Bi-criteria Pareto optimization to balance irradiation time and dosimetric objectives in proton arc therapy

Abstract

Objective. Proton arc therapy (PAT) is a new delivery technique that exploits the continuous rotation of the gantry to distribute the therapeutic dose over many angular windows instead of using a few static fields, as in conventional (intensity-modulated) proton therapy. Although coming along with many potential clinical and dosimetric benefits, PAT has also raised a new optimization challenge. In addition to the dosimetric goals, the beam delivery time (BDT) needs to be considered in the objective function. Considering this bi-objective formulation, the task of finding a good compromise with appropriate weighting factors can turn out to be cumbersome. Approach. We have computed Pareto-optimal plans for three disease sites: a brain, a lung, and a liver, following a method of iteratively choosing weight vectors to approximate the Pareto front with few points. Mixed-Integer Programming (MIP) was selected to state the bi-criteria PAT problem and to find Pareto optimal points with a suited solver. Main results. The trade-offs between plan quality and beam irradiation time (static BDT) are investigated by inspecting three plans from the Pareto front. The latter are carefully picked to demonstrate significant differences in dose distribution and delivery time depending on their location on the frontier. The results were benchmarked against IMPT and SPArc plans showing the strength of degrees of freedom coming along with MIP optimization. Significance. This paper presents for the first time the application of bi-criteria optimization to the PAT problem, which eventually permits the planners to select the best treatment strategy according to the patient conditions and clinical resources available.

Optimizing the traversal time for gantry trajectories for proton arc therapy treatment plans

“…It is worth noting that a faster algorithm would open up the possibility to take dynamic BDT into account during the creation of a treatment plan. For example, algorithms such as ELSA (Engwall et al 2022) and the MCO-based algorithm by Wuyckens et al (2022) design plans with short delivery times by minimizing the number of upward energy switches. Further reduction in the delivery time may be achievable by tailoring the time estimate to a specific treatment machine and optimizing it directly accounting for the specific characteristics and capabilities of the treatment machine in use.…”

“…modeled BDT as proportional to the number of spots that also increases considerably in PAT plans and derived a method to enforce sparsity in the spot selection. Another group developed a technique to generate a Pareto front balancing delivery time and plan quality for proton arcs, using an approximate static BDT model taking into account energy switches and layer irradiation time (Wuyckens et al 2022). A common dynamic BDT model assumes a constant gantry rotation speed of 6 °/s, plus the time added by irradiation segments and energy switching (Ding et al 2019, Chang et al 2020, Liu et al 2020.…”

Efficient proton arc optimization and delivery through energy layer pre‐selection and post‐filtering

“…A Pareto front represents the set of optimal solutions in a multi-objective optimization problem, where improving one objective comes at the expense of worsening another. [29][30][31] In this context, the Pareto front generated relates the attainable dosimetric objective values to the necessary dynamic delivery times. By examining the trade-off between these two sides of the problem, one can select the most suitable trade-off plan from the Pareto front.…”

FLASH instead of proton arc therapy is a more promising advancement for the next generation proton radiotherapy

“…The proton system manufacturers such as IBA are taking the key steps to such development, while the Treatment Planning System (TPS) providers such as RaySearch and Elekta are also providing the proton arc module in support of future clinical implementations 68,69 . Additionally, many ideas have been formed to optimize particle arc therapy in a more efficient way 70–75 . In recent years, we saw exponentially increased publications on the topic of particle arc therapy.…”

“…68,69 Additionally, many ideas have been formed to optimize particle arc therapy in a more efficient way. [70][71][72][73][74][75] In recent years, we saw exponentially increased publications on the topic of particle arc therapy.These encouraging trends and global efforts might suggest that the proton RT is at an important turning point, similar to the invention of VMAT in the 2000s in the photon world. 30 Besides the potential clinical benefits, one driving factor that pushes particle arc therapy to dominate the future market is simplifying the clinical workflow and shortening the treatment delivery time.…”