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A Comparative Study of Fractional Anisotropy Measures and ICH Score in Predicting Functional Outcomes After Intracerebral Hemorrhage

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Abstract

Background

Improved prognostication during the acute phase of intracerebral hemorrhage (ICH) could influence goals of care. We investigated the utility of diffusion tensor imaging (DTI)-derived data obtained during the acute phase of ICH in predicting outcome, compared with the ICH score.

Methods

We measured fractional anisotropy (FA) values in 5 slices below the level of the lesion on the affected and unaffected corticospinal tracts (CST) and in the cerebral peduncles (CPs) in 32 patients with supratentorial ICH who had DTI MRI within 4 days after ictus. We calculated the FA ratio (rFA = FAaffected side/FAunaffected side), and examined the value of the ICH score and rFA in predicting functional outcome assessed by modified Ranking Scale (mRS) at follow-up, using ROC analyses.

Results

The rFA values at the CPs level, but not the 5 slices below the lesion, were significantly lower in the group with poor functional outcome (defined as mRS > 2) than in those with good functional outcome (0.96 ± 0.14 vs. 0.99 ± 0.08, p = 0.025). The ICH score had greater areas under ROC curve in predicting functional outcome compared to the mean rFA (AUC 0.74 vs. 0.44; p = 0.01 for mRS > 2; and 0.84 vs. 0.40; p < 0.001 for mRS > 3).

Conclusions

The prognostic value of the ICH score surpassed that of DTI-derived data during the acute phase of ICH in this cohort of patients. Prospective and larger studies are needed to validate our findings and to assess the prognostic role of various DTI-derived measures at different times following ICH.

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References

  1. Saver JL, Johnston KC, Homer D, et al. Infarct volume as a surrogate or auxiliary outcome measure in ischemic stroke clinical trials. The RANTTAS investigators. Stroke. 1999;30:293–8.

    Article  CAS  PubMed  Google Scholar 

  2. Crafton KR, Mark AN, Cramer SC. Improved understanding of cortical injury by incorporating measures of functional anatomy. Brain. 2003;126:1650–9.

    Article  PubMed  Google Scholar 

  3. Shelton FN, Reding MJ. Effect of lesion location on upper limb motor recovery after stroke. Stroke. 2001;32:107–12.

    Article  CAS  PubMed  Google Scholar 

  4. 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.

    Article  CAS  PubMed  Google Scholar 

  5. Helweg-Larsen S, Sommer W, Strange P, Lester J, Boysen G. Prognosis for patients treated conservatively for spontaneous intracerebral hematomas. Stroke. 1984;15:1045–8.

    Article  CAS  PubMed  Google Scholar 

  6. Luo GG, Ramchurn A, Chen YF, et al. Early predictors of hematoma resorption rate in medically treated patients with spontaneous supratentorial hemorrhage. J Neurol Sci. 2013;327:55–60.

    Article  PubMed  Google Scholar 

  7. Brouwers HB, Greenberg SM. Hematoma expansion following acute intracerebral hemorrhage. Cerebrovasc Dis. 2013;35:195–201.

    Article  PubMed Central  PubMed  Google Scholar 

  8. Juvela S. Risk factors for impaired outcome after spontaneous intracerebral hemorrhage. Arch Neurol. 1995;52:1193–200.

    Article  CAS  PubMed  Google Scholar 

  9. Hemphill JC III, Bonovich DC, Besmertis L, Manley GT, Johnston SC. The ICH score: a simple, reliable grading scale for intracerebral hemorrhage. Stroke. 2001;32:891–7.

    Article  PubMed  Google Scholar 

  10. Becker KJ, Baxter AB, Cohen WA, et al. Withdrawal of support in intracerebral hemorrhage may lead to self-fulfilling prophecies. Neurology. 2001;56:766–72.

    Article  CAS  PubMed  Google Scholar 

  11. Mori S, Zhang J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron. 2006;51:527–39.

    Article  CAS  PubMed  Google Scholar 

  12. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G. Diffusion tensor mr imaging of the human brain. Radiology. 1996;201:637–48.

    Article  CAS  PubMed  Google Scholar 

  13. Cho SH, Kim SH, Choi BY, et al. Motor outcome according to diffusion tensor tractography findings in the early stage of intracerebral hemorrhage. Neurosci Lett. 2007;421:142–6.

    Article  CAS  PubMed  Google Scholar 

  14. Yu C, Zhu C, Zhang Y, et al. A longitudinal diffusion tensor imaging study on wallerian degeneration of corticospinal tract after motor pathway stroke. Neuroimage. 2009;47:451–8.

    Article  PubMed  Google Scholar 

  15. Kim DG, Ahn YH, Byun WM, et al. Degeneration speed of corticospinal tract in patients with cerebral infarct. NeuroRehabilitation. 2007;22:273–7.

    PubMed  Google Scholar 

  16. Koyama T, Tsuji M, Miyake H, Ohmura T, Domen K. Motor outcome for patients with acute intracerebral hemorrhage predicted using diffusion tensor imaging: an application of ordinal logistic modeling. J Stroke Cerebrovasc Dis. 2012;21:704–11.

    Article  PubMed  Google Scholar 

  17. Puig J, Pedraza S, Blasco G, et al. Wallerian degeneration in the corticospinal tract evaluated by diffusion tensor imaging correlates with motor deficit 30 days after middle cerebral artery ischemic stroke. AJNR Am J Neuroradiol. 2010;31:1324–30.

    Article  PubMed  Google Scholar 

  18. Moller M, Frandsen J, Andersen G, Gjedde A, Vestergaard-Poulsen P, Ostergaard L. Dynamic changes in corticospinal tracts after stroke detected by fibretracking. J Neurol Neurosurg Psychiatry. 2007;78:587–92.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  19. Radlinska B, Ghinani S, Leppert IR, Minuk J, Pike GB, Thiel A. Diffusion tensor imaging, permanent pyramidal tract damage, and outcome in subcortical stroke. Neurology. 2010;75:1048–54.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Lindenberg R, Zhu LL, Ruber T, Schlaug G. Predicting functional motor potential in chronic stroke patients using diffusion tensor imaging. Hum Brain Mapp. 2012;33:1040–51.

    Article  PubMed Central  PubMed  Google Scholar 

  21. Zhu LL, Lindenberg R, Alexander MP, Schlaug G. Lesion load of the corticospinal tract predicts motor impairment in chronic stroke. Stroke. 2010;41:910–5.

    Article  PubMed Central  PubMed  Google Scholar 

  22. Kuzu Y, Inoue T, Kanbara Y, et al. Prediction of motor function outcome after intracerebral hemorrhage using fractional anisotropy calculated from diffusion tensor imaging. Cerebrovasc Dis. 2012;33:566–73.

    Article  PubMed  Google Scholar 

  23. Kusano Y, Seguchi T, Horiuchi T, et al. Prediction of functional outcome in acute cerebral hemorrhage using diffusion tensor imaging at 3t: a prospective study. AJNR Am J Neuroradiol. 2009;30:1561–5.

    Article  CAS  PubMed  Google Scholar 

  24. Wang DM, Li J, Liu JR, Hu HY. Diffusion tensor imaging predicts long-term motor functional outcome in patients with acute supratentorial intracranial hemorrhage. Cerebrovasc Dis. 2012;34:199–205.

    Article  PubMed  Google Scholar 

  25. Koyama T, Tsuji M, Nishimura H, Miyake H, Ohmura T, Domen K. Diffusion tensor imaging for intracerebral hemorrhage outcome prediction: comparison using data from the corona radiata/internal capsule and the cerebral peduncle. J Stroke Cerebrovasc Dis. 2013;22:72–9.

    Article  PubMed  Google Scholar 

  26. Kothari RU, Brott T, Broderick JP, et al. The ABCs of measuring intracerebral hemorrhage volumes. Stroke. 1996;27:1304–5.

    Article  CAS  PubMed  Google Scholar 

  27. Patel N, Rao VA, Heilman-Espinoza ER, Lai R, Quesada RA, Flint AC. Simple and reliable determination of the modified ranking scale score in neurosurgical and neurological patients: The mrs-9q. Neurosurgery. 2012;71:971–5 discussion 975.

    Article  PubMed  Google Scholar 

  28. Jung YJ, Jang SH. The fate of injured corticospinal tracts in patients with intracerebral hemorrhage: diffusion tensor imaging study. AJNR Am J Neuroradiol. 2012;33(9):1775–8.

    Article  CAS  PubMed  Google Scholar 

  29. Kwak SY, Son SM, Choi BY, et al. Prognostic factors for motor outcome in patients with compressed corticospinal tract by intracerebral hematoma. NeuroRehabilitation. 2011;29:85–90.

    PubMed  Google Scholar 

  30. Yoshioka H, Horikoshi T, Aoki S, et al. Diffusion tensor tractography predicts motor functional outcome in patients with spontaneous intracerebral hemorrhage. Neurosurgery. 2008;62:97–103 discussion 103.

    Article  PubMed  Google Scholar 

  31. Haris M, Gupta RK, Husain N, Hasan KM, Husain M, Narayana PA. Measurement of DTI metrics in hemorrhagic brain lesions: possible implication in MRI interpretation. J Magn Reson Imaging. 2006;24:1259–68.

    Article  PubMed  Google Scholar 

  32. Clarke JL, Johnston SC, Farrant M, Bernstein R, Tong D, Hemphill JC III. External validation of the ICH score. Neurocrit Care. 2004;1:53–60.

    Article  PubMed  Google Scholar 

  33. Cheung RT, Zou LY. Use of the original, modified, or new intracerebral hemorrhage score to predict mortality and morbidity after intracerebral hemorrhage. Stroke. 2003;34:1717–22.

    Article  PubMed  Google Scholar 

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Funding

Drs. Wen-Dan Tao and Ming Liu are supported in part by the research grants from the National Natural Science Foundation of P.R. China (Grant No. 81371282) and Construct Program of Key Clinical Disciplines of the Ministry of Health of P.R. China (Project 010202). Dr. Selim receives grant support (U01 NS 074425) from the NIH/NINDS.

Conflict of interest

None.

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Authors and Affiliations

  1. Stroke Division, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Ave, Palmer 127, Boston, MA, 02115, USA

    Wen-Dan Tao, Jasmine Wang, Gottfried Schlaug & Magdy H. Selim

  2. Neuroimaging and Stroke Recovery Laboratories, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA

    Jasmine Wang & Gottfried Schlaug

  3. Stroke Clinical Research Unit, Department of Neurology, West China Hospital, Sichuan University, No 37, Guo Xue Xiang, Chengdu, 610041, Sichuan, People’s Republic of China

    Wen-Dan Tao & Ming Liu

  4. State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, People’s Republic of China

    Ming Liu

Authors
  1. Wen-Dan Tao
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  2. Jasmine Wang
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  3. Gottfried Schlaug
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  4. Ming Liu
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Correspondence to Ming Liu or Magdy H. Selim.

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Tao, WD., Wang, J., Schlaug, G. et al. A Comparative Study of Fractional Anisotropy Measures and ICH Score in Predicting Functional Outcomes After Intracerebral Hemorrhage. Neurocrit Care 21, 417–425 (2014). https://doi.org/10.1007/s12028-014-9999-2

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  • DOI: https://doi.org/10.1007/s12028-014-9999-2

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