Intraoperative stenosis detection in X-ray coronary angiography via temporal fusion and attention-based CNN.

Journal: Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PMID: 40081144

Abstract

BACKGROUND AND OBJECTIVE: Coronary artery disease (CAD), the leading cause of mortality, is caused by atherosclerotic plaque buildup in the arteries. The gold standard for the diagnosis of CAD is via X-ray coronary angiography (XCA) during percutaneous coronary intervention, where locating coronary artery stenosis is fundamental and essential. However, due to complex vascular features and motion artifacts caused by heartbeat and respiratory movement, manually recognizing stenosis is challenging for physicians, which may prolong the surgery decision-making time and lead to irreversible myocardial damage. Therefore, we aim to provide an automatic method for accurate stenosis localization.

Authors

  • Meidi Chen
    School of Biomedical Engineering, Shanghai Jiao Tong University, China.
  • Siyin Wang
    Department of Ophthalmology, Shanghai Children's Hospital, Shanghai Jiaotong University, Shanghai, China.
  • Ke Liang
    Pennsylvania State University, PA 16801, USA.
  • Xiao Chen
  • Zihan Xu
    Shenzhen Sixcarbon Technology, Shenzhen 518106, China.
  • Chen Zhao
    Department of Ophthalmology, Fudan Eye & ENT Hospital, Shanghai, China.
  • Weimin Yuan
    Department of Diagnostic Radiology, Qingdao Special Servicemen Recuperation Center of PLA Navy, Qingdao, 266071, China.
  • Jing Wan
    State Key Laboratory of ASIC and System, School of Information Science and Technology, Fudan University, Shanghai 200433, China.
  • Qiu Huang
    Department of Nuclear Medicine, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.

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