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

J Gajewski ,Liyong Lin,Marco Durante,Francesco Tommasino,Natalia Mojżeszek,Katarzyna Krzempek,Katarzyna Czerska,Marzena Rydygier,Renata Kopeć,Agata Skrzypek,Nils Krah,Elżbieta Pluta ,V Patera ,M Garbacz ,E Scifoni ,I Rinaldi ,M Pawlik-Niedźwiecka ,A Schiavi ,Chung‐Cheng Chang ,Antoni Ruciński

doi:10.3389/fphy.2020.567300

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.

Highlights

In proton radiation therapy, Monte Carlo (MC) methods offer more accurate modeling of proton interactions with heterogeneous media and improve dose calculation accuracy in complex geometries with respect to analytical pencil beam algorithms [1,2,3,4]
The physical interaction models implemented in FRED are trimmed down with respect to general purpose MC codes, such as Geant4/FLUKA within the regime that is relevant for particle therapy, in order to speed up the execution time without compromising the accuracy of dose-deposition calculations
We share our experience on commissioning and validation of GPU-accelerated MC code FRED based on commissioning measurements of two proton beam therapy facilities of different beam line design: CCB (Krakow) from IBA and EMORY (Atlanta) from Varian

Summary

Introduction

Monte Carlo (MC) methods offer more accurate modeling of proton interactions with heterogeneous media and improve dose calculation accuracy in complex geometries with respect to analytical pencil beam algorithms [1,2,3,4]. The time performance of the MC-based TPS remains to be an issue, especially when applying robust optimization algorithms that require computing several dose distributions for one computed tomography (CT) image or in treatments of moving targets where 4D-CT consisting of a series of CT images of several motion phases of one patient are employed in treatment plan optimization [8]. Proton radiation therapy quality assurance (QA) procedures are time consuming and require manpower for experimental measurements of dose distributions in phantoms, typically performed at a few depths in water for each treatment field. Supplementing or replacing patient QA measurements with dose distribution recalculation using a second, independent, dose-calculation engines can be beneficial for PBT facilities

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