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The Application of PenH Simulation on Proton Imaging

6 pagesPublished: May 14, 2020

Abstract

Proton therapy is one of the most accurate forms of cancer therapies, which requires accurate knowledge of the dose delivered to the patient and verification of the correct patient position with respect to the proton beam to avoid damage to critical normal tissues and geographical tumor misses. In existing proton treatment centers, dose calculation is performed based on X-ray computed tomography (CT), and the patient is positioned with x-ray radiographs. The use of X-ray CT images for proton treatment planning ignores fundamental differences in physical interaction processes between photons and protons and is therefore inherently inaccurate. Further, X-ray radiographs depict only skeletal structures; they do not show the tumor itself. Ideally, the image of the patient taken directly with proton CT by measuring the energy loss of high-energy protons that traverse the patient. The main content of this report is the application of simulation program PENH proton transmission via phantom associated with the PENEASY creation in proton imaging that can be applied in proton therapy.

Keyphrases: penh simulation, proton imaging, proton therapy

In: Tich Thien Truong, Trung Nghia Tran, Quoc Khai Le and Thanh Nha Nguyen (editors). Proceedings of International Symposium on Applied Science 2019, vol 3, pages 36-41.

BibTeX entry
@inproceedings{ISAS2019:Application_PenH_Simulation_Proton,
  author    = {Anh Duy Nguyen and Thi Kim Lan Tran and Anh Tu Ly},
  title     = {The Application of PenH Simulation on Proton Imaging},
  booktitle = {Proceedings of International Symposium on Applied Science 2019},
  editor    = {Tich Thien Truong and Trung Nghia Tran and Quoc Khai Le and Thanh Nha Nguyen},
  series    = {Kalpa Publications in Engineering},
  volume    = {3},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2515-1770},
  url       = {/publications/paper/zj5h},
  doi       = {10.29007/sbgz},
  pages     = {36-41},
  year      = {2020}}
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