MRI-based deep learning and radiomics for prediction of occult cervical lymph node metastasis and prognosis in early-stage oral and oropharyngeal squamous cell carcinoma: a diagnostic study.

Journal: International journal of surgery (London, England)
PMID: 38729119

Abstract

INTRODUCTION: The incidence of occult cervical lymph node metastases (OCLNM) is reported to be 20-30% in early-stage oral cancer and oropharyngeal cancer. There is a lack of an accurate diagnostic method to predict occult lymph node metastasis and to help surgeons make precise treatment decisions.

Authors

  • Tianjun Lan
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Shijia Kuang
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Peisheng Liang
    Guanghua School of Stomatology, Hospital of Stomatology, Guangdong Province Key Laboratory of Stomatology, Sun Yat-Sen University, Guangzhou.
  • Chenglin Ning
    School of Biomedical Engineering, Southern Medical University, Guangzhou.
  • Qunxing Li
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Liansheng Wang
    Department of Computer Science, Xiamen University, Xiamen 361005, China.
  • Youyuan Wang
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Zhaoyu Lin
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Huijun Hu
    Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.
  • Lingjie Yang
    Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Jintao Li
    High Performance Computer Research Center, Institute of Computing Technology Chinese Academy of Sciences, Beijing 100190, China.
  • Jingkang Liu
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.
  • Yanyan Li
    Department of Center of Integrated Traditional Chinese and Western Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing, People's Republic of China.
  • Fan Wu
    Department of Product Design, Dalian Polytechnic University, Dalian 116034, China.
  • Hua Chai
    Faculty of Information Technology & State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Technology, Avenida Wai Long,Taipa, Macau, 999078, China.
  • Xinpeng Song
    School of Mathematics and Big Data, Foshan University, Foshan, Guangdong.
  • Yiqian Huang
    School of Mathematics and Big Data, Foshan University, Foshan, Guangdong.
  • Xiaohui Duan
    Department of Radiology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. Electronic address: duanxh5@mail.sysu.edu.cn.
  • Dong Zeng
  • Jinsong Li
    Department of Spine Surgery, The Third Xiangya Hospital of Central South University, 138 Tongzipo Rd, Changsha, 410013, Hunan, China.
  • Haotian Cao
    Department of Oral and Maxillofacial Surgery, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou.

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