Deep Learning-Based Dose Prediction for Automated, Individualized Quality Assurance of Head and Neck Radiation Therapy Plans.

Journal: Practical radiation oncology
Published Date:

Abstract

PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.

Authors

  • Mary P Gronberg
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Beth M Beadle
    Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA, 94305, USA.
  • Adam S Garden
  • Heath Skinner
    Department of Radiation Oncology, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Skylar Gay
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Tucker Netherton
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Wenhua Cao
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Carlos E Cardenas
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas. Electronic address: cecardenas@mdanderson.org.
  • Christine Chung
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • David T Fuentes
    Department of Imaging Physics, Division of Diagnostic Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX.
  • Clifton D Fuller
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Rebecca M Howell
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Anuja Jhingran
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Tze Yee Lim
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Barbara Marquez
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Raymond Mumme
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Adenike M Olanrewaju
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Christine B Peterson
    Department of Biostatistics, Division of Basic Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Ivan Vazquez
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
  • Thomas J Whitaker
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, Texas.
  • Zachary Wooten
    Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Statistics, Rice University, Houston, Texas.
  • Ming Yang
    Wuhan Institute for Food and Cosmetic Control, Wuhan 430014, China.
  • Laurence E Court
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.