Multimodal MRI-Based Triage for Acute Stroke Therapy: Challenges and Progressopen access
- Authors
- Bang, Oh Young; Chung, Jong-Won; Son, Jeong Pyo; Ryu, Wi-Sun; Kim, Dong-Eog; Seo, Woo-Keun; Kim, Gyeong-Moon; Kim, Yoon-Chul
- Issue Date
- 24-Jul-2018
- Publisher
- FRONTIERS MEDIA SA
- Keywords
- stroke; MRI; endovascular treatment; machine learning; triage
- Citation
- FRONTIERS IN NEUROLOGY, v.9, no.JUL
- Indexed
- SCIE
SCOPUS
- Journal Title
- FRONTIERS IN NEUROLOGY
- Volume
- 9
- Number
- JUL
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/9303
- DOI
- 10.3389/fneur.2018.00586
- ISSN
- 1664-2295
- 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.
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Collections - Graduate School > Department of Medicine > 1. Journal Articles

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