Journal of Nuclear Science, Engineering and Technology (JONSAT)
In cooperation with the Iranian Nuclear Society

Elemental analysis of tumor in eye phantom using prompt gamma-rays counting in proton therapy

Document Type : Research Paper

Authors

F. Saheli 1
N. Vosoughi 1
Z. Riazi 2
F.S. Rasouli 3

1 Department of Energy Engineering, Sharif University of Technology , P.O.BOX: 1458889694, Tehran – Iran

2 Physics and Accelerators Research School, Nuclear Science and Technology Research Institute, AEOI, P.O.Box:14155-1339, Tehran-Iran

3 Department of Physics, K.N. Toosi University of Technology, P.O.Box: 1969764499, Tehran - Iran

https://doi.org/10.24200/nst.2022.1189.1777
Abstract

The proton induced prompt gamma spectrum is applied for elemental analysis of irradiation tissues. The main purpose of the analysis in proton therapy is to track oxygen concentration in abnormal tissues. Online monitoring of oxygen concentration over a full course of treatment could provide a direct method for evaluating the response of these tissues to proton therapy and this information on the response of the tumor and healthy tissues to irradiation could then be used by the oncologist to adjust the patient’s treatment plan to ensure proper dose delivery to the tumor. In this study, the prompt gamma spectrum of a human eye phantom is simulated in an HPGe detector using the Geant4 toolkit, and the elemental analysis is accomplished using an artificial neural network (ANN). In the analysis, 33 eye phantoms are considered with different tumors, including different densities and elemental compositions. 21 samples were used as train data in ANN and 6 samples for testing and 6 samples for validation. The results show that there is a good correlation between outputs and targets. They show that the error percent of oxygen, carbon, and nitrogen in test samples are less than 5.8, 12.7, and 25%, respectively. Finally, the potential of quantitative elemental analysis of inhomogeneous targets is confirmed for providing a method to track change in the oxygen level of tumors.

Highlights

1. J.M. Verburg, J. Seco, Proton range verification through prompt gamma-ray spectroscopy, Phys. Med Biol, 59(23), 7089 (2014).
 
2. J. Krimmer, et al., Prompt-gamma monitoring in hadrontherapy: A review, NIMA, 878, 58-73 (2018).
 
3. J. Polf, et al., Measurement of characteristic prompt gamma rays emitted from oxygen and carbon in tissue-equivalent samples during proton beam irradiation, Phys. Med Biol, 58(17), 5821 (2013).
 
4. F. Saheli, et al, Single peak analysis of proton induced prompt gamma counts, NIMB, 475, 63-70 (2020).
 
5. J. Polf, et al., Prompt gamma-ray emission from biological tissues during proton irradiation: preliminary study, Phys. Med Biol, 54(3), 731 (2009).
 
6. J. Polf, et al., Measurement and calculation of characteristic prompt gamma ray spectra emitted during proton irradiation, Phys. Med Biol, 54(22), N519 (2009).

 

7. F. Saheli, et al, Evaluation the Nonlinear Response Function of a HPGe Detector for 59 keV to 10.7 MeV gamma-rays Using Monte Carlo Simulation and Experimental Study, JINST, 16, P07003 (2021).
 
8. M. Lesperance, M. Inglis‐Whalen, R.P. Thomson, Model‐based dose calculations for COMS eye plaque brachytherapy using an anatomically realistic eye phantom, Med Phys, 41(2), 021717 (2014).
 
9. F.S. Rasouli, et al., Effect of elemental compositions on Monte Carlo dose calculations in proton therapy of eye tumors, Rad Phys Chem, 117, 112-119 (2015).
 
10. J.M. Verburg, H.A. Shih, J. Seco, Simulation of prompt gamma-ray emission during proton radiotherapy, Phys. Med Biol, 57(17), 5459 (2012).
 
11. J.P. Jeyasugiththan, W. Stephen, Evaluation of proton inelastic reaction models in Geant4 for prompt gamma production during proton radiotherapy, Phys. Med Biol., 60,7617 (2015).

Keywords

Elemental analysis
Prompt gamma
Proton therapy
Eye phantom
Neural network
1. J.M. Verburg, J. Seco, Proton range verification through prompt gamma-ray spectroscopy, Phys. Med Biol, 59(23), 7089 (2014).
 
2. J. Krimmer, et al., Prompt-gamma monitoring in hadrontherapy: A review, NIMA, 878, 58-73 (2018).
 
3. J. Polf, et al., Measurement of characteristic prompt gamma rays emitted from oxygen and carbon in tissue-equivalent samples during proton beam irradiation, Phys. Med Biol, 58(17), 5821 (2013).
 
4. F. Saheli, et al, Single peak analysis of proton induced prompt gamma counts, NIMB, 475, 63-70 (2020).
 
5. J. Polf, et al., Prompt gamma-ray emission from biological tissues during proton irradiation: preliminary study, Phys. Med Biol, 54(3), 731 (2009).
 
6. J. Polf, et al., Measurement and calculation of characteristic prompt gamma ray spectra emitted during proton irradiation, Phys. Med Biol, 54(22), N519 (2009).
 
7. F. Saheli, et al, Evaluation the Nonlinear Response Function of a HPGe Detector for 59 keV to 10.7 MeV gamma-rays Using Monte Carlo Simulation and Experimental Study, JINST, 16, P07003 (2021).
 
8. M. Lesperance, M. Inglis‐Whalen, R.P. Thomson, Model‐based dose calculations for COMS eye plaque brachytherapy using an anatomically realistic eye phantom, Med Phys, 41(2), 021717 (2014).
 
9. F.S. Rasouli, et al., Effect of elemental compositions on Monte Carlo dose calculations in proton therapy of eye tumors, Rad Phys Chem, 117, 112-119 (2015).
 
10. J.M. Verburg, H.A. Shih, J. Seco, Simulation of prompt gamma-ray emission during proton radiotherapy, Phys. Med Biol, 57(17), 5459 (2012).
 
11. J.P. Jeyasugiththan, W. Stephen, Evaluation of proton inelastic reaction models in Geant4 for prompt gamma production during proton radiotherapy, Phys. Med Biol., 60,7617 (2015).

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