Diagnosis of skull-base invasion by nasopharyngeal tumors on CT with a deep-learning approach.

Journal: Japanese journal of radiology
PMID:

Abstract

PURPOSE: To develop a convolutional neural network (CNN) model to diagnose skull-base invasion by nasopharyngeal malignancies in CT images and evaluate the model's diagnostic performance.

Authors

  • Junichi Nakagawa
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Noriyuki Fujima
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.
  • Kenji Hirata
    Department of Diagnostic Imaging, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, Sapporo, Japan.
  • Taisuke Harada
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Naoto Wakabayashi
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Yuki Takano
    Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, N15 W7, Kita-Ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Akihiro Homma
    Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Satoshi Kano
    Otolaryngology-Head and Neck Surgery, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan.
  • Kazuyuki Minowa
    Faculty of Dental Medicine, Department of Radiology, Hokkaido University, N13 W7, Kita-ku, Sapporo, Hokkaido, 060-8586, Japan.
  • Kohsuke Kudo
    Departments of Diagnostic Imaging, Hokkaido University Graduate School of Medicine, kita 15, nishi 7, kita-ku, Sapporo, Hokkaido, 060-8638, Japan.