Development and validation of a 1.5 T MR-Linac full accelerator head and cryostat model for Monte Carlo dose simulations.
MR-linac
Monte Carlo simulations
magnetic resonance guided radiotherapy
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Nov 2019
Nov 2019
Historique:
received:
29
05
2019
revised:
26
07
2019
accepted:
21
08
2019
pubmed:
19
9
2019
medline:
19
3
2020
entrez:
19
9
2019
Statut:
ppublish
Résumé
To develop, implement, and validate a full 1.5 T/7 MV magnetic resonance (MR)-Linac accelerator head and cryostat model in EGSnrc for high precision dose calculations accounting for magnetic field effects that are independent from the vendor treatment planning system. Primary electron beam parameters for the implemented model were adapted to be in accordance with measured dose profiles of the Elekta Unity (Elekta AB, Stockholm, Sweden). Parameters to be investigated were the mean electron energy as well as the Gaussian radial intensity and energy distributions. Energy tuning was done comparing depth dose profiles simulated with monoenergetic beams of varying energies to measurements. The optimum radial intensity distribution was found by varying the radial full width at half maximum (FWHM) and comparing simulated and measured lateral profiles. The influence of the energy distribution was investigated by comparing simulated lateral and depth dose profiles with varying energy spreads to measured data. Comparison of simulations and measurements was performed by calculating average and maximum local dose deviations. The model was validated recalculating a clinical intensity-modulated radiation therapy plan for the MR-Linac and comparing the resulting dose distribution with simulations from the commercial treatment planning system Monaco using the gamma criterion. Comparison of simulated and measured data showed that the optimum initial electron beam for MR-Linac simulations was monoenergetic with an electron energy of (7.4 ± 0.2) MeV. The optimum Gaussian radial intensity distribution has a FWHM of (2.2 ± 0.3) mm. The average relative deviations were smaller than 1% for all simulated profiles with optimum electron parameters, whereas the largest maximum deviation of 2.07% was found for the 22 × 22 cm The EGSnrc MR-Linac model developed in this study showed good accordance with measurements and was successfully used to recalculate a first full clinical IMRT treatment plan. Thus, it shows the general possibility for future secondary dose calculations of full IMRT plans with EGSnrc, which needs further detailed investigations before clinical use.
Types de publication
Journal Article
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
5304-5313Subventions
Organisme : German Research Foundation
ID : INST 39/963-1
Informations de copyright
© 2019 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.
Références
Nguyen NP, Davis R, Bose SR, et al. Potential applications of image-guided radiotherapy for radiation dose escalation in patients with early stage high-risk prostate cancer. Front Oncol. 2015;5:18.
Lagendijk JJ, Raaymakers BW, Raaijmakers AJ, et al. MRI/linac integration. Radiother Oncol. 2008;86:25-29.
Raaijmakers AJE, Hårdemark B, Raaymakers BW, Raaijmakers CPJ, Lagendijk JJW. Dose optimization for the MRI-accelerator: IMRT in the presence of a magnetic field. Phys Med Biol. 2007;52:7045-7054.
Pathmanathan AU, van As NJ, Kerkmeijer LG, et al. Magnetic resonance imaging-guided adaptive radiation therapy: a “Game Changer" for prostate treatment? Int J Radiat Oncol Biol Phys. 2018;100:361-373.
Ménard C, van der Heide U. Introduction: systems for magnetic resonance image guided radiation therapy. Semin Radiat Oncol. 2014;24:192.
Lagendijk JJ, Raaymakers BW, van Vulpen M. The magnetic resonance imaging-linac system. Semin Radiat Oncol. 2014;24:207-209.
Pojtinger S, Dohm OS, Kapsch R-P, Thorwarth D. Ionization chamber correction factors for MR-linacs. Phys Med Biol. 2018;63:11NT03.
Lagendijk JJW, Raaymakers BW, den Berg CATV, Moerland MA, Philippens ME, van Vulpen M. MR guidance in radiotherapy. Phys Med Biol. 2014;59:R349-R369.
Winkel D, Bol GH, Kroon PS, et al. Adaptive radiotherapy: the Elekta unity MR-linac concept. Clin Transl Radiat Oncol. 2019;18:54-59.
Raaijmakers AJE, Raaymakers BW, Lagendijk JJW. Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose increase at tissue-air interfaces in a lateral magnetic field due to returning electrons. Phys Med Biol. 2005;50:1363-1376.
Raaymakers BW, Raaijmakers AJE, Kotte ANTJ, Jette D, Lagendijk JJW. Integrating a MRI scanner with a 6 MV radiotherapy accelerator: dose deposition in a transverse magnetic field. Phys Med Biol. 2004;49:4109-4118.
Raaijmakers AJE, Raaymakers BW, Lagendijk JJW. Magnetic-field-induced dose effects in MR-guided radiotherapy systems: dependence on the magnetic field strength. Phys Med Biol. 2008;53:909-923.
Richter S, Mönnich D, Pojtinger S, Dohm O, Zips D, Thorwarth D, PO-0887: Influence of a magnetic field on the dose deposited by a 6 MV linac at tissue interfaces. Radiother Oncol. 2018;127:S469-S470. ESTRO 37, April 20-24, 2018, Barcelona, Spain.
Ahmad SB, Sarfehnia A, Paudel MR, et al. Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT4. Med Phys. 2016;43:894-907.
Zelyak O, Fallone B, St Aubin J. Stability analysis of a novel dose calculation algorithm for MRI guided radiotherapy. Med Phys. 2016;43:3855.
Bol GH, Hissoiny S, Lagendijk JJW, Raaymakers BW. Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator. Phys Med Biol. 2012;57:1375-1385.
Hissoiny S, Raaijmakers AJE, Ozell B, Despres P, Raaymakers BW. Fast dose calculation in magnetic fields with GPUMCD. Phys Med Biol. 2011;56:5119-5129.
Raaymakers BW, Bol GH, Glitzner M, et al. First patients treated with a 1.5 T MRI-Linac: clinical proof of concept of a high-precision, high-field MRI guided radiotherapy treatment. Phys Med Biol. 2017;62:L41-L50.
Kawrakow I, Mainegra-Hing E, Rogers DWO, Tessier F, Walters BRB. The EGSnrc Code System: Monte Carlo simulation of electron and photon transport. Technical Report PIRS-701, National Research Council Canada; 2018.
Kawrakow I, Mainegra-Hing E, Rogers DWO, Tessier F, Walters BRB. BEAMnrc Users Manual. Technical Report PIRS-0509(A)revL, National Research Council Canada; 2018.
Kawrakow I, Walters BRB. Efficient photon beam dose calculations using DOSXYZnrc with BEAMnrc. Med Phys. 2006;33:3046-3056.
Kawrakow I, Rogers DWO, Walters BRB. Large efficiency improvements in BEAMnrc using directional bremsstrahlung splitting. Med Phys. 2004;31:2883-2898.
Tzedakis A, Damilakis JE, Mazonakis M, Stratakis J, Varveris H, Gourtsoyiannis N. Influence of initial electron beam parameters on Monte Carlo calculated absorbed dose distributions for radiotherapy photon beams. Med Phys. 2004;31:907-913.
Ding GX. Energy spectra, angular spread, fluence profiles and dose distributions of 6 and 18 MV photon beams: results of Monte carlo simulations for a Varian 2100EX accelerator. Phys Med Biol. 2002;47:1025-1046.
Sheikh-Bagheri D, Rogers D, Ross CK, Seuntjens JP. Comparison of measured and Monte Carlo calculated dose distributions from the NRC linac. Med Phys. 2000;27:2256-2266.
Walters B, Kawrakow I, Rogers DWO. DOSXYZnrc Users Manual. Technical Report PIRS-794revB. National Research Council Canada. 2018. 2018
Sheikh-Bagheri D, Rogers DWO. Sensitivity of megavoltage photon beam Monte Carlo simulations to electron beam and other parameters. Med Phys. 2002;29:379-390.
Chetty IJ, Curran B, Cygler JE, et al. Report of the AAPM Task Group No. 105: issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Med Phys. 2007;34:4818-4853.
Low DA, Harms WB, Mutic S, Purdy JA. A technique for the quantitative evaluation of dose distributions. Med Phys. 1998;25:656-661.
O’Brien DJ, Roberts DA, Ibbott GS, Sawakuchi GO. Reference dosimetry in magnetic fields: formalism and ionization chamber correction factors. Med Phys. 2016;43:4915-4927.
Makrani DS, Hasanzadeh H, Pourfallah TA, Ghasemi A, Jadidi M, Babapour H. Determination of primary electron beam parameters in a Siemens Primus Linac using Monte Carlo simulation. J Paramed Sci. 2015;6:850-858.