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E-152 Subarachnoid hemorrhage quantitative volume analysis: blood volume predicts cerebral vasospasm, delayed cerebral infarction and clinical outcome
  1. B Daou,
  2. S Khalsa,
  3. S Anand,
  4. C Williamson,
  5. K Rajajee,
  6. K Sheehan,
  7. A Pandey
  1. Neurosurgery, University of Michigan, Ann Arbor, MI


Introduction Conventional grading scales in aneurysmal subarachnoid hemorrhage (aSAH) do not take into account the total blood volume and have been criticized for being open to variability in interpretation. We aimed to evaluate an automatic tool for quantification of the hemorrhage volume in aSAH.

Methods Blood volumes were retrospectively analyzed and added to a comprehensive prospectively maintained institutional SAH database. Patients with non-aSAH were excluded. We designed an automatic quantitative blood volume analysis tool that utilizes a segmentation system that differentiates seed points corresponding to the different intracranial compartments. Through logistic regression analysis, we evaluated the association of blood volume with clinical cerebral vasospasm, delayed cerebral infarction (DCI) and 3-months clinical outcome. The diagnostic accuracy (AUC) of the quantitative blood volume analysis was compared to the modified Fisher score, the Hunt and Hess sore, the Hijdra score, and the World Federation of Neurosurgical Societies (WFNS) score.

Results 288 aSAH patients with a mean total blood volume of 74.9 ml (± 39.7 ml) made up the study population. 73 patients developed clinical vasospasm (25.3%) and 52 patients developed DCI (18.06%). In univariate and multivariate analysis, total blood volume was significantly predictive of clinical vasospasm, DCI and clinical outcome. Blood volume had the highest AUC for clinical vasospasm as well as DCI when compared to conventional SAH scales. The modified Fisher score was not significantly predictive of either outcome.

Conclusion Quantitative analysis of blood volume in aSAH provides a tool for prediction of cerebral vasospasm, DCI and clinical outcome that may have a higher performance and improved accuracy when compared to grading systems used in current practice.

Disclosures B. Daou: None. S. Khalsa: None. S. Anand: None. C. Williamson: None. K. Rajajee: None. K. Sheehan: None. A. Pandey: None.

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