Fast optimized Monte Carlo phase-space generation and dose prediction for low energy x-ray intra-operative radiation therapy

Vidal, M.; García, Pilar; Guerra, P.; Valdivieso-Casique, M; Rodríguez, R.; Illana, C.; Udı́as, J. M.

doi:10.1088/1361-6560/ab03e7

Cited by 11 publications

(16 citation statements)

References 53 publications

(60 reference statements)

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“…The XIORT-MC described in this work is a powerful tool for treatment planning with the INTRABEAM. [24][25][26][27][28]45 The user can select between CPU or GPU execution and between a MC or a HMC algorithm while keeping a high-dose prediction accuracy. The CPU-based version of the code already reaches a speed-up factor of about 50-100 when compared to a regular MC.…”

Section: Discussionmentioning

confidence: 99%

“…The XIORT‐MC described in this work is a powerful tool for treatment planning with the INTRABEAM 24–28,45 . The user can select between CPU or GPU execution and between a MC or a HMC algorithm while keeping a high‐dose prediction accuracy.…”

Section: Discussionmentioning

confidence: 99%

“…In the case of needle and spherical applicators,we followed the parameterization described in Ref. 28, where PHSP files are fully defined by the distribution of particles in energy E and two angles α and β, the first to position the particle on the sphere surface, and the second to determine the direction of emission of the particle.For the case of flat and surface applicators, the parameterized PHSP files were defined by the distribution of particles in energy E, radial distance to the applicator axis ρ, and angle θ, representing the deviation of the particle with respect to the primary angle of the trajectory. 33 The variables employed are shown in Figure 3.…”

Section: Debinningmentioning

confidence: 99%

“…Therefore, asymmetric tolerances of 7% in dose difference and 0.5 mm in distance-to-agreement were chosen to compute the gamma for the steep gradient of INTRABEAM dose distributions. 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%

“…In previous works, we very briefly introduced a new algorithm running in CPU, named Hybrid MC (HMC), [24][25][26][27][28] to calculate dose deposited by the INTRA-BEAM device within minutes,fully taking into account the different tissues and structures of the patient, that is, as derived from a 3D Computed Tomography (CT) image. The HMC includes all the relevant physics of a regular MC minimizing the contribution of statistical noise, so dose distributions may be obtained in a CPU in a much shorter time than a regular full-MC simulation.…”

Section: Introductionmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Debinningmentioning

confidence: 99%

Section: F I G U R Ementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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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AAPM WGDCAB Report 372: A joint AAPM, ESTRO, ABG, and ABS report on commissioning of model‐based dose calculation algorithms in brachytherapy

et al. 2023

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The introduction of model‐based dose calculation algorithms (MBDCAs) in brachytherapy provides an opportunity for a more accurate dose calculation and opens the possibility for novel, innovative treatment modalities. The joint AAPM, ESTRO, and ABG Task Group 186 (TG‐186) report provided guidance to early adopters. However, the commissioning aspect of these algorithms was described only in general terms with no quantitative goals. This report, from the Working Group on Model‐Based Dose Calculation Algorithms in Brachytherapy, introduced a field‐tested approach to MBDCA commissioning. It is based on a set of well‐characterized test cases for which reference Monte Carlo (MC) and vendor‐specific MBDCA dose distributions are available in a Digital Imaging and Communications in Medicine—Radiotherapy (DICOM‐RT) format to the clinical users. The key elements of the TG‐186 commissioning workflow are now described in detail, and quantitative goals are provided. This approach leverages the well‐known Brachytherapy Source Registry jointly managed by the AAPM and the Imaging and Radiation Oncology Core (IROC) Houston Quality Assurance Center (with associated links at ESTRO) to provide open access to test cases as well as step‐by‐step user guides. While the current report is limited to the two most widely commercially available MBDCAs and only for 192Ir‐based afterloading brachytherapy at this time, this report establishes a general framework that can easily be extended to other brachytherapy MBDCAs and brachytherapy sources. The AAPM, ESTRO, ABG, and ABS recommend that clinical medical physicists implement the workflow presented in this report to validate both the basic and the advanced dose calculation features of their commercial MBDCAs. Recommendations are also given to vendors to integrate advanced analysis tools into their brachytherapy treatment planning system to facilitate extensive dose comparisons. The use of the test cases for research and educational purposes is further encouraged.

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Effective energy assessment during breast cancer intraoperative radiotherapy by low-energy X-rays: A Monte Carlo study

Shamsabadi

Baghani

Mowlavi

et al. 2021

Radiat Environ Biophys

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Fast optimized Monte Carlo phase-space generation and dose prediction for low energy x-ray intra-operative radiation therapy

Cited by 11 publications

References 53 publications

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

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

AAPM WGDCAB Report 372: A joint AAPM, ESTRO, ABG, and ABS report on commissioning of model‐based dose calculation algorithms in brachytherapy

Effective energy assessment during breast cancer intraoperative radiotherapy by low-energy X-rays: A Monte Carlo study

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