GEANT4 simulation of cyclotron radioisotope production in a solid target

F. Poignant, S. Penfold, J. Asp, P. Takhar, P. Jackson

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

The use of radioisotopes in nuclear medicine is essential for diagnosing and treating cancer. The optimization of their production is a key factor in maximizing the production yield and minimizing the associated costs. An efficient approach to this problem is the use of Monte Carlo simulations prior to experimentation. By predicting isotopes yields, one can study the isotope of interest expected activity for different energy ranges. One can also study the target contamination with other radioisotopes, especially undesired radioisotopes of the wanted chemical element which are difficult to separate from the irradiated target and might result in increasing the dose when delivering the radiopharmaceutical product to the patient.The aim of this work is to build and validate a Monte Carlo simulation platform using the GEANT4 toolkit to model the solid target system of the South Australian Health and Medical Research Institute (SAHMRI) GE Healthcare PETtrace cyclotron. It includes a GEANT4 Graphical User Interface (GUI) where the user can modify simulation parameters such as the energy, shape and current of the proton beam, the target geometry and material, the foil geometry and material and the time of irradiation.The paper describes the simulation and presents a comparison of simulated and experimental/theoretical yields for various nuclear reactions on an enriched nickel 64 target using the GEANT4 physics model QGSP_BIC_AllHP, a model recently developed to evaluate with high precision the interaction of protons with energies below 200 MeV available in Geant4 version 10.1. The simulation yield of the 64Ni(p,n)64Cu reaction was found to be 7.67 ± 0.074 mCi·μA-1 for a target energy range of 9-12 MeV. Szelecsenyi et al. (1993) gives a theoretical yield of 6.71 mCi·μA-1 and an experimental yield of 6.38 mCi·μA-1. The 64Ni(p,n)64Cu cross section obtained with the simulation was also verified against the yield predicted from the nuclear database TENDL and compared to experimental yield obtained from literature.

LanguageEnglish
Pages728-734
Number of pages7
JournalPhysica Medica
Volume32
Issue number5
DOIs
Publication statusPublished - 1 May 2016

Keywords

  • Copper-64 production
  • GEANT4 simulation
  • Low energy cyclotron
  • Yield evaluation

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging
  • Physics and Astronomy(all)

Cite this

Poignant, F. ; Penfold, S. ; Asp, J. ; Takhar, P. ; Jackson, P. / GEANT4 simulation of cyclotron radioisotope production in a solid target. In: Physica Medica. 2016 ; Vol. 32, No. 5. pp. 728-734.
@article{c74e77d9cd54444d90af496762ebe179,
title = "GEANT4 simulation of cyclotron radioisotope production in a solid target",
abstract = "The use of radioisotopes in nuclear medicine is essential for diagnosing and treating cancer. The optimization of their production is a key factor in maximizing the production yield and minimizing the associated costs. An efficient approach to this problem is the use of Monte Carlo simulations prior to experimentation. By predicting isotopes yields, one can study the isotope of interest expected activity for different energy ranges. One can also study the target contamination with other radioisotopes, especially undesired radioisotopes of the wanted chemical element which are difficult to separate from the irradiated target and might result in increasing the dose when delivering the radiopharmaceutical product to the patient.The aim of this work is to build and validate a Monte Carlo simulation platform using the GEANT4 toolkit to model the solid target system of the South Australian Health and Medical Research Institute (SAHMRI) GE Healthcare PETtrace cyclotron. It includes a GEANT4 Graphical User Interface (GUI) where the user can modify simulation parameters such as the energy, shape and current of the proton beam, the target geometry and material, the foil geometry and material and the time of irradiation.The paper describes the simulation and presents a comparison of simulated and experimental/theoretical yields for various nuclear reactions on an enriched nickel 64 target using the GEANT4 physics model QGSP_BIC_AllHP, a model recently developed to evaluate with high precision the interaction of protons with energies below 200 MeV available in Geant4 version 10.1. The simulation yield of the 64Ni(p,n)64Cu reaction was found to be 7.67 ± 0.074 mCi·μA-1 for a target energy range of 9-12 MeV. Szelecsenyi et al. (1993) gives a theoretical yield of 6.71 mCi·μA-1 and an experimental yield of 6.38 mCi·μA-1. The 64Ni(p,n)64Cu cross section obtained with the simulation was also verified against the yield predicted from the nuclear database TENDL and compared to experimental yield obtained from literature.",
keywords = "Copper-64 production, GEANT4 simulation, Low energy cyclotron, Yield evaluation",
author = "F. Poignant and S. Penfold and J. Asp and P. Takhar and P. Jackson",
year = "2016",
month = "5",
day = "1",
doi = "10.1016/j.ejmp.2016.04.006",
language = "English",
volume = "32",
pages = "728--734",
journal = "Physica Medica",
issn = "1120-1797",
publisher = "Associazione Italiana di Fisica Medica",
number = "5",

}

GEANT4 simulation of cyclotron radioisotope production in a solid target. / Poignant, F.; Penfold, S.; Asp, J.; Takhar, P.; Jackson, P.

In: Physica Medica, Vol. 32, No. 5, 01.05.2016, p. 728-734.

Research output: Contribution to journalArticle

TY - JOUR

T1 - GEANT4 simulation of cyclotron radioisotope production in a solid target

AU - Poignant, F.

AU - Penfold, S.

AU - Asp, J.

AU - Takhar, P.

AU - Jackson, P.

PY - 2016/5/1

Y1 - 2016/5/1

N2 - The use of radioisotopes in nuclear medicine is essential for diagnosing and treating cancer. The optimization of their production is a key factor in maximizing the production yield and minimizing the associated costs. An efficient approach to this problem is the use of Monte Carlo simulations prior to experimentation. By predicting isotopes yields, one can study the isotope of interest expected activity for different energy ranges. One can also study the target contamination with other radioisotopes, especially undesired radioisotopes of the wanted chemical element which are difficult to separate from the irradiated target and might result in increasing the dose when delivering the radiopharmaceutical product to the patient.The aim of this work is to build and validate a Monte Carlo simulation platform using the GEANT4 toolkit to model the solid target system of the South Australian Health and Medical Research Institute (SAHMRI) GE Healthcare PETtrace cyclotron. It includes a GEANT4 Graphical User Interface (GUI) where the user can modify simulation parameters such as the energy, shape and current of the proton beam, the target geometry and material, the foil geometry and material and the time of irradiation.The paper describes the simulation and presents a comparison of simulated and experimental/theoretical yields for various nuclear reactions on an enriched nickel 64 target using the GEANT4 physics model QGSP_BIC_AllHP, a model recently developed to evaluate with high precision the interaction of protons with energies below 200 MeV available in Geant4 version 10.1. The simulation yield of the 64Ni(p,n)64Cu reaction was found to be 7.67 ± 0.074 mCi·μA-1 for a target energy range of 9-12 MeV. Szelecsenyi et al. (1993) gives a theoretical yield of 6.71 mCi·μA-1 and an experimental yield of 6.38 mCi·μA-1. The 64Ni(p,n)64Cu cross section obtained with the simulation was also verified against the yield predicted from the nuclear database TENDL and compared to experimental yield obtained from literature.

AB - The use of radioisotopes in nuclear medicine is essential for diagnosing and treating cancer. The optimization of their production is a key factor in maximizing the production yield and minimizing the associated costs. An efficient approach to this problem is the use of Monte Carlo simulations prior to experimentation. By predicting isotopes yields, one can study the isotope of interest expected activity for different energy ranges. One can also study the target contamination with other radioisotopes, especially undesired radioisotopes of the wanted chemical element which are difficult to separate from the irradiated target and might result in increasing the dose when delivering the radiopharmaceutical product to the patient.The aim of this work is to build and validate a Monte Carlo simulation platform using the GEANT4 toolkit to model the solid target system of the South Australian Health and Medical Research Institute (SAHMRI) GE Healthcare PETtrace cyclotron. It includes a GEANT4 Graphical User Interface (GUI) where the user can modify simulation parameters such as the energy, shape and current of the proton beam, the target geometry and material, the foil geometry and material and the time of irradiation.The paper describes the simulation and presents a comparison of simulated and experimental/theoretical yields for various nuclear reactions on an enriched nickel 64 target using the GEANT4 physics model QGSP_BIC_AllHP, a model recently developed to evaluate with high precision the interaction of protons with energies below 200 MeV available in Geant4 version 10.1. The simulation yield of the 64Ni(p,n)64Cu reaction was found to be 7.67 ± 0.074 mCi·μA-1 for a target energy range of 9-12 MeV. Szelecsenyi et al. (1993) gives a theoretical yield of 6.71 mCi·μA-1 and an experimental yield of 6.38 mCi·μA-1. The 64Ni(p,n)64Cu cross section obtained with the simulation was also verified against the yield predicted from the nuclear database TENDL and compared to experimental yield obtained from literature.

KW - Copper-64 production

KW - GEANT4 simulation

KW - Low energy cyclotron

KW - Yield evaluation

UR - http://www.scopus.com/inward/record.url?scp=84964915235&partnerID=8YFLogxK

U2 - 10.1016/j.ejmp.2016.04.006

DO - 10.1016/j.ejmp.2016.04.006

M3 - Article

VL - 32

SP - 728

EP - 734

JO - Physica Medica

T2 - Physica Medica

JF - Physica Medica

SN - 1120-1797

IS - 5

ER -