Deep learning algorithm-based multimodal MRI radiomics and pathomics data improve prediction of bone metastases in primary prostate cancer.

Journal: Journal of cancer research and clinical oncology
Published Date: Feb 5, 2024

Abstract

PURPOSE: Bone metastasis is a significant contributor to morbidity and mortality in advanced prostate cancer, and early diagnosis is challenging due to its insidious onset. The use of machine learning to obtain prognostic information from pathological images has been highlighted. However, there is a limited understanding of the potential of early prediction of bone metastasis through the feature combination method from various sources. This study presents a method of integrating multimodal data to enhance the feasibility of early diagnosis of bone metastasis in prostate cancer.

Authors

  • Yun-Feng Zhang
    The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China.
  • Chuan Zhou
    Department of Radiology, The University of Michigan, Ann Arbor, MI, 48109, USA.
  • Sheng Guo
    Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, And Jiangsu Key Laboratory for High Technology Research of TCM Formulae, Nanjing University of Chinese Medicine, Nanjing, 210023, China.
  • Chao Wang
    College of Agriculture, Shanxi Agricultural University, Taigu, Shanxi, China.
  • Jin Yang
    Department of Critical Care Medicine, Chongqing General Hospital, Chongqing, China.
  • Zhi-Jun Yang
    The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.
  • Rong Wang
    College of Food Science and Engineering, Northwest A&F University, Yangling 712100, Shanxi, China. Electronic address: wangrong91@nwsuaf.edu.cn.
  • Xu Zhang
    China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China.
  • Feng-Hai Zhou
    The First Clinical Medical College of Gansu University of Chinese Medicine, Lanzhou, 730000, China. ldyy_zhoufh@lzu.edu.cn.

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