Deep learning based on carotid transverse B-mode scan videos for the diagnosis of carotid plaque: a prospective multicenter study.

Journal: European radiology
PMID:

Abstract

OBJECTIVES: Accurate detection of carotid plaque using ultrasound (US) is essential for preventing stroke. However, the diagnostic performance of junior radiologists (with approximately 1 year of experience in carotid US evaluation) is relatively poor. We thus aim to develop a deep learning (DL) model based on US videos to improve junior radiologists' performance in plaque detection.

Authors

  • Jia Liu
    Department of Colorectal Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, China.
  • Xinrui Zhou
    School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798, Singapore.
  • Hui Lin
    Department of Mechanical Aerospace and Nuclear Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States of America.
  • Xue Lu
    Guangdong Key Laboratory of Liver Disease Research, Department of Medical Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Jian Zheng
    Biospheric Assessment for Waste Disposal Team, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan; Fukushima Project Headquarters, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, 4-9-1 Anagawa, Inage, Chiba 263-8555, Japan. Electronic address: zheng.jian@qst.go.jp.
  • Erjiao Xu
    The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
  • Dianhu Jiang
    The Second People's Hospital of Foshan, Foshan, China.
  • Hui Zhang
    Department of Pulmonary Vessel and Thrombotic Disease, Sixth Medical Center, Chinese PLA General Hospital, Beijing, China.
  • Xin Yang
    Department of Oral Maxillofacial-Head Neck Oncology, Ninth People's Hospital, College of Stomatology, Shanghai Jiao Tong University School of Medicine, National Clinical Research Center for Oral Diseases, Shanghai Key Laboratory of Stomatology & Shanghai Research Institute of Stomatology, Shanghai, China.
  • Junlin Zhong
    The Third Affiliated Hospital of Sun Yat-sen University, 600 Tianhe Road, Tianhe District, Guangzhou, 510630, China.
  • Xindi Hu
    Shenzhen RayShape Medical Technology Co. Ltd., Shenzhen, China.
  • Yuhao Huang
    Department of Neurosurgery, Stanford University School of Medicine, Palo Alto, CA, USA. yhhuang@stanford.edu.
  • Yanling Zhang
    1 School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 100102, P. R. China.
  • Jiamin Liang
    Medical UltraSound Computing (MUSIC) Lab, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Provincial Key Laboratory of Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China.
  • Qin Liu
    School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social risk Governance in Health, Chongqing Medical University, Chongqing 400016, China.
  • Min Zhong
    Longgang District People's Hospital, Shenzhen, China.
  • Yuansen Chen
    The Third People's Hospital of Longgang District, Shenzhen, China.
  • Huixiang Yan
    The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China.
  • Haowen Deng
    Department of Information Management and Information Systems, Fudan University, Shanghai, China.
  • Rongqin Zheng
    Guangdong Key Laboratory of Liver Disease Research, Department of Medical Ultrasound, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
  • Dong Ni
  • Jie Ren
    Digital Clinical Measures, Translational Medicine, Merck & Co., Inc., Rahway, NJ, United States.