21-22 November 2019
Paul Scherrer Institute
Europe/Zurich timezone
A WARM WELCOME in VILLIGEN

The importance of the Monte Carlo physics settings for simulations in proton therapy

22 Nov 2019, 13:45
15m

Speaker

Carla WINTERHALTER (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK)

Description

Introduction: The Christie NHS Foundation Trust began treating patients using proton therapy in Dec. 2018. As part of the current patient specific quality assurance, each proton field is delivered to a SolidWater (SW) phantom (1 hour for preparation/analysis per patient plus 2 hours of beam time per plan). Monte Carlo (MC) based independent dose calculations have been proposed to reduce these measurements, however, when implementing a multi-purpose Monte-Carlo code such as Geant4, the underlying physics settings have to be chosen from a wide range of possible options. We aim to characterize their influence on clinical dose calculations when taking the whole MC beam-modelling process into account.
Material and Methods: A GATE 8.1 (Geant4 10.3.3) based MC system was set-up for clinical dose calculations as follows: 1) Choose underlying Geant 4 settings, 2) define initial beam optics, 3) adjust energy and energy spread to reproduce proton integral depth dose curves, 4) model beam modifying devices (pre-absorber, 2/3/5 cm Lexan plates to treat superficial tumours). This process was repeated using two pre-built MC physics lists, which differ in the modelling of electro-magnetic interactions, namely QGSP_BIC (EM Opt 0) and QGSP_BIC_EMZ (EM Opt 4). Example simulation results showing spot sizes in air with and without a pre-absorber positioned 46 cm upstream of iso-center are presented in comparison to commissioning measurements. Finally, for one clinical plan (paediatric patient, sarcoma of the neck, 5cm pre-absorber) the influence of different physics settings is shown in the patient CT, and dose distributions simulated in a SW phantom are compared to patient specific quality assurance measurements (two sets of repeated measurements, analysed with 2%/2mm gamma analysis).
Results: Without pre-absorber, beam sizes (sigma) in air are marginally affected by the choice of physics settings (agreement between QGSP_BIC/QGSP_BIC_EMZ simulated spot sizes within 0.1mm, red lines in Figure 1a). Differences in simulated scattering are however relevant when a pre-absorber is inserted into the beam (green/blue/black lines in figure 1a, differences of up to 1 mm for a 5 cm Lexan pre-absorber), with QGSP_BIC_EMZ showing closer agreement to measurements than QGSP_BIC (0.24mm vs 0.72mm difference). The influence of this scattering difference is demonstrated for a clinical case in figure 1b and 1c. Agreement to patient specific quality assurance measurements is higher for QGSP_BIC_EMZ when compared to QGSP_BIC (100% vs. 98.2%at 1.3 cm depth, 99.5% vs. 99.0% at 4.3 cm depth (treatment room 1) and 94.8% vs 92.7% at 1.3 cm depth, 97.9% vs 97.7% at 4.3 cm depth (repeat measurements in treatment room 2). Calculation times are higher (factor of 1.6/1.4 in the CT/SW) for QGSP_BIC_EMZ.
Conclusion: First results indicate that in Geant4 10.3.3, QGSP_BIC_EMZ reproduces measurements more accurately when compared to QGSP_BIC for treatments with pre-absorber, which comes at the cost of increased calculation time. As such, MC simulations are a promising tool to reduce the amount of physical measurements for proton therapy, but it is crucial to carefully choose the underlying settings, as for example differences in electro-magnetic models included in pre-built Geant4 physics lists affect the scattering of clinical proton beams and lead to differences in simulated doses. This work forms the first part of a multi-institutional study which aims to establish recommendations for MC settings for proton therapy.

Acknowledgements: This work was funded by the Engineering and Physical Sciences Council [grant number EP/R023220/1] and the Science and Technology Facilities Council [grant number ST/N002423/1]. Supported by the NIHR Manchester Biomedical Research Council.

Primary author

Carla WINTERHALTER (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK)

Co-authors

Michael TAYLOR (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK) Peter SITCH (2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK) Ranald MACKAY (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK) Karen KIRKBY (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK) Adam AITKENHEAD (1 Division of Cancer Sciences, University of Manchester, M13 9PL, Manchester, UK; 2 The Christie NHS Foundation Trust, M20 4BX, Manchester, UK)

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