Prioritized efficiency optimization for intensity modulated proton therapy

Combined optimization of spot positions and weights for better FLASH proton therapy

Objective.In Intensity Modulated Proton Therapy (IMPT), the weights of individual pencil-beams or spots are optimized to fulfil dosimetric constraints. Theses spots are usually located on a regular lattice and their positions are fixed during optimization. In many cases, the range of spot weights may however be limited, leading sometimes to sub-optimal plan quality. An emblematic use case is the delivery of a plan at ultra-high dose rate (FLASH-RT), for which the spot weights are typically constrained to high values.Approach. To improve further the quality of IMPT FLASH plans, we propose here a novel algorithm to optimize both the spot weights and positions directly based on the objectives defined by the treatment planner.Main results. For all cases considered, optimizing the spot positions lead to an enhanced dosimetric score, while maintaining a high dose rate.Significance. Overall, this approach resulted in a substantial plan quality improvement compared to optimizing only the spot weights, and in a similar execution time.

Effect of the initial energy layer and spot placement parameters on IMPT delivery efficiency and plan quality

PURPOSE

Improving efficiency of intensity modulated proton therapy (IMPT) treatment can be achieved by shortening the beam delivery time. The purpose of this study is to reduce the delivery time of IMPT, while maintaining the plan quality, by finding the optimal initial proton spot placement parameters.

METHODS

Seven patients previously treated in the thorax and abdomen with gated IMPT and voluntary breath-hold were included. In the clinical plans, the energy layer spacing (ELS) and spot spacing (SS) were set to 0.6-0.8 (as a scale factor of the default values). For each clinical plan, we created four plans with ELS increased to 1.0, 1.2, 1.4, and SS to 1.0 while keeping all other parameters unchanged. All 35 plans (130 fields) were delivered on a clinical proton machine and the beam delivery time was recorded for each field.

RESULTS

Increasing ELS and SS did not cause target coverage reduction. Increasing ELS had no effect on critical organ-at-risk (OAR) doses or the integral dose, while increasing SS resulted in slightly higher integral and selected OAR doses. Beam-on times were 48.4 ± 9.2 (range: 34.1-66.7) seconds for the clinical plans. Time reductions were 9.2 ± 3.3 s (18.7 ± 5.8%), 11.6 ± 3.5 s (23.1 ± 5.9%), and 14.7 ± 3.9 s (28.9 ± 6.1%) when ELS was changed to 1.0, 1.2, and 1.4, respectively, corresponding to 0.76-0.80 s/layer. SS change had a minimal effect (1.1 ± 1.6 s, or 1.9 ± 2.9%) on the beam-on time.

CONCLUSION

Increasing the energy layers spacing can reduce the beam delivery time effectively without compromising IMPT plan quality; increasing the SS had no meaningful impact on beam delivery time and resulted in plan-quality degradation in some cases.

Improving delivery efficiency using spots and energy layers reduction algorithms based on a large momentum acceptance beamline

BACKGROUND

Intensity-modulated proton therapy (IMPT) is a well-known delivery method of proton therapy. Besides higher plan quality, reducing the delivery time is also essential to IMPT plans. It can enhance patient comfort, reduce treatment costs, and improve delivery efficiency. From the perspective of treatment efficacy, it contributes to mitigating the intra-fractional motions and improving the accuracy of radiotherapy, especially for moving tumors.

PURPOSE

However, there is a tradeoff problem between the plan quality and delivery time. We consider the potential of a large momentum acceptance (LMA) beamline and apply the spots and energy layers reduction method to reduce the delivery time.

METHODS

The delivery time for each field consists of the energy layer switching time, spot traveling time, and dose delivery time. The larger momentum spread and higher intensity beam offered by the LMA beamline contribute to reducing the total delivery time compared to the conventional beamline. In addition to the dose fidelity term, an L1 and logarithm items were added to the objective function to increase the sparsity of the low-weighted spots and energy layers. After that, the low-weighted spots and layers were iteratively excluded in the reduced plan, which reduced the energy layer switching time and spot traveling time. We used the standard, reduced, and LMA-reduced plans to validate the proposed method and tested it on prostate and nasopharyngeal cases. Then, we compared and evaluated the plan quality, treatment time, and plan robustness against delivery uncertainty.

RESULTS

Compared with the standard plans, the number of spots in the LMA-reduced plans was on average reduced by 13 400 (95.6%) for prostate cases and by 48 300 (80.7%) for nasopharyngeal cases and the number of energy layers was on average reduced by 49 (61.3%) for prostate cases and by 97 (50.5%) for nasopharyngeal cases. And, the delivery time of the LMA-reduced plans was shortened from 34.5 to 8.6 s for prostate cases and from 163.8 to 53.6 s for nasopharyngeal cases. The LMA-reduced plans had comparable robustness to the spot monitor unit (MU) error compared with the standard plans, but the LMA-reduced plans became more sensitive to spot position uncertainty.

CONCLUSION

The delivery efficiency can be significantly improved using the LMA beamline and spots and energy layers reduction strategies. The method is promising to improve the efficiency of motion mitigation strategies for treating moving tumors.

Investigation of the impact of machine operating parameters on beam delivery time and its correlation with treatment plan characteristics for synchrotron-based proton pencil beam spot scanning system

Purpose

To investigate the beam delivery time (BDT) reduction due to the improvement of machine parameters for Hitachi synchrotron-based proton PBS system.

Methods

BDTs for representative treatment plans were calculated to quantitatively estimate the BDT improvement from our 2015 system at Mayo Clinic in Arizona to our system to be implemented in 2025 at Mayo Clinic in Florida, and to a hypothetical future system. To specifically assess how each incremental improvement in the operating parameters reduced the total BDT, for each plan, we simulated the BDT 10,368 times with various settings of the nine different operating parameters. The effect of each operating parameter on BDT reduction and its correlation with treatment plan characteristics were analyzed. The optimal number of multiple energy extraction (MEE) layers per spill for different systems was also investigated.

Results

The median (range) decrease in BDT was 60% (56%-70%) from the 2015 to the 2025 system. The following incremental improvement in parameters of the 2015 system for the 2025 system played an important role in this decreased BDT: beam intensity (8 to 20 MU/s), recapture efficiency (50% to 80%), number of MEE layers per spill (4 to 8), scanning magnet preparation and verification time (1.9 to 0.95 msec), and MEE layer switch time (200 to 100 msec). Reducing the total spill change time and scanning magnet preparation and verification time from those of the 2025 system further reduced BDT in the hypothetical future system. 8 MEE layers per spill is optimal for a system with 50% recapture efficiency; 16 MEE layers per spill is optimal for a system with 80% recapture efficiency; and more than 16 MEE layers per spill is beneficial only for a system close to 100% recapture efficiency.

Conclusions

We systematically studied the effect of each machine operating parameter on the reduction in total BDT and its correlation with treatment plan characteristics. Our findings will aid new and existing synchrotron-based proton beam therapy centers to make balanced decisions on BDT benefits vs. costs when considering machine upgrade or new system selection.

Future Developments in Charged Particle Therapy: Improving Beam Delivery for Efficiency and Efficacy

The physical and clinical benefits of charged particle therapy (CPT) are well recognized. However, the availability of CPT and complete exploitation of dosimetric advantages are still limited by high facility costs and technological challenges. There are extensive ongoing efforts to improve upon these, which will lead to greater accessibility, superior delivery, and therefore better treatment outcomes. Yet, the issue of cost remains a primary hurdle as utility of CPT is largely driven by the affordability, complexity and performance of current technology. Modern delivery techniques are necessary but limited by extended treatment times. Several of these aspects can be addressed by developments in the beam delivery system (BDS) which determines the overall shaping and timing capabilities enabling high quality treatments. The energy layer switching time (ELST) is a limiting constraint of the BDS and a determinant of the beam delivery time (BDT), along with the accelerator and other factors. This review evaluates the delivery process in detail, presenting the limitations and developments for the BDS and related accelerator technology, toward decreasing the BDT. As extended BDT impacts motion and has dosimetric implications for treatment, we discuss avenues to minimize the ELST and overview the clinical benefits and feasibility of a large energy acceptance BDS. These developments support the possibility of advanced modalities and faster delivery for a greater range of treatment indications which could also further reduce costs. Further work to realize methodologies such as volumetric rescanning, FLASH, arc, multi-ion and online image guided therapies are discussed. In this review we examine how increased treatment efficiency and efficacy could be achieved with improvements in beam delivery and how this could lead to faster and higher quality treatments for the future of CPT.

Shortening delivery times for intensity-modulated proton therapy by reducing the number of proton spots: an experimental verification

Delivery times of intensity-modulated proton therapy (IMPT) can be shortened by reducing the number of spots in the treatment plan, but this may affect clinical plan delivery. Here, we assess the experimental deliverability, accuracy and time reduction of spot-reduced treatment planning for a clinical case, as well as its robustness. For a single head-and-neck cancer patient, a spot-reduced plan was generated and compared with the conventional clinical plan. The number of proton spots was reduced using the iterative 'pencil beam resampling' technique. This involves repeated inverse optimization, while adding in each iteration a small sample of randomly selected spots and subsequently excluding low-weighted spots until plan quality deteriorates. Field setup was identical for both plans and comparable dosimetric quality was a prerequisite. Both IMPT plans were delivered on PSI Gantry 2 and measured in water, while delivery log-files were used to extract delivery times and reconstruct the delivered dose via Monte-Carlo dose calculations. In addition, robustness simulations were performed to assess sensitivity to machine inaccuracies and errors in patient setup and proton range. The number of spots was reduced by 96% (from 33 855 to 1510 in total) without compromising plan quality. The spot-reduced plan was deliverable on our gantry in standard clinical mode and resulted in average delivery times per field being shortened by 46% (from 51.2 to 27.6 s). For both plans, differences between measured and calculated dose were within clinical tolerance for patient-specific verifications and Monte-Carlo dose reconstructions were in accordance with clinical experience. The spot-reduced plan was slightly more sensitive to machine inaccuracies, but more robust against setup and range errors. In conclusion, for an example head-and-neck case, spot-reduced IMPT planning provided a deliverable treatment plan and enabled considerable shortening of the delivery time (∼50%) without compromising plan quality or delivery accuracy, and without substantially affecting robustness.

Automating proton treatment planning with beam angle selection using Bayesian optimization

PURPOSE

To present a fully automated treatment planning process for proton therapy including beam angle selection using a novel Bayesian optimization approach and previously developed constrained hierarchical fluence optimization method.

METHODS

We adapted our in-house automated intensity modulated radiation therapy (IMRT) treatment planning system, which is based on constrained hierarchical optimization and referred to as ECHO (expedited constrained hierarchical optimization), for proton therapy. To couple this to beam angle selection, we propose using a novel Bayesian approach. By integrating ECHO with this Bayesian beam selection approach, we obtain a fully automated treatment planning framework including beam angle selection. Bayesian optimization is a global optimization technique which only needs to search a small fraction of the search space for slowly varying objective functions (i.e., smooth functions). Expedited constrained hierarchical optimization is run for some initial beam angle candidates and the resultant treatment plan for each beam configuration is rated using a clinically relevant treatment score function. Bayesian optimization iteratively predicts the treatment score for not-yet-evaluated candidates to find the best candidate to be optimized next with ECHO. We tested this technique on five head-and-neck (HN) patients with two coplanar beams. In addition, tests were performed with two noncoplanar and three coplanar beams for two patients.

RESULTS

For the two coplanar configurations, the Bayesian optimization found the optimal beam configuration after running ECHO for, at most, 4% of all potential configurations (23 iterations) for all patients (range: 2%-4%). Compared with the beam configurations chosen by the planner, the optimal configurations reduced the mandible maximum dose by 6.6 Gy and high dose to the unspecified normal tissues by 3.8 Gy, on average. For the two noncoplanar and three coplanar beam configurations, the algorithm converged after 45 iterations (examining <1% of all potential configurations).

CONCLUSIONS

A fully automated and efficient treatment planning process for proton therapy, including beam angle optimization was developed. The algorithm automatically generates high-quality plans with optimal beam angle configuration by combining Bayesian optimization and ECHO. As the Bayesian optimization is capable of handling complex nonconvex functions, the treatment score function which is used in the algorithm to evaluate the dose distribution corresponding to each beam configuration can contain any clinically relevant metric.