Risk assessment of hemorrhagic transformation of acute middle cerebral artery stroke using multimodal CT

J Neuroimaging. 2012 Apr;22(2):160-6. doi: 10.1111/j.1552-6569.2010.00562.x. Epub 2010 Dec 9.

Abstract

Purpose: Multimodal CT with CT angiography (CTA) and CT perfusion (CTP) are increasingly used in stroke triage. Our aim was to identify parameters most predictive of hemorrhagic transformation (HT), especially symptomatic intracerebral hemorrhage (SICH).

Methods: This retrospective study included patients evaluated by baseline multimodal CT ≤ 9 hours from ictus with acute nonlacunar middle cerebral artery (MCA) territory infarction. Two readers independently evaluated CTP maps for ischemic severity and CTA source images (CTA-SI) for infarct extent (as measured by ASPECTS). Presence of proximal occlusion (ICA or M1) and degree of collateralization (collateral score) were also assessed on CTA. HT was defined as SICH if associated with deterioration ≥ 4-points on NIHSS. Multivariate logistic regression analysis identified independent predictors of SICH. ROC curves selected optimal thresholds.

Results: Of 84 patients reviewed, HT occurred in 22 (26.2%) and SICH in 8 (9.5%). Univariate predictors for SICH were proximal occlusion (OR = 8.65, P= .049), collateral score (OR = .34, P= .017), ASPECTS (OR = .46, P= .001), and CBV (OR = .001, P= .005). Multivariate analysis revealed ASPECTS as the only independent predictor with optimal threshold ≤ 5 and sensitivity and specificity of 75.0% and 85.5%, respectively.

Conclusion: For acute MCA infarcts ≤ 9 hours, the strongest predictor of SICH on multimodal CT was ASPECTS on CTA-SI.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Brain Ischemia / diagnostic imaging*
  • Cerebral Angiography
  • Female
  • Humans
  • Infarction, Middle Cerebral Artery / diagnostic imaging*
  • Intracranial Hemorrhages / diagnostic imaging*
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Retrospective Studies
  • Risk Assessment
  • Sensitivity and Specificity
  • Severity of Illness Index