Question 20

a) List the common CT and MRI features of severe hypoxic ischaemic encephalopathy (HIE) that appear after 72 hours. (40% marks)
b) Outline how neuro-imaging findings may assist in prognostication for HIE. (60% marks)

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College answer

What was required to score well in this question was an understanding of positive and negative predictive value of these imaging modalities, and how they need to be used and interpreted in conjunction with other prognostication tests. Many candidates mentioned a multimodal prognostic model, however, they failed to elaborate on how they are utilised in a multimodal approach.

Discussion

If "what was required to score well in this question was an understanding of positive and negative predictive value", then perhaps the words "positive and negative predictive value"  should have appeared in the stem, otherwise it would seem unfair to expect the exam candidates to guess their way to the optimum marks. Still, one may be able to argue that the stem is about diagnostic tests, and is phrased in a way that leads naturally to the discussion of their validity, of which NPV and PPV are an important part

a)

CT features of hypoxic ischaemic encephalopathy:

  • Specific findings
    • Loss of grey-white matter differentiation
    • Reversal of grey-white differentiation
    • "White cerebellum" sign
    • Effacement of CSF structures (ventricles, sulci, gyri)
    • Tonsillar herniation
    • Pseudosubarachnoid (a late and severe sign)
    • Cortical laminar necrosis
  • Generalised features:
    • Bilateral diffuse lesions
    • Predominantly grey matter damage
    • Distribution along watershed areas

MRI features of hypoxic ischaemic encephalopathy:

  • Early increased signal intensity on DWI
  • Diffusion restriction on ADC
  • Later, increased signal intensity on T2/FLAIR
  • Very late, cortical laminar necrosis on T1

b)

  • Predictive value of CT 
    • Early (within 12-24 hrs) CT may not demonstrate any findings.
    • Loss of grey white differentiation at 24-48 hrs has false positive rate of around 8% (qualitative) but close to 0% with quantitative measurements of the grey-white ratio (threshold values vary in the literature
    • Sensitivity for predicting poor neurological outcome remains poor.
    •  Thus, CT has good positive predictive value, but poor negative predictive value (i.e. a normal CT does not rule out a severe HIE)
  • Predictive value of MRI
    • A diffuse pattern of restricted diffusion on MRI (DWI with ADC analysis) at days 2 to 7 post ROSC has a very high positive predictive value (0.95, sensitivity 63%, specificity 96%).
    • Absence of DWI lesions (or an isolated lesion) has a sensitivity of 94% and a specificity of 92% for good 6-month functional outcome (Rajajee et al, 2023)
    • Therefore MRI has good positive and negative predictive value, with a false positive rate quoted as  0-5%.
  • Integration into a multimodal prognostic model:
    • The stand-alone predictive value of imaging in neuroprognostication is low.
    • Prognostication algorithms such as the ERC/ESICM (2020) or NCS (2023) incorporate imaging as "useful but less robust predictors", to be used together with other predictors.
    • When strongly suggestive CT or MRI are combined with one other clinical predictor (eg. poor motor score or absent pupillary reflex), the false positive rate drops to 0% (Youn et al, 2022).

References

Lopez Soto, Carmen, et al. "Imaging for neuroprognostication after cardiac arrest: systematic review and meta-analysis." Neurocritical Care 32 (2020): 206-216.

Rajajee, Venkatakrishna, et al. "Guidelines for Neuroprognostication in Comatose Adult Survivors of Cardiac Arrest." Neurocritical Care (2023): 1-31.

Bertoni, M., et al. "Neuroimaging assessment of hypoxic ischemic brain injury of the adult with perfusion computed tomography.Journal of the Neurological Sciences 381 (2017): 71-72.

Sandroni, Claudio, et al. "Prognostication in comatose survivors of cardiac arrest: an advisory statement from the European Resuscitation Council and the European Society of Intensive Care Medicine." Intensive care medicine 40 (2014): 1816-1831.

Huang, Benjamin Y., and Mauricio Castillo. "Hypoxic-ischemic brain injury: imaging findings from birth to adulthood." Radiographics 28.2 (2008): 417-439.

Gutierrez, Leonardo Guilhermino, et al. "CT and MR in non-neonatal hypoxic–ischemic encephalopathy: radiological findings with pathophysiological correlations." Neuroradiology 52 (2010): 949-976.

Parada-Duarte, Óscar Andrés, et al. "Cortical Laminar Necrosis in Computed Tomography Scan: A Case Report." Rev. Colomb. Radiol. 2019; 30(4): 5239-41

Muttikkal, Thomas J. Eluvathingal, and Max Wintermark. "MRI patterns of global hypoxic-ischemic injury in adults." Journal of Neuroradiology 40.3 (2013): 164-171.

Han, B. Kim, et al. "Reversal sign on CT: effect of anoxic/ischemic cerebral injury in children." AJR. American journal of roentgenology 154.2 (1990): 361-368.

Krishnan, Prasad, and Siddhartha Roy Chowdhury. "“White cerebellum” sign-A dark prognosticator.Journal of Neurosciences in Rural Practice 5.04 (2014): 433-433.

Chakraborty, Santanu, et al. "Diffuse ischemia in noncontrast computed tomography predicts outcome in patients in intensive care unit." Canadian Association of Radiologists Journal 63.2 (2012): 129-134.

Torbey, Michel T., et al. "Quantitative analysis of the loss of distinction between gray and white matter in comatose patients after cardiac arrest." Stroke 31.9 (2000): 2163-2167.

Scheel, Michael, et al. "The prognostic value of gray-white-matter ratio in cardiac arrest patients treated with hypothermia.Scandinavian journal of trauma, resuscitation and emergency medicine 21 (2013): 1-7.

Lang, Margareta, et al. "A Pilot Study of Methods for Assessment of Hypoxic-Ischaemic Encephalopathy on Head Computed Tomography after Cardiac Arrest."

Yuzawa, Hironao, et al. "Pseudo-subarachnoid hemorrhage found in patients with postresuscitation encephalopathy: characteristics of CT findings and clinical importance." American journal of neuroradiology 29.8 (2008): 1544-1549.

Maurya, V. K., et al. "Hypoxic–ischemic brain injury in an adult: magnetic resonance imaging findings." Medical Journal, Armed Forces India 72.1 (2016): 75.

White, Matthew L., et al. "Anatomical patterns and correlated MRI findings of non-perinatal hypoxic–ischaemic encephalopathy." The British journal of radiology 86.1021 (2013): 20120464-20120464.

Wei, Ruili, et al. "Prediction of poor outcome after hypoxic-ischemic brain injury by diffusion-weighted imaging: A systematic review and meta-analysis." Plos one 14.12 (2019): e0226295.

Velly, Lionel, 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." The Lancet Neurology 17.4 (2018): 317-326.

Tchofo, P. Jissendi, et al. "Apparent diffusion coefficient (ADC) and magnetization transfer ratio (MTR) in pediatric hypoxic-ischemic brain injury." Journal of neuroradiology 32.1 (2005): 10-19.

Schlaug, G., et al. "Time course of the apparent diffusion coefficient (ADC) abnormality in human stroke." Neurology 49.1 (1997): 113-119.

Oren, Nisa Cem, et al. "Brain diffusion imaging findings may predict clinical outcome after cardiac arrest." Journal of Neuroimaging 29.4 (2019): 540-547.

Hirsch, Karen G., et al. "Prognostic value of diffusion-weighted MRI for post-cardiac arrest coma." Neurology 94.16 (2020): e1684-e1692.

Takahashi, Shoki, et al. "Hypoxic brain damage: cortical laminar necrosis and delayed changes in white matter at sequential MR imaging." Radiology 189.2 (1993): 449-456.

Youn, Chun Song, et al. "External validation of the 2020 ERC/ESICM prognostication strategy algorithm after cardiac arrest." Critical Care 26.1 (2022): 1-9.