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Keijzer, Hanneke M.; Duering, Marco; Pasternak, Ofer; Meijer, Frederick J. A.; Verhulst, Marlous M. L. H.; Tonino, Bart A. R.; Blans, Michiel J.; Hoedemaekers, Cornelia W. E.; Klijn, Catharina J. M. und Hofmeijer, Jeannette (2022): Free water corrected diffusion tensor imaging discriminates between good and poor outcomes of comatose patients after cardiac arrest. In: European Radiology, Bd. 33, Nr. 3: S. 2139-2148

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Abstract

Objectives Approximately 50% of comatose patients after cardiac arrest never regain consciousness. Cerebral ischaemia may lead to cytotoxic and/or vasogenic oedema, which can be detected by diffusion tensor imaging (DTI). Here, we evaluate the potential value of free water corrected mean diffusivity (MD) and fractional anisotropy (FA) based on DTI, for the prediction of neurological recovery of comatose patients after cardiac arrest. Methods A total of 50 patients after cardiac arrest were included in this prospective cohort study in two Dutch hospitals. DTI was obtained 2-4 days after cardiac arrest. Outcome was assessed at 6 months, dichotomised as poor (cerebral performance category 3-5;n = 20) or good (n = 30) neurological outcome. We calculated the whole brain mean MD and FA and compared between patients with good and poor outcomes. In addition, we compared a preliminary prediction model based on clinical parameters with or without the addition of MD and FA. Results We found significant differences between patients with good and poor outcome of mean MD (good: 726 [702-740] x 10(-6) mm(2)/s vs. poor: 663 [575-736] x 10(-6) mm(2)/s;p = 0.01) and mean FA (0.30 +/- 0.03 vs. 0.28 +/- 0.03;p = 0.03). An exploratory prediction model combining clinical parameters, MD and FA increased the sensitivity for reliable prediction of poor outcome from 60 to 85%, compared to the model containing clinical parameters only, but confidence intervals are overlapping. Conclusions Free water-corrected MD and FA discriminate between patients with good and poor outcomes after cardiac arrest and hold the potential to add to multimodal outcome prediction.

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