An isodose-constrained automatic treatment planning strategy using a multicriteria predicted dose rating.

Journal: Medical physics
Published Date: Apr 4, 2025

Abstract

BACKGROUND: Previous knowledge-based planning studies have demonstrated the feasibility of predicting three-dimensional photon dose distributions and subsequently generating treatment plans. The steepness of dose fall-off represents a critical metric for clinical plan evaluation; however, dose fall-off similarity is frequently overlooked in dose prediction tasks. Our study introduces a novel automatic treatment planning methodology that specifically focuses on dose fall-off reconstruction for nasopharyngeal carcinoma (NPC).

Authors

  • Zihan Sun
    Department of Ophthalmology and Visual Sciences, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, Hong Kong, China.
  • Jiazhou Wang
    Department of radiation oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Weigang Hu
    Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
  • Yongheng Yan
    Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China. Electronic address: 1521011@zju.edu.cn.
  • Yuanhua Chen
    Radiation Oncology Department, 1st Affiliated Hospital of Medical School of Zhejiang University, Zhejiang, China.
  • Guorong Yao
    Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
  • Zhongjie Lu
    Radiation Oncology Department, 1st Affiliated Hospital of Medical School of Zhejiang University, Zhejiang, China.
  • SenXiang Yan
    Department of Radiation Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou, 310003, Zhejiang, China; Cancer Center, Zhejiang University, 866 Yuhangtang Road, Hangzhou, 310027, Zhejiang, China. Electronic address: yansenxiang@zju.edu.cn.

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