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Neurocritical Care

, Volume 22, Issue 1, pp 74–81 | Cite as

Brain Injury Visible on Early MRI After Subarachnoid Hemorrhage Might Predict Neurological Impairment and Functional Outcome

  • Gian Marco De Marchis
  • Christopher G. Filippi
  • Xiaotao Guo
  • Deborah Pugin
  • Christopher D. Gaffney
  • Neha S. Dangayach
  • Sureerat Suwatcharangkoon
  • M. Cristina Falo
  • J. Michael Schmidt
  • Sachin Agarwal
  • E. Sander ConnollyJr.
  • Jan Claassen
  • Binsheng Zhao
  • Stephan A. MayerEmail author
Original Article

Abstract

Background

In subarachnoid hemorrhage (SAH), brain injury visible within 48 h of onset may impact on admission neurological disability and 3-month functional outcome. With volumetric MRI, we measured the volume of brain injury visible after SAH, and assessed the association with admission clinical grade and 3-month functional outcome.

Methods

Retrospective cohort study conducted in the Neurocritical Care Division, Columbia University Medical Center, New York, USA. On brain MRI acquired within 48 h of SAH-onset and before aneurysm-securing (n = 27), two blinded readers measured DWI and FLAIR-lesion volumes using semi-automated, computer segmentation software.

Results

Compared to post-resuscitation Hunt–Hess grade 1–3 (70 %), high-grade patients (30 %) had higher lesion volumes on DWI (34 ml [IQR: 0–64] vs. 2 ml [IQR: 0.5–7], P = 0.02) and on FLAIR (81 ml [IQR: 24–127] vs. 3 ml [IQR: 0–27], P = 0.02). On DWI, each 10 ml increase in lesion volume was associated with a 101 %-increase in the odds of presenting with 1 grade more in the Hunt–Hess scale (aOR 2.01, 95 % CI 1.10–3.68, P = 0.02), but was not significantly associated with 3-month outcome. On FLAIR, each 10 ml increase in lesion volume was associated with 34 % higher odds of a 1-point increase on the Hunt–Hess scale (aOR 1.34, 95 % CI 1.06–1.68, P = 0.01) and 139 % higher odds of a 1-point increase on the 3-month mRS (aOR 2.39, 95 % CI 1.13–5.07, P = 0.02).

Conclusion

The volume of brain injury visible on DWI and FLAIR within 48 h after SAH is proportional to neurological impairment on admission. Moreover, FLAIR-imaging implicates chronic brain injury—predating SAH—as potentially relevant cause of poor functional outcome.

Keywords

Subarachnoid hemorrhage Brain injury MRI Biomarker Neurological disability Outcome 

Notes

Acknowledgments

Gian Marco De Marchis was supported by the following Grants: Career Development Grant for junior investigators (PBBEP3_139388) by the Swiss National Science Foundation; Swisslife Jubiläumsstiftung for Medical Research; Swiss Neurological Society; Fondazione Dr. Ettore Balli (Switzerland); peer reviewed De Quervain research Grant for young clinical investigators of the Clinical Trial Unit, University of Bern (Switzerland).

Conflict of interest

Christopher G. Filippi, Xiaotao Guo, Deborah Pugin, Christopher D. Gaffney, Neha S. Dangayach, Sureerat Suwatcharangkoon, M. Cristina Falo, Michael Schmidt, Sachin Agarwal, E. Sander Connolly Jr., Jan Claassen, Binsheng Zhao, Stephan A. Mayer declare that they have no conflict of interest.

Supplementary material

Video: Example of Computed Aided Volumetry (CAV). On an axial slice of DWI, the reader is manually contouring a region of injured brain in the bilateral, parasagittal region of the frontal and parietal lobes. In a second step, the CAV software automatically localizes the boundaries of injured brain within the contoured region, excluding the surrounding non-injured brain. After contouring all injured brain regions on all slices, the software computes the total volume of injured brain. The video file format is mp4. (MP4 1,673 kb)

12028_2014_8_MOESM2_ESM.jpg (212 kb)
Supplementary material 2 (JPEG 212 kb)

References

  1. 1.
    Schmidt JM, Rincon F, Fernandez A, Resor C, Kowalski RG, Claassen J, et al. Cerebral infarction associated with acute subarachnoid hemorrhage. Neurocrit Care. 2007;7:10–7.PubMedCrossRefGoogle Scholar
  2. 2.
    Wartenberg KE, Sheth SJ, Michael Schmidt J, Frontera JA, Rincon F, Ostapkovich N, et al. Acute ischemic injury on diffusion-weighted magnetic resonance imaging after poor grade subarachnoid hemorrhage. Neurocrit Care. 2010;14:407–15.CrossRefGoogle Scholar
  3. 3.
    Hadeishi H, Suzuki A, Yasui N, Hatazawa J, Shimosegawa E. Diffusion-weighted magnetic resonance imaging in patients with subarachnoid hemorrhage. Neurosurgery. 2002;50:741–7.PubMedCrossRefGoogle Scholar
  4. 4.
    Kissela B, Lindsell CJ, Kleindorfer D, Alwell K, Moomaw CJ, Woo D, et al. Clinical prediction of functional outcome after ischemic stroke: the surprising importance of periventricular white matter disease and race. Stroke. 2009;40:530–6.PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Arsava EM, Rahman R, Rosand J, Lu J, Smith EE, Rost NS, et al. Severity of leukoaraiosis correlates with clinical outcome after ischemic stroke. Neurology. 2009;72:1403–10.PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Hunt WE, Hess RM. Surgical risk as related to time of intervention in the repair of intracranial aneurysms. J Neurosurg. 1968;28:14–20.PubMedCrossRefGoogle Scholar
  7. 7.
    Teasdale GM, Drake CG, Hunt W, Kassell N, Sano K, Pertuiset B, et al. A universal subarachnoid hemorrhage scale: report of a committee of the World Federation of Neurosurgical Societies. J Neurol Neurosurg Psychiatry. 1988;51:1457.PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Claassen J, Bernardini GL, Kreiter K, Bates J, Du YE, Copeland D, et al. Effect of cisternal and ventricular blood on risk of delayed cerebral ischemia after subarachnoid hemorrhage: the Fisher scale revisited. Stroke. 2001;32:2012–20.PubMedCrossRefGoogle Scholar
  9. 9.
    Hijdra A, Brouwers PJ, Vermeulen M, van Gijn J. Grading the amount of blood on computed tomograms after subarachnoid hemorrhage. Stroke. 1990;21:1156–61.PubMedCrossRefGoogle Scholar
  10. 10.
    Brouwers PJ, Dippel DW, Vermeulen M, Lindsay KW, Hasan D, van Gijn J. Amount of blood on computed tomography as an independent predictor after aneurysm rupture. Stroke. 1993;24:809–14.PubMedCrossRefGoogle Scholar
  11. 11.
    Broderick JP, Brott TG, Duldner JE, Tomsick T, Huster G. Volume of intracerebral hemorrhage. A powerful and easy-to-use predictor of 30-day mortality. Stroke. 1993;24:987–93.PubMedCrossRefGoogle Scholar
  12. 12.
    van Gijn J, Hijdra A, Wijdicks EF, Vermeulen M, van Crevel H. Acute hydrocephalus after aneurysmal subarachnoid hemorrhage. J Neurosurg. 1985;63:355–62.PubMedCrossRefGoogle Scholar
  13. 13.
    Claassen J, Carhuapoma JR, Kreiter KT, Du EY, Connolly ES, Mayer SA. Global cerebral edema after subarachnoid hemorrhage: frequency, predictors, and impact on outcome. Stroke. 2002;33:1225–32.PubMedCrossRefGoogle Scholar
  14. 14.
    Komotar RJ, Schmidt JM, Starke RM, Claassen J, Wartenberg KE, Lee K, et al. Resuscitation and critical care of poor-grade subarachnoid hemorrhage. Neurosurgery. 2009;64:397–410.PubMedCrossRefGoogle Scholar
  15. 15.
    Chow DS, Qi J, Guo X, Miloushev VZ, Iwamoto FM, Bruce JN, et al. Semiautomated volumetric measurement on post contrast mr imaging for analysis of recurrent and residual disease in glioblastoma multiforme. AJNR Am J Neuroradiol. 2014;35:498–503.PubMedCrossRefGoogle Scholar
  16. 16.
    van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988;19:604–7.PubMedCrossRefGoogle Scholar
  17. 17.
    Lin LI. A concordance correlation coefficient to evaluate reproducibility. Biometrics. 1989;45:255–68.PubMedCrossRefGoogle Scholar
  18. 18.
    Wartenberg KE, Schmidt JM, Claassen J, Temes RE, Frontera JA, Ostapkovich N, et al. Impact of medical complications on outcome after subarachnoid hemorrhage. Crit Care Med. 2006;34:617–23.PubMedCrossRefGoogle Scholar
  19. 19.
    Schmidt JM, Ko SB, Helbok R, Kurtz P, Stuart RM, Presciutti M, et al. Cerebral perfusion pressure thresholds for brain tissue hypoxia and metabolic crisis after poor-grade subarachnoid hemorrhage. Stroke. 2011;42:1351–6.PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Auriel E, Gurol ME, Ayres A, Dumas AP, Schwab KM, Vashkevich A, et al. Characteristic distributions of intracerebral hemorrhage-associated diffusion-weighted lesions. Neurology. 2012;79:2335–41.PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Petzold A, Keir G, Kay A, Kerr M, Thompson EJ. Axonal damage and outcome in subarachnoid haemorrhage. J Neurol Neurosurg Psychiatry. 2006;77:753–9.PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Gian Marco De Marchis
    • 1
    • 5
  • Christopher G. Filippi
    • 3
  • Xiaotao Guo
    • 3
  • Deborah Pugin
    • 1
  • Christopher D. Gaffney
    • 1
  • Neha S. Dangayach
    • 1
  • Sureerat Suwatcharangkoon
    • 1
    • 4
  • M. Cristina Falo
    • 1
  • J. Michael Schmidt
    • 1
  • Sachin Agarwal
    • 1
  • E. Sander ConnollyJr.
    • 1
  • Jan Claassen
    • 1
  • Binsheng Zhao
    • 3
  • Stephan A. Mayer
    • 1
    • 2
    Email author
  1. 1.Division of Neurocritical Care, Department of Neurology and NeurosurgeryColumbia UniversityNew YorkUSA
  2. 2.Department of Critical CareMount Sinai HospitalNew YorkUSA
  3. 3.Division of Neuroradiology, Department of RadiologyColumbia University Medical CenterNew YorkUSA
  4. 4.Division of Neurology, Department of Medicine, Ramathibodi HospitalMahidol UniversityBangkokThailand
  5. 5.Department of NeurologyUniversity HospitalBaselSwitzerland

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