Predicting gamma passing rates for portal dosimetry-based IMRT QA using machine learning.

Journal: Medical physics
Published Date: Aug 27, 2019

Abstract

PURPOSE: Intensity-modulated radiation therapy (IMRT) quality assurance (QA) measurements are routinely performed prior to treatment delivery to verify dose calculation and delivery accuracy. In this work, we applied a machine learning-based approach to predict portal dosimetry based IMRT QA gamma passing rates.

Authors

  • Dao Lam
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
  • Xizhe Zhang
    School of Computer Science and Engineering, Northeastern University, Shenyang, Liaoning, 110819, China.
  • Harold Li
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
  • Yang Deshan
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
  • Brayden Schott
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
  • Tianyu Zhao
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.
  • Weixiong Zhang
    Department of Computer Science and Engineering, Washington University, One Brookings Drive, CampusBox 1045, St. Louis, MO, 63130, USA.
  • Sasa Mutic
    Department of Radiation Oncology, Washington University, St. Louis, MO, USA.
  • Baozhou Sun
    Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus Box 8224, St. Louis, MO, 63110, USA.

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