Extending Geant4 Based Particle Therapy System Simulation Framework to Medical Imaging Applications

被引:0
|
作者
Aso, T. [1 ]
Mastushita, K. [2 ]
Nishio, T. [2 ]
Kabuki, S. [3 ]
Sasaki, T. [4 ]
机构
[1] Toyama Coll, Natl Inst Technol, Dept Elect & Comp Engn, Toyama, Japan
[2] Hiroshima Univ, Inst Biomed & Hlth Sci, Hiroshima, Japan
[3] Tokai Univ, Sch Med, Dept Radiat Oncol, Hiratsuka, Kanagawa, Japan
[4] High Energy Accelerator Res Org KEK, Comp Res Ctr, Tsukuba, Ibaraki, Japan
关键词
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中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Particle therapy system simulation framework, PTSIM, is a simulation framework based on Geant4 Monte Carlo simulation. It has been originally developed for particle radiotherapy to simulate dose distribution inside patient. PTSIM has provided a common platform to model proton and ion therapy facilities, allowing users who are not Geant4 experts to accurately and efficiently run Geant4 simulations with the pre-build configurations. Efforts on further development of PTSIM are still under way to include more functionality and improve the performance. In proton therapy, innovations of treatment machines such as a layer-stacking irradiation system and a pencil beam scanning irradiation system have been made for delivering more ideal dose distributions. In order to perform a specially optimized treatment for each patient, e.g. a tailor made proton therapy, there is a strong request to monitor the dose distribution inside patient by measurements in addition to the calculations. Such dose monitoring is performed by reconstructing dose images by detecting prompt and annihilation gamma rays that are produced from radioisotopes in nuclear interactions by primary protons with patient tissues. The PTSIM has an important roll to simulate the secondary isotope productions, its decay, and the signals in imaging devices in addition to delivered dose distributions. The results are used for optimizing detector configurations and mapping the reconstructed dose images to the delivered dose distribution. In this paper, we reports on the implementations of extending functions in PTSIM to medical imaging applications.
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