-265.
  35. Pipitone J, Park MT, Winterburn J, et al. Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates. Neuroimage 2014;101:494-512.
  36. Nieman BJ, Flenniken AM, Adamson SL, et al. Anatomical pheno- typing in the brain and skull of a mutant mouse by magnetic reso- nance imaging and computed tomography. Physiol Genomics 2006; 24:154-162.
  37. Dorr AE, Lerch JP, Spring S, et al. High resolution three-dimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice. Neuroimage 2008;42:60-69.
  38. Lerch JP, Carroll JB, Spring S, et al. Automated deformation analysis in the YAC128 Huntington disease mouse model. Neuroimage 2008; 39:32-39.
  39. Zilles K, Armstrong E, Schleicher A, et al. The human pattern of gyrification in the cerebral cortex. Anat Embryol (Berl) 1988;179: 173-179.
  40. Reddick WE, Shan ZY, Glass JO, et al. Smaller white-matter vol- umes are associated with larger deficits in attention and learning among long-term survivors of acute lymphoblastic leukemia. Cancer 2006;106:941-949.
  41. Courchesne E, Chisum HJ, Townsend J, et al. Normal brain devel- opment and aging: Quantitative analysis at in vivo MR imaging in healthy volunteers. Radiology 2000;216:672-682.
  42. Shaw P, Kabani NJ, Lerch JP, et al. Neurodevelopmental trajectories of the human cerebral cortex. J Neurosci 2008;28:3586-3594.
  43. Webb SJ, Monk CS, Nelson CA. Mechanisms of postnatal neurobi- ological development: Implications for human development. Dev Neuropsychol 2001;19:147-171.
  44. Liu AK, Marcus KJ, Fischl B, et al. Changes in cerebral cortex of children treated for medulloblastoma. Int J Radiat Oncol Biol Phys 2007;68:992-998.
  45. Spalding KL, Bergmann O, Alkass K, et al. Dynamics of hippo- campal neurogenesis in adult humans. Cell 2013;153:1219-1227.
  46. Ninkovic J, Mori T, Go ¨tz M. Distinct modes of neuron addition in adult mouse neurogenesis. J Neurosci 2007;27:10906-10911.
  47. Clarkson R, Lindsay PE, Ansell S, et al. Characterization of image quality and image-guidance performance of a preclinical micro- irradiator. Med Phys 2011;38:845-856.

Cited by

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  • Brain structure, working memory and response inhibition in childhood leukemia survivors

    van der Plas, E., Schachar, R. J., Hitzler, J., Crosbie, J., Guger, S. L., Spiegler, B. J., Ito, S., & Nieman, B. J. (2017) · Brain and Behavior · doi:10.1002/brb3.621 · Cited by 59 · see citing works

    “In a study on the adverse impact of cranial irradiation on brain structure, we showed that brain changes in radiation- treated cancer survivors were very similar to those observed in radiation- treated mice (Nieman et al., 2015), highlighting the potential of using mice as a representative model.”
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Authors
Nieman, B. J., de Guzman, A. E., Gazdzinski, L. M., Lerch, J. P., Chakravarty, M. M., Pipitone, J., Strother, D., Fryer, C., Bouffet, E., Laughlin, S., Laperriere, N., Riggs, L., Skocic, J., & Mabbott, D. J.
Affiliations
  • Ontario Institute for Cancer Research (CA)
  • Hospital for Sick Children (CA)
  • University of Toronto (CA)
  • Douglas Mental Health University Institute (CA)
  • Centre for Addiction and Mental Health (CA)
  • University of Calgary (CA)
  • University of British Columbia (CA)
Corresponding author
Nieman, Brian J.
ORCID
Venue
International Journal of Radiation Oncology*Biology*Physics
Publisher
Elsevier BV
Published
2015-11
Volume
93
Issue
4
Pages
882-891
ISSN
0360-3016 (ISSN-L)
DOI
10.1016/j.ijrobp.2015.07.2293
OpenAlex
W1938203438
Cited by
62
References
5
Citations by year
2026: 2 · 2025: 5 · 2024: 4 · 2023: 7 · 2022: 8 · 2021: 7 · 2020: 6 · 2019: 5 · 2018: 8 · 2017: 4 · 2016: 6
FWCI
4.87
Type
journal article
Language
en
Open access
Licence
Locations
  • International Journal of Radiation Oncology*Biology*Physics (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • TSpace (University of Toronto) (submittedVersion, cc-by-nc-nd)
Funders
  • Ontario Institute for Cancer Research
  • Government of Ontario
  • Canadian Institutes of Health Research
  • Natural Sciences and Engineering Research Council of Canada
Topics
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Effects of Radiation Exposure
  • Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Cancer-related cognitive impairment studies
  • Health Sciences › Medicine › Genetics › Glioma Diagnosis and Treatment
Keywords
cranial irradiation, pediatric radiotherapy, white matter loss, gray matter volume, cortical thickness, hippocampal volume, olfactory bulb, radiation-induced cognitive impairment, brain development, mouse model, treatment age, species comparison
MeSH terms
Animals, Cerebral Cortex, Child, Hippocampus, Humans, Magnetic Resonance Imaging, Mice, Inbred C57BL, Radiation Dosage, Radiation Injuries, Radiation Injuries, Experimental, Retrospective Studies, Time Factors, Case-Control Studies, Cranial Irradiation, Models, Animal, Mice, White Matter, Gray Matter

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