Development and validation of a combined nomogram model based on deep learning contrast-enhanced ultrasound and clinical factors to predict preoperative aggressiveness in pancreatic neuroendocrine neoplasms.

Journal: European radiology
Published Date: Apr 7, 2022

Abstract

OBJECTIVES: This study aimed to develop and validate a combined nomogram model based on deep learning (DL) contrast-enhanced ultrasound (CEUS) and clinical factors to preoperatively predict the aggressiveness of pancreatic neuroendocrine neoplasms (PNENs).

Authors

  • Jingzhi Huang
    Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
  • Xiaohua Xie
    School of Data and Computer Science, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Hong Wu
    Department of Liver Surgery, Liver Transplantation Division, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Xiaoer Zhang
    Department of Medical Ultrasound, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, China.
  • Yanling Zheng
    College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830054, People's Republic of China. zhengyl_math@sina.cn.
  • Xiaoyan Xie
    Department of Medical Ultrasonics, Institute of Diagnostic and Interventional Ultrasound, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510080, China.
  • Yi Wang
    Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China.
  • Ming Xu
    Shenyang Analytical Application Center, Shimadzu (China) Co. Ltd., Shenyang, 167 Qingnian Street, Shenyang, 110016, PR China.

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