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Susceptibility-weighted MR imaging of radiation therapy-induced cerebral microbleeds in patients with glioma: a comparison between 3T and 7T

  • Diagnostic Neuroradiology
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Abstract

Introduction

Cerebral microbleeds have been observed in normal-appearing brain tissue of patients with glioma years after receiving radiation therapy. The contrast of these paramagnetic lesions varies with field strength due to differences in the effects of susceptibility. The purpose of this study was to compare 3T and 7T MRI as platforms for detecting cerebral microbleeds in patients treated with radiotherapy using susceptibility-weighted imaging (SWI).

Methods

SWI was performed with both 3T and 7T MR scanners on ten patients with glioma who had received prior radiotherapy. Imaging sequences were optimized to obtain data within a clinically acceptable scan time. Both T2*-weighted magnitude images and SWI data were reconstructed, minimum intensity projection was implemented, and microbleeds were manually identified. The number of microbleeds was counted and compared among datasets.

Results

Significantly more microbleeds were identified on SWI than magnitude images at both 7T (p = 0.002) and 3T (p = 0.023). Seven-tesla SWI detected significantly more microbleeds than 3T SWI for seven out of ten patients who had tumors located remote from deep brain regions (p = 0.016), but when the additional three patients with more inferior tumors were included, the difference was not significant.

Conclusion

SWI is more sensitive for detecting microbleeds than magnitude images at both 3T and 7T. For areas without heightened susceptibility artifacts, 7T SWI is more sensitive to detecting radiation therapy-induced microbleeds than 3T SWI. Tumor location should be considered in conjunction with field strength when selecting the most appropriate strategy for imaging microbleeds.

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References

  1. Valk PE, Dillon WP (1991) Radiation-injury of the brain. Am J Neuroradiol 12(1):45–62

    CAS  PubMed  Google Scholar 

  2. Lupo JM et al (2012) 7-Tesla susceptibility-weighted imaging to assess the effects of radiotherapy on normal-appearing brain in patients with glioma. Int J Radiat Oncol Biol Phys 82(3):e493–e500

    Article  PubMed Central  PubMed  Google Scholar 

  3. Shobha N, Smith EE, Demchuk AM, Weir NU (2009) Small vessel infarcts and microbleeds associated with radiation exposure. Can J Neurol Sci 36(3):376–378

    PubMed  Google Scholar 

  4. Charidimou A, Werring DJ (2011) Cerebral microbleeds: detection, mechanisms and clinical challenges. Futur Neurol 6(5):587–611

    Article  Google Scholar 

  5. Greenberg SM et al (2009) Cerebral microbleeds: a guide to detection and interpretation. Lancet Neurol 8(2):165–174

    Article  PubMed Central  PubMed  Google Scholar 

  6. Cordonnier C, Al-Shahi Salman R, Wardlaw J (2007) Spontaneous brain microbleeds: systematic review, subgroup analyses and standards for study design and reporting. Brain 130(Pt 8):1988–2003

    Article  PubMed  Google Scholar 

  7. Theysohn JM et al (2011) 7 tesla MRI of microbleeds and white matter lesions as seen in vascular dementia. J Magn Reson Imaging 33(4):782–791

    Article  PubMed  Google Scholar 

  8. Conijn MM et al (2011) Cerebral microbleeds on MR imaging: comparison between 1.5 and 7T. AJNR Am J Neuroradiol 32(6):1043–1049

    Article  CAS  PubMed  Google Scholar 

  9. Ayaz M et al (2010) Imaging cerebral microbleeds using susceptibility weighted imaging: one step toward detecting vascular dementia. J Magn Reson Imaging 31(1):142–148

    Article  PubMed Central  PubMed  Google Scholar 

  10. Nandigam RNK et al (2009) MR imaging detection of cerebral microbleeds: effect of susceptibility-weighted imaging, section thickness, and field strength. Am J Neuroradiol 30(2):338–343

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  11. Lupo JM et al (2009) GRAPPA-based susceptibility-weighted imaging of normal volunteers and patients with brain tumor at 7 T. Magn Reson Imaging 27(4):480–488

    Article  PubMed  Google Scholar 

  12. Haacke EM et al (2004) Susceptibility weighted imaging (SWI). Magn Reson Med 52(3):612–618

    Article  PubMed  Google Scholar 

  13. Charidimou A, Krishnan A, Werring DJ, Rolf Jäger H (2013) Cerebral microbleeds: a guide to detection and clinical relevance in different disease settings. Neuroradiology 55(6):655–674

    Article  PubMed  Google Scholar 

  14. Ayaz M, Boikov AS, Haacke EM, Kido DK, Kirsch WM (2010) Imaging cerebral microbleeds using susceptibility weighted imaging: one step toward detecting vascular dementia. J Magn Reson Imaging 31(1):142–148

    Article  PubMed Central  PubMed  Google Scholar 

  15. van Norden AG, van den Berg HA, de Laat KF, Gons RA, van Dijk EJ, de Leeuw FE (2011) Frontal and temporal microbleeds are related to cognitive function: The Radboud University Nijmegen Diffusion Tensor and Magnetic Resonance Cohort (RUN DMC) Study. Stroke 42(12):3382–3386

    Article  PubMed  Google Scholar 

  16. Werring DJ, Gregoire SM, Cipolotti L (2010) Cerebral microbleeds and vascular cognitive impairment. J Neurol Sci 299:131–135

    Article  PubMed  Google Scholar 

  17. Goos JD, Kester MI, Barkhof F et al (2009) Patients with Alzheimer disease with multiple microbleeds: relation with cerebrospinal fluid biomarkers and cognition. Stroke 40:3455–3460

    Article  PubMed  Google Scholar 

  18. Kinnunen KM, Greenwood R, Powell JH, Leech R, Hawkins PC, Bonnelle V, Patel MC, Counsell SJ, Sharp DJ (2011) White matter damage and cognitive impairment after traumatic brain injury. Brain 134(Pt 2):449–463

    Article  PubMed  Google Scholar 

  19. Scheid R, Preul C, Gruber O, Wiggins C, von Cramon DY (2003) Diffuse axonal injury associated with chronic traumatic brain injury: evidence from T2*-weighted gradient-echo imaging at 3 T. AJNR Am J Neuroradiol 24(6):1049–1056

    PubMed  Google Scholar 

  20. Shaw EG (1990) Low-grade gliomas: to treat or not to treat? A radiation oncologist’s viewpoint. Arch Neurol 47(10):1138–1140

    Article  CAS  PubMed  Google Scholar 

  21. Jin Z, Xia L, Du YP (2008) Reduction of artifacts in susceptibility-weighted MR venography of the brain. J Magn Reson Imaging 28(2):327–333

    Article  PubMed Central  PubMed  Google Scholar 

  22. Liu T et al (2012) Cerebral microbleeds: burden assessment by using quantitative susceptibility mapping. Radiology 262(1):269–278

    Article  PubMed  Google Scholar 

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Acknowledgments

The authors would like to thank Andre Cote, Adam Elkhaled, Angela Jakary and Trey Jalbert for their work in MR image acquisition and Bert Jimenez and Mary McPolin for their clinical coordination of patient MR scans. This work was supported by UC Discovery grant ITL-BIO04-10148, which is an academic-industry partnership grant with General Electric Healthcare, a UCSF REAC Cohn & Simon Memorial Fund and a fellowship from the Graduate Education in Medical Sciences (GEMS) training program funded by Howard Hughes Medical Institute (HHMI).

Conflict of interest

Grant support for this project was funded in part by GE Healthcare.

Author information

Authors and Affiliations

  1. The UC Berkeley & UCSF Graduate Program in Bioengineering, University of California San Francisco, San Francisco, CA, USA

    Wei Bian & Sarah J. Nelson

  2. Department of Radiology and Biomedical Imaging, University of California San Francisco, 1700 4th Street, Byers Hall Room 303, UCSF Campus Box 2532, San Francisco, CA, 94158, USA

    Wei Bian, Christopher P. Hess, Sarah J. Nelson & Janine M. Lupo

  3. Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA

    Susan M. Chang

  4. Department of Bioengineeing and Therapeutic Sciences, University of California San Francisco, San Francisco, CA, USA

    Sarah J. Nelson

Authors
  1. Wei Bian
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  2. Christopher P. Hess
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  3. Susan M. Chang
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  4. Sarah J. Nelson
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  5. Janine M. Lupo
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Corresponding author

Correspondence to Janine M. Lupo.

Additional information

This study was presented in part at the 20th annual meeting of the International Society for Magnetic Resonance in Medicine, 2012, Melbourne, Australia.

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Bian, W., Hess, C.P., Chang, S.M. et al. Susceptibility-weighted MR imaging of radiation therapy-induced cerebral microbleeds in patients with glioma: a comparison between 3T and 7T. Neuroradiology 56, 91–96 (2014). https://doi.org/10.1007/s00234-013-1297-8

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  • DOI: https://doi.org/10.1007/s00234-013-1297-8

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