Cerebral microbleeds in adult survivors of childhood acute lymphoblastic leukemia treated with cranial radiation.
Adult
Cancer Survivors
/ psychology
Cerebral Hemorrhage
/ diagnostic imaging
Cranial Irradiation
/ adverse effects
Cross-Sectional Studies
Dose-Response Relationship, Radiation
Female
Frontal Lobe
/ diagnostic imaging
Humans
Magnetic Resonance Imaging
/ methods
Male
Mental Status and Dementia Tests
Precursor Cell Lymphoblastic Leukemia-Lymphoma
/ radiotherapy
Retrospective Studies
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
20 01 2020
20 01 2020
Historique:
received:
30
07
2019
accepted:
03
01
2020
entrez:
22
1
2020
pubmed:
22
1
2020
medline:
18
11
2020
Statut:
epublish
Résumé
Cranial radiation therapy is associated with white matter-specific brain injury, cortical volume loss, mineralization, microangiopathy and neurocognitive impairment in survivors of childhood acute lymphoblastic leukemia. In this retrospective cross-sectional analysis, neurocognitive testing and 3 T brain MRI's were obtained in 101 survivors treated with cranial radiation. Small focal intracerebral hemorrhages only visible on exquisitely sensitive MRI sequences were identified and localized using susceptibility weighted imaging. Modified Poisson regression was used to assess the effect of cranial radiation on cumulative number and location of microbleeds in each brain region, and multiple linear regression was used to evaluate microbleeds on neurocognitive outcomes, adjusting for age at diagnosis and sex. At least one microbleed was present in 85% of survivors, occurring more frequently in frontal lobes. Radiation dose of 24 Gy conveyed a 5-fold greater risk (95% CI 2.57-10.32) of having multiple microbleeds compared to a dose of 18 Gy. No significant difference was found in neurocognitive scores with either the absence or presence of microbleeds or their location. Greater prevalence of microbleeds in our study compared to prior reports is likely related to longer time since treatment, better sensitivity of SWI for detection of microbleeds and the use of a 3 T MRI platform.
Identifiants
pubmed: 31959839
doi: 10.1038/s41598-020-57682-8
pii: 10.1038/s41598-020-57682-8
pmc: PMC6971068
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
692Subventions
Organisme : NCI NIH HHS
ID : T32 CA225590
Pays : United States
Organisme : NCI NIH HHS
ID : R25 CA023944
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA138998
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA021765
Pays : United States
Organisme : NIAAA NIH HHS
ID : U01 AA016647
Pays : United States
Références
Mulhern, R. K., Fairclough, D. & Ochs, J. A prospective comparison of neuropsychologic performance of children surviving leukemia who received 18-Gy, 24-Gy, or no cranial irradiation. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 9, 1348–1356, https://doi.org/10.1200/jco.1991.9.8.1348 (1991).
doi: 10.1200/jco.1991.9.8.1348
Spiegler, B. J., Bouffet, E., Greenberg, M. L., Rutka, J. T. & Mabbott, D. J. Change in neurocognitive functioning after treatment with cranial radiation in childhood. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 22, 706–713, https://doi.org/10.1200/JCO.2004.05.186 (2004).
doi: 10.1200/JCO.2004.05.186
Krull, K. R. et al. Neurocognitive outcomes decades after treatment for childhood acute lymphoblastic leukemia: a report from the St Jude lifetime cohort study. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 31, 4407–4415, https://doi.org/10.1200/jco.2012.48.2315 (2013).
doi: 10.1200/jco.2012.48.2315
Koike, S. et al. Asymptomatic radiation-induced telangiectasia in children after cranial irradiation: frequency, latency, and dose relation. Radiology 230, 93–99, https://doi.org/10.1148/radiol.2301021143 (2004).
doi: 10.1148/radiol.2301021143
pubmed: 14645879
Greene-Schloesser, D. et al. Radiation-induced brain injury: A review. Front Oncol 2, 73, https://doi.org/10.3389/fonc.2012.00073 (2012).
doi: 10.3389/fonc.2012.00073
pubmed: 22833841
pmcid: 3400082
Edelmann, M. N. et al. Diffusion tensor imaging and neurocognition in survivors of childhood acute lymphoblastic leukaemia. Brain 137, 2973–2983, https://doi.org/10.1093/brain/awu230 (2014).
doi: 10.1093/brain/awu230
pubmed: 25125614
pmcid: 4208463
Akoudad, S. et al. Cerebral Microbleeds Are Associated With an Increased Risk of Stroke: The Rotterdam Study. Circulation 132, 509–516, https://doi.org/10.1161/CIRCULATIONAHA.115.016261 (2015).
doi: 10.1161/CIRCULATIONAHA.115.016261
pubmed: 26137955
Barnaure, I. et al. Clinicoradiologic Correlations of Cerebral Microbleeds in Advanced Age. AJNR Am J Neuroradiol 38, 39–45, https://doi.org/10.3174/ajnr.A4956 (2017).
doi: 10.3174/ajnr.A4956
pubmed: 27686485
Chan, M. S., Roebuck, D. J., Yuen, M. P., Li, C. K. & Chan, Y. L. MR imaging of the brain in patients cured of acute lymphoblastic leukemia–the value of gradient echo imaging. AJNR Am J Neuroradiol 27, 548–552 (2006).
pubmed: 16551991
Roddy, E. et al. Presence of cerebral microbleeds is associated with worse executive function in pediatric brain tumor survivors. Neuro Oncol 18, 1548–1558, https://doi.org/10.1093/neuonc/now163 (2016).
doi: 10.1093/neuonc/now163
pubmed: 27540084
pmcid: 5063522
Chung, C. P. et al. Strictly Lobar Cerebral Microbleeds Are Associated With Cognitive Impairment. Stroke 47, 2497–2502, https://doi.org/10.1161/STROKEAHA.116.014166 (2016).
doi: 10.1161/STROKEAHA.116.014166
pubmed: 27625380
Faraci, M. et al. Magnetic resonance imaging in childhood leukemia survivors treated with cranial radiotherapy: a cross sectional, single center study. Pediatr Blood Cancer 57, 240–246, https://doi.org/10.1002/pbc.22923 (2011).
doi: 10.1002/pbc.22923
pubmed: 21671360
Haacke, E. M., Xu, Y., Cheng, Y. C. & Reichenbach, J. R. Susceptibility weighted imaging (SWI). Magn Reson Med 52, 612–618, https://doi.org/10.1002/mrm.20198 (2004).
doi: 10.1002/mrm.20198
pubmed: 15334582
Neu, M. A. et al. Susceptibility-weighted magnetic resonance imaging of cerebrovascular sequelae after radiotherapy for pediatric brain tumors. Radiother Oncol 127, 280–286, https://doi.org/10.1016/j.radonc.2018.03.010 (2018).
doi: 10.1016/j.radonc.2018.03.010
pubmed: 29605477
Morrison, M. A. et al. Risk factors of radiotherapy-induced cerebral microbleeds and serial analysis of their size compared with white matter changes: A 7T MRI study in 113 adult patients with brain tumors. J Magn Reson Imaging. https://doi.org/10.1002/jmri.26651 (2019).
doi: 10.1002/jmri.26651
pubmed: 30663150
Larson, J. J., Ball, W. S., Bove, K. E., Crone, K. R. & Tew, J. M. Jr. Formation of intracerebral cavernous malformations after radiation treatment for central nervous system neoplasia in children. J Neurosurg 88, 51–56, https://doi.org/10.3171/jns.1998.88.1.0051 (1998).
doi: 10.3171/jns.1998.88.1.0051
pubmed: 9420072
Heckl, S., Aschoff, A. & Kunze, S. Radiation-induced cavernous hemangiomas of the brain: a late effect predominantly in children. Cancer 94, 3285–3291, https://doi.org/10.1002/cncr.10596 (2002).
doi: 10.1002/cncr.10596
pubmed: 12115362
Shams, S. et al. SWI or T2*: which MRI sequence to use in the detection of cerebral microbleeds? The Karolinska Imaging Dementia Study. AJNR Am J Neuroradiol 36, 1089–1095, https://doi.org/10.3174/ajnr.A4248 (2015).
doi: 10.3174/ajnr.A4248
pubmed: 25698623
Trimble, M. Body image and the parietal lobes. CNS Spectr 12, 540–544 (2007).
doi: 10.1017/S1092852900021283
Haacke, E. M., Mittal, S., Wu, Z., Neelavalli, J. & Cheng, Y. C. Susceptibility-weighted imaging: technical aspects and clinical applications, part 1. AJNR Am J Neuroradiol 30, 19–30, https://doi.org/10.3174/ajnr.A1400 (2009).
doi: 10.3174/ajnr.A1400
pubmed: 19039041
Wechsler, D. Wechsler Abbreviated Scale of Intelligence-second edition, Manual. (Pearson, 2011).
Woodcock, R. W., McGrew, K. S. & Mather, N. Woodcock-Johnson III tests of achievement. (Riverside Pub., 2001).
Reitan, R. M. T M Test, Manual. (Reitan Neuropyschology Laboratory, 1992).
Conners, C. K. The Computerized Continuous Performance-Test. Psychopharmacology Bulletin 21, 891–892 (1985).
pubmed: 4089110
Wechsler, D. Wechsler Adult Intelligence Scale -third edition, Manual. (NCS Pearson, 1997).
Delis, D. C., Kramer, J. H., Kaplan, E., &Ober, B. A. California Verbal Learning Test -second edition. Adult Version Manual. (Psychological Corporation, 2000).
Merker, B. & Podell, K. In Encyclopedia of Clinical Neuropsychology (eds Jeffrey S. Kreutzer, John DeLuca, & Bruce Caplan) 1176–1178 (Springer New York, 2011).
Stroop, J. R. Studies of interference in serial verbal reactions, George Peabody College for Teachers (1935).
Gloia, G. A., Isquith, P.K., Guy, S.C. & Kenworthy, L. Behavior Rating Inventory of Executive Function- second edition, Manual. (PAR inc., 2015).
Passos, J. et al. Microbleeds and cavernomas after radiotherapy for paediatric primary brain tumours. J Neurol Sci 372, 413–416, https://doi.org/10.1016/j.jns.2016.11.005 (2017).
doi: 10.1016/j.jns.2016.11.005
pubmed: 27856004
Zabramski, J. M. et al. The natural history of familial cavernous malformations: results of an ongoing study. J Neurosurg 80, 422–432, https://doi.org/10.3171/jns.1994.80.3.0422 (1994).
doi: 10.3171/jns.1994.80.3.0422
pubmed: 8113854
Penny, W. D., Friston, K. J., Ashburner, J. T., Kiebel, S. J. & Nichols, T. E. Statistical parametric mapping: the analysis of functional brain images. (Elsevier, 2011).
Lancaster, J. L. et al. Bias between MNI and Talairach coordinates analyzed using the ICBM-152 brain template. Hum Brain Mapp 28, 1194–1205, https://doi.org/10.1002/hbm.20345 (2007).
doi: 10.1002/hbm.20345
pubmed: 17266101
Fox, P. T. & Lancaster, J. L. Opinion: Mapping context and content: the BrainMap model. Nat Rev Neurosci 3, 319–321, https://doi.org/10.1038/nrn789 (2002).
doi: 10.1038/nrn789
pubmed: 11967563
Fox, P. T. et al. BrainMap taxonomy of experimental design: description and evaluation. Hum Brain Mapp 25, 185–198, https://doi.org/10.1002/hbm.20141 (2005).
doi: 10.1002/hbm.20141