Brain imaging in comatose survivors of cardiac arrest: Pathophysiological correlates and prognostic properties
SourceResuscitation, 133, (2018), pp. 124-136
Article / Letter to editor
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PI Group Systems Neurology
Subject240 Systems Neurology; Radboudumc 0: Other Research RIMLS: Radboud Institute for Molecular Life Sciences; Radboudumc 3: Disorders of movement DCMN: Donders Center for Medical Neuroscience; Radboudumc 9: Rare cancers RIHS: Radboud Institute for Health Sciences
INTRODUCTION: Hypoxic-ischemic brain injury is the main cause of death and disability of comatose patients after cardiac arrest. Early and reliable prognostication is challenging. Common prognostic tools include clinical neurological examination and electrophysiological measures. Brain imaging is well established for diagnosis of focal cerebral ischemia but has so far not found worldwide application in this patient group. OBJECTIVE: To review the value of Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET) for early prediction of neurological outcome of comatose survivors of cardiac arrest. METHODS: A literature search was performed to identify publications on CT, MRI or PET in comatose patients after cardiac arrest. RESULTS: We included evidence from 51 articles, 21 on CT, 27 on MRI, 1 on CT and MRI, and 2 on PET imaging. Studies varied regarding timing of measurements, choice of determinants, and cut-off values predicting poor outcome. Most studies were small (n = 6-398) and retrospective (60%). In general, cytotoxic oedema, defined by a grey-white matter ratio <1.10, derived from CT, or MRI-diffusion weighted imaging <650 x 10(-6) mm(2)/s in >10% of the brain could differentiate between patients with favourable and unfavourable outcomes on a group level within 1-3 days after cardiac arrest. Advanced imaging techniques such as functional MRI or diffusion tensor imaging show promising results, but need further evaluation. CONCLUSION: CT derived grey-white matter ratio and MRI based measures of diffusivity and connectivity hold promise to improve outcome prediction after cardiac arrest. Prospective validation studies in a multivariable approach are needed to determine the additional value for the individual patient.
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