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

BACKGROUND: Proton arc therapy (PAT) has emerged as a promising approach for improving dose distribution, but also enabling simpler and faster treatment delivery in comparison to conventional proton treatments. However, the delivery speed achievable in proton arc relies on dedicated algorithms, which currently do not generate plans with a clear speed-up and sometimes even result in increased delivery time. PURPOSE: This study aims to address the challenge of minimizing delivery time through a hybrid method combining a fast geometry-based energy layer (EL) pre-selection with a dose-based EL filtering, and comparing its performance to a baseline approach without filtering. METHODS: Three methods of EL filtering were developed: unrestricted, switch-up (SU), and switch-up gap (SU gap) filtering. The unrestricted method filters the lowest weighted EL while the SU gap filtering removes the EL around a new SU to minimize the gantry rotation braking. The SU filtering removes the lowest weighted group of EL that includes a SU. These filters were combined with the RayStation dynamic proton arc optimization framework energy layer selection and spot assignment (ELSA). Four bilateral oropharyngeal and four lung cancer patients' data were used for evaluation. Objective function values, target coverage robustness, organ-at-risk doses and normal tissue complication probability evaluations, as well as comparisons to intensity-modulated proton therapy (IMPT) plans, were used to assess plan quality. RESULTS: The SU gap filtering algorithm performed best in five out of the eight cases, maintaining plan quality within tolerance while reducing beam delivery time, in particular for the oropharyngeal cohort. It achieved up to approximately 22% and 15% reduction in delivery time for oropharyngeal and lung treatment sites, respectively. The unrestricted filtering algorithm followed closely. In contrast, the SU filtering showed limited improvement, suppressing one or two SU without substantial delivery time shortening. Robust target coverage was kept within 1% of variation compared to the PAT baseline plan while organs-at-risk doses slightly decreased or kept about the same for all patients. CONCLUSIONS: This study provides insights to accelerate PAT delivery without compromising plan quality. These advancements could enhance treatment efficiency and patient throughput.

Partitioning of discrete proton arcs into interlaced subplans can bring proton arc advances to existing proton facilities.

BACKGROUND: Proton arcs have shown potential to reduce the dose to organs at risks (OARs) by delivering the protons from many different directions. While most previous studies have been focused on dynamic arcs (delivery during rotation), an alternative approach is discrete arcs, where step-and-shoot delivery is used over a large number of beam directions. The major advantage of discrete arcs is that they can be delivered at existing proton facilities. However, this advantage comes at the expense of longer treatment times. PURPOSE: To exploit the dosimetric advantages of proton arcs, while achieving reasonable delivery times, we propose a partitioning approach where discrete arc plans are split into subplans to be delivered over different fractions in the treatment course. METHODS: For three oropharyngeal cancer patients, four different arc plans have been created and compared to the corresponding clinical IMPT plan. The treatment plans are all planned to be delivered in 35 fractions, but with different delivery approaches over the fractions. The first arc plan (1×30) has 30 directions to be delivered every fraction, while the others are partitioned into subplans with 10 and 6 beam directions, each to be delivered every third (3×10), fifth fraction (5×6), or seventh fraction (7×10). All plans are assessed with respect to delivery time, target robustness over the treatment course, doses to OARs and NTCP for dysphagia and xerostomia. RESULTS: The delivery time (including an additional delay of 30 s between the discrete directions to simulate manual interaction with the treatment control system) is reduced from on average 25.2 min for the 1×30 plan to 9.2 min for the 3×10 and 7×10 plans and 5.7 min for the 5×6 plans. The delivery time for the IMPT plan is 7.9 min. When accounting for the combination of delivery time, target robustness, OAR sparing, and NTCP reduction, the plans with 10 directions in each fraction are the preferred choice. Both the 3×10 and 7×10 plans show improved target robustness compared to the 1×30 plans, while keeping OAR doses and NTCP values at almost as low levels as for the 1×30 plans. For all patients the NTCP values for dysphagia are lower for the partitioned plans with 10 directions compared to the IMPT plans. NTCP reduction for xerostomia compared to IMPT is seen in two of the three patients. The best results are seen for the first patient, where the NTCP reductions for the 7×10 plan are 1.6 p.p. (grade 2 xerostomia) and 1.5 p.p. (grade 2 dysphagia). The corresponding NTCP reductions for the 1×30 plan are 2.7 p.p. (xerostomia, grade 2) and 2.0 p.p. (dysphagia, grade 2). CONCLUSIONS: Discrete proton arcs can be implemented at any proton facility with reasonable treatment times using a partitioning approach. The technique also makes the proton arc treatments more robust to changes in the patient anatomy.

Fast robust optimization of proton PBS arc therapy plans using early energy layer selection and spot assignment.

Objective.Proton pencil-beam scanning arcs (PBS arcs) have gained much attention during the past years, due to its potential for increased clinical benefit compared to conventional proton therapy. Previous studies on PBS arcs have primarily been focused on plan quality, and lately efforts have been made to reduce the delivery time. However, the methods presented so far suffer from slow optimization processes.Approach.We present a new method for fast robust optimization of PBS arc plans. The new method assigns a single energy layer per discretized direction prior to spot weight optimization and reduces the number of initial spots considerably compared to conventional methods. We used the new method for three prostate cancer patients with a prescribed dose to the CTV of 77 GyRBEin 35 fractions. For each of the patients, four plans were created: 2-beam IMPT (2IMPT), 1-beam PBS arc (1Arc), 1-beam PBS arc without focus on reducing upward energy jumps (1Arc_unseq) and two-beam PBS arc (2Arc).Main results.All PBS arc plans show a reduced integral dose compared to their respective 2IMPT plans. In the nominal case, the average CTV D98 and D2 metrics over the three patients were best for the 2Arc, followed by 2IMPT (D98¯/D2¯:7523/7986 cGyRBE(2IMPT), 7478/7984 cGy (1Arc), 7486/7951 cGy (1Arc_unseq), 7531/7951 cGyRBE(2Arc)). The average robust target coverage in terms of V95 of the voxelwise minimum dose distribution (evaluated over 42 scenarios) was: 98.0% (2IMPT), 88.6% (1Arc), 92.5% (1Arc_unseq), 97.3% (2Arc). The optimization time, including spot selection and spot dose computation, is longest for the 2Arc plan, but is below 6 min for all patients. The maximum estimated delivery time for all types of arc plans is just above 5 minSignificance.The ability for efficient treatment planning constitutes an important step towards clinical introduction of proton PBS arcs.

Damage shielding mechanisms in hierarchical composites in nature with potential for design of tougher structural materials.

Load-carrying materials in nature, such as wood and bone, consist of relatively simple building blocks assembled into a hierarchical structure, ranging from the molecular scale up to the macroscopic level. This results in composites with a combination of high strength and high toughness, showing very large fracture surfaces indicating energy dissipation by cracking on multiple length scales. Man-made composites instead consist typically of fibres embedded in a uniform matrix, and frequently show brittle failure through the growth of critical clusters of broken fibres. In this paper, a hierarchical structure inspired by wood is presented. It is designed to incapacitate cluster growth, with the aim of retaining high strength. This is done by introducing new structural levels of successively weaker interfaces with the purpose of reducing the stress concentrations if large clusters appear. To test this hypothesis, a probability density field of further damage growth has been calculated for different microstructures and initial crack sizes. The results indicate that the hierarchical structure should maintain its strength by localization of damage, yet rendering large clusters less harmful by weakening the resulting stress concentration to its surroundings, which would lead to an increase in strain to failure. In this context, the potential of using the biomimetic hierarchical structure in design of composite materials is discussed.