Using Deep-Learning-Based Artificial Intelligence Technique to Automatically Evaluate the Collateral Status of Multiphase CTA in Acute Ischemic Stroke.

Journal: Tomography (Ann Arbor, Mich.)
Published Date: Mar 16, 2023

Abstract

BACKGROUND: Collateral status is an important predictor for the outcome of acute ischemic stroke with large vessel occlusion. Multiphase computed-tomography angiography (mCTA) is useful to evaluate the collateral status, but visual evaluation of this examination is time-consuming. This study aims to use an artificial intelligence (AI) technique to develop an automatic AI prediction model for the collateral status of mCTA.

Authors

  • Chun-Chao Huang
    Department of Radiology, MacKay Memorial Hospital, Taipei 104217, Taiwan.
  • Hsin-Fan Chiang
    Department of Radiology, MacKay Memorial Hospital, Taipei 104217, Taiwan.
  • Cheng-Chih Hsieh
    Department of Radiology, MacKay Memorial Hospital, Taipei 104217, Taiwan.
  • Chao-Liang Chou
    Department of Medicine, MacKay Medical College, New Taipei City 252005, Taiwan.
  • Zong-Yi Jhou
    Institute of Mechatronic Engineering, National Taipei University of Technology, Taipei 106344, Taiwan.
  • Ting-Yi Hou
    Institute of Mechatronic Engineering, National Taipei University of Technology, Taipei 106344, Taiwan.
  • Jin-Siang Shaw
    Institute of Mechatronic Engineering, National Taipei University of Technology, No.1, Sec. 3, Zhongxiao E. Rd., Da'an Dist, Taipei City, 106, Taiwan. jshaw@ntut.edu.tw.

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