The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules.

Journal: BMC cancer
Published Date: Jul 1, 2025

Abstract

BACKGROUND AND AIMS: More cases of thyroid micro-nodules have been diagnosed annually in recent years because of advancements in diagnostic technologies and increased public health awareness. To explore the application value of various machine learning (ML) algorithms based on dual-layer spectral computed tomography (DLCT) quantitative parameters in distinguishing benign from malignant thyroid micro-nodules.

Authors

  • Zuhua Song
    Department of Radiology, Chongqing General Hospital, Chongqing University, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Jie Huang
    Department of Critical Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.
  • Dan Zhang
    School of Pharmacy, Southwest Medical University, Luzhou 646000, China.
  • Jiayi Yu
    Department of Stomatology, Shenzhen University General Hospital, Shenzhen University, Shenzhen 518000, China.
  • Bi Zhou
    Department of Radiology and Medical Imaging, Shanghai Sixth People's Hospital, Shanghai Jiao Tong University, Shanghai 200233, China.
  • Jiang Ma
    Department of Radiology, Chongqing General Hospital, Chongqing University, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China.
  • Ya Zou
    Department of Radiology, Chongqing General Hospital, Chongqing University, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China.
  • Yuwei Chen
    Department of Radiology, Chongqing General Hospital, Chongqing University, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China.
  • Zhuoyue Tang
    Department of Radiology, Chongqing General Hospital, Chongqing University, No.118, Xingguang Avenue, Liangjiang New Area, Chongqing, 401147, China. zhuoyue_tang@cqu.edu.cn.

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