Impact of varying planning parameters on proton pencil beam scanning dose distributions in four commercial treatment planning systems

Purpose In pencil beam scanning proton therapy, target coverage is achieved by scanning the pencil beam laterally in the x- and y-directions and delivering spots of dose to positions at a given radiological depth (layer). Dose is delivered to the spots on different layers by pencil beams of different energy until the entire volume has been irradiated. The aim of this study is to investigate the implementation of proton planning parameters (spot spacing, layer spacing and margins) in four commercial proton treatment planning systems (TPSs): Eclipse, Pinnacle(3), RayStation and XiO. Materials and Methods Using identical beam data in each TPS, plans were created on uniform material synthetic phantoms with cubic targets. The following parameters were systematically varied in each TPS to observe their different implementations: spot spacing, layer spacing and margin. Additionally, plans were created in Eclipse to investigate the impact of these parameters on plan delivery and optimal values are suggested. Results It was found that all systems except Eclipse use a variable layer spacing per beam, based on the Bragg peak width of each energy layer. It is recommended that if this cannot be used, then a constant value of 5 mm will ensure good dose homogeneity. Only RayStation varies the spot spacing according to the variable spot size with depth. If a constant spot spacing is to be used, a value of 5 mm is recommended as a good compromise between dose homogeneity, plan robustness and planning time. It was found that both Pinnacle(3) and RayStation position spots outside of the defined volume (target plus margin). Conclusions All four systems are capable of delivering uniform dose distributions to simple targets, but their implementation of the various planning parameters is different. In this paper comparisons are made between the four systems and recommendations are made as to the values that will provide the best compromise in dose homogeneity and planning time. (c) 2019 American Association of Physicists in Medicine