Evaluation of a highly refined prediction model in knowledge-based volumetric modulated arc therapy planning for cervical cancer.

Journal: Radiation oncology (London, England)
Published Date: Mar 22, 2021

Abstract

BACKGROUND AND PURPOSE: To explore whether a highly refined dose volume histograms (DVH) prediction model can improve the accuracy and reliability of knowledge-based volumetric modulated arc therapy (VMAT) planning for cervical cancer.

Authors

  • Mingli Wang
    Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
  • Huikuan Gu
    Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
  • Jiang Hu
    Department of Orthopedics, Sichuan Academy of Medical Science·Sichuan Provincal People's Hospital, Chengdu Sichuan, 610072, P.R.China.hujiang8711@163.com.
  • Jian Liang
    Cloud and Smart Industries Group, Tencent, Beijing, China.
  • Sisi Xu
    Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
  • Zhenyu Qi
    Institute of Automation, Chinese Academy of Sciences (CAS), China. Electronic address: zhenyu.qi@ia.ac.cn.

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