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337 Voxel size effects on Monte Carlo dose calculation for clinical radiotherapy electron beams
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Posters discussed. Skin doses were simulated, for a 18F point source located in the center of the phantom and a 18F uniformly distributed source in the heart. The resulting doses are very close: Dpon = 0.87 mGy and Dhea~ = 0.86 mGy and they are in agreement with simulations by other authors (Herzog, Mejia and Stabin). They are about 1.6 times higher than the values measured in patients (0.533 mGy +0.266), but close to the measurement uncertainty bounds. The upper boundary of the uncertainty range quoted by Gonzalez is 0.8 mGy, which is quite close to our simulated value. Possible reasons for the difference between simulated and measured results are discussed. While the viability of using Monte Carlo simulations, based on geometrical model of a phantom, for estimating patient doses is established, it is clear that the model needs to be more realistic. 337 Voxel size effects on Monte Carlo dose calculation for clinical r a d i o t h e r a p y electron beams
F. Husson, C. Guillerminet DOSIsoft s,a., Radiation Physics, Cachan, France Introduction: The significant physical parameters for the Monte Carlo dose calculations are the mass density (p) and the material of the irradiated medium. In Radiotherapy, these data are extracted from the CT scan images and are used to build a voxel anatomical patient geometry. For the Monte Carlo code implementation into a TPS, the conversion of the CT scan images into a voxel geometry is a very important but critical procedure. In fact, because of the expensive time calculation, it is not realistic to use the primary resolution of the matrix CT data as the voxel resolution for the Monte Carlo simulation. Therefore, the images must be resampled with a larger voxel size and potential misassignments of media and mass density must be taken into account. The purpose of this work is to illustrate the consequences of this conversion procedure on the accuracy of the dose calculation function of the following parameters: topologic spatial resolution, spatial resolution in density and in material, time calculation and used memory space. Material and Method: A clinical 12 MeV electron beam is used for the irradiation in three different situations: homogeneous media, mediastin, nasal air cavity. The resampling of the images is applied function of a reduction factor on the voxel size from 1 mm 3 (reference) to 10 mm 3. The impact of the conversion on the accuracy of the dose distribution obtained with our ISOGRAY software (DOSIsoft) integrating the Monte Carlo code PENELOPE adapted for voxel geometry. Results and Conclusion: For the same statistical accuracy, a voxel size of 10 mm 3 allows to reduce by a factor of almost three the time calculation compared to the reference. Moreover, because of the average of the Hounsfield Units (HU) due to the resampling, the conversion of the CT scan data can misassign the mass density and the media, which can lead high inaccuracy (50 %) in local area. These introduced artefacts are noticeable in heterogeneous media and high dose gradient zones. In order to take into account the accuracy of the dose calculation and of the anatomical patient representation, it is important to establish some recommendations for the use of resampled CT images with electron beams in an implemented Monte Carlo code in a clinical TPS. 338 Commissioning of a photon beam model for Monte Carlo dose calculation in dynamic IMRT and comparison with a t r e a t m e n t planning system
M. Hartmann 1, M. FippeP, G. Kunz I iKlinik f(~r Radio-Onkologie, Universit~tsspital Z#rich, Z~rich (Switzerland)
2Medizinische Physik Universitaetsklinikum, Tuebingen, Germany I n t r o d u c t i o n : With the introduction of the Intensity Modulated Radiation Therapy (IMRT) as a standard treatment technique, the accuracy of dose calculation becomes particularly important. Conventional dose calculation algorithms like pencil beam or collapsed cone can lead to pronounced dose errors in areas without secondary electron equilibrium. Only Monte Carlo (MC) algorithms have the potential to reduce these dose calculation errors to an acceptable limit. However, this requires an accurate linac head model. Material and methods: A virtual energy fluence model (VEFM) [1], developed at the University of T~bingen, is used to determine the primary fluence for calculations of dose distributions in patients with the VoxeI-Monte-CarloAlgorithm (XVMC) [2]. The analytical VEFM includes two photon sources with Gaussian shape, simulating primary and head scatter photons, and one uniform electron source to account for electron contamination. In addition to the parameters for the weights of each source, their positions, widths and energy distributions, the model involves further parameters to consider off-axis fluence corrections and spectrum softening. These parameters are fitted to profiles and depth dose measurements in air and water. The commissioning of the VEFM is performed for a Varian 6EX accelerator equipped with a 120-leaf Millenium MLC (Varian Medical Systems), used routinely for dynamic IMRT. In this work the VEFM is verified by additional measurements in water. Moreover, the evaluation of the model for the application of dynamic field segments was accomplished. Finally, the measurements and the doses computed by XVMC/VEFM are compared with common dose engines of commercial treatment planning systems. Results and Conclusion: Using the VEFM it is possible to model the primary photon fluence for dynamic IMRT. Therefore, the code system is implemented in the inverse treatment planning system IKO [3], developed at the University of Regensburg, to calculate the dose distributions during the different optimisation steps. [1] Fippel M e t al 2003 A virtual photon energy fluence model for Monte Carlo dose calculation Med. Phys. 3 0 ( 3 ) 301-11 [2] Fippel M 1999 Fast Monte -Carlo dose calculation for photon beams based on the VMC electron Monte Carlo algorithm Med. Phys. 26 1466-75 [3] Hartmann M. et al 2001 IMRT optimisation based on a new inverse Monte-Carlo code. Radiother. Oncol. 61 (Suppl.1) 47 339 A novel inverse Monte Carlo m e t h o d
G. Jarrv. F. Verhaegen McGill University Health Center, Medical Physics, Montreal, Canada We present a novel inverse Monte Carlo (MC) method based on inverse Compton scattering and discuss some of its applications for EPID dosimetry. This Monte Carlo technique uses the information carried by the particles exiting a geometry to recover the dose they deposited in that geometry. Particles are started with known energy, angular and spatial distributions on a plane downstream from the geometry of interest. This information can be derived from a phase space file or from pre-calculated estimates for the energy, angular and spatial distributions of the particles. The particles are then transported backwards through a user-defined voxelized geometry. The particles interaction sites are sampled using an algorithm based on attenuation coefficients. At the interaction site, the new energy and angle of the particles are sampled using inverse Compton sampling. The latter is based on a cross-section look-up table derived from forward MC calculations and on
Posters discussed. Skin doses were simulated, for a 18F point source located in the center of the phantom and a 18F uniformly distributed source in the heart. The resulting doses are very close: Dpon = 0.87 mGy and Dhea~ = 0.86 mGy and they are in agreement with simulations by other authors (Herzog, Mejia and Stabin). They are about 1.6 times higher than the values measured in patients (0.533 mGy +0.266), but close to the measurement uncertainty bounds. The upper boundary of the uncertainty range quoted by Gonzalez is 0.8 mGy, which is quite close to our simulated value. Possible reasons for the difference between simulated and measured results are discussed. While the viability of using Monte Carlo simulations, based on geometrical model of a phantom, for estimating patient doses is established, it is clear that the model needs to be more realistic. 337 Voxel size effects on Monte Carlo dose calculation for clinical r a d i o t h e r a p y electron beams
F. Husson, C. Guillerminet DOSIsoft s,a., Radiation Physics, Cachan, France Introduction: The significant physical parameters for the Monte Carlo dose calculations are the mass density (p) and the material of the irradiated medium. In Radiotherapy, these data are extracted from the CT scan images and are used to build a voxel anatomical patient geometry. For the Monte Carlo code implementation into a TPS, the conversion of the CT scan images into a voxel geometry is a very important but critical procedure. In fact, because of the expensive time calculation, it is not realistic to use the primary resolution of the matrix CT data as the voxel resolution for the Monte Carlo simulation. Therefore, the images must be resampled with a larger voxel size and potential misassignments of media and mass density must be taken into account. The purpose of this work is to illustrate the consequences of this conversion procedure on the accuracy of the dose calculation function of the following parameters: topologic spatial resolution, spatial resolution in density and in material, time calculation and used memory space. Material and Method: A clinical 12 MeV electron beam is used for the irradiation in three different situations: homogeneous media, mediastin, nasal air cavity. The resampling of the images is applied function of a reduction factor on the voxel size from 1 mm 3 (reference) to 10 mm 3. The impact of the conversion on the accuracy of the dose distribution obtained with our ISOGRAY software (DOSIsoft) integrating the Monte Carlo code PENELOPE adapted for voxel geometry. Results and Conclusion: For the same statistical accuracy, a voxel size of 10 mm 3 allows to reduce by a factor of almost three the time calculation compared to the reference. Moreover, because of the average of the Hounsfield Units (HU) due to the resampling, the conversion of the CT scan data can misassign the mass density and the media, which can lead high inaccuracy (50 %) in local area. These introduced artefacts are noticeable in heterogeneous media and high dose gradient zones. In order to take into account the accuracy of the dose calculation and of the anatomical patient representation, it is important to establish some recommendations for the use of resampled CT images with electron beams in an implemented Monte Carlo code in a clinical TPS. 338 Commissioning of a photon beam model for Monte Carlo dose calculation in dynamic IMRT and comparison with a t r e a t m e n t planning system
M. Hartmann 1, M. FippeP, G. Kunz I iKlinik f(~r Radio-Onkologie, Universit~tsspital Z#rich, Z~rich (Switzerland)
2Medizinische Physik Universitaetsklinikum, Tuebingen, Germany I n t r o d u c t i o n : With the introduction of the Intensity Modulated Radiation Therapy (IMRT) as a standard treatment technique, the accuracy of dose calculation becomes particularly important. Conventional dose calculation algorithms like pencil beam or collapsed cone can lead to pronounced dose errors in areas without secondary electron equilibrium. Only Monte Carlo (MC) algorithms have the potential to reduce these dose calculation errors to an acceptable limit. However, this requires an accurate linac head model. Material and methods: A virtual energy fluence model (VEFM) [1], developed at the University of T~bingen, is used to determine the primary fluence for calculations of dose distributions in patients with the VoxeI-Monte-CarloAlgorithm (XVMC) [2]. The analytical VEFM includes two photon sources with Gaussian shape, simulating primary and head scatter photons, and one uniform electron source to account for electron contamination. In addition to the parameters for the weights of each source, their positions, widths and energy distributions, the model involves further parameters to consider off-axis fluence corrections and spectrum softening. These parameters are fitted to profiles and depth dose measurements in air and water. The commissioning of the VEFM is performed for a Varian 6EX accelerator equipped with a 120-leaf Millenium MLC (Varian Medical Systems), used routinely for dynamic IMRT. In this work the VEFM is verified by additional measurements in water. Moreover, the evaluation of the model for the application of dynamic field segments was accomplished. Finally, the measurements and the doses computed by XVMC/VEFM are compared with common dose engines of commercial treatment planning systems. Results and Conclusion: Using the VEFM it is possible to model the primary photon fluence for dynamic IMRT. Therefore, the code system is implemented in the inverse treatment planning system IKO [3], developed at the University of Regensburg, to calculate the dose distributions during the different optimisation steps. [1] Fippel M e t al 2003 A virtual photon energy fluence model for Monte Carlo dose calculation Med. Phys. 3 0 ( 3 ) 301-11 [2] Fippel M 1999 Fast Monte -Carlo dose calculation for photon beams based on the VMC electron Monte Carlo algorithm Med. Phys. 26 1466-75 [3] Hartmann M. et al 2001 IMRT optimisation based on a new inverse Monte-Carlo code. Radiother. Oncol. 61 (Suppl.1) 47 339 A novel inverse Monte Carlo m e t h o d
G. Jarrv. F. Verhaegen McGill University Health Center, Medical Physics, Montreal, Canada We present a novel inverse Monte Carlo (MC) method based on inverse Compton scattering and discuss some of its applications for EPID dosimetry. This Monte Carlo technique uses the information carried by the particles exiting a geometry to recover the dose they deposited in that geometry. Particles are started with known energy, angular and spatial distributions on a plane downstream from the geometry of interest. This information can be derived from a phase space file or from pre-calculated estimates for the energy, angular and spatial distributions of the particles. The particles are then transported backwards through a user-defined voxelized geometry. The particles interaction sites are sampled using an algorithm based on attenuation coefficients. At the interaction site, the new energy and angle of the particles are sampled using inverse Compton sampling. The latter is based on a cross-section look-up table derived from forward MC calculations and on