Automated coronary artery segmentation / tissue characterization and detection of lipid-rich plaque: An integrated backscatter intravascular ultrasound study.

Journal: International journal of cardiology
Published Date: Aug 8, 2025

Abstract

BACKGROUND: Intravascular ultrasound (IVUS)-based tissue characterization has been used to detect vulnerable plaque or lipid-rich plaque (LRP). Recently, advancements in artificial intelligence (AI) technology have enabled automated coronary arterial plaque segmentation and tissue characterization. The purpose of this study was to evaluate the feasibility and diagnostic accuracy of a deep learning model for plaque segmentation, tissue characterization and identification of LRP.

Authors

  • Yuto Masuda
    Department of Medical Education, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi Mizuho-cho Mizuho-ku, Nagoya, 467-8601, Japan.
  • Ryo Takeshita
    Department of Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan.
  • Akiko Tsujimoto
    Department of Cardiology, Gifu University Gradual School of Medicine, Gifu, Japan.
  • Yuki Sahashi
    Department of Cardiovascular Medicine, Gifu Heart Center, Gifu, Japan.
  • Takatomo Watanabe
    Department of Cardiology, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, Gifu, Japan.
  • Daisuke Fukuoka
    The United Graduate School of Drug Discovery and Medical Information Sciences, Gifu University.
  • Takeshi Hara
    Department of Psychosomatic Medicine, Endocrinology and Diabetes Mellitus, Fukuoka Tokushukai Hospital, Kasuga, Fukuoka, Japan.
  • Hiromitsu Kanamori
    Department of Cardiology, Gifu University Gradual School of Medicine, Gifu, Japan.
  • Hiroyuki Okura
    Department of Cardiology, Gifu University Graduate School of Medicine, 1-1 Yanagido, Gifu City, Gifu, Japan.

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