Radiomics-based MRI model to predict hypoperfusion in lacunar infarction.

Journal: Magnetic resonance imaging
Published Date: Mar 21, 2025

Abstract

BACKGROUND: Approximately 20-30 % of patients with acute ischemic stroke due to lacunar infarction experience early neurological deterioration (END) within the first three days after onset, leading to disability or more severe sequelae. Hemodynamic perfusion deficits may play a crucial role in END, causing growth in the infarcted area and functional impairments, and even poor long-term prognosis. Therefore, it is vitally important to predict which patients may be at risk of perfusion deficits to initiate treatment and close monitoring early, preparing for potential reperfusion. Our goal is to utilize radiomic features from magnetic resonance imaging (MRI) and machine learning techniques to develop a predictive model for hypoperfusion.

Authors

  • Chia-Peng Chang
    Department of Emergency Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan; Department of Nursing, Chang Gung University of Science and Technology, Chiayi Campus, Chiayi, Taiwan; In-service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University.
  • Yen-Chu Huang
    College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Neurology, Chang Gung Memorial Hospital, Chiayi, Taiwan. Electronic address: deepblue@cgmh.org.tw.
  • Yuan-Hsiung Tsai
    School of Medicine, Chang Gung University, Taoyuan, Taiwan.
  • Leng-Chieh Lin
    Department of Emergency Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan. Electronic address: a3456711@cloud.cgmh.org.tw.
  • Jen-Tsung Yang
    College of Medicine, Chang Gung University, Taoyuan, Taiwan; Department of Neurosurgery, Chang Gung Memorial Hospital, Chiayi, Taiwan. Electronic address: dr1469@cgmh.org.tw.
  • Kai-Hsiang Wu
    Department of Emergency Medicine, Chang Gung Memorial Hospital, No. 6, W. Sec., Jiapu Rd., Puzih, Chiayi County, 613, Taiwan. eilrahc1219@hotmail.com.
  • Po-Han Wu
    Department of Emergency Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan.
  • Syu-Jyun Peng
    Biomedical Electronics Translational Research Center, National Chiao Tung University, Hsin-Chu, Taiwan; Institute of Electronics, National Chiao Tung University, Hsin-Chu, Taiwan. Electronic address: blue.year@msa.hinet.net.

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