Radiomic machine learning for pretreatment assessment of prognostic risk factors for endometrial cancer and its effects on radiologists' decisions of deep myometrial invasion.

Journal: Magnetic resonance imaging
Published Date: Oct 20, 2021

Abstract

PURPOSE: To evaluate radiomic machine learning (ML) classifiers based on multiparametric magnetic resonance images (MRI) in pretreatment assessment of endometrial cancer (EC) risk factors and to examine effects on radiologists' interpretation of deep myometrial invasion (dMI).

Authors

  • Satoshi Otani
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyoku, Kyoto, 606-8507, Japan.
  • Yuki Himoto
    Body Imaging Service, Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
  • Mizuho Nishio
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Koji Fujimoto
    Human Brain Research Center, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Yusaku Moribata
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyoku, Kyoto, 606-8507, Japan.
  • Masahiro Yakami
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
  • Yasuhisa Kurata
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyoku, Kyoto, 606-8507, Japan; Department of Diagnostic Radiology, Kobe City Medical Center General Hospital, 2-1-1, Minatojimaminamimachi, Chuo-ku, Kobe, Hyogo, 650-0047, Japan.
  • Junzo Hamanishi
    Department of Gynecology and Obstetrics, Kyoto University, Kyoto 606-8507, Japan.
  • Akihiko Ueda
    Department of Gynecology and Obstetrics, Kyoto University, Kyoto 606-8507, Japan.
  • Sachiko Minamiguchi
    Department of Diagnostic Pathology, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
  • Masaki Mandai
    Department of Gynecology and Obstetrics, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyoku, Kyoto, 606-8507, Japan.
  • Aki Kido
    Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyoku, Kyoto, 606-8507, Japan.

Keywords

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