Prediction of dosimetric accuracy for VMAT plans using plan complexity parameters via machine learning.

Journal: Medical physics
Published Date: Jul 9, 2019

Abstract

PURPOSE: The dosimetric accuracies of volumetric modulated arc therapy (VMAT) plans were predicted using plan complexity parameters via machine learning.

Authors

  • Tomohiro Ono
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.
  • Hideaki Hirashima
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.
  • Hiraku Iramina
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.
  • Nobutaka Mukumoto
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.
  • Yuki Miyabe
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.
  • Mitsuhiro Nakamura
    Department of Radiation Oncology and Image-Applied Therapy, Kyoto University, Japan.
  • Takashi Mizowaki
    Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto, 606-8507, Japan.

Keywords

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