Skip to main content

Advertisement

SpringerLink
Log in

Imaging for Neuroprognostication After Cardiac Arrest: Systematic Review and Meta-analysis

  • Original Work
  • Published:
Neurocritical Care Aims and scope Submit manuscript

Abstract

Background

Predicting neurological outcome in comatose survivors of cardiac arrest relies on clinical findings, radiological and neurophysiological test results. To evaluate the predictive accuracy of brain computed tomography (CT) and magnetic resonance imaging (MRI) for prognostication of neurological outcomes after cardiac arrest.

Methods

We searched MEDLINE (database inception to August 2018) and included all observational cohort studies or randomized controlled trials including adult (16 years or older) survivors of cardiac arrest which evaluated the diagnostic accuracy of CT or MRI for predicting neurologic outcome or mortality. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All review stages were conducted independently by 2 reviewers, and where possible data were pooled using bivariate meta-analysis. The main outcome was to evaluate the of accuracy of CT and MRI in neuroprognostication of patients after cardiac arrest.

Results

We included 44 studies that examined brain CT (n = 24) or MRI (n = 21) in 4008 (n per study, 9-398) patients. Decreased grey to white matter ratio on CT (20 studies) was useful for predicting poor neurological outcome (sensitivity 0.44, 95% CI 0.29-0.60; specificity 0.97, 95% CI 0.93-0.99; positive likelihood ratio [LR+] 13.8, 95% CI 6.9-27.7). Similarly, diffusion-weighted imaging (DWI) on MRI (16 studies; sensitivity 0.77, 95% CI 0.65-0.85; specificity 0.92, 95% CI 0.85-0.96; LR+ 9.2, 95% CI 5.2-16.4) and DWI and fluid-attenuated inversion recovery (FLAIR) MRI (4 studies, sensitivity 0.70, 95% CI 0.43-0.88; specificity 0.95, 95% CI 0.79-0.99; LR+ 13.4, 95% CI 3.5-51.2) were useful for predicting poor neurological outcomes. We found marked heterogeneity in timing of radiological examinations and neurological assessments relative to the cardiac arrest.

Conclusion

Decreased grey to white matter ratio on CT and DWI or DWI and FLAIR on MRI are useful adjuncts for predicting poor early neurological outcome after cardiac arrest.

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. Girotra S, Nallamothu BK, Spertus JA, et al. Trends in survival after in-hospital cardiac arrest. N Engl J Med. 2012;367:1912–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Hinchey PR, Myers JB, Lewis R, et al. Improved out-of-hospital cardiac arrest survival after the sequential implementation of 2005 AHA guidelines for compressions, ventilations, and induced hypothermia: the Wake County experience. Ann Emerg Med. 2010;56:348–57.

    Article  PubMed  Google Scholar 

  3. Laver S, Farrow C, Turner D, Nolan J. Mode of death after admission to an intensive care unit following cardiac arrest. Intensive Care Med. 2004;30:2126–8.

    Article  PubMed  Google Scholar 

  4. Callaway CW, Soar J, Aibiki M, et al. Part 4: advanced life support: 2015 international consensus on cardiopulmonary resuscitation and emergency cardiovascular care science with treatment recommendations. Circulation. 2015;132:S84–145.

    Article  PubMed  Google Scholar 

  5. Edgren E, Enblad P, Grenvik A, et al. Cerebral blood flow and metabolism after cardiopulmonary resuscitation. A pathophysiologic and prognostic positron emission tomography pilot study. Resuscitation. 2003;57:161–70.

    Article  PubMed  Google Scholar 

  6. Gutierrez LG, Rovira A, Portela LA, Leite Cda C, Lucato LT. CT and MR in non-neonatal hypoxic-ischemic encephalopathy: radiological findings with pathophysiological correlations. Neuroradiology. 2010;52:949–76.

    Article  PubMed  Google Scholar 

  7. Tha KK, Terae S, Yamamoto T, et al. Early detection of global cerebral anoxia: improved accuracy by high-b-value diffusion-weighted imaging with long echo time. AJNR Am J Neuroradiol. 2005;26:1487–97.

    PubMed  PubMed Central  Google Scholar 

  8. Kjos BO, Brant-Zawadzki M, Young RG. Early CT findings of global central nervous system hypoperfusion. AJR Am J Roentgenol. 1983;141:1227–32.

    Article  CAS  PubMed  Google Scholar 

  9. Torbey MT, Selim M, Knorr J, Bigelow C, Recht L. Quantitative analysis of the loss of distinction between gray and white matter in comatose patients after cardiac arrest. Stroke. 2000;31:2163–7.

    Article  CAS  PubMed  Google Scholar 

  10. Muttikkal TJ, Wintermark M. MRI patterns of global hypoxic-ischemic injury in adults. J Neuroradiol. 2013;40:164–71.

    Article  PubMed  Google Scholar 

  11. Arbelaez A, Castillo M, Mukherji SK. Diffusion-weighted MR imaging of global cerebral anoxia. AJNR Am J Neuroradiol. 1999;20:999–1007.

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Hahn DK, Geocadin RG, Greer DM. Quality of evidence in studies evaluating neuroimaging for neurologic prognostication in adult patients resuscitated from cardiac arrest. Resuscitation. 2014;85:165–72.

    Article  PubMed  Google Scholar 

  13. Nolan JP, Soar J, Cariou A, et al. European Resuscitation Council and European Society of Intensive Care Medicine Guidelines for Post-resuscitation Care 2015: Section 5 of the European Resuscitation Council Guidelines for Resuscitation 2015. Resuscitation. 2015;95:202–22.

    Article  PubMed  Google Scholar 

  14. McInnes MDF, Moher D, Thombs BD, et al. Preferred reporting items for a systematic review and meta-analysis of diagnostic test accuracy studies: the PRISMA-DTA statement. JAMA. 2018;319:388–96.

    Article  PubMed  Google Scholar 

  15. van Enst WA, Scholten RJ, Whiting P, Zwinderman AH, Hooft L. Meta-epidemiologic analysis indicates that MEDLINE searches are sufficient for diagnostic test accuracy systematic reviews. J Clin Epidemiol. 2014;67:1192–9.

    Article  PubMed  Google Scholar 

  16. Edgren E, Hedstrand U, Kelsey S, Sutton-Tyrrell K, Safar P. Assessment of neurological prognosis in comatose survivors of cardiac arrest. BRCT I Study Group. Lancet. 1994;343:1055–9.

    Article  CAS  PubMed  Google Scholar 

  17. 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.

    Article  PubMed  Google Scholar 

  18. Jennett B, Snoek J, Bond MR, Brooks N. Disability after severe head injury: observations on the use of the Glasgow Outcome Scale. J Neurol Neurosurg Psychiatry. 1981;44:285–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Teasdale GM, Pettigrew LE, Wilson JT, Murray G, Jennett B. Analyzing outcome of treatment of severe head injury: a review and update on advancing the use of the Glasgow Outcome Scale. J Neurotrauma. 1998;15:587–97.

    Article  CAS  PubMed  Google Scholar 

  20. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155:529–36.

    Article  PubMed  Google Scholar 

  21. Macaskill PGC, Deeks JJ, Harbord RM, Takwoingi Y. Chapter 10: Analysing and presenting results. In: Deeks JJ BP, Gatsonis C, editors. Cochrane handbook for systematic reviews of diagnostic test accuracy version 10. The Cochrane Collaboration 2010. http://srdta.cochrane.org/.

  22. Takwoingi Y. MetaDAS: a SAS macro for meta-analysis of diagnostic accuracy studies. Quick reference and worked example Version 1.3. 2010 July. http://srdta.cochrane.org.

  23. Barrett KM, Freeman WD, Weindling SM, et al. Brain injury after cardiopulmonary arrest and its assessment with diffusion-weighted magnetic resonance imaging. Mayo Clin Proc. 2007;82:828–35.

    Article  PubMed  Google Scholar 

  24. Chae MK, Ko E, Lee JH, et al. Better prognostic value with combined optic nerve sheath diameter and grey-to-white matter ratio on initial brain computed tomography in post-cardiac arrest patients. Resuscitation. 2016;104:40–5.

    Article  PubMed  Google Scholar 

  25. Choi SP, Park HK, Park KN, et al. The density ratio of grey to white matter on computed tomography as an early predictor of vegetative state or death after cardiac arrest. Emerg Med J. 2008;25:666–9.

    Article  CAS  PubMed  Google Scholar 

  26. Choi SP, Park KN, Park HK, et al. Diffusion-weighted magnetic resonance imaging for predicting the clinical outcome of comatose survivors after cardiac arrest: a cohort study. Crit Care. 2010;14:R17.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Cristia C, Ho ML, Levy S, et al. The association between a quantitative computed tomography (CT) measurement of cerebral edema and outcomes in post-cardiac arrest—a validation study. Resuscitation. 2014;85:1348–53.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Els T, Kassubek J, Kubalek R, Klisch J. Diffusion-weighted MRI during early global cerebral hypoxia: a predictor for clinical outcome? Acta Neurol Scand. 2004;110:361–7.

    Article  PubMed  Google Scholar 

  29. Gentsch A, Storm C, Leithner C, et al. Outcome prediction in patients after cardiac arrest: a simplified method for determination of gray-white matter ratio in cranial computed tomography. Clin Neuroradiol. 2015;25:49–54.

    Article  CAS  PubMed  Google Scholar 

  30. Greer D, Scripko P, Bartscher J, et al. Serial MRI changes in comatose cardiac arrest patients. Neurocrit Care. 2011;14:61–7.

    Article  PubMed  Google Scholar 

  31. Greer D, Scripko P, Bartscher J, et al. Clinical MRI interpretation for outcome prediction in cardiac arrest. Neurocrit Care. 2012;17:240–4.

    Article  PubMed  Google Scholar 

  32. Hanning U, Sporns PB, Lebiedz P, et al. Automated assessment of early hypoxic brain edema in non-enhanced CT predicts outcome in patients after cardiac arrest. Resuscitation. 2016;104:91–4.

    Article  PubMed  Google Scholar 

  33. Heradstveit BE, Larsson EM, Skeidsvoll H, et al. Repeated magnetic resonance imaging and cerebral performance after cardiac arrest—a pilot study. Resuscitation. 2011;82:549–55.

    Article  PubMed  Google Scholar 

  34. Hirsch KG, Mlynash M, Eyngorn I, et al. Multi-center study of diffusion-weighted imaging in coma after cardiac arrest. Neurocrit Care. 2016;24:82–9.

    Article  CAS  PubMed  Google Scholar 

  35. Hirsch KG, Mlynash M, Jansen S, et al. Prognostic value of a qualitative brain MRI scoring system after cardiac arrest. J Neuroimaging. 2015;25:430–7.

    Article  PubMed  Google Scholar 

  36. Hwan Kim Y, Ho Lee J, Kun Hong C, et al. Feasibility of optic nerve sheath diameter measured on initial brain computed tomography as an early neurologic outcome predictor after cardiac arrest. Acad Emerg Med. 2014;21:1121–8.

    Article  PubMed  Google Scholar 

  37. Inamasu J, Miyatake S, Nakatsukasa M, Koh H, Yagami T. Loss of gray-white matter discrimination as an early CT sign of brain ischemia/hypoxia in victims of asphyxial cardiac arrest. Emerg Radiol. 2011;18:295–8.

    Article  PubMed  Google Scholar 

  38. Inamasu J, Miyatake S, Suzuki M, et al. Early CT signs in out-of-hospital cardiac arrest survivors: temporal profile and prognostic significance. Resuscitation. 2010;81:534–8.

    Article  PubMed  Google Scholar 

  39. Jeon CH, Park JS, Lee JH, et al. Comparison of brain computed tomography and diffusion-weighted magnetic resonance imaging to predict early neurologic outcome before target temperature management comatose cardiac arrest survivors. Resuscitation. 2017;118:21–6.

    Article  PubMed  Google Scholar 

  40. Kim J, Choi BS, Kim K, et al. Prognostic performance of diffusion-weighted MRI combined with NSE in comatose cardiac arrest survivors treated with mild hypothermia. Neurocrit Care. 2012;17:412–20.

    Article  PubMed  Google Scholar 

  41. Kim J, Kim K, Hong S, et al. Low apparent diffusion coefficient cluster-based analysis of diffusion-weighted MRI for prognostication of out-of-hospital cardiac arrest survivors. Resuscitation. 2013;84:1393–9.

    Article  PubMed  Google Scholar 

  42. Kim SH, Choi SP, Park KN, Youn CS, Oh SH, Choi SM. Early brain computed tomography findings are associated with outcome in patients treated with therapeutic hypothermia after out-of-hospital cardiac arrest. Scand J Trauma Resusc Emerg Med. 2013;21:57.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Lee BK, Jeung KW, Lee HY, Jung YH, Lee DH. Combining brain computed tomography and serum neuron specific enolase improves the prognostic performance compared to either alone in comatose cardiac arrest survivors treated with therapeutic hypothermia. Resuscitation. 2013;84:1387–92.

    Article  CAS  PubMed  Google Scholar 

  44. Lee BK, Jeung KW, Song KH, et al. Prognostic values of gray matter to white matter ratios on early brain computed tomography in adult comatose patients after out-of-hospital cardiac arrest of cardiac etiology. Resuscitation. 2015;96:46–52.

    Article  PubMed  Google Scholar 

  45. Lee BK, Kim WY, Shin J, et al. Prognostic value of gray matter to white matter ratio in hypoxic and non-hypoxic cardiac arrest with non-cardiac etiology. Am J Emerg Med. 2016;34:1583–8.

    Article  PubMed  Google Scholar 

  46. Lee BK, Kim YJ, Ryoo SM, et al. ”Pseudo-subarachnoid hemorrhage sign” on early brain computed tomography in out-of-hospital cardiac arrest survivors receiving targeted temperature management. J Crit Care. 2017;40:36–40.

    Article  PubMed  Google Scholar 

  47. Lee DH, Lee BK, Jeung KW, et al. Relationship between ventricular characteristics on brain computed tomography and 6-month neurologic outcome in cardiac arrest survivors who underwent targeted temperature management. Resuscitation. 2018;129:37–42.

    Article  PubMed  Google Scholar 

  48. Lee KS, Lee SE, Choi JY, et al. Useful computed tomography score for estimation of early neurologic outcome in post-cardiac arrest patients with therapeutic hypothermia. Circ J. 2017;81:1628–35.

    Article  PubMed  Google Scholar 

  49. Luyt CE, Galanaud D, Perlbarg V, et al. Diffusion tensor imaging to predict long-term outcome after cardiac arrest: a bicentric pilot study. Anesthesiology. 2012;117:1311–21.

    Article  PubMed  Google Scholar 

  50. Mettenburg JM, Agarwal V, Baldwin M, Rittenberger JC. Discordant observation of brain injury by MRI and malignant electroencephalography patterns in comatose survivors of cardiac arrest following therapeutic hypothermia. AJNR Am J Neuroradiol. 2016;37:1787–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Metter RB, Rittenberger JC, Guyette FX, Callaway CW. Association between a quantitative CT scan measure of brain edema and outcome after cardiac arrest. Resuscitation. 2011;82:1180–5.

    Article  PubMed  PubMed Central  Google Scholar 

  52. Nogami K, Fujii M, Kato S, et al. Analysis of magnetic resonance imaging (MRI) morphometry and cerebral blood flow in patients with hypoxic-ischemic encephalopathy. J Clin Neurosci. 2004;11:376–80.

    Article  PubMed  Google Scholar 

  53. Park JS, Lee SW, Kim H, et al. Efficacy of diffusion-weighted magnetic resonance imaging performed before therapeutic hypothermia in predicting clinical outcome in comatose cardiopulmonary arrest survivors. Resuscitation. 2015;88:132–7.

    Article  PubMed  Google Scholar 

  54. Reynolds AS, Guo X, Matthews E, et al. Post-anoxic quantitative MRI changes may predict emergence from coma and functional outcomes at discharge. Resuscitation. 2017;117:87–90.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ryoo SM, Jeon SB, Sohn CH, et al. Predicting outcome with diffusion-weighted imaging in cardiac arrest patients receiving hypothermia therapy: Multicenter Retrospective Cohort Study. Crit Care Med. 2015;43:2370–7.

    Article  CAS  PubMed  Google Scholar 

  56. Scheel M, Storm C, Gentsch A, et al. The prognostic value of gray-white-matter ratio in cardiac arrest patients treated with hypothermia. Scand J Trauma Resusc Emerg Med. 2013;21:23.

    Article  PubMed  PubMed Central  Google Scholar 

  57. Shankar JJS, Stewart-Perrin B, Quraishi AU, Bata I, Vandorpe R. Computed tomography perfusion aids in the prognostication of comatose postcardiac arrest patients. Am J Cardiol. 2018;121:874–8.

    Article  PubMed  Google Scholar 

  58. Sugimori H, Kanna T, Yamashita K, et al. Early findings on brain computed tomography and the prognosis of post-cardiac arrest syndrome: application of the score for stroke patients. Resuscitation. 2012;83:848–54.

    Article  PubMed  Google Scholar 

  59. Topcuoglu MA, Oguz KK, Buyukserbetci G, Bulut E. Prognostic value of magnetic resonance imaging in post-resuscitation encephalopathy. Intern Med. 2009;48:1635–45.

    Article  PubMed  Google Scholar 

  60. Torbey MT, Geocadin R, Bhardwaj A. Brain arrest neurological outcome scale (BrANOS): predicting mortality and severe disability following cardiac arrest. Resuscitation. 2004;63:55–63.

    Article  PubMed  Google Scholar 

  61. Velly L, Perlbarg V, Boulier T, et al. Use of brain diffusion tensor imaging for the prediction of long-term neurological outcomes in patients after cardiac arrest: a multicentre, international, prospective, observational, cohort study. Lancet Neurol. 2018;17:317–26.

    Article  PubMed  Google Scholar 

  62. Wang GN, Chen XF, Lv JR, Sun NN, Xu XQ, Zhang JS. The prognostic value of gray-white matter ratio on brain computed tomography in adult comatose cardiac arrest survivors. J Chin Med Assoc. 2018;81:599–604.

    Article  PubMed  Google Scholar 

  63. Wijdicks EF, Campeau NG, Miller GM. MR imaging in comatose survivors of cardiac resuscitation. AJNR Am J Neuroradiol. 2001;22:1561–5.

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Wijman CAC, Mayer SA, Meschia JF, et al. Prognostic value of quantitative brain diffusion-weighted imaging after cardiac arrest: a multi-center validation study. Neurocrit Care. 2012;17:S131.

    Article  CAS  Google Scholar 

  65. Yamamura H, Kaga S, Kaneda K, Yamamoto T, Mizobata Y. Head computed tomographic measurement as an early predictor of outcome in hypoxic-ischemic brain damage patients treated with hypothermia therapy. Scand J Trauma Resusc Emerg Med. 2013;21:37.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Youn CS, Callaway CW, Rittenberger JC, Post Cardiac Arrest Service. Combination of initial neurologic examination, quantitative brain imaging and electroencephalography to predict outcome after cardiac arrest. Resuscitation. 2017;110:120–5.

    Article  PubMed  Google Scholar 

  67. Topcuoglu MA, Oguz KK, Buyukserbetci G, Bulut E. Prognostic value of magnetic resonance imaging in post-resuscitation encephalopathy. Intern Med. 2009;48:1635–45.

    Article  PubMed  Google Scholar 

  68. Wijman CA, Mlynash M, Caulfield AF, et al. Prognostic value of brain diffusion-weighted imaging after cardiac arrest. Ann Neurol. 2009;65:394–402.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Golan E, Barrett K, Alali AS, et al. Predicting neurologic outcome after targeted temperature management for cardiac arrest: systematic review and meta-analysis. Crit Care Med. 2014;42:1919–30.

    Article  PubMed  Google Scholar 

  70. Sandroni C, Cavallaro F, Callaway CW, et al. Predictors of poor neurological outcome in adult comatose survivors of cardiac arrest: a systematic review and meta-analysis. Part 2: patients treated with therapeutic hypothermia. Resuscitation. 2013;84:1324–38.

    Article  PubMed  Google Scholar 

  71. Kucinski T, Vaterlein O, Glauche V, et al. Correlation of apparent diffusion coefficient and computed tomography density in acute ischemic stroke. Stroke. 2002;33:1786–91.

    Article  PubMed  Google Scholar 

  72. Cropp RJ, Seslija P, Tso D, Thakur Y. Scanner and kVp dependence of measured CT numbers in the ACR CT phantom. J Appl Clin Med Phys. 2013;14:4417.

    Article  PubMed  Google Scholar 

Download references

Funding

No source of support to declare.

Author information

Author notes

  1. Neill K. J. Adhikari and Damon C. Scales contributed equally to this manuscript.

Authors and Affiliations

  1. Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON, M4N 3M5, Canada

    Carmen Lopez Soto, Laura Dragoi, Ruxandra Pinto, Neill K. J. Adhikari & Damon C. Scales

  2. Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada

    Carmen Lopez Soto, Laura Dragoi, Neill K. J. Adhikari & Damon C. Scales

  3. Department of Medical Imaging, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada

    Chinthaka C. Heyn

  4. Departments of Critical Care Medicine and Clinical Neurosciences, University of Calgary, Calgary, AB, Canada

    Andreas Kramer

  5. Department of Critical Care Medicine, King’s College Hospital NHS Foundation Trust, London, UK

    Carmen Lopez Soto

Authors
  1. Carmen Lopez Soto
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Laura Dragoi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Chinthaka C. Heyn
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Andreas Kramer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ruxandra Pinto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Neill K. J. Adhikari
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Damon C. Scales
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

CLS, LD, CCH, AK, RP, NKJA, DCS contributed to the concept and design of study. CLS and LD contributed to the acquisition of data. CLS, LD, CCH, AK, RP, NKJA, DCS contributed to the analyses and interpretation of data. CLS, LD, CCH, AK, RP, NKJA, DCS contributed to the drafting and critical revision of manuscript. NKJA and DCS contributed to the supervision of study. NKJA and DCS contributed equally to this study.

Corresponding author

Correspondence to Damon C. Scales.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval and Informed consent

No ethical approval or informed consent needed for this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 67 kb)

Supplementary material 2 (DOCX 28 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lopez Soto, C., Dragoi, L., Heyn, C.C. et al. Imaging for Neuroprognostication After Cardiac Arrest: Systematic Review and Meta-analysis. Neurocrit Care 32, 206–216 (2020). https://doi.org/10.1007/s12028-019-00842-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12028-019-00842-0

Keywords

Search

Navigation