Novel Imaging Biomarker Prediction of Parenchymal Hemorrhage after Mechanical Thrombectomy in Patients with Large Ischemic Core

J Stroke Cerebrovasc Dis. 2022 Jan;31(1):106125. doi: 10.1016/j.jstrokecerebrovasdis.2021.106125. Epub 2021 Oct 24.

Abstract

Background: Recently studies have shown that select acute ischemic stroke (AIS) patients with large ischemic core could be deemed as reasonable candidates to receive mechanical thrombectomy (MT) with low risk of developing parenchymal hemorrhage (PH) or symptomatic intracerebral hemorrhage (sICH); however, the selection criterion remains lacking. Our study aims to investigate the relationship between a novel imaging biomarker of largest core mass volume (LCMV) and development of PH in stroke patients with large ischemic core who have undergone MT.

Methods: A total of 26 AIS patients with large ischemic core (defined as ischemic core volume ≧ 50 ml) were enrolled in the study. Volume of ischemic core and the LCMV measured with Mistar software were measured in all patients. Fourteen patients with AIS developed PH while 12 patients showed no signs of PH based on CT imaging obtained between 24 h and 3 day after MT. We compared the volume of ischemic core and LCMV between two groups.

Results: Volume of ischemic core showed no significant difference between the PH and no PH group [105.5 (62.4-131.5) vs 75.0 (56.3-102.2), p = 0.105], whereas LCMV was significantly higher in the PH (14.80 ± 5.23) vs. no PH group (8.40 ± 2.61, p = 0.001). ROC analysis revealed that LCMV was positively correlated with PH (area under the curve = 0.905). The optimal LCMV associated with PH was ≧ 9.67 ml.

Conclusion: LCMV is an effective and easy-to-use imaging biomarker to predict PH after MT in AIS patients with large ischemic core.

Keywords: Large Ischemic Core; Largest core mass volume; Mechanical thrombectomy; Parenchymal hemorrhage.

MeSH terms

  • Biomarkers
  • Cerebral Hemorrhage* / diagnostic imaging
  • Humans
  • Ischemic Stroke* / therapy
  • Mechanical Thrombolysis* / adverse effects
  • Predictive Value of Tests

Substances

  • Biomarkers