Commissioning of GPU–Accelerated Monte Carlo Code FRED for Clinical Applications in Proton Therapy

Abstract

We present commissioning and validation of Fred, a graphical processing unit (GPU)–accelerated Monte Carlo code, for two proton beam therapy facilities of different beam line design: CCB (Krakow, IBA) and EMORY (Atlanta, Varian). We followed clinical acceptance tests required to approve the certified treatment planning system for clinical use. We implemented an automated and efficient procedure to build a parameter library characterizing the clinical proton pencil beam. Beam energy, energy spread, lateral propagation model, and a dosimetric calibration factor were parametrized based on measurements performed during the facility start-up. The Fred beam model was validated against commissioning and supplementary measurements performed with and without range shifter. We obtained 1) submillimeter agreement of Bragg peak shapes in water and lateral beam profiles in air and slab phantoms, 2) <2% dose agreement for spread out Bragg peaks of different ranges, 3) average gamma index (2%/2 mm) passing rate of >95% for >1000 patient verification measurements using a two-dimensional array of ionization chambers, and 4) gamma index passing rate of >99% for three-dimensional dose distributions computed with Fred and measured with an array of ionization chambers behind an anthropomorphic phantom. The results of example treatment planning study on >100 patients demonstrated that Fred simulations in computed tomography enable an accurate prediction of dose distribution in patient and application of Fred as second patient quality assurance tool. Computation of a patient treatment in a CT using 104 protons per pencil beam took on average 2′30 min with a tracking rate of 2.9×105p+/s. Fred was successfully commissioned and validated against the clinical beam model, showing that it could potentially be used in clinical routine. Thanks to high computational performance due to GPU acceleration and an automated beam model implementation method, the application of Fred is now possible for research or quality assurance purposes in most of the proton facilities.

Development and Benchmarking of a Monte Carlo Dose Engine for Proton Radiation Therapy

“…This underestimation could in part be explained through the fact that the current approach for sampling the initial particles neglects secondary d, t, 3 He and 4 He particles produced in the beamline. Our predictions are in line with other fast MC engines available in literature, for example [73], using FRED have found relative differences of up to about 3% for 200 MeV protons in water.…”

“…The 3D gamma pass rate was calculated to be 99.8% showing that the implemented models and approximations for electromagnetic and nuclear interactions approximate the underlying physics well, also in a clinical setting. Computed 3D gamma pass rates were in line with those obtained by other fast MC engines [28,33,73].…”

“…For this the python package pymedphys version 0.37.1 was used. For the calculation, similar to previous proton MC engines [28,31,73,74], the dose percentage threshold was set to 2%, the distance threshold to 2 mm and the dose cutoff to 5% of the maximum dose. During the calculation of the gamma pass rate, dose outside the patient was not considered as it is clinically irrelevant.…”

3D Dosimetry Based on LiMgPO4 OSL Silicone Foils: Facilitating the Verification of Eye-Ball Cancer Proton Radiotherapy

“…Images were captured using the Fiji open-source software [ 23 ]. Next, in the context of signal processing, images were corrected and analyzed in the Python environment, importing, among others, the functionalities FRED tools module [ 24 , 25 , 26 ]. Pixel intensities depend on several parameters and may be reflected in the camera setup parameters, image distortions or powder distribution inside the silicone matrix.…”

Management of Motion and Anatomical Variations in Charged Particle Therapy: Past, Present, and Into the Future

“…For example, Riberio et al reported on the development and application of a plan evaluation tool, 4D robust evaluation method (4DREM), which considers both setup errors as well as respiratory motion and the interplay effects (112), while Korevaar et al developed a scenariobased plan evaluation method which allows for comparison between photon and proton plans (113). In another hand, fast 4D dose calculation with GPU-accelerated dose-engines enable potential clinical use and can be integrated into the optimization process (114)(115)(116). Another consideration for 4D dose calculation is that the temporal resolution used can impact the calculated final accumulated dose distribution, a recent simulation study found that the use of finer temporal resolutions for 4D dose calculations can help to reduce the over-estimation of interplay effects for hypo-fractionated treatments (19).…”