Deep learning-based prediction of tumor aggressiveness in RCC using multiparametric MRI: a pilot study.

Journal: International urology and nephrology
PMID: 39671158

Abstract

OBJECTIVE: To investigate the value of multiparametric magnetic resonance imaging (MRI) as a non-invasive method to predict the aggressiveness of renal cell carcinoma (RCC) by developing a convolutional neural network (CNN) model and fusing it with clinical characteristics.

Authors

  • Guiying Du
    Department of Radiology, The First Central Clinical College, Tianjin Medical University, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China.
  • Lihua Chen
    Department of Radiology, Southwest Hospital, Chongqing, China.
  • Baole Wen
    College of Medicine, Nankai University, Tianjin, 300350, China.
  • Yujun Lu
    Department of Radiology, The First Central Clinical College, Tianjin Medical University, No. 24 Fukang Road, Nankai District, Tianjin, 300192, China.
  • Fangjie Xia
    Department of Radiology, TEDA International Cardiovascular Hospital, No.61, Third Avenue, Binhai New Area, Tianjin, 300457, China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Wen Shen

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