Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.

Journal: JAMA network open
PMID:

Abstract

IMPORTANCE: Accurate identification of lymph node metastasis preoperatively and noninvasively in patients with cervical cancer can avoid unnecessary surgical intervention and benefit treatment planning.

Authors

  • Qingxia Wu
    College of Medicine and Biomedical Information Engineering, Northeastern University, Shenyang, Liaoning, China.
  • Shuo Wang
    College of Tea & Food Science, Anhui Agricultural University, Hefei, China.
  • Shuixing Zhang
    Medical Imaging Center, First Affiliated Hospital of Jinan University, Guangzhou, Guangdong, PR China; Institute of Molecular and Functional Imaging, Jinan University, Guangzhou, Guangdong, PR China. Electronic address: shui7515@126.com.
  • Meiyun Wang
  • Yingying Ding
    Department of Radiology, the Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Kunming, Yunnan, China.
  • Jin Fang
    Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Wei Qian
    Department of Electrical and Computer Engineering, University of Texas at El Paso, 500 West University Avenue, El Paso, TX 79968, USA; Sino-Dutch Biomedical and Information Engineering School, Northeastern University, No.11, Lane 3, Wenhua Road, Heping District, Shenyang, Liaoning 110819, China. Electronic address: wqian@utep.edu.
  • Zhenyu Liu
    School of Electronic Information, Hangzhou Dianzi University, Hangzhou 310018, China.
  • Kai Sun
    Department of Materials Science and Engineering, Jinan University.
  • Yan Jin
    Lilly Research Laboratories, Lilly Corporate Center, Indianapolis, IN 46285, USA.
  • He Ma
    Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang 110819, China and Key Laboratory of Medical Image Computing, Ministry of Education, Northeastern University, Shenyang 110819, China.
  • Jie Tian
    CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.