NCS Report 16: Monte Carlo treatment planning: An introduction

Reynaert, N.; Marck, Steven van der; Schaart, Dennis R.; Zee, W. van der; Tomsej, M.; Vroegindeweij, C.; Coghe, M.; Wagter, C. De; Heijmen, B.

doi:10.25030/ncs-016

Cited by 18 publications

(13 citation statements)

References 0 publications

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“…The spectrum was measured at a distance of 100 cm, where phase space was placed. Energy spectra are dependent on the accelerator tube and scattering foil [10]. As illustrated, the energy spectrum had on the ended at 6 MeV (6 MV photon mode) due to its initial kinetic energy.…”

Section: Monte Carlo Modelling and Validationmentioning

confidence: 99%

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Calculation of dose distribution on Rhizophora spp soy protein phantom at 6 MV photon beam energy using Monte Carlo method

Rabaiee

Aziz

Hashim

et al. 2018

J. Fundam and Appl Sci.

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Section: Monte Carlo Modelling and Validationmentioning

confidence: 99%

“…Monte Carlo is widely used for treatment planning in photon and electron beams [8]. This technique is proved to provide accuracy between 2-3 % in various phantom setup [9][10][11]. It uses a random numbers and probability statistics to model a complex physical system calculation.…”

Section: Introductionmentioning

confidence: 99%

Calculation of dose distribution on Rhizophora spp soy protein phantom at 6 MV photon beam energy using Monte Carlo method

Rabaiee

Aziz

Hashim

et al. 2018

J. Fundam and Appl Sci.

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“…Monte Carlo (MC) simulation for radiation transport and usage in medical physics and dosimetry have increased rapidly and been proven to be a safe and fast approach to innovation and development in radiation therapy (Ahnesjö and Aspradakis, 1999;Reynaert et al, 2006;Sardari et al, 2010;Seco & Verhaegen, 2013). Therefore, (MC) codes have been successfully employed by many research groups in radiation therapy.…”

Section: Introductionmentioning

confidence: 99%

Representation and illustration of the initial parameters in GATE 8.1 monte carlo simulation of an Elekta Versa-HD linear accelerator

Abolaban

Taha

2020

Journal of Radiation Research and Applied Sciences

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The purpose of this study is to validate GATE 8.1 Radiotherapy Monte Carlo (MC) simulation of a 6 MV Elekta Versa-HD linear accelerator at King Abdulaziz University Hospital (KAUH). The simulation data using GATE 8.1 was benchmarked against measured data at KAUH. The simulation comprises treatment head, Multi-Leaf Collimators (MLCs), and homogeneous water phantom, whereas the measured data was performed using MP3 phantom and PTW 31,010, 0.125 cm 3 Semiflex Chamber. Dose depth distribution and dose profiles were carried out at three different field sizes 10x10, 20x20, and 30 × 30 cm 2. The calculated TPR 20,10 for the simulated data was found to be 0.658, 1.1% less than the measured TPR 20,10 which was found to be 0.666. The obtained results indicate good agreement between the simulated and measured data, where Gamma Index 3%/3 mm criteria reached values of 97% and 90% for relative dose and dose profiles, respectively.

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“…Stochastic simulations based on the Monte Carlo method are an established tool in radiation treatment planning. 17 Stochastic ray tracing is commonly used in applications such as light transport 18 and room acoustics. 19,20 The method was previously applied to analyze focal distortion caused by the tissue heterogeneity in a breast phantom; 21 a peculiarity of the breast set-up was that the transducer can partially surround the phantom.…”

Section: Introductionmentioning

confidence: 99%

Stochastic ray tracing for simulation of high intensity focal ultrasound therapy

Koskela

Vahala

Greef

et al. 2014

The Journal of the Acoustical Society of America

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An algorithm is presented for rapid simulation of high-intensity focused ultrasound (HIFU) fields. Essentially, the method combines ray tracing with Monte Carlo integration to evaluate the Rayleigh-Sommerfeld integral. A large number of computational particles, phonons, are distributed among the elements of a phase-array transducer. The phonons are emitted into random directions and are propagated along trajectories computed with the ray tracing method. As the simulation progresses, an improving stochastic estimate of the acoustic field is obtained. The method can adapt to complicated geometries, and it is well suited to parallelization. The method is verified against reference simulations and pressure measurements from an ex vivo porcine thoracic tissue sample. Results are presented for acceleration with graphics processing units (GPUs). The method is expected to serve in applications, where flexibility and rapid computation time are crucial, in particular clinical HIFU treatment planning.

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NCS Report 16: Monte Carlo treatment planning: An introduction

Cited by 18 publications

References 0 publications

Calculation of dose distribution on Rhizophora spp soy protein phantom at 6 MV photon beam energy using Monte Carlo method

Calculation of dose distribution on Rhizophora spp soy protein phantom at 6 MV photon beam energy using Monte Carlo method

Representation and illustration of the initial parameters in GATE 8.1 monte carlo simulation of an Elekta Versa-HD linear accelerator

Stochastic ray tracing for simulation of high intensity focal ultrasound therapy

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