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Multimodal MRI-based triage for acute stroke therapy: Challenges and progress

  • Sungkyunkwan University
  • Dongguk University

Research output: Contribution to journalArticlepeer-review

Abstract

Revascularization therapies have been established as the treatment mainstay for acute ischemic stroke. However, a substantial number of patients are either ineligible for revascularization therapy, or the treatment fails or is futile. At present, non-contrast computed tomography is the first-line neuroimaging modality for patients with acute stroke. The use of magnetic resonance imaging (MRI) to predict the response to early revascularization therapy and to identify patients for delayed treatment is desirable. MRI could provide information on stroke pathophysiologies, including the ischemic core, perfusion, collaterals, clot, and blood-brain barrier status. During the past 20 years, there have been significant advances in neuroimaging as well as in revascularization strategies for treating patients with acute ischemic stroke. In this review, we discuss the role of MRI and post-processing, including machine-learning techniques, and recent advances in MRI-based triage for revascularization therapies in acute ischemic stroke.

Original languageEnglish
Article number586
JournalFrontiers in Neurology
Volume9
Issue numberJUL
DOIs
StatePublished - 24 Jul 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Endovascular treatment
  • MRI
  • Machine learning
  • Stroke
  • Triage

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