Added prognostic value of 3D deep learning-derived features from preoperative MRI for adult-type diffuse gliomas.

Journal: Neuro-oncology
Published Date:

Abstract

BACKGROUND: To investigate the prognostic value of spatial features from whole-brain MRI using a three-dimensional (3D) convolutional neural network for adult-type diffuse gliomas.

Authors

  • Jung Oh Lee
    Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Sung Soo Ahn
    Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea. sungsoo@yuhs.ac.
  • Kyu Sung Choi
    Graduate School of Medical Science and Engineering, Korea Advanced Institute for Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Junhyeok Lee
    Department of Software Convergence, Kyung Hee University, Yongin 17104, Korea.
  • Joon Jang
    Department of Biomedical Sciences, Seoul National University, Seoul, South Korea.
  • Jung Hyun Park
    2Department of Food Science and Technology, Yeungnam University, Gyeongsan, Gyeongsanbuk-do 38541 Republic of Korea.
  • Inpyeong Hwang
    Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Chul-Kee Park
    Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Republic of Korea.
  • Sung Hye Park
    Department of Pathology, Seoul National University Hospital, Seoul, Republic of Korea.
  • Jin Wook Chung
    Department of Radiology, Seoul National University Hospital, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
  • Seung Hong Choi
    From the Graduate School of Medical Science and Engineering (K.H.K., S.H.P.) and Department of Bio and Brain Engineering (S.H.P.), Korea Advanced Institute of Science and Technology, Room 1002, CMS (E16) Building, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea; Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea (S.H.C.); Department of Radiology, Seoul National University College of Medicine, and Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea (S.H.C.); and Center for Nanoparticle Research, Institute for Basic Science, Seoul, Republic of Korea (S.H.C.).