An Ultrasound Image-Based Deep Learning Radiomics Nomogram for Differentiating Between Benign and Malignant Indeterminate Cytology (Bethesda III) Thyroid Nodules: A Retrospective Study.

Journal: Journal of clinical ultrasound : JCU
Published Date: May 21, 2025

Abstract

RATIONALE AND OBJECTIVES: Our objective is to develop and validate a deep learning radiomics nomogram (DLRN) based on preoperative ultrasound images and clinical features, for predicting the malignancy of thyroid nodules with indeterminate cytology (Bethesda III).

Authors

  • Lichang Zhong
    Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China.
  • Lin Shi
    Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, China.
  • Weimei Li
    Department of Ultrasound in Medicine, Sixth People's Hospital Affiliated to Medical College of Shanghai Jiaotong University, Shanghai Institute of Ultrasound in Medicine, Shanghai, China.
  • Liang Zhou
    Department of Otorhinolaryngology, Eye & ENT Hospital, Fudan University, Shanghai, 200031, China. liang.zhou@fdeent.org.
  • Kui Wang
    The Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong.
  • Liping Gu
    Department of Endocrinology and Metabolism, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai, China.

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