• Neuroradiol J · Jun 2019

    Computed tomography perfusion as a predictor of delayed cerebral ischemia and functional outcome in spontaneous subarachnoid hemorrhage: A single center experience.

    • Isabel Fragata, Marta Alves, Ana Luísa Papoila, Ana Paiva Nunes, Patrícia Ferreira, Mariana Diogo, Nuno Canto-Moreira, and Patrícia Canhão.
    • 1 Department of Neuroradiology, Centro Hospitalar Lisboa Central, Lisbon, Portugal.
    • Neuroradiol J. 2019 Jun 1; 32 (3): 179-188.

    BackgroundComputed tomography (CT) perfusion has been studied as a tool to predict delayed cerebral ischemia (DCI) and clinical outcome in spontaneous subarachnoid hemorrhage (SAH). The purpose of the study was to determine whether quantitative CT perfusion performed within 72 hours after admission can predict the occurrence of DCI and clinical outcome as measured with a modified Rankin scale (mRS) at 3 months after ictus.MethodsCerebral perfusion was assessed in a prospective cohort of patients with acute SAH. CT perfusion parameters at <72 h post SAH were quantitatively measured in the main vascular territories and represented as whole-brain means. Spearman rank correlation coefficient and generalized additive regression models for binary outcome were used.ResultsA total of 66 patients underwent CT perfusion at <72 h. Poor clinical grade on admission was correlated with worse cerebral perfusion in all parameters. Multivariable analysis yielded an association of time to peak (TTP; odds ratio (OR) = 0.89; 95% confidence interval (CI): 0.77, 1.02; p = 0.083) with the occurrence of DCI. We also found an association of TTP values with poor outcome, with an 8% increase in the odds of mRS > 3 for each one second increase in TTP at admission (OR = 1.08; 95% CI: 1.00, 1.17; p = 0.061).ConclusionsWe identified an association of early TTP changes with DCI and poor clinical outcome. However, there were no associations with cerebral blood flow or mean transit time and DCI/clinical outcome. CT perfusion still remains to be validated as a tool in predicting outcome in SAH.

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