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Background and purpose: IMPT faces challenges in lung cancer treatment, like maintaining plan robustness for moving tumors against setup, range errors, and interplay effects. Proton Arc Therapy (PAT) is an alternative to maintain target coverage, potentially improving organ at risk (OAR) sparing, reducing beam delivery time (BDT), and enhancing patient experience. We aim to perform a systematic plan comparison study between IMPT and ELSA-PAT to assess its potential for lung cancer treatment. Material and Methods: 14 Lung ELSA-PAT plans were compared retrospectively with IMPT plans. 4D worst-case minimax robust optimization was performed, including 84 scenarios (3%,3 mm). Dosimetry assessment included target (CTV) and important OARs, on nominal and worst-case scenarios. Most relevant normal tissue complication probabilities (NTCP), target coverage robustness against interplay effect and beam delivery time (BDT) were evaluated. Results: CTV D95% and D98% showed no significant difference in comparison. PAT demonstrated better conformality by 66% (p = 0.00012) but delivered a higher heart mean dose (HMD,23%). There was a 2% increase in NTCP 2-year mortality risk with PAT. Total BDT was comparable among techniques. IMPT was more robust than PAT against interplay effect, considering both D1% (1,0 $\pm$ 0.8 Gy vs 1.1 $\pm$ 1.4 Gy) and D98% bandwidths (0.9$\pm$0.9 Gy vs 1.1 $\pm$ 1.3 Gy). Interpretation: both techniques provide a similar level of dose coverage to the target volume. Although PAT improved dose conformality, higher HMD translated into increased heart toxicity, presumably due to chosen planning methodology and OAR proximity to target. Increased energy layers and spots raised PAT beam delivery time, although it could improve daily treatment workflow.

Purpose: The FLASH effect, which reduces the radiosensitivity of healthy tissue while maintaining tumor control at high dose rates, has shown potential for improving radiation therapy. Conformal FLASH proton therapy involves advanced beam-shaping technologies and specialized nozzle designs to confine the dose to the target volume. Optimizing the spot delivery pattern and range modulators can enhance the local dose rate, and genetic algorithms have been used to optimize scan patterns for stereotactic FLASH proton therapy of early-stage lung cancer and lung metastases. A fast and effective method based on graph theory is proposed to optimize the dose rate in specific regions of interest. Methods: We have created a graph-based algorithm to optimize the trajectory of proton spots to maximize the 100th percentile dose rate. Since this problem is NP-hard, we have employed an approximation algorithm that can solve this kind of Traveling Salesman Problem efficiently. Results: When compared to a conventional serpentine pattern, the optimized scanning trajectory led to a doubling of the median dose rate, but only a minor increase in DR95. Our approach is more efficient and requires fewer evaluations of the objective function and hyper-parameters compared to existing genetic algorithms. Conclusions: The optimized scanning trajectory led to a doubling of the median dose rate, but only a minor increase in DR95. The extent to which the dose rate can be increased depends on the size and shape of the region of interest. Future research could explore integrating FLASH objectives into treatment planning and incorporating the proposed method into plan optimization., Comment: 10 pages, 4 figures

Purpose: A promising approach to enable FLASH conformal proton therapy is to passively degrade a single energy layer using a patient-specific range modulator. We propose an innovative method to directly optimize the geometrical characteristics of the range modulator and the treatment plan with respect to user defined constraints, similarly to state-of-the-art IMPT inverse planning. Methods: The kind of range modulators proposed in this study is a voxelized object which can be placed in the CT for dose computation, which simplifies the simulation pipeline. Both the geometrical characteristics of the range modulator and the weights of the PBS spots were directly optimized with respect to constraints on the dose using a first-order method. A modified Monte Carlo dose engine was used to provide an estimate of the gradient of the relaxed constraints with respect to the elevation values of the range modulator. Results: Assessed on a head and neck case, dose conformity logically appeared to be significantly degraded compared to IMPT. We then demonstrated that this degradation came mainly from the use of a large range shifter and therefore from physical limitations inherent in the passive degradation of beam energy. The geometry of the range modulator, on the other hand, was shown to be very close to being optimal. PBS dose rates were computed and discussed with respect to FLASH objectives. Conclusions: The voxelized range modulators optimized with the proposed method were proven to be optimal on a head and neck case characterized by two rather large volumes, with irregular contours and variable depths. The optimized geometry differed from conventional ridge filters as it was arbitrarily set by the optimizer. This kind of range modulators can be directly added in the CT for dose computation and is well suited for 3D printing., Comment: 12 pages, 6 figures

Purpose: Highlight the distinctions, both in terms of concept and numerical values, of the various definitions that can be established for the dose rate in PBS proton therapy. Methods: In an in silico study, five definitions of the dose rate, namely the PBS dose rate, the percentile dose rate, the maximum percentile dose rate, the average dose rate, and the dose averaged dose rate (DADR) were analyzed first through theoretical comparison, and then applied to a head and neck case. To carry out this study, a treatment plan utilizing a single energy level and requiring the use of a patient-specific range modulator was employed. The dose rate values were compared both locally and by means of dose rate volume histograms (DRVHs). Results: The PBS dose rate, the percentile dose rate, and the maximum percentile dose are definitions that are specifically designed to take into account the time structure of the delivery of a PBS treatment plan. Although they may appear similar, our study shows that they can vary locally by up to 10%. On the other hand, the DADR values were approximately twice as high as those of the PBS, percentile and maximum percentile dose rates, since the DADR disregards the periods when a voxel does not receive any dose. Finally, the average dose rate can be defined in various ways, as discussed in this paper. The average dose rate is found to be lower by a factor of approximately 1/2 than the PBS, percentile and maximum percentile dose rates. Conclusions: We have shown that using different definitions for the dose rate in FLASH proton therapy can lead to variations in calculated values ranging from a few percent to a factor of two. Since the dose rate is a critical parameter in FLASH radiation therapy, it is essential to carefully consider the choice of definition. However, to make an informed decision, additional biological data and models are needed.

The use of neural networks to directly predict three-dimensional dose distributions for automatic planning is becoming popular. However, the existing methods only use patient anatomy as input and assume consistent beam configuration for all patients in the training database. The purpose of this work is to develop a more general model that, in addition to patient anatomy, also considers variable beam configurations, to achieve a more comprehensive automatic planning with a potentially easier clinical implementation, without the need of training specific models for different beam settings.

Proton radiotherapy promises accurate dose delivery to a tumor and minimal dose deposition to all other tissues. However, in practice the planned dose distribution may not conform to the actual one due to noisy data and different types of errors. One such error comes in a form of potentially inaccurate conversion of the Hounsfield units (HU) to stopping powers (SP) of protons. We propose a method of improving the CC based on a planning CT and proton range measurements acquired during treatment. The range data were simulated using a virtual CC and a planning CT. The range data were given two types of noise: range shift due to patient setup errors; and range noise due to measurement imprecision, including a misalignment of the range measuring device. The method consists of two parts. The first part involves a Taylor expansion of the water equivalent path length (WEPL) map in terms of the range shift caused by the difference between the planning and the virtual CC. The range shift is then solved for explicitly, leading to a polynomial function of the difference between the two CCs. The second part consists in minimizing a score function relating the range due to the virtual CC and the range due to the optimized CC. Tested on ten different CCs, our results show that, with range data collected over a few fractions (less than 10), the optimized CC leads to an overall reduction of the range difference. More precisely, on average, the uncertainty of the CC was reduced from 2.67% to 1.62%, while the average reduction of the WEPL bias was reduced from 2.14% to 0.74%. The advantage of our method over others is 1) its speed, and 2) the fact that the range data it necessitates are acquired during the treatment itself, and as such it does not burden the patient with additional dose.