Literature DB >> 27569917

Gray Matter-White Matter De-Differentiation on Brain Computed Tomography Predicts Brain Death Occurrence.

C Vigneron1, V Labeye2, M Cour3, S Hannoun4, A Grember1, F Rampon1, F Cotton5.   

Abstract

BACKGROUND: Previous studies have shown that a loss of distinction between gray matter (GM) and white matter (WM) on unenhanced CT scans was predictive of poor outcome after cardiac arrest. The aim of this study was to identify a marker/predictor of imminent brain death.
METHODS: In this retrospective study, 15 brain-dead patients after anoxia and cardiac arrest were included. Patients were paired (1:1) with normal control subjects. Only patients' unenhanced CT scans performed before brain death and during the 24 hours after initial signs were analyzed. WM and GM densities were measured in predefined regions of interest (basal ganglia level, centrum semi-ovale level, high convexity level, brainstem level). At each level, GM and WM density and GM/WM ratio for brain-dead patients and normal control subjects were compared using the Wilcoxon signed-rank test.
RESULTS: At each level, a lower GM/WM ratio and decreased GM and WM densities were observed in brain-dead patients' CT scans when compared with normal control subject CT scans. A cut-off value of 1.21 at the basal ganglia level was identified, below which brain death systematically occurred.
CONCLUSIONS: GM/WM dedifferentiation on unenhanced CT scan is measurable before the occurrence of brain death, highlighting its importance in brain death prediction. The mechanism of GM/WM differentiation loss could be explained by the lack of oxygen caused by ischemia initially affecting the mitochondrial system.
Copyright © 2016 Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27569917     DOI: 10.1016/j.transproceed.2016.05.006

Source DB:  PubMed          Journal:  Transplant Proc        ISSN: 0041-1345            Impact factor:   1.066


  1 in total

1.  Utility of brain parenchyma density measurement and computed tomography perfusion imaging in predicting brain death.

Authors:  Asli I Akdogan; Hilal Sahin; Yeliz Pekcevik; Hatice Uluer
Journal:  Pol J Radiol       Date:  2020-11-25
  1 in total

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