Skip to main content
SpringerLink
Log in

Susceptibility-weighted imaging predicts infarct size and early-stage clinical prognosis in acute ischemic stroke

  • Original Article
  • Published:
Neurological Sciences Aims and scope Submit manuscript

Abstract

Susceptibility-weighted imaging (SWI) is a non-invasive technique that can reveal venous structures and iron in the brain. This retrospective study evaluated SWI, relative to other imaging techniques, for determining cerebral infarct size and early-stage clinical prognosis in patients with acute ischemic stroke. Within 3 days after onset, 22 patients with acute ischemic stroke underwent SWI, diffusion-weighted imaging (DWI), perfusion-weighted imaging (PWI), fluid-attenuated inversion recovery (FLAIR), and magnetic resonance angiography (MRA). At least 7 days after onset, the patients also underwent cranial FLAIR or computed tomography (CT). The severity of neurological damage was adjudged with NIHSS (National Institutes of Health Stroke Scale) scores. The imaged cranial lesions were evaluated according to ASPECTS (Alberta Stroke Program Early CT Score). The SWI-ASPECTS significantly correlated with mean transit time (MTT)-ASPECTS (Spearman’s test, r = 0.662, P = 0.001) in evaluating ischemic penumbra and significantly correlated with the FLAIR and CT-ASPECTS (Spearman’s test, r = 0.765, P < 0.001) in predicting infarct size. SWI is feasible for the early evaluation of cerebral infarct size and clinical prognosis of patients with acute cerebral infarction. SWI is a useful predictor of early infarct growth and early-stage outcome.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Lövblad KO, Altrichter S, Viallon M, Sztajzel R, Delavelle J, Vargas MI, el-Koussy M, Federspiel A, Sekoranja L (2008) Neuro-imaging of cerebral ischemic stroke. J Neuroradiol 35(4):197–209

    Article  PubMed  Google Scholar 

  2. Cho KH, Kwon SU, Lee DH, Shim WH, Choi CG, Kim SJ, Suh DC, Kim JS, Kang DW (2012) An early infarct growth predicts long-term clinical outcome after thrombolysis [J]. J Neurol Sci 316:99–103

    Article  PubMed  Google Scholar 

  3. Rivers CS, Wardlaw JM, Armitage PA, Bastin ME, Carpenter TK, Cvoro V, Hand PJ, Dennis MS (2006) Do acute diffusion- and perfusion-weighted MRI lesions identify final infarct volume in ischemic stroke? [J]. Stroke 37:98–104

    Article  PubMed  CAS  Google Scholar 

  4. Davis SM, Donnan GA, Parsons MW, Levi C, Butcher KS, Peeters A, Barber PA, Bladin C, de Silva DA, Byrnes G, Chalk JB, Fink JN, Kimber TE, Schultz D, Hand PJ, Frayne J, Hankey G, Muir K, Gerraty R, Tress BM, Desmond PM, EPITHET Investigators (2008) Effects of alteplase beyond 3 h after stroke in the Echo planar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomized trial [J]. Lancet Neurol 7:299–309

    Article  PubMed  Google Scholar 

  5. Kidwell CS, Alger JR, Saver JL (2003) Beyond mismatch evolving paradigms in imaging the ischemic penumbra with multimodal magnetic resonance imaging [J]. Stroke 34:2729–2735

    Article  PubMed  Google Scholar 

  6. Luo S, Yang L, Wang L (2015) Comparison of susceptibility-weighted and perfusion-weighted magnetic resonance imaging in the detection of penumbra in acute ischemic stroke. J Neuroradiol [J] 42:255–260

    Article  CAS  Google Scholar 

  7. Kao HW, Tsai FY, Hasso AN (2012) Predicting stroke evolution: comparison of susceptibility-weighted MR imaging with MR perfusion [J]. Eur Radiol 22(7):1397–1403

    Article  PubMed  Google Scholar 

  8. Mittal S, Wu Z, Neelavalli J (2009) Susceptibility-weighted imaging: technical aspects and clinical applications. Part 2 [J]. AJNR Am J Neuroradiol 30(2):232–252

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Tsui YK, Tsai FY, Hasso AN, Greensite F, Nguyen BV (2009) Susceptibility-weighted imaging for differential diagnosis of cerebral vascular pathology: a pictorial review [J]. Neurol Sci 287(1–2):7–16

    Article  Google Scholar 

  10. Tamura H, Hatazawa J, Toyoshima H (2002) Detection of deoxygenation-related signal change in acute ischemic stroke patients by T2-weighted magnetic resonance imaging [J]. Stroke 33(4):967–971

    Article  PubMed  Google Scholar 

  11. Kesavadas C, Thomas B, Pendharakar H, Sylaja PN (2011) Susceptibility weighted imaging: does it give information similar to perfusion weighted imaging in acute stroke [J]. Neurol 258(5):932–934

    Article  CAS  Google Scholar 

  12. Derdeyn CP, Yundt KD, Videen TO et al (1998) Increased oxygen extraction fraction is associated with prior ischemic events in patients with carotid occlusion. Stroke 29:754–758

    Article  PubMed  CAS  Google Scholar 

  13. Grubb Jr RL, Derdeyn CP, Fritsch SM et al (1998) Importance of hemodynamic factors in the prognosis of symptomatic carotid occlusion. JAMA 280:1055–1060

    Article  CAS  Google Scholar 

  14. Chalian M, Tekes A, Meoded A, Poretti A, Huisman TAGM (2011) Susceptibility-weighted imaging (SWI): a potential non-invasive imaging tool for characterizing ischemic brain injury? [J]. J Neuroradiol 38:187–190

    Article  PubMed  CAS  Google Scholar 

  15. Meoded A, Poretti A, Benson JE, Tekes A, Huisman TAGM (2014) Evaluation of the ischemic penumbra focusing on the venous drainage: the role of susceptibility weighted image (SWI) in pediatric ischemic cerebral stroke [J]. J Neuroradiol 41:108–116

    Article  PubMed  Google Scholar 

  16. Polan RM, Poretti A, Huisman TA, et al. (2014) Susceptibility-weighted imaging in pediatric arterial ischemic stroke: a valuable alternative for the noninvasive evaluation of altered cerebral hemodynamics. Am J Neuroradiol

  17. Chia-Yuen C, Chin-I C, Tsai Fong Y et al (2015) Prominent vessel sign on susceptibility-weighted imaging in acute stroke: prediction of infarct growth and clinical outcome [J]. PLoS One 10(6):e0131118

    Article  CAS  Google Scholar 

  18. Ueda T, Yuh WT, Maley JE, Quets JP, Hahn PY, Magnotta VA (1999) Outcome of acute ischemia lesions evaluated by diffusion and perfusion MR imaging [J]. AJNR 20(6):983–989

    PubMed  CAS  Google Scholar 

  19. Barber PA, Demchuk AM, Zhang J, Buchan AM (2000) Validity and reliability of a quantitative computed tomography score in predicting outcome of hyperacute stroke before thrombolytic therapy. ASPECTS Study Group. Alberta Stroke Programme Early CT Score [J]. Lancet 355(9216):1670–1674

    Article  PubMed  CAS  Google Scholar 

  20. Huang P, Chen CH, Lin WC, Lin RT, Khor GT, Liu CK (2012) Clinical applications of susceptibility weighted imaging in patients with major stroke. J Neurol 259:1426–1432

    Article  PubMed  Google Scholar 

  21. Yamashita E, Kanasaki Y, Fujii S, Tanaka T, Hirata Y, Ogawa T (2011) Comparison of increased venous contrast in ischemic stroke using phase-sensitive MR imaging with perfusion changes on flow-sensitive alternating inversion recovery at 3 Tesla. Acta Radiol 52:905–910

    Article  PubMed  Google Scholar 

  22. Baik SK, Choi W, Oh SJ, Park KP, Park MG, Yang TI, Jeong HW (2012) Change in cortical vessel signs on susceptibility-weighted images after full recanalization in hyperacute ischemic stroke. Cerebrovasc Dis 34:206–212

    Article  PubMed  Google Scholar 

  23. Greer DM, Koroshetz WJ, Cullen S, Gonzalez RG, Lev MH (2004) Magnetic resonance imaging improves detection of intra-cerebral hemorrhage over computed tomography after intra-arterial thrombolysis. Stroke 35:491–495

    Article  PubMed  Google Scholar 

  24. Hermier M, Nighoghossian N (2004) Contribution of susceptibility weighted imaging to acute stroke assessment. Stroke 35:1989–1994

    Article  PubMed  Google Scholar 

  25. Morita N, Harada M, Uno M, Matsubara S, Matsuda T, Nagahiro S, Nishitani H (2008) Ischemic findings of T2*-weighted 3-Tesla MRI in acute stroke patients. Cerebrovasc Dis 26:367–375

    Article  PubMed  Google Scholar 

  26. Geisler BS, Brandhoff F, Fiehler J, Saager C, Speck O, Rother J, Zeumer H, Kucinski T (2006) Blood-oxygen-level-dependent MRI allows metabolic description of tissue at risk in acute stroke patients. Stroke 37:1778–1784

    Article  PubMed  Google Scholar 

  27. Hermier M, Nighoghossian N, Derex L, Wiart M, Nemoz C, Berthezene Y, Froment JC (2005) Hypointense leptomeningeal vessels at T2*-weighted MRI in acute ischemic stroke. Neurology 65:652–653

    Article  PubMed  CAS  Google Scholar 

  28. Yata K, Suzuki A, Hatazawa J, Shimosegawa E, Nagata K, Sato M, Moroi J (2006) Relationship between cerebral circulatory reserve and oxygen extraction fraction in patients with major cerebral artery occlusive disease: a positron emission tomography study [J]. Stroke 37(2):534–536

    Article  PubMed  Google Scholar 

  29. Kamath A, Smith WS, Powers WJ, Cianfoni A, Chien JD, Videen T, Lawton MT, Finley B, Dillon WP, Wintermark M (2008) Perfusion CT compared to H2 (15)O/O (15)O PET in patients with chronic cervical carotid artery occlusion[J]. Neuroradiology 50(9):745–751

    Article  PubMed  PubMed Central  Google Scholar 

  30. Chalela JA, Kang DW, Warach S (2004) Multiple cerebral microbleeds: MRI marker of a diffuse hemorrhage-prone state [J]. Neuroimaging 14:54–57

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Neurology, The First Affiliated Hospital of Bengbu Medical College, Bengbu, 233004, China

    Song Luo

  2. Department of Pediatrics, The First Affiliated Hospital of Bengbu Medical College, Bengbu, 233004, China

    Lijuan Yang

  3. Department of Urology, The Second Affiliated Hospital of Bengbu Medical College, Bengbu, 233000, China

    Yanfei Luo

Authors
  1. Song Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lijuan Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yanfei Luo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Song Luo.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luo, S., Yang, L. & Luo, Y. Susceptibility-weighted imaging predicts infarct size and early-stage clinical prognosis in acute ischemic stroke. Neurol Sci 39, 1049–1055 (2018). https://doi.org/10.1007/s10072-018-3324-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10072-018-3324-3

Keywords

Search

Navigation