Dosimetric Study of Deep Learning-Guided ITV Prediction in Cone-beam CT for Lung Stereotactic Body Radiotherapy.

Journal: Frontiers in public health
PMID: 35392465

Abstract

PURPOSE: The purpose of this study was to evaluate the accuracy of a lung stereotactic body radiotherapy (SBRT) treatment plan with the target of a newly predicted internal target volume (ITV) and the feasibility of its clinical application. ITV was automatically generated by our in-house deep learning model according to the cone-beam CT (CBCT) image database.

Authors

  • Shujun Zhang
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.
  • Bo Lv
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.
  • Xiangpeng Zheng
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.
  • Ya Li
    a State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering , Lanzhou University , Lanzhou , People's Republic of China.
  • Weiqiang Ge
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.
  • Libo Zhang
    Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology Kunming 650093 China hyxia@kust.edu.cn zhanglibopaper@126.com.
  • Fan Mo
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.
  • Jianjian Qiu
    Department of Radiation Oncology, Huadong Hospital, Fudan University, Shanghai, China.

Keywords

External Resources

Popular Topics
Recent Journals