Deep learning-based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers.

Journal: Medical physics
Published Date: Sep 14, 2023

Abstract

BACKGROUND: In recent years, deep-learning models have been used to predict entire three-dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated.

Authors

  • Mary P Gronberg
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Anuja Jhingran
    Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA.
  • Tucker J Netherton
    Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
  • Skylar S Gay
    Department of Radiation Physics, University of Texas MD Anderson Cancer Center, Houston, Texas.
  • 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 Fuentes
    Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, United States.
  • 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.
  • Meena Khan
    Department of Radiation Physics, 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.
  • 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.

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