Experimental depth dose curves of a 67.5 MeV proton beam for benchmarking and validation of Monte Carlo simulation

The effect of voxelization in Monte Carlo simulation to validate Bragg peak characteristics for a pencil proton beam

Background

The purpose of this research was to show how the Bragg peak (BP) characteristics were affected by changing the voxel size in longitudinal and transverse directions in Monte Carlo (MC) simulations by using Geant4 and to calculate BP characteristics accurately by considering the voxel size effect for 68 MeV and 235.81 MeV.

Materials and methods

Different interpolation techniques were applied to simulation data to find the closest results to the experimental data.

Results

When the x-size of the voxel was increased 2 times at low energy, the maximum dose increase in the entrance and plateau regions were 17.8% and 17%, respectively, while BP curve shifted to the shallower region, resulting in a 0.5 mm reduction in the curable tumor width (W_80pd). At high energy, the maximum dose increase at the entrance and plateau regions were 0.4% and 0.6%, respectively, while it was observed that W_80pd did not change. When the y-z sizes of the voxel were increased 2 times at low energy, the maximum dose reduction at the entrance and plateau regions was 3.4%, but no change was observed in W_80pd. At high energy, when the y-z sizes of the voxel were increased 2.2 times, the maximum dose reduction at the entrance and plateau regions were 8.9% and 9.1%, respectively, while W_80pd increased by 0.5 mm. When linear, cubic spline, and Akima interpolations were applied to the simulation data, it was found that the results closest to the experimental data were obtained for Akima interpolations for both energies.

Conclusion

it has been shown that the voxel size effect for the longitudinal direction was more effective at low energy than at high energy. However, the voxel size effect for the transverse direction was more effective for high energy.

Comparing Geant4 physics models for proton-induced dose deposition and radiolysis enhancement from a gold nanoparticle

Gold nanoparticles (GNPs) are materials that make the tumor cells more radiosensitive when irradiated with ionizing radiation. The present study aimed to evaluate the impact of different physical interaction models on the dose calculations and radiochemical results around the GNP. By applying the Geant4 Monte Carlo (MC) toolkit, a single 50-nm GNP was simulated, which was immersed in a water phantom and irradiated with 5, 50, and 150 MeV proton beams. The present work assessed various parameters including the secondary electron spectra, secondary photon spectra, radial dose distribution (RDD), dose enhancement factor (DEF), and radiochemical yields around the GNP. The results with an acceptable statistical uncertainty of less than 1% indicated that low-energy electrons deriving from the ionization process formed a significant part of the total number of secondary particles generated in the presence of GNP; the Penelope model produced a larger number of these electrons by a factor of about 30%. Discrepancies of the secondary electron spectrum between Livermore and Penelope were more obvious at energies of less than 1 keV and reached the factor of about 30% at energies between 250 eV and 1 keV. The RDDs for Livermore and Penelope models were very similar with small variations within the first 6 nm from NP surface by a factor of 10%. In addition, neither the G-value nor the REF was affected by the choice of physical interaction models with the same energy cut-off. This work illustrated the similarity of the Livermore and Penelope models (within 15%) available in Geant4 for future simulation studies of GNP enhanced proton therapy with physical, physicochemical, and chemical mechanisms.

Artificial intelligence supported single detector multi-energy proton radiography system

Proton radiography imaging was proposed as a promising technique to evaluate internal anatomical changes, to enable pre-treatment patient alignment, and most importantly, to optimize the patient specific CT number to stopping-power ratio conversion. The clinical implementation rate of proton radiography systems is still limited due to their complex bulky design, together with the persistent problem of (in)elastic nuclear interactions and multiple Coulomb scattering (i.e. range mixing). In this work, a compact multi-energy proton radiography system was proposed in combination with an artificial intelligence network architecture (ProtonDSE) to remove the persistent problem of proton scatter in proton radiography. A realistic Monte Carlo model of the Proteus^®One accelerator was built at 200 and 220 MeV to isolate the scattered proton signal in 236 proton radiographies of 80 digital anthropomorphic phantoms. ProtonDSE was trained to predict the proton scatter distribution at two beam energies in a 60%/25%/15% scheme for training, testing, and validation. A calibration procedure was proposed to derive the water equivalent thickness image based on the detector dose response relationship at both beam energies. ProtonDSE network performance was evaluated with quantitative metrics that showed an overall mean absolute percentage error below 1.4% ± 0.4% in our test dataset. For one example patient, detector dose to WET conversions were performed based on the total dose (ITotal), the primary proton dose (IPrimary), and the ProtonDSE corrected detector dose (ICorrected). The determined WET accuracy was compared with respect to the reference WET by idealistic raytracing in a manually delineated region-of-interest inside the brain. The error was determined 4.3% ± 4.1% forWET(ITotal),2.2% ± 1.4% forWET(IPrimary),and 2.5% ± 2.0% forWET(ICorrected).

Report on G4-Med, a Geant4 benchmarking system for medical physics applications developed by the Geant4 Medical Simulation Benchmarking Group

BACKGROUND

Geant4 is a Monte Carlo code extensively used in medical physics for a wide range of applications, such as dosimetry, micro- and nanodosimetry, imaging, radiation protection, and nuclear medicine. Geant4 is continuously evolving, so it is crucial to have a system that benchmarks this Monte Carlo code for medical physics against reference data and to perform regression testing.

AIMS

To respond to these needs, we developed G4-Med, a benchmarking and regression testing system of Geant4 for medical physics.

MATERIALS AND METHODS

G4-Med currently includes 18 tests. They range from the benchmarking of fundamental physics quantities to the testing of Monte Carlo simulation setups typical of medical physics applications. Both electromagnetic and hadronic physics processes and models within the prebuilt Geant4 physics lists are tested. The tests included in G4-Med are executed on the CERN computing infrastructure via the use of the geant-val web application, developed at CERN for Geant4 testing. The physical observables can be compared to reference data for benchmarking and to results of previous Geant4 versions for regression testing purposes.

RESULTS

This paper describes the tests included in G4-Med and shows the results derived from the benchmarking of Geant4 10.5 against reference data.

DISCUSSION

Our results indicate that the Geant4 electromagnetic physics constructor G4EmStandardPhysics_option4 gives a good agreement with the reference data for all the tests. The QGSP_BIC_HP physics list provided an overall adequate description of the physics involved in hadron therapy, including proton and carbon ion therapy. New tests should be included in the next stage of the project to extend the benchmarking to other physical quantities and application scenarios of interest for medical physics.

CONCLUSION

The results presented and discussed in this paper will aid users in tailoring physics lists to their particular application.

A Millimeter-scale Single Charged Particle Dosimeter for Cancer Radiotherapy

This paper presents a millimeter-scale CMOS 64×64 single charged particle radiation detector system for external beam cancer radiotherapy. A 1×1 μm² diode measures energy deposition by a single charged particle in the depletion region, and the array design provides a large detection area of 512×512 μm². Instead of sensing the voltage drop caused by radiation, the proposed system measures the pulse width, i.e., the time it takes for the voltage to return to its baseline. This obviates the need for using power-hungry and large analog-to-digital converters. A prototype ASIC is fabricated in TSMC 65 nm LP CMOS process and consumes the average static power of 0.535 mW under 1.2 V analog and digital power supply. The functionality of the whole system is successfully verified in a clinical 67.5 MeV proton beam setting. To our' knowledge, this is the first work to demonstrate single charged particle detection for implantable in-vivo dosimetry.

The TOPAS tool for particle simulation, a Monte Carlo simulation tool for physics, biology and clinical research

PURPOSE

This paper covers recent developments and applications of the TOPAS TOol for PArticle Simulation and presents the approaches used to disseminate TOPAS.

MATERIALS AND METHODS

Fundamental understanding of radiotherapy and imaging is greatly facilitated through accurate and detailed simulation of the passage of ionizing radiation through apparatus and into a patient using Monte Carlo (MC). TOPAS brings Geant4, a reliable, experimentally validated MC tool mainly developed for high energy physics, within easy reach of medical physicists, radiobiologists and clinicians. Requiring no programming knowledge, TOPAS provides all of the flexibility of Geant4.

RESULTS

After 5 years of development followed by its initial release, TOPAS was subsequently expanded from its focus on proton therapy physics to incorporate radiobiology modeling. Next, in 2018, the developers expanded their user support and code maintenance as well as the scope of TOPAS towards supporting X-ray and electron therapy and medical imaging. Improvements have been achieved in user enhancement through software engineering and a graphical user interface, calculational efficiency, validation through experimental benchmarks and QA measurements, and either newly available or recently published applications. A large and rapidly increasing user base demonstrates success in our approach to dissemination of this uniquely accessible and flexible MC research tool.

CONCLUSIONS

The TOPAS developers continue to make strides in addressing the needs of the medical community in applications of ionizing radiation to medicine, creating the only fully integrated platform for four-dimensional simulation of all forms of radiotherapy and imaging with ionizing radiation, with a design that promotes inter-institutional collaboration.