CT-based machine learning radiomics predicts Ki-67 expression level and its relationship with overall survival in resectable pancreatic ductal adenocarcinoma.

Journal: Abdominal radiology (New York)
Published Date: Jan 22, 2025

Abstract

BACKGROUND: The prognostic prediction of pancreatic ductal adenocarcinoma (PDAC) remains challenging. This study aimed to develop a radiomics model to predict Ki-67 expression status in PDAC patients using radiomics features from dual-phase enhanced CT, and integrated clinical characteristics to create a radiomics-clinical nomogram for prognostic prediction.

Authors

  • Jiahao Chen
    The First School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, 310006, China.
  • Zhuangxuan Ma
    Department of Radiology, Huadong Hospital, Fudan University, Shanghai, China.
  • Yamin Xu
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
  • Jieqiong Ge
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
  • Hongfei Yao
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
  • Chunjing Li
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
  • Xiao Hu
    Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, United States.
  • Yunlong Pu
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China.
  • Ming Li
    Radiology Department, Huadong Hospital, Affiliated with Fudan University, Shanghai, China.
  • Chongyi Jiang
    Department of Hepato-Biliary-Pancreatic Surgery, Huadong Hospital affiliated to Fudan University, Shanghai, China. jiangzhongyi9@sina.com.

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