Literature DB >> 22398196

Monte Carlo calculations of positron emitter yields in proton radiotherapy.

E Seravalli1, C Robert, J Bauer, F Stichelbaut, C Kurz, J Smeets, C Van Ngoc Ty, D R Schaart, I Buvat, K Parodi, F Verhaegen.   

Abstract

Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring.
© 2012 Institute of Physics and Engineering in Medicine

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Year:  2012        PMID: 22398196     DOI: 10.1088/0031-9155/57/6/1659

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  8 in total

1.  Feasibility of proton-activated implantable markers for proton range verification using PET.

Authors:  Jongmin Cho; Geoffrey Ibbott; Michael Gillin; Carlos Gonzalez-Lepera; Uwe Titt; Harald Paganetti; Matthew Kerr; Osama Mawlawi
Journal:  Phys Med Biol       Date:  2013-10-08       Impact factor: 3.609

2.  Feasibility of Using Distal Endpoints for In-room PET Range Verification of Proton Therapy.

Authors:  Kira Grogg; Xuping Zhu; Chul Hee Min; Brian Winey; Thomas Bortfeld; Harald Paganetti; Helen A Shih; Georges El Fakhri
Journal:  IEEE Trans Nucl Sci       Date:  2013-10       Impact factor: 1.679

3.  Determination of elemental tissue composition following proton treatment using positron emission tomography.

Authors:  Jongmin Cho; Geoffrey Ibbott; Michael Gillin; Carlos Gonzalez-Lepera; Chul Hee Min; Xuping Zhu; Georges El Fakhri; Harald Paganetti; Osama Mawlawi
Journal:  Phys Med Biol       Date:  2013-05-16       Impact factor: 3.609

Review 4.  Proton therapy verification with PET imaging.

Authors:  Xuping Zhu; Georges El Fakhri
Journal:  Theranostics       Date:  2013-09-19       Impact factor: 11.556

5.  The FLUKA Code: An Accurate Simulation Tool for Particle Therapy.

Authors:  Giuseppe Battistoni; Julia Bauer; Till T Boehlen; Francesco Cerutti; Mary P W Chin; Ricardo Dos Santos Augusto; Alfredo Ferrari; Pablo G Ortega; Wioletta Kozłowska; Giuseppe Magro; Andrea Mairani; Katia Parodi; Paola R Sala; Philippe Schoofs; Thomas Tessonnier; Vasilis Vlachoudis
Journal:  Front Oncol       Date:  2016-05-11       Impact factor: 6.244

6.  Proton Therapy for Mandibula Plate Phantom.

Authors:  Güler Burcu Senirkentli; Fatih Ekinci; Erkan Bostanci; Mehmet Serdar Güzel; Özlem Dağli; Ahmed M Karim; Alok Mishra
Journal:  Healthcare (Basel)       Date:  2021-02-04

7.  Verification of a Monte Carlo dose calculation engine in proton minibeam radiotherapy in a passive scattering beamline for preclinical trials.

Authors:  Consuelo Guardiola; Ludovic De Marzi; Yolanda Prezado
Journal:  Br J Radiol       Date:  2020-01-06       Impact factor: 3.039

Review 8.  Range Verification Methods in Particle Therapy: Underlying Physics and Monte Carlo Modeling.

Authors:  Aafke Christine Kraan
Journal:  Front Oncol       Date:  2015-07-07       Impact factor: 6.244

  8 in total

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