Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function.

Journal: International journal of radiation oncology, biology, physics
Published Date: Feb 7, 2018

Abstract

PURPOSE: Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin expansions to auto-delineate high-risk CTVs, very little work has been performed to provide patient- and disease-specific high-risk CTVs. The aim of the present study was to develop a deep neural network for the auto-delineation of high-risk CTVs.

Authors

  • Carlos E Cardenas
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: cecardenas@mdanderson.org.
  • Rachel E McCarroll
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Laurence E Court
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Baher A Elgohari
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, Mansoura University, Mansoura, Egypt.
  • Hesham Elhalawani
    The Johns Hopkins Hospital, Department of Radiology, 601 N Caroline St, Room 4223, Baltimore, MD 21287 (S.K.); Cleveland Clinic, Department of Radiation Oncology, Cleveland, Ohio (H.E.); Emory University School of Medicine, Department of Radiology, Atlanta, Georgia (J.G.); University of Pennsylvania, Department of Radiology, Philadelphia, Pennsylvania (C.E.K.).
  • Clifton D Fuller
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Mona J Kamal
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • Mohamed A M Meheissen
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Clinical Oncology and Nuclear Medicine, Faculty of Medicine, University of Alexandria, Alexandria, Egypt.
  • Abdallah S R Mohamed
    Anderson Cancer Center.
  • Arvind Rao
    Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Bowman Williams
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Andrew Wong
    School of Medicine, University of California, San Francisco.
  • Jinzhong Yang
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Michalis Aristophanous
    Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, Illinois.

Keywords

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