Deep learning radiomics nomograms predict Isocitrate dehydrogenase (IDH) genotypes in brain glioma: A multicenter study.

Journal: Magnetic resonance imaging
PMID:

Abstract

PURPOSE: To explore the feasibility of Deep learning radiomics nomograms (DLRN) in predicting IDH genotype.

Authors

  • Darui Li
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Wanjun Hu
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Laiyang Ma
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Wenxia Yang
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Jie Zou
    Institute of Intelligent Control and Robotics, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China.
  • Xin Ge
  • Yuping Han
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Tiejun Gan
    Department of Nuclear Magnetic Resonance, The Second Hospital & Clinical Medical School, Lanzhou University, Lanzhou 730030, China; Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China.
  • Dan Cheng
    Massachusetts General Hospital, Boston, MA.
  • Kai Ai
    Philips Healthcare, Xi'an, China.
  • Guangyao Liu
  • Jing Zhang
    MOEMIL Laboratory, School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu, China.