Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer.

Journal: BMC cancer
PMID: 39075447

Abstract

PURPOSE: A practical noninvasive method is needed to identify lymph node (LN) status in breast cancer patients diagnosed with a suspicious axillary lymph node (ALN) at ultrasound but a negative clinical physical examination. To predict ALN metastasis effectively and noninvasively, we developed an artificial intelligence-assisted ultrasound system and validated it in a retrospective study.

Authors

  • Xuefei Wang
    Department of Breast Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
  • Lunyiu Nie
    Department of Computer Science and Technology, Tsinghua University, Beijing, China.
  • Qingli Zhu
    Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Science & Peking Union Medical College, Shuaifuyuan 1St, Beijing, 100730, China. zqlpumch@126.com.
  • Zhichao Zuo
    School of Mathematics and Computational Science, Xiangtan University, Xiangtan, Hunan, China.
  • Guanmo Liu
    Breast Surgery Department, Chinese Academy of Medical Sciences and Peking Union Medical College, Peking Union Medical College and Hospital, No. 3 Dongdan, Dongcheng District, Beijing, China.
  • Qiang Sun
    Research Center for Agricultural and Sideline Products Processing, Henan Academy of Agricultural Sciences, 116 Park Road, Zhengzhou 450002, PR China.
  • Jidong Zhai
    Department of Computer Science and Technology, Tsinghua University, Beijing, China. zhaijidong@tsinghua.edu.cn.
  • Jianchu Li
    Department of Ultrasound, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.1 Shuai Fu Yuan, Dong Cheng District, Beijing, 100730, China.

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