Uncertainty quantification for CT dosimetry based on 10 281 subjects using automatic image segmentation and fast Monte Carlo calculations.

Journal: Medical physics
Published Date: Apr 1, 2025

Abstract

BACKGROUND: Computed tomography (CT) scans are a major source of medical radiation exposure worldwide. In countries like China, the frequency of CT scans has grown rapidly, thus making available a large volume of organ dose information. With modern computational methods, we are now able to overcome challenges in automatic organ segmentation and rapid Monte Carlo (MC) dose calculations. We hypothesize that it is possible to process an extremely large number of patient-specific organ dose datasets in order to quantify and understand the range of CT dose uncertainties associated with inter-individual variability.

Authors

  • Zirui Ye
    School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, China.
  • Bei Yao
    The First Affiliated Hospital, University of Science and Technology of China, Hefei, China.
  • Haoran Zheng
    School of Computer Science and Technology, University of Science and Technology of China, Huangshan Road, Hefei, 230026, People's Republic of China. zhulx@mail.ustc.edu.cn.
  • Li Tao
    Molecular Imaging Instrumentation Laboratory, Stanford University, Stanford, United States of America.
  • Ripeng Wang
    School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, China.
  • Yankui Chang
    Department of Engineering and Applied Physics, School of Physics, University of Science and Technology of China, Hefei, Anhui, China.
  • Zhi Chen
    Duke University.
  • Yingming Zhao
    The First Affiliated Hospital, University of Science and Technology of China, Hefei, China.
  • Wei Wei
    Dept. Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA, USA.
  • Xie George Xu
    School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, People's Republic of China.

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