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Relationship between 7T MR-angiography features of vascular injury and cognitive decline in young brain tumor patients treated with radiation therapy

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Purpose

Although radiation therapy (RT) is a common treatment for pediatric brain tumors, it is associated with detrimental long-term effects such as impaired cognition, vascular injury, and increased stroke risk. This study aimed to develop metrics that describe vascular injury and relate them to the presence of cerebral microbleeds (CMBs) and cognitive performance scores.

Methods

Twenty-five young adult survivors of pediatric brain tumors treated with either whole-brain (n = 12), whole-ventricular (n = 7), or no RT (n = 6) underwent 7T MRI and neurocognitive testing. Simultaneously acquired MR angiography and susceptibility-weighted images were used to segment CMBs and vessels and quantify their radii and volume.

Results

Patients treated with whole-brain RT had significantly lower arterial volumes (p = 0.003) and a higher proportion of smaller vessels (p = 0.003) compared to the whole-ventricular RT and non-irradiated control patients. Normalized arterial volume decreased with increasing CMB count (R = − 0.66, p = 0.003), and decreasing trends were observed with time since RT and at longitudinal follow-up. Global cognition and verbal memory significantly decreased with smaller normalized arterial volume (p ≤ 0.05).

Conclusions

Arterial volume is reduced with increasing CMB presence and is influenced by the total brain volume exposed to radiation. This work highlights the potential use of vascular-derived metrics as non-invasive markers of treatment-induced injury and cognitive impairment in pediatric brain tumor patients.

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References

  1. https://www.cancer.org/cancer/cancer-in-children/types-of-childhood-cancers.html

  2. https://www.childrensoncologygroup.org/index.php/braintumors

  3. Knab B, Connell PP (2007) Radiotherapy for pediatric brain tumors: when and how. Expert Rev Anticancer Ther 7(sup1):S69–S77

    Article  Google Scholar 

  4. Taphoorn MJ, Klein M (2004) Cognitive deficits in adult patients with brain tumors. Lancet Neurol 3(3):159–168

    Article  Google Scholar 

  5. Lupo JM, Chuang CF, Chang SM, Barani IJ, Jimenez B, Hess CP, Nelson SJ (2012) 7-Tesla susceptibility-weighted imaging to assess the effects of radiotherapy on normal-appearing brain in patients with glioma. Int J RadiatOncolBiolPhys 82(3):e493-500

    Google Scholar 

  6. Greene-Schloesser D, Robbins ME, Peiffer AM, Shaw EG, Wheeler KT, Chan MD (2012) Radiation-induced brain injury: a review. Front Oncol 2:73

    Article  CAS  Google Scholar 

  7. Campen CJ, Kranick SM, Kasner SE et al (2012) Cranial irradiation increases risk of stroke in pediatric brain tumor survivors. Stroke J CerebCirc 43(11):3035–3040

    Article  Google Scholar 

  8. Wahl M, Anwar M, Hess CP, Chang SM, Lupo JM (2017) Relationship between radiation dose and microbleed formation in patients with malignant glioma. RadiatOncol 12(1):12

    Google Scholar 

  9. Lupo JM, Molinaro AM, Essock-Burns E, Butowski N, Chang SM, Cha S, Nelson SJ (2016) The effects of anti-angiogenic therapy on the formation of radiation-induced microbleeds in normal brain tissue of patients with glioma. NeuroOncol 18(1):87–95

    Google Scholar 

  10. Morrison MA, Hess CP, Clarke JL, Butowski N, Chang SM, Molinaro AM, Lupo JM (2019) 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 MagnReson Imaging 50(3):868–877

    Article  Google Scholar 

  11. Deshpande SS, Donneys A, Farberg AS, Tchanque-Fossuo CN, Felice PA, Buchman SR (2014) Quantification and characterization of radiation-induced changes to mandibular vascularity using micro-computed tomography. Ann PlastSurg 72(1):100–103

    CAS  Google Scholar 

  12. Gutierrez J, Cheung K, Bagci A et al (2015) Brain arterial diameters as a risk factor for vascular events. J Am Heart Assoc 4(8):e002289

    Article  Google Scholar 

  13. Mazighi M, Labreuche J, Gongora-Rivera F, Duyckaerts C, Hauw JJ, Amarenco P (2009) Autopsy prevalence of proximal extracranial atherosclerosis in patients with fatal stroke. Stroke 40(3):713–718

    Article  Google Scholar 

  14. Roth NM, Sontag MR, Kiani MF (1999) Early effects of ionizing radiation on the microvascular networks in normal tissue. Radiat Res 151(3):270–277

    Article  CAS  Google Scholar 

  15. Cole FM, Yates P (1967) Intracerebralmicroaneurysms and small cerebrovascular lesions. Brain 90:759–768

    Article  CAS  Google Scholar 

  16. Haacke EM, Xu Y, Cheng YC, Reichenbach JR (2004) Susceptibility weighted imaging (SWI). MagnReson Med 52(3):612–618

    Article  Google Scholar 

  17. Lupo JM, Banerjee S, Hammond KE, Kelley DA, Xu D, Chang SM, Vigneron DB, Majumdar S, Nelson SJ (2009) GRAPPA-based susceptibility-weighted imaging of normal volunteers and patients with brain tumor at 7 T. MagnReson Imaging 27(4):480–488

    Article  Google Scholar 

  18. Bian W, Hess CP, Chang SM, Nelson SJ, Lupo JM (2014) Susceptibility-weighted MR imaging of radiation therapy-induced cerebral microbleeds in patients with glioma: a comparison between 3T and 7T. Neuroradiology 56(2):91–96

    Article  Google Scholar 

  19. Roddy E, Sear K, Felton E et al (2016) Presence of cerebral microbleeds is associated with worse executive function in pediatric brain tumor survivors. NeuroOncol 18(11):1548–1558

    Google Scholar 

  20. Akers A, Al-Shahi Salman R, Awad IA et al (2017) Synopsis of guidelines for the clinical management of cerebral cavernous malformations: consensus recommendations based on systematic literature review by the angioma alliance scientific advisory board clinical experts panel. Neurosurgery 80:665–680

    Article  Google Scholar 

  21. Salehi A, Zhang JH, Obenaus A (2017) Response of the cerebral vasculature following traumatic brain injury. J Cereb Blood Flow Metab 37(7):2320–2339

    Article  Google Scholar 

  22. Poels MMF, Ikram MA, Van Der Lugt A, Hofman A, Niessen WJ, Krestin GP, Breteler MM, Vernooij MW (2012) Cerebral microbleeds are associated with worse cognitive function: the rotterdam scan study. Neurology 78(5):326–333

    Article  CAS  Google Scholar 

  23. Maruff P, Thomas E, Cysique L et al (2009) Validity of the CogState brief battery: relationship to standardized tests and sensitivity to cognitive impairment in mild traumatic brain injury, schizophrenia, and AIDS dementia complex. Arch ClinNeuropsychol 24(2):165–178

    Article  Google Scholar 

  24. Morrison MA, Mueller S, Felton E et al (2021) Rate of radiation-induced microbleed formation on 7T MRI relates to cognitive impairment in young patients treated with radiation therapy for a brain tumor. Radiother Oncol 154(1):145–153

    Article  CAS  Google Scholar 

  25. Bian W, Banerjee S, Kelly DA et al (2015) Simultaneous imaging of radiation-induced cerebral microbleeds, arteries and veins, using a multiple gradient echo sequence at 7 Tesla. J MagnReson Imaging 42(2):269–279

    Article  Google Scholar 

  26. Smith SM (2002) Fast robust automated brain extraction. Ann Meet Organ Hum Brain Mapp 17(3):143–155

    Article  Google Scholar 

  27. Avadiappan S, Payabvash S, Morrison MA et al (2020) A fully automated method for segmenting arteries and quantifying vessel radii on magnetic resonance angiography images of varying projection thickness. Frontiers Neurosci Brain Imaging Methods 14:537

    Google Scholar 

  28. Frangi AF, Niessen WJ, Vincken KL, Viergever MA (1998) Multiscale vessel enhancement filtering. In: Proceedings of medical image computing and computer-assisted intervention (MICCAI.), pp 130–137

  29. Sethian JA (1996) A fast marching level set method for monotonically advancing fronts. ProcNatlAcadSci USA 93(4):1591–1595

    Article  CAS  Google Scholar 

  30. Bullitt E, Zeng D, Mortamet B et al (2010) The effects of healthy aging on intracerebral blood vessels visualized by magnetic resonance angiography. Neurobiol Aging 31(2):290–300

    Article  Google Scholar 

  31. Bian W, Hess CP, Chang SM, Nelson SJ, Lupo JM (2013) Computer-aided detection of radiation-induced cerebral microbleeds on susceptibility-weighted MR images. NeuroimageClin 2(1):282–290

    Google Scholar 

  32. Bullitt E, Lin NU, Smith KJ et al (2009) Blood vessel morphological changes as visualized by MRA during treatment of brain metastases: a feasibility study. Radiology 245(3):824–830

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by NIH-NICHD grant RO1HD079568 and funding from the La Roche family. We thank all the patients and families for their participation in this study.

Funding

This work was supported by NIH-NICHD grant RO1HD079568 as well as the La Roche family.

Author information

Author notes

  1. Erin Felton

    Present address: The George Washington University School of Medicine and Health Sciences, Washington, DC, USA

Authors and Affiliations

  1. Department of Radiology and Biomedical Imaging, University of California, San Francisco, Byers Hall, 1700 4th Street, Suite 303D, Box 2532, San Francisco, CA, 94158-2330, USA

    Sivakami Avadiappan, Melanie A. Morrison, Angela Jakary, Christopher P. Hess & Janine M. Lupo

  2. Department of Neurology, University of California, San Francisco, CA, USA

    Erin Felton, Schuyler Stoller, Christopher P. Hess & Sabine Mueller

  3. Department of Neurosurgery, University of California, San Francisco, CA, USA

    Annette M. Molinaro & Sabine Mueller

  4. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA

    Annette M. Molinaro

  5. Department of Radiation Oncology, University of California, San Francisco, CA, USA

    Steve E. Braunstein

  6. Department of Pediatrics, University of California, San Francisco, CA, USA

    Sabine Mueller

  7. University Children’s Hospital Zurich, Zurich, Switzerland

    Sabine Mueller

  8. UCSF/UC Berkeley Graduate Program in Bioengineering, Berkeley and San Francisco, CA, USA

    Janine M. Lupo

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  1. Sivakami Avadiappan
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Contributions

Study design: JML, SM. Data collection: AJ, EF, SS. Image processing and analysis: SA, MAM. Statistical analysis: SA, AMM, MAM. Data interpretation: JML, SA, SM, AMM, SEB, CPH. Manuscript preparation: SA, MAM, JML. All authors approved the final manuscript content.

Corresponding author

Correspondence to Janine M. Lupo.

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Conflict of interest

The authors have no conflict of interest to report with respect to this study.

Ethical approval

This study was approved by our institutional review board and performed in accordance with the ethical standards of the institutional and national research committees or comparable ethical standards. Written informed consent, or assent when appropriate, was obtained from all individual participants and additional parental consent was obtained for all minors.

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All work was performed while at UCSF.

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Avadiappan, S., Morrison, M.A., Jakary, A. et al. Relationship between 7T MR-angiography features of vascular injury and cognitive decline in young brain tumor patients treated with radiation therapy. J Neurooncol 153, 143–152 (2021). https://doi.org/10.1007/s11060-021-03753-3

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  • DOI: https://doi.org/10.1007/s11060-021-03753-3

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