Ultrasound-based radiomics machine learning models for diagnosing cervical lymph node metastasis in patients with non-small cell lung cancer: a multicentre study.

Journal: BMC cancer
Published Date:

Abstract

BACKGROUND: Cervical lymph node metastasis (LNM) is an important prognostic factor for patients with non-small cell lung cancer (NSCLC). We aimed to develop and validate machine learning models that use ultrasound radiomic and descriptive semantic features to diagnose cervical LNM in patients with NSCLC.

Authors

  • Zhiqiang Deng
    Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803, United States. Electronic address: zdeng@lsu.edu.
  • Xiaoling Liu
    Department of Endocrinology, Affiliated Hospital of Guilin Medical University, Guilin, Guangxi, China.
  • Renmei Wu
    Department of Ultrasound, Suining Central Hospital, Suining, China.
  • Haoji Yan
    Department of General Thoracic Surgery, Juntendo University School of Medicine, Tokyo, Japan.
  • Lingyun Gou
    Department of Ultrasound, Affiliated Hospital of North Sichuan Medical College, Nanchong, China.
  • Wenlong Hu
    Department of Clinical Medicine, North Sichuan Medical College, Nanchong, China.
  • Jiaxin Wan
    Department of Clinical Medicine, North Sichuan Medical College, Nanchong, China.
  • Chenwanqiu Song
    College of Medical Imaging, North Sichuan Medical College, Nanchong, China.
  • Jing Chen
    Department of Vascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi 530021, P.R. China.
  • Daiyuan Ma
    Department of Oncology, Affiliated Hospital of North Sichuan Medical College, Nanchong, China. mdylx@163.com.
  • Haining Zhou
    Department of Thoracic Surgery, Suining Central Hospital, Sunning, China. haining_zhou@zmu.edu.cn.
  • Dong Tian
    Department of Thoracic Surgery, West China Hospital, Sichuan University, Chengdu, China.