Deep learning-based detection and classification of multi-leaf collimator modeling errors in volumetric modulated radiation therapy.

Journal: Journal of applied clinical medical physics
PMID: 37633834

Abstract

PURPOSE: The purpose of this study was to create and evaluate deep learning-based models to detect and classify errors of multi-leaf collimator (MLC) modeling parameters in volumetric modulated radiation therapy (VMAT), namely the transmission factor (TF) and the dosimetric leaf gap (DLG).

Authors

  • Sae Nakamura
    Department of Radiation Oncology, Niigata Neurosurgical Hospital, Nishi-ku, Niigata City, Niigata, Japan.
  • Madoka Sakai
    Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Natsuki Ishizaka
    Department of Radiology, Niigata Prefectural Shibata Hospital, Shibata City, Niigata, Japan.
  • Kazuki Mayumi
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, Chuo-ku, Niigata City, Niigata, Japan.
  • Tomotaka Kinoshita
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, Chuo-ku, Niigata City, Niigata, Japan.
  • Shinya Akamatsu
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, Chuo-ku, Niigata City, Niigata, Japan.
  • Takayuki Nishikata
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, Chuo-ku, Niigata City, Niigata, Japan.
  • Shunpei Tanabe
    Department of Radiation Oncology, Niigata University Medical and Dental Hospital, Chuo-ku, Niigata City, Niigata, Japan.
  • Hisashi Nakano
    Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Satoshi Tanabe
    Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Takeshi Takizawa
    Department of Radiation Oncology, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Takumi Yamada
    Section of Radiology, Department of Clinical Support, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Hironori Sakai
    Section of Radiology, Department of Clinical Support, Niigata University Medical and Dental Hospital, 1-754 Asahimachi-dori, Chuo-ku, Niigata, 951-8520, Japan.
  • Motoki Kaidu
    Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata, 951-8510, Japan.
  • Ryuta Sasamoto
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, 2-746 Asahimachi-dori, Chuo-ku, Niigata, 951-8518, Japan.
  • Hiroyuki Ishikawa
    Department of Radiology and Radiation Oncology, Niigata University Graduate School of Medical and Dental Sciences, 1-757 Asahimachi-dori, Chuo-ku, Niigata, 951-8510, Japan.
  • Satoru Utsunomiya
    Department of Radiological Technology, Niigata University Graduate School of Health Sciences, 2-746 Asahimachi-dori, Chuo-ku, Niigata, 951-8518, Japan.

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