Machine learning model based on preoperative contrast-enhanced CT and clinical features to predict perineural invasion in gallbladder carcinoma patients.

Journal: European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
PMID: 39987815

Abstract

BACKGROUND: Perineural invasion (PNI) is an independent prognostic risk factor for gallbladder carcinoma (GBC). However, there is currently no reliable method for the preoperative noninvasive prediction of PNI.

Authors

  • Hengchao Liu
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Zhenqi Tang
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Xue Feng
    Department of Radiology and Medical Imaging, University of Virginia, Charlottesville, Virginia.
  • Yali Cheng
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China.
  • Chen Chen
    The George Institute for Global Health, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
  • Dong Zhang
    Institute of Acoustics, Nanjing University, Nanjing 210093, China.
  • Jianjun Lei
  • Zhimin Geng
    Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061, Shaanxi, China. gengzhimin@mail.xjtu.edu.cn.
  • Qi Li
    The First Affiliated Hospital of Yangtze University, Jingzhou, Hubei, China.

Keywords

External Resources

Popular Topics
Recent Journals