Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

Journal: European radiology
PMID: 32524219

Abstract

OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).

Authors

  • Noriyuki Fujima
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.
  • V Carlota Andreu-Arasa
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.
  • Sara K Meibom
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.
  • Gustavo A Mercier
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA.
  • Andrew R Salama
    Department of Otolaryngology - Head and Neck Surgery, Boston Medical Center, Boston University School of Medicine, Boston, USA.
  • Minh Tam Truong
    Department of Radiation Oncology, Boston Medical Center, Boston University School of Medicine, Boston, USA.
  • Osamu Sakai
    Department of Radiology, Boston Medical Center, Boston University School of Medicine, FGH Building, 3rd Floor, 820 Harrison Avenue, Boston, MA, 02118, USA. Osamu.Sakai@bmc.org.

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