Ng Wei Siang, Kelvin (2019) Validating Monte Carlo Calculations of Clinical Proton Beams in Animal Tissue Phantoms. Master's Thesis / Essay, Applied Physics.
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Abstract
Purpose: In proton therapy, the common practice to perform patient Quality Assurance (QA) is time-consuming in-beam measurements. The measurements are performed in a water equivalent phantom, but in practice, it is not easy to correlate the in-beam in-phantom measurements with the impact on in-patient dose distribution and the eventual clinical impact, even more so with a homogeneous phantom. Moreover, when considering an environment in which frequent plan adaptation must be performed, this time consuming approach is simply not feasible. As such, an independent Monte Carlo (MC) re-calculation based QA workflow is constructed in attempt to speed up independent QA verification. Here, we will support implementation of this workflow by evaluating dose calculation accuracy of the MC dose engine using heterogeneous animal-like tissues. Methods: The heterogeneous phantom is a pig’s head, and proton beam measurements were performed on the phantom using an array of ionization chambers. We delivered three mono-energetic beams with different energies, as well as a Spread Out Bragg Peak (SOPB) beam through our sample. The results obtained were compared with calculations performed by the independent dose engine MCsquare, and the MC algorithm of RayStation Treatment Planning System (TPS, RaySearch Laboratories AB). Conclusions: Our study demonstrates that the MCsquare algorithm is sufficiently accurate in predicting the dose delivered in highly heterogeneous medium. This observation supports clinical implementation, providing another, more time efficient, independent verification model for patient QA.
| Item Type: | Thesis (Master's Thesis / Essay) |
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| Supervisor name: | Meijers, A. and Meijers, A. and Graaf, E.R. van der |
| Degree programme: | Applied Physics |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 19 Mar 2019 |
| Last Modified: | 06 Sep 2023 09:02 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/19278 |
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