Phase space determination from measured dose data for intraoperative electron radiation therapy

Herranz, Elena; Herraiz, Joaquín L.; García, Pilar; Pérez-Liva, Mailyn; Puebla, Ricardo; Cal-González, Jacobo; Guerra, P.; Rodríguez, R.; Illana, C.; Udı́as, J. M.

doi:10.1088/0031-9155/60/1/375

Cited by 10 publications

(11 citation statements)

References 55 publications

(86 reference statements)

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“…The MC calculations were performed using penEasy (v. 2015‐05‐30), a modular program for PENELOPE2014 . PENELOPE2014 allows simulating the transport of particles from 50 eV to 1 GeV through matter and has been successfully used to study both radioisotope and electronic sources and extensively benchmarked …”

Section: Methodsmentioning

confidence: 99%

A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit

Valdes-Cortez

Niatsetski²,

Pérez‐Calatayud

et al. 2018

Medical Physics

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Purpose: The purpose of this work is threefold: First, to obtain the phase space of an electronic brachytherapy (eBT) system designed for surface skin treatments. Second, to explore the use of some efficiency enhancing (EFEN) strategies in the determination of the phase space. Third, to use the phase space previously obtained to perform a dosimetric characterization of the Esteya eBT system. Methods: The Monte Carlo study of the 69.5 kVp x-ray beam of the Esteya â unit (Elekta Brachytherapy, Veenendaal, The Netherlands) was performed with PENELOPE2014. The EFEN strategies included the use of variance reduction techniques and mixed Class II simulations, where transport parameters were fine-tuned. Four source models were studied varying the most relevant parameters characterizing the electron beam impinging the target: the energy spectrum (mono-energetic or Gaussian shaped), and the electron distribution over the focal spot (uniform or Gaussian shaped). Phase spaces obtained were analyzed to detect differences in the calculated data due to the EFEN strategy or the source configuration. Depth dose curves and absorbed dose profiles were obtained for each source model and compared to experimental data previously published. Results: In our EFEN strategy, the interaction forcing variance reduction (VRIF) technique increases efficiency by a factor~20. Tailoring the transport parameters values (C1 and C2) does not increase the efficiency in a significant way. Applying a universal cutoff energy EABS of 10 keV saves 84% of CPU time while showing negligible impact on the calculated results. Disabling the electron transport by imposing an electron energy cutoff of 70 keV (except for the target) saves an extra 8% (losing in the process 1.2% of the photons). The Gaussian energy source (FWHM = 10%, centered at the nominal kVp, homogeneous electron distribution) shows characteristic K-lines in its energy spectrum, not observed experimentally. The average photon energy using an ideal source (mono-energetic, homogeneous electron distribution) was 36.19 AE 0.09 keV, in agreement with the published measured data of 36.2 AE 0.2 keV. The use of a Gaussian-distributed electron source (mono-energetic) increases the penumbra by 50%, which is closer to the measurement results. The maximum discrepancy of the calculated percent depth dose with the corresponding measured values is 4.5% (at the phantom surface, less than 2% beyond 1 mm depth) and 5% (for the 80% of the field) in the dose profile. Our results agree with the findings published by other authors and are consistent within the expected Type A and B uncertainties. Conclusions: Our results agree with the published measurement results within the reported uncertainties. The observed differences in PDD, dose profiles, and photon spectrum come from three main sources of uncertainty: intermachine variations, measurements, and Monte Carlo calculations. It has been observed that a mono-energetic source with a Gaussian electron distribution over the focal spot is a suitable choice to reproduc...

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Section: Methodsmentioning

confidence: 99%

A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit

Valdes-Cortez

Niatsetski²,

Pérez‐Calatayud

et al. 2018

Medical Physics

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“…3,11,28,43 A solution would be accepted if at least 95% of the voxels pass the gamma evaluation with respect to the reference dose, with a threshold set at 5% of the maximum dose D max . 33…”

Section: F I G U R Ementioning

confidence: 99%

XIORT‐MC: A real‐time MC‐based dose computation tool for low‐ energy X‐rays intraoperative radiation therapy

et al. 2021

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Purpose: The INTRABEAM system is a miniature accelerator for low-energy X-ray Intra-Operative Radiation Therapy (IORT), and it could benefit from a fast and accurate dose computation tool. With regards to accuracy, dose computed with Monte Carlo (MC) simulations are the gold standard, however, they require a large computational effort and consequently they are not suitable for realtime dose planning. This work presents a comparison of the implementation on Graphics Processing Unit (GPU) of two different dose calculation algorithms based on MC phase-space (PHSP) information to compute dose distributions for the INTRABEAM device within seconds and with the accuracy of realistic MC simulations. Methods: The MC-based algorithms we present incorporate photoelectric, Compton and Rayleigh effects for the interaction of low-energy X-rays. XIORT-MC (X-ray Intra-Operative Radiation Therapy Monte Carlo) includes two dose calculation algorithms; a Woodcock-based MC algorithm (WC-MC) and a Hybrid MC algorithm (HMC), and it is implemented in CPU and in GPU. Detailed MC simulations have been generated to validate our tool in homogeneous and heterogeneous conditions with all INTRABEAM applicators, including three clinically realistic CT-based simulations. A performance study has been done to determine the acceleration reached with the code, in both CPU and GPU implementations. Results: Dose distributions were obtained with the HMC and the WC-MC and compared to standard reference MC simulations with more than 95% voxels fulfilling a 7%-0.5 mm gamma evaluation in all the cases considered. The CPU-HMC is 100 times more efficient than the reference MC, and the CPU-WC-MC is about 50 times more efficient. With the GPU implementation, the particle tracking of the WC-MC is faster than the HMC, with the extraction of the particle's information from the PHSP file taking a major part of the time. However, thanks to the variance reduction techniques implemented in the HMC, up to 400 times less particles are needed in the HMC to reach the same level of noise than the WC-MC. Therefore, in our implementation for INTRABEAM energies, the HMC is about 1.3 times more efficient than the WC-MC in an NVIDIA GeForce GTX 1080 Ti card and about 5.5 times more efficient in an NVIDIA GeForce RTX 3090. Dose with noise below 5% has been obtained in realistic situations in less than 5 s with the WC-MC and in less than 0.5 s with the HMC. Conclusions:The XIORT-MC is a dose computation tool designed to take full advantage of modern GPUs, making possible to obtain MC-grade accurate dose distributions within seconds. Its high speed allows a real-time dose calculation that includes the realistic effects of the beam in voxelized geometries

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“…Dose distributions are calculated with a treatment planning system (TPS) specifically developed for IOERT (radiance, GMV) [ 22 , 23 ] based on a Monte Carlo algorithm that takes account of the LINAC phase space [ 24 ] and tissue heterogeneities [ 25 ] (data obtained from CT studies after converting Hounsfield units (HU) values to physical density [ 10 , 25 ]).…”

Section: Methodsmentioning

confidence: 99%

Surface scanning for 3D dose calculation in intraoperative electron radiation therapy

et al. 2018

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BackgroundDose calculations in intraoperative electron radiation therapy (IOERT) rely on the conventional assumption of water-equivalent tissues at the applicator end, which defines a flat irradiation surface. However, the shape of the irradiation surface modifies the dose distribution. Our study explores, for the first time, the use of surface scanning methods for three-dimensional dose calculation of IOERT.MethodsTwo different three-dimensional scanning technologies were evaluated in a simulated IOERT scenario: a tracked conoscopic holography sensor (ConoProbe) and a structured-light three-dimensional scanner (Artec). Dose distributions obtained from computed tomography studies of the surgical field (gold standard) were compared with those calculated under the conventional assumption or from pseudo-computed tomography studies based on surfaces.ResultsIn the simulated IOERT scenario, the conventional assumption led to an average gamma pass rate of 39.9% for dose values greater than 10% (two configurations, with and without blood in the surgical field). Results improved when considering surfaces in the dose calculation (88.5% for ConoProbe and 92.9% for Artec).ConclusionsMore accurate three-dimensional dose distributions were obtained when considering surfaces in the dose calculation of the simulated surgical field. The structured-light three-dimensional scanner provided the best results in terms of dose distributions. The findings obtained in this specific experimental setup warrant further research on surface scanning in the IOERT context owing to the clinical interest of improving the documentation of the actual IOERT scenario.

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Phase space determination from measured dose data for intraoperative electron radiation therapy

Cited by 10 publications

References 55 publications

A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit

A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit

XIORT‐MC: A real‐time MC‐based dose computation tool for low‐ energy X‐rays intraoperative radiation therapy

Surface scanning for 3D dose calculation in intraoperative electron radiation therapy

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Phase space determination from measured dose data for intraoperative electron radiation therapy

Cited by 10 publications

References 55 publications

A Monte Carlo‐based dosimetric characterization of Esteya®, an electronic surface brachytherapy unit

A Monte Carlo‐based dosimetric characterization of Esteya®, an electronic surface brachytherapy unit

XIORT‐MC: A real‐time MC‐based dose computation tool for low‐ energy X‐rays intraoperative radiation therapy

Surface scanning for 3D dose calculation in intraoperative electron radiation therapy

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A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit

A Monte Carlo‐based dosimetric characterization of Esteya^®, an electronic surface brachytherapy unit