Purpose: Arc Proton Therapy (ArcPT) is an emerging technique that has the possibility of improving both the outcome and the efficiency of the treatment. This modality constrains the number of energy switches as it primarily determines the treatment delivery time. Therefore, the challenge lies in selecting as few energy layers as possible for each beam direction. In this study, we designed a beamlet-based algorithm for the optimization of ArcPT plans that distributes a number of energy layers similar to conventional therapy over more gantry angles.
Methods: The ArcPT optimization problem is formulated with an objective function defined conventionally as the quantitative evaluation criterion for the delivered dose distribution combined with new objectives respecting constraints on the number of energy layers used over the arc.The proposed method was tested on a lung tumor case and evaluated according to these criteria: objective function value, layer sparsity and DVH metrics.
Results: An ArcPT plan with 98.4% of the beams delivering only one energy layer per control point was successfully obtained with good dosimetry results, some of which are even better than the ones obtained with a conventional IMPT plan. Actually, the target D95 reached 96.5% of the prescription in ArcPT versus 95.6% in IMPT. Although the mean doses in the heart (0.4 Gy) and right lung (6.1 Gy) obtained with ArcPT slightly exceed those with IMPT (0.3 Gy and 5.6 Gy for the heart and right lung respectively), they still achieve the clinical goals
Conclusion: The algorithm proposed for ArcPT treatment plan optimization has successfully solved the energy layer selection problem by generating acceptable plans with good dosimetric results. The definition of our objective function will be completed with a sequencing energy term that favors small consecutive energy decrements to further reduce irradiation time.
Funding Support, Disclosures, and Conflict of Interest: Funded by the Walloon Region. Research agreement with Ion Beam Applications SA (IBA).