Shortening delivery times of intensity modulated proton therapy by reducing proton energy layers during treatment plan optimization

Validation of Fully Automated Robust Multicriterial Treatment Planning for Head and Neck Cancer IMPT

PURPOSE

Our purpose was to compare robust intensity modulated proton therapy (IMPT) plans, automatically generated with wish-list-based multicriterial optimization as implemented in Erasmus-iCycle, with manually created robust clinical IMPT plans for patients with head and neck cancer.

METHODS AND MATERIALS

Thirty-three patients with head and neck cancer were retrospectively included. All patients were previously treated with a manually created IMPT plan with 7000 cGy dose prescription to the primary tumor (clinical target volume [CTV]7000) and 5425 cGy dose prescription to the bilateral elective volumes (CTV5425). Plans had a 4-beam field configuration and were generated with scenario-based robust optimization (21 scenarios, 3-mm setup error, and ±3% density uncertainty for the CTVs). Three clinical plans were used to configure the Erasmus-iCycle wish-list for automated generation of robust IMPT plans for the other 30 included patients, in line with clinical planning requirements. Automatically and manually generated IMPT plans were compared for (robust) target coverage, organ-at-risk (OAR) doses, and normal tissue complication probabilities (NTCP). No manual fine-tuning of automatically generated plans was performed.

RESULTS

For all automatically generated plans, voxel-wise minimum D98% values for the CTVs were within clinical constraints and similar to manual plans. All investigated OAR parameters were favorable in the automatically generated plans (all P < .001). Median reductions in mean dose to OARs went up to 667 cGy for the inferior pharyngeal constrictor muscle, and median reductions in D0.03cm3 in serial OARs ranged up to 1795 cGy for the spinal cord surface. The observed lower mean dose in parallel OARs resulted in statistically significant lower NTCP for xerostomia (grade ≥2: 34.4% vs 38.0%; grade ≥3: 9.0% vs 10.2%) and dysphagia (grade ≥2: 11.8% vs 15.0%; grade ≥3: 1.8% vs 2.8%).

CONCLUSIONS

Erasmus-iCycle was able to produce IMPT dose distributions fully automatically with similar (robust) target coverage and improved OAR doses and NTCPs compared with clinical manual planning, with negligible hands-on planning workload.

Technical note: Dosimetry and FLASH potential of UHDR proton PBS for small lung tumors: Bragg-peak-based delivery versus transmission beam and IMPT

BACKGROUND

High-energy transmission beams (TBs) are currently the main delivery method for proton pencil beam scanning ultrahigh dose-rate (UHDR) FLASH radiotherapy. TBs place the Bragg-peaks behind the target, outside the patient, making delivery practical and achievement of high dose-rates more likely. However, they lead to higher integral dose compared to conventional intensity-modulated proton therapy (IMPT), in which Bragg-peaks are placed within the tumor. It is hypothesized that, when energy changes are not required and high beam currents are possible, Bragg-peak-based beams can not only achieve more conformal dose distributions than TBs, but also have more FLASH-potential.

PURPOSE

This works aims to verify this hypothesis by taking three different Bragg-peak-based delivery techniques and comparing them with TB and IMPT-plans in terms of dosimetry and FLASH-potential for single-fraction lung stereotactic body radiotherapy (SBRT).

METHODS

For a peripherally located lung target of various sizes, five different proton plans were made using "matRad" and inhouse-developed algorithms for spot/energy-layer/beam reduction and minimum monitor unit maximization: (1) IMPT-plan, reference for dosimetry, (2) TB-plan, reference for FLASH-amount, (3) pristine Bragg-peak plan (non-depth-modulated Bragg-peaks), (4) Bragg-peak plan using generic ridge filter, and (5) Bragg-peak plan using 3D range-modulated ridge filter.

RESULTS

Bragg-peak-based plans are able to achieve sufficient plan quality and high dose-rates. IMPT-plans resulted in lowest OAR-dose and integral dose (also after a FLASH sparing-effect of 30%) compared to both TB-plans and Bragg-peak-based plans. Bragg-peak-based plans vary only slightly between themselves and generally achieve lower integral dose than TB-plans. However, TB-plans nearly always resulted in lower mean lung dose than Bragg-peak-based plans and due to a higher amount of FLASH-dose for TB-plans, this difference increased after including a FLASH sparing-effect.

CONCLUSION

This work indicates that there is no benefit in using Bragg-peak-based beams instead of TBs for peripherally located, UHDR stereotactic lung radiotherapy, if lung dose is the priority.

Simultaneous reduction of number of spots and energy layers in intensity modulated proton therapy for rapid spot scanning delivery

BACKGROUND

Reducing proton treatment time improves patient comfort and decreases the risk of error from intrafractional motion, but must be balanced against clinical goals and treatment plan quality.

PURPOSE

To improve the delivery efficiency of spot scanning proton therapy by simultaneously reducing the number of spots and energy layers using the reweightedl 1 $l_1$ regularization method.

METHODS

We formulated the proton treatment planning problem as a convex optimization problem with a cost function consisting of a dosimetric plan quality term plus a weightedl 1 $l_1$ regularization term. We iteratively solved this problem and adaptively updated the regularization weights to promote the sparsity of both the spots and energy layers. The proposed algorithm was tested on four head-and-neck cancer patients, and its performance, in terms of reducing the number of spots and energy layers, was compared with existing standardl 1 $l_1$ and groupl 2 $l_2$ regularization methods. We also compared the effectiveness of the three methods (l 1 $l_1$ , groupl 2 $l_2$ , and reweightedl 1 $l_1$ ) at improving plan delivery efficiency without compromising dosimetric plan quality by constructing each of their Pareto surfaces charting the trade-off between plan delivery and plan quality.

RESULTS

The reweightedl 1 $l_1$ regularization method reduced the number of spots and energy layers by an average over all patients of40 % $40\%$ and35 % $35\%$ , respectively, with an insignificant cost to dosimetric plan quality. From the Pareto surfaces, it is clear that reweightedl 1 $l_1$ provided a better trade-off between plan delivery efficiency and dosimetric plan quality than standardl 1 $l_1$ or groupl 2 $l_2$ regularization, requiring the lowest cost to quality to achieve any given level of delivery efficiency.

CONCLUSIONS

Reweightedl 1 $l_1$ regularization is a powerful method for simultaneously promoting the sparsity of spots and energy layers at a small cost to dosimetric plan quality. This sparsity reduces the time required for spot scanning and energy layer switching, thereby improving the delivery efficiency of proton plans.

Development of a standalone delivery sequence model for proton arc therapy

BACKGROUND

Spot-scanning proton arc (SPArc) has been drawing significant interests in recent years because of its capability of continuous proton irradiation during the gantry rotation. Previous studies demonstrated SPArc plans were delivered on a prototype of the DynamicARC solution, IBA ProteusONE.

PURPOSE

We built a novel delivery sequence model through an independent experimental approach: the first SPArc delivery sequence model (DSMSPArc). Based on the model, we investigated SPArc treatment efficiency improvement in the routine proton clinical operation.

METHODS

SPArc test plans were generated and delivered on a prototype of the DynamicARC solution, IBA ProteusONE. An independent gantry inclinometer and the machine logfiles were used to derive the DSMSPArc. Seventeen SPArc plans were used to validate the model's accuracy independently. Two random clinical operation dates (6th January and 22nd March, 2021) from a single-room proton therapy center (PTC) were selected to quantitatively assess the improvement of treatment efficiency compared to the IMPT.

RESULTS

The difference between the logfile and DSMSPArc is about 3.2 ± 4.8%. SPArc reduced 58.1% of the average treatment delivery time per patient compared to IMPT (p < 0.01). Daily treatment throughput could be increased by 30% using SPArc using a single-room proton therapy system.

CONCLUSIONS

The first model of dynamic arc therapy is established in this study through an independent experimental approach using logfiles and measurements which allows clinical users and investigators to simulate the dynamic treatment delivery and assess the daily treatment throughput improvement.

SISS-MCO: large scale sparsity-induced spot selection for fast and fully-automated robust multi-criteria optimisation of proton plans

Objective.Intensity modulated proton therapy (IMPT) is an emerging treatment modality for cancer. However, treatment planning for IMPT is labour-intensive and time-consuming. We have developed a novel approach for multi-criteria optimisation (MCO) of robust IMPT plans (SISS-MCO) that is fully automated and fast, and we compare it for head and neck, cervix, and prostate tumours to a previously published method for automated robust MCO (IPBR-MCO, van de Water 2013).Approach.In both auto-planning approaches, the applied automated MCO of spot weights was performed with wish-list driven prioritised optimisation (Breedveld 2012). In SISS-MCO, spot weight MCO was applied once for every patient after sparsity-induced spot selection (SISS) for pre-selection of the most relevant spots from a large input set of candidate spots. IPBR-MCO had several iterations of spot re-sampling, each followed by MCO of the weights of the current spots.Main results.Compared to the published IPBR-MCO, the novel SISS-MCO resulted in similar or slightly superior plan quality. Optimisation times were reduced by a factor of 6 i.e. from 287 to 47 min. Numbers of spots and energy layers in the final plans were similar.Significance.The novel SISS-MCO automatically generated high-quality robust IMPT plans. Compared to a published algorithm for automated robust IMPT planning, optimisation times were reduced on average by a factor of 6. Moreover, SISS-MCO is a large scale approach; this enables optimisation of more complex wish-lists, and novel research opportunities in proton therapy.

A novel planning framework for efficient spot-scanning proton arc therapy via particle swarm optimization (SPArc-particle swarm)

Objective.Delivery efficiency is the bottleneck of spot-scanning proton arc therapy (SPArc) because of the numerous energy layers (ELs) ascending switches. This study aims to develop a new algorithm to mitigate the need for EL ascending via water equivalent thickness (WET) sector selection followed by particle swarm optimization (SPArc-particle swarm).Approach.SPArc-particle swarmdivided the full arc trajectory into the optimal sectors based on K-means clustering analysis of the relative mean WET. Within the sector, particle swarm optimization was used to minimize the total energy switch time, optimizing the energy selection integrated with the EL delivery sequence and relationship. This novel planning framework was implemented on the open-source platform matRad (Department of Medical Physics in Radiation Oncology, German Cancer Research Center-DKFZ). Three representative cases (brain, liver, and prostate cancer) were selected for testing purposes. Two kinds of plans were generated: SPArc_seq and SPArc-particle swarm. The plan quality and delivery efficiency were evaluated.Main results. With a similar plan quality, the delivery efficiency was significantly improved using SPArc-particle swarmcompared to SPArc_seq. More specifically, it reduces the number of ELs ascending switching compared to the SPArc_seq (from 21 to 7 in the brain, from 21 to 5 in the prostate, from 21 to 6 in the liver), leading to a 16%-26% reduction of the beam delivery time (BDT) in the SPArc treatment.Significance. A novel planning framework, SPArc-particle swarm, could significantly improve the delivery efficiency, which paves the roadmap towards routine clinical implementation.

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.

Automation of pencil beam scanning proton treatment planning for intracranial tumours

PURPOSE

To evaluate the feasibility of comprehensive automation of an intra-cranial proton treatment planning.

MATERIALS AND METHODS

Class solution (CS) beam configuration selection allows the user to identify predefined beam configuration based on target localization; automatic CS (aCS) will then explore all the possible CS beam geometries. Ten patients, already used for the evaluation of the automatic selection of the beam configuration, have been also employed to training an algorithm based on the computation of a benchmark dose exploit automatic general planning solution (GPS) optimization with a wish list approach for the planning optimization. An independent cohort of ten patients has been then used for the evaluation step between the clinical and the GPS plan in terms of dosimetric quality of plans and the time needed to generate a plan.

RESULTS

The definition of a beam configuration requires on average 22 min (range 9-29 min). The average time for GPS plan generation is 18 min (range 7-26 min). Median dose differences (GPS-Manual) for each OAR constraints are: brainstem -1.60 Gy, left cochlea -1.22 Gy, right cochlea -1.42 Gy, left eye 0.55 Gy, right eye -2.33 Gy, optic chiasm -1.87 Gy, left optic nerve -4.45 Gy, right optic nerve -2.48 Gy and optic tract -0.31 Gy. Dosimetric CS and aCS plan evaluation shows a slightly worsening of the OARs values except for the optic tract and optic chiasm for both CS and aCS, where better results have been observed.

CONCLUSION

This study has shown the feasibility and implementation of the automatic planning system for intracranial tumors. The method developed in this work is ready to be implemented in a clinical workflow.

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.

Using Artificial Intelligence for Optimization of the Processes and Resource Utilization in Radiotherapy

The radiotherapy (RT) process from planning to treatment delivery is a multistep, complex operation involving numerous levels of human-machine interaction and requiring high precision. These steps are labor-intensive and time-consuming and require meticulous coordination between professionals with diverse expertise. We reviewed and summarized the current status and prospects of artificial intelligence and machine learning relevant to the various steps in RT treatment planning and delivery workflow specifically in low- and middle-income countries (LMICs). We also searched the PubMed database using the search terms (Artificial Intelligence OR Machine Learning OR Deep Learning OR Automation OR knowledge-based planning AND Radiotherapy) AND (list of Low- and Middle-Income Countries as defined by the World Bank at the time of writing this review). The search yielded a total of 90 results, of which results with first authors from the LMICs were chosen. The reference lists of retrieved articles were also reviewed to search for more studies. No language restrictions were imposed. A total of 20 research items with unique study objectives conducted with the aim of enhancing RT processes were examined in detail. Artificial intelligence and machine learning can improve the overall efficiency of RT processes by reducing human intervention, aiding decision making, and efficiently executing lengthy, repetitive tasks. This improvement could permit the radiation oncologist to redistribute resources and focus on responsibilities such as patient counseling, education, and research, especially in resource-constrained LMICs.

Beam properties within the momentum acceptance of a clinical gantry beamline for proton therapy

PURPOSE

Energy changes in Pencil Beam Scanning (PBS) proton therapy can be a limiting factor in delivery time, hence limiting patient throughput and the effectiveness of motion mitigation techniques requiring fast irradiation. In this study, we investigate the feasibility of performing fast and continuous energy modulation within the momentum acceptance of a clinical beamline for proton therapy.

METHODS

The alternative use of a local beam degrader at the gantry coupling point has been compared with a more common upstream regulation. Focusing on clinically relevant parameters, a complete beam properties characterization has been carried out. In particular, the acquired empirical data allowed to model and parametrize the errors in range and beam current to deliver clinical treatment plans.

RESULTS

For both options, the local and the upstream degrader, depth-dose curves measured in water for off-momentum beams were only marginally distorted (γ(1%,1mm) > 90%) and the errors in the spot position were within the clinical tolerance, even though increasing at the boundaries of the investigated scan range. The impact on the beam size was limited for the upstream degrader while dedicated strategies could be required to tackle the beam broadening through the local degrader. Range correction models were investigated for the upstream regulation. The impaired beam transport required a dedicated strategy for fine range control and compensation of beam intensity losses. Our current parametrization based on empirical data allowed energy modulation within acceptance with range errors (median 0.05 mm) and transmission (median -14%) compatible with clinical operation and remarkably low average 27 ms dead time for small energy changes. The technique, tested for the delivery of a skull glioma treatment, resulted in high gamma pass rates at 1%,1mm compared to conventional deliveries in experimental measurements with about 45% reduction of the energy switching time when regulation could be performed within acceptance.

CONCLUSIONS

Fast energy modulation within beamline acceptance has potential for clinical applications and, when realized with an upstream degrader, does not require modification in the beamline hardware, therefore being potentially applicable in any running facility. Centers with slow energy switching time can particularly profit from such a technique for reducing dead time during treatment delivery. This article is protected by copyright. All rights reserved.

A quantitative FLASH effectiveness model to reveal potentials and pitfalls of high dose rate proton therapy

Purpose

In ultrahigh dose rate radiotherapy, the FLASH effect can lead to substantially reduced healthy tissue damage without affecting tumor control. Although many studies show promising results, the underlying biological mechanisms and the relevant delivery parameters are still largely unknown. It is unclear, particularly for scanned proton therapy, how treatment plans could be optimized to maximally exploit this protective FLASH effect.

Materials and Methods

To investigate the potential of pencil beam scanned proton therapy for FLASH treatments, we present a phenomenological model, which is purely based on experimentally observed phenomena such as potential dose rate and dose thresholds, and which estimates the biologically effective dose during FLASH radiotherapy based on several parameters. We applied this model to a wide variety of patient geometries and proton treatment planning scenarios, including transmission and Bragg peak plans as well as single‐ and multifield plans. Moreover, we performed a sensitivity analysis to estimate the importance of each model parameter.

Results

Our results showed an increased plan‐specific FLASH effect for transmission compared with Bragg peak plans (19.7% vs. 4.0%) and for single‐field compared with multifield plans (14.7% vs. 3.7%), typically at the cost of increased integral dose compared to the clinical reference plan. Similar FLASH magnitudes were found across the different treatment sites, whereas the clinical benefits with respect to the clinical reference plan varied strongly. The sensitivity analysis revealed that the threshold dose as well as the dose per fraction strongly impacted the FLASH effect, whereas the persistence time only marginally affected FLASH. An intermediate dependence of the FLASH effect on the dose rate threshold was found.

Conclusions

Our model provided a quantitative measure of the FLASH effect for various delivery and patient scenarios, supporting previous assumptions about potentially promising planning approaches for FLASH proton therapy. Positive clinical benefits compared to clinical plans were achieved using hypofractionated, single‐field transmission plans. The dose threshold was found to be an important factor, which may require more investigation.

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.

Evaluation of alternative parameter settings for dose restoration and full plan adaptation in IMPT for prostate cancer

BACKGROUND/PURPOSE

Intensity-modulated proton therapy is highly sensitive to anatomical variations. A dose restoration method and a full plan adaptation method have been developed earlier, both requiring several parameter settings. This study evaluates the validity of the previously selected settings by systematically comparing them to alternatives.

MATERIALS/METHODS

The dose restoration method takes a prior plan and uses an energy-adaptation followed by a spot-intensity re-optimization to restore the plan to its initial state. The full adaptation method uses an energy-adaptation followed by the addition of new spots and a spot-intensity optimization to fit the new anatomy. We varied: 1) The margins and robustness settings of the prior plan, 2) the spot-addition sample size, i.e. the number of added spots, 3) the spot-addition stopping criterion, and 4) the spot-intensity optimization approach. The last three were evaluated only for the full plan adaptation. Evaluations were done on 88 CT scans of 11 prostate cancer patients. Dose was prescribed as 55 Gy(RBE) to the lymph nodes and seminal vesicles with a boost to 74 Gy(RBE) to the prostate.

RESULTS

For the dose restoration method, changing the applied CTV-to-PTV margins and plan robustness in the prior plans yielded insufficient target coverage or increased OAR doses. For the full plan adaptation, more spot-addition iterations and using a different optimization approach resulted in lower OAR doses compared to the default settings while maintaining target coverage. However, the calculation times increased by up to 20 times, making these variations infeasible for online-adaptation.

CONCLUSION

We recommend maintaining the default setting for the dose restoration approach. For the full plan adaptation we recommend to focus on fine-tuning the optimization-parameters, and apart from this using the default settings.

Impact of a spatially dependent dose delivery time structure on the biological effectiveness of scanning proton therapy

PURPOSE

In the scanning beam delivery of protons, different portions of the target are irradiated with different linear energy transfer protons with various time intervals and irradiation times. This research aimed to evaluate the spatially dependent biological effectiveness of protracted irradiation in scanning proton therapy.

METHODS

One and two parallel opposed fields plans were created in water phantom with the prescribed dose of 2 Gy. Three scenarios (instantaneous, continuous, and layered scans) were used with the corresponding beam delivery models. The biological dose (physical dose × relative biological effectiveness) was calculated using the linear quadratic model and the theory of dual radiation action to quantitatively evaluate the dose delivery time effect. In addition, simulations using clinical plans (postoperative seminoma and prostate tumor cases) were conducted to assess the impact of the effects on the dose volume histogram parameters and homogeneity coefficient (HC) in targets.

RESULTS

In a single-field plan of water phantom, when the treatment time was 19 min, the layered-scan scenario showed a decrease of <0.2% (almost 3.3%) in the biological dose from the plan on the distal (proximal) side because of the high (low) dose rate. This is in contrast to the continuous scenario, where the biological dose was almost uniformly decreased over the target by approximately 3.3%. The simulation with clinical geometry showed that the decrease rates in D_99% were 0.9% and 1.5% for every 10 min of treatment time prolongation for postoperative seminoma and prostate tumor cases, respectively, whereas the increase rates in HC were 0.7% and 0.2%.

CONCLUSIONS

In protracted irradiation in scanning proton therapy, the spatially dependent dose delivery time structure in scanning beam delivery can be an important factor for accurate evaluation of biological effectiveness.

Adaptive proton therapy

Radiation therapy treatments are typically planned based on a single image set, assuming that the patient's anatomy and its position relative to the delivery system remains constant during the course of treatment. Similarly, the prescription dose assumes constant biological dose-response over the treatment course. However, variations can and do occur on multiple time scales. For treatment sites with significant intra-fractional motion, geometric changes happen over seconds or minutes, while biological considerations change over days or weeks. At an intermediate timescale, geometric changes occur between daily treatment fractions. Adaptive radiation therapy is applied to consider changes in patient anatomy during the course of fractionated treatment delivery. While traditionally adaptation has been done off-line with replanning based on new CT images, online treatment adaptation based on on-board imaging has gained momentum in recent years due to advanced imaging techniques combined with treatment delivery systems. Adaptation is particularly important in proton therapy where small changes in patient anatomy can lead to significant dose perturbations due to the dose conformality and finite range of proton beams. This review summarizes the current state-of-the-art of on-line adaptive proton therapy and identifies areas requiring further research.

Linear Energy Transfer Incorporated Spot-Scanning Proton Arc Therapy Optimization: A Feasibility Study

Purpose

To integrate dose-averaged linear energy transfer (LET_d) into spot-scanning proton arc therapy (SPArc) optimization and to explore its feasibility and potential clinical benefits.

Methods

An open-source proton planning platform (OpenREGGUI) has been modified to incorporate LET_d into optimization for both SPArc and multi-beam intensity-modulated proton therapy (IMPT) treatment planning. SPArc and multi-beam IMPT plans with different beam configurations for a prostate patient were generated to investigate the feasibility of LET_d-based optimization using SPArc in terms of spatial LET_d distribution and plan delivery efficiency. One liver and one brain case were studied to further evaluate the advantages of SPArc over multi-beam IMPT.

Results

With similar dose distributions, the efficacy of spatially optimizing LET_d distributions improves with increasing number of beams. Compared with multi-beam IMPT plans, SPArc plans show substantial improvement in LET_d distributions while maintaining similar delivery efficiency. Specifically, for the liver case, the average LET_d in the GTV was increased by 124% for the SPArc plan, and only 9.6% for the 2-beam IMPT plan compared with the 2-beam non-LET_d optimized IMPT plan. In case of LET optimization for the brain case, the SPArc plan could effectively increase the average LET_d in the CTV and decrease the values in the critical structures while smaller improvement was observed in 3-beam IMPT plans.

Conclusion

This work demonstrates the feasibility and significant advantages of using SPArc for LET_d-based optimization, which could maximize the LET_d distribution wherever is desired inside the target and averts the high LET_d away from the adjacent critical organs-at-risk.

Cost-Effectiveness Models of Proton Therapy for Head and Neck: Evaluating Quality and Methods to Date

PURPOSE

Proton beam therapy (PBT) is associated with less toxicity relative to conventional photon radiotherapy for head-and-neck cancer (HNC). Upfront delivery costs are greater, but PBT can provide superior long-term value by minimizing treatment-related complications. Cost-effectiveness models (CEMs) estimate the relative value of novel technologies (such as PBT) as compared with the established standard of care. However, the uncertainties of CEMs can limit interpretation and applicability. This review serves to (1) assess the methodology and quality of pertinent CEMs in the existing literature, (2) evaluate their suitability for guiding clinical and economic strategies, and (3) discuss areas for improvement among future analyses.

MATERIALS AND METHODS

PubMed was queried for CEMs specific to PBT for HNC. General characteristics, modeling information, and methodological approaches were extracted for each identified study. Reporting quality was assessed via the Consolidated Health Economic Evaluation Reporting Standards 24-item checklist, whereas methodologic quality was evaluated via the Philips checklist. The Cooper evidence hierarchy scale was employed to analyze parameter inputs referenced within each model.

RESULTS

At the time of study, only 4 formal CEMs specific to PBT for HNC had been published (2005, 2013, 2018, 2020). The parameter inputs among these various Markov cohort models generally referenced older literature, excluding many clinically relevant complications and applying numerous hypothetical assumptions for toxicity states, incorporating inputs from theoretical complication-probability models because of limited availability of direct clinical evidence. Case numbers among study cohorts were low, and the structural design of some models inadequately reflected the natural history of HNC. Furthermore, cost inputs were incomplete and referenced historic figures.

CONCLUSION

Contemporary CEMs are needed to incorporate modern estimates for toxicity risks and costs associated with PBT delivery, to provide a more accurate estimate of value, and to improve their clinical applicability with respect to PBT for HNC.

Dictionary-based protoacoustic dose map imaging for proton range verification

Proton radiotherapy has the potential to provide state-of-the-art dose conformality in the tumor area, reducing possible adverse effects on surrounding organs at risk. However, uncertainties in the exact location of the proton Bragg peak inside the patient prevent this technique from achieving full clinical potential. In this context, in vivo verification of the range of protons in patients is key to reduce uncertainty margins. Protoacoustic range verification employs acoustic pressure waves generated by protons due to the radio-induced thermoacoustic effect to reconstruct the dose deposited in a patient during proton therapy. In this paper, we propose to use the a priori knowledge of the shape of the proton dose distribution to create a dictionary with the expected ultrasonic signals at predetermined detector locations. Using this dictionary, the reconstruction of deposited dose is performed by matching pre-calculated dictionary acoustic signals with data acquired online during treatment. The dictionary method was evaluated on a single-field proton plan for a prostate cancer patient. Dose calculation was performed with the open-source treatment planning system matRad, while acoustic wave propagation was carried out with k-Wave. We studied the ability of the proposed dictionary method to detect range variations caused by anatomical changes in tissue density, and alterations of lateral and longitudinal beam position. Our results show that the dictionary-based protoacoustic method was able to identify the changes in range originated by all the alterations introduced, with an average accuracy of 1.4 mm. This procedure could be used for in vivo verification, comparing the measured signals with the precalculated dictionary.

A static beam delivery device for fast scanning proton arc-therapy

Arc-therapy is a dose delivery technique regularly applied in photon radiation therapy, and is currently subject of great interest for proton therapy as well. In this technique, proton beams are aimed at a tumor from different continuous ranges of incident directions (so called 'arcs'). This technique can potentially yield a better dose conformity around the tumor and a very low dose in the surrounding healthy tissue. Currently, proton-arc therapy is performed by rotating a proton gantry around the patient, adapting the normally used dose-delivery method to the arc-specific motion of the gantry. Here we present first results from a feasibility study of the conceptual design of a new static fast beam delivery device/system for proton-arc therapy, which could be used instead of a gantry. In this novel concept, the incident angle of proton beams can be set rapidly by only changing field strengths of small magnets. This device eliminates the motion of the heavy gantry and related hardware. Therefore, a reduction of the total treatment time is expected. In the feasibility study presented here, we concentrate on the concept of the beam transport. Based on several simple, but realistic assumptions and approximations, proton tracking calculations were performed in a 3D magnetic field map, to calculate the beam transport in this device and to investigate and address several beam-optics challenges. We propose and simulate corresponding solutions and discuss their outcomes. To enable the implementation of some usually applied techniques in proton therapy, such as pencil beam scanning, energy modulation and beam shaping, we present and discuss our proposals. Here we present the concept of a new idea to perform fast proton arc-scanning and we report on first results of a feasibility study. Based on these results, we propose several options and next steps in the design.

Quantitative analysis of treatments using real-time image gated spot-scanning with synchrotron-based proton beam therapy system log data

A synchrotron-based real-time image gated spot-scanning proton beam therapy (RGPT) system with inserted fiducial markers can irradiate a moving tumor with high accuracy. As gated treatments increase the beam delivery time, this study aimed to investigate the frequency of intra-field adjustments corresponding to the baseline shift or drift and the beam delivery efficiency of a synchrotron-based RGPT system. Data from 118 patients corresponding to 127 treatment plans and 2810 sessions between October 2016 and March 2019 were collected. We quantitatively analyzed the proton beam delivery time, the difference between the ideal beam delivery time based on a simulated synchrotron magnetic excitation pattern and the actual treatment beam delivery time, frequency corresponding to the baseline shift or drift, and the gating efficiency of the synchrotron-based RGPT system according to the proton beam delivery machine log data. The mean actual beam delivery time was 7.1 min, and the simulated beam delivery time in an ideal environment with the same treatment plan was 2.9 min. The average difference between the actual and simulated beam delivery time per session was 4.3 min. The average frequency of intra-field adjustments corresponding to baseline shift or drift and beam delivery efficiency were 21.7% and 61.8%, respectively. Based on our clinical experience with a synchrotron-based RGPT system, we determined the frequency corresponding to baseline shift or drift and the beam delivery efficiency using the beam delivery machine log data. To maintain treatment accuracy within ± 2.0 mm, intra-field adjustments corresponding to baseline shift or drift were required in approximately 20% of cases. Further improvements in beam delivery efficiency may be realized by shortening the beam delivery time.

A novel energy sequence optimization algorithm for efficient spot-scanning proton arc (SPArc) treatment delivery

BACKGROUND

Spot-scanning proton arc therapy (SPArc) has been proposed to improve dosimetric outcome and to simplify treatment workflow. To efficiently deliver a SPArc plan, it's crucial to minimize the number of energy layer switches (ELS) a sending because of the magnetic hysteresis effect. In this study, we introduced a new SPArc energy sequence optimization algorithm (SPArc_seq) to reduce ascended ELS and to investigate its impact on the beam delivery time (BDT).

METHOD AND MATERIALS

An iterative energy layer sorting and re-distribution mechanism following the direction of the gantry rotation was implemented in the original SPArc algorithm (SPArc_orig). Five disease sites, including prostate, lung, brain, head neck cancer (HNC) and breast cancer were selected to evaluate this new algorithm. Dose-volume histogram (DVH) and plan robustness were used to assess the plan quality for both SPArc_seq and SPArc_orig plans. The BDT evaluations were analyzed through two methods: 1. fixed gantry angle delivery (BDT_fixed) and 2. An in-house dynamic arc scanning controller simulation which considered of gantry rotation speed, acceleration and deceleration (BDT_arc).

RESULTS

With a similar total number of energy layers, SPArc_seq plans provided a similar nominal plan quality and plan robustness compared to SPArc_orig plans. SPArc_seq significantly reduced the number of ascended ELS by 83% (19 vs.115), 70% (16 vs. 64), 82% (19 vs. 104), 80% (19 vs. 94) and 70% (9 vs. 30), which effectively shortened the BDT_fixed by 65% (386 vs. 1091 s), 61% (235 vs. 609 s), 64% (336 vs. 928 s), 48% (787 vs.1521 s) and 25% (384 vs. 511 s) and shortened BDT_arc by 54% (522 vs.1128 s), 52% (310 vs.645 s), 53% (443 vs. 951 s), 49% (803 vs.1583 s) and 26% (398 vs. 534 s) in prostate, lung, brain, HNC and breast cancer, respectively.

CONCLUSIONS

The SPArc_seq optimization algorithm could effectively reduce the BDT compared to the original SPArc algorithm. The improved efficiency of the SPArc_seq algorithm has the potential to increase patient throughput, thereby reducing the operation cost of proton therapy.

A scintillator-based range telescope for particle therapy

The commissioning and operation of a particle therapy centre requires an extensive set of detectors for measuring various parameters of the treatment beam. Among the key devices are detectors for beam range quality assurance. In this work, a novel range telescope based on a plastic scintillator and read out by a large-scale CMOS sensor is presented. The detector is made of a stack of 49 plastic scintillator sheets with a thickness of 2-3 mm and an active area of 100 × 100 mm², resulting in a total physical stack thickness of 124.2 mm. This compact design avoids optical artefacts that are common in other scintillation detectors. The range of a proton beam is reconstructed using a novel Bragg curve model that incorporates scintillator quenching effects. Measurements to characterise the performance of the detector were carried out at the Heidelberger Ionenstrahl-Therapiezentrum (HIT, Heidelberg, GER) and the Clatterbridge Cancer Centre (CCC, Bebington, UK). The maximum difference between the measured range and the reference range was found to be 0.41 mm at a proton beam range of 310 mm and was dominated by detector alignment uncertainties. With the new detector prototype, the water-equivalent thickness of PMMA degrader blocks has been reconstructed within ± 0.1 mm. An evaluation of the radiation hardness proves that the range reconstruction algorithm is robust following the deposition of 6,300 Gy peak dose into the detector. Furthermore, small variations in the beam spot size and transverse beam position are shown to have a negligible effect on the range reconstruction accuracy. The potential for range measurements of ion beams is also investigated.

Online-adaptive versus robust IMPT for prostate cancer: How much can we gain?

BACKGROUND/PURPOSE

Intensity-modulated proton therapy (IMPT) is highly sensitive to anatomical variations which can cause inadequate target coverage during treatment. Available mitigation techniques include robust treatment planning and online-adaptive IMPT. This study compares a robust planning strategy to two online-adaptive IMPT strategies to determine the benefit of online adaptation.

MATERIALS/METHODS

We derived the robustness settings and safety margins needed to yield adequate target coverage (V_95%≥98%) for >90% of 11 patients in a prostate cancer cohort (88 repeat CTs). For each patient, we also adapted a non-robust prior plan using a simple restoration and a full adaptation method. The restoration uses energy-adaptation followed by a fast spot-intensity re-optimization. The full adaptation uses energy-adaptation followed by the addition of new spots and a range-robust spot-intensity optimization. Dose was prescribed as 55 Gy(RBE) to the low-dose target (lymph nodes and seminal vesicles) with a boost to 74 Gy(RBE) to the high-dose target (prostate). Daily patient set-up was simulated using implanted intra-prostatic markers.

RESULTS

Margins of 4 and 8 mm around the high- and low-dose target regions, a 6 mm setup error and a 3% range error were found to obtain adequate target coverage for all repeat CTs of 10/11 patients (94.3% of all 88 repeat CTs). Both online-adaptive strategies yielded V_95%≥98% and better OAR sparing in 11/11 patients. Median OAR improvements up to 11%-point and 16%-point were observed when moving from robust planning to respectively restoration and full adaption.

CONCLUSION

Both full plan adaptation and simple dose restoration can increase OAR sparing besides better conforming to the target criteria compared to robust treatment planning.

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.

A novel energy layer optimization framework for spot-scanning proton arc therapy

PURPOSE

Spot-scanning proton arc therapy (SPAT) is an emerging modality to improve plan conformality and delivery efficiency. A greedy and heuristic method is proposed in the existing SPAT algorithm to select energy layers and sequence energy switching with gantry rotation, which does not promise optimality in either dosimetry or efficiency. We aim to develop a method to solve the energy layer switching and dosimetry optimization problems in an integrated framework for SPAT.

METHODS

In an integrated approach, energy layer optimization for spot-scanning proton arc therapy (ELO-SPAT) is formulated with a dose fidelity term, a group sparsity regularization, a log barrier regularization, and an energy sequencing (ES) penalty. The combination of L2,1/2-norm group sparsity regularization and log barrier function allows one energy layer being selected per control point. The ES regularization term sorts the delivery sequence from high energy to low energy to reduce the total energy layer switching time (ELST) and subsequently the total delivery time. Within the ES penalty, the gradient of layer weights between adjacent beams is first calculated along beam direction and then along energy direction. The gradients indicate energy switch patterns between two adjacent beams. The time-wise costly energy switch-up is more heavily penalized in the ES term. This ELO-SPAT method was tested on one frontal base-of-skull (BOS) patient, one chordoma (CHDM) patient with a simultaneous integrated boost, one bilateral head-and-neck (H&N) patient, and one lung (LNG) patient. We compared ELO-SPAT with intensity-modulated proton therapy (IMPT) using discrete beams and SPArc by Ding et al. For the two arc algorithms, both the plans with and without energy sequencing were created and compared.

RESULTS

Energy layer optimization for spot-scanning proton arc therapy reduced the runtime of optimization by 84% on average compared with the greedy SPArc method. In both the ELO-SPAT plans with and without ES, one energy layer per control point was selected. Without ES regularization, the energy sequence was arbitrary, with around 40-60 switch-up for the tested cases. After adding ES regularization, the number of energy switch-up was reduced to less than 20. Compared with the energy sequenced SPArc plans, the ELO-SPAT plans with ES led to 24% less total ELST for synchrotron plans and 14% less for cyclotron plans. Both the ELO-SPAT and SPArc plans achieved better sparing compared with the IMPT plans for most Organs-at-risks (OARs), with or without ES. Without ES, the ELO-SPAT plans achieved further improvement of the OARs compared with the SPArc plans, with an averaged reduction of OAR [Dmean, Dmax] by [1.57, 3.34] GyRBE. Adding the ES regularization degraded the plan quality, but the ELO-SPAT plans still had comparable or slightly better sparing than the SPArc plans with ES, with an averaged reduction of OAR [Dmean, Dmax] by [1.42, 2.34] GyRBE.

CONCLUSION

We developed a computationally efficient spot-scanning proton arc optimization method, which solved energy layer selection and sequencing in an integrated framework, generating plans with good dosimetry and high delivery efficiency.

Plan-library supported automated replanning for online-adaptive intensity-modulated proton therapy of cervical cancer

Background: Intensity-modulated proton therapy is sensitive to inter-fraction variations, including density changes along the pencil-beam paths and variations in organ-shape and location. Large day-to-day variations are seen for cervical cancer patients. The purpose of this study was to develop and evaluate a novel method for online selection of a plan from a patient-specific library of prior plans for different anatomies, and adapt it for the daily anatomy. Material and methods: The patient-specific library of prior plans accounting for altered target geometries was generated using a pretreatment established target motion model. Each fraction, the best fitting prior plan was selected. This prior plan was adapted using (1) a restoration of spot-positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast optimization of the spot-weights with the reference point method (RPM) to obtain a Pareto-optimal plan for the daily anatomy. Spot addition and spot-weight optimization could be repeated iteratively. The patient cohort consisted of six patients with in total 23 repeat-CT scans, with a prescribed dose of 45 Gy(RBE) to the primary tumor and the nodal CTV. Using a 1-plan-library (one prior plan based on all motion in the motion model) was compared to choosing from a 2-plan-library (two prior plans based on part of the motion). Results: Applying the prior-plan adaptation method with one iteration of adding spots resulted in clinically acceptable target coverage ( V95%≥95% and V107%≤2% ) for 37/46 plans using the 1-plan-library and 41/46 plans for the 2-plan-library. When adding spots twice, the 2-plan-library approach could obtain acceptable coverage for all scans, while the 1-plan-library approach showed V107%>2% for 3/46 plans. Similar OAR results were obtained. Conclusion: The automated prior-plan adaptation method can successfully adapt for the large day-to-day variations observed in cervical cancer patients.

Treatment planning for proton therapy: what is needed in the next 10 years?

Treatment planning is the process where the prescription of the radiation oncologist is translated into a deliverable treatment. With the complexity of contemporary radiotherapy, treatment planning cannot be performed without a computerized treatment planning system. Proton therapy (PT) enables highly conformal treatment plans with a minimum of dose to tissues outside the target volume, but to obtain the most optimal plan for the treatment, there are a multitude of parameters that need to be addressed. In this review areas of ongoing improvements and research in the field of PT treatment planning are identified and discussed. The main focus is on issues of immediate clinical and practical relevance to the PT community highlighting the needs for the near future but also in a longer perspective. We anticipate that the manual tasks performed by treatment planners in the future will involve a high degree of computational thinking, as many issues can be solved much better by e.g. scripting. More accurate and faster dose calculation algorithms are needed, automation for contouring and planning is required and practical tools to handle the variable biological efficiency in PT is urgently demanded just to mention a few of the expected improvements over the coming 10 years.

Robust contour propagation using deep learning and image registration for online adaptive proton therapy of prostate cancer

Purpose

To develop and validate a robust and accurate registration pipeline for automatic contour propagation for online adaptive Intensity‐Modulated Proton Therapy (IMPT) of prostate cancer using elastix software and deep learning.

Methods

A three‐dimensional (3D) Convolutional Neural Network was trained for automatic bladder segmentation of the computed tomography (CT) scans. The automatic bladder segmentation alongside the computed tomography (CT) scan is jointly optimized to add explicit knowledge about the underlying anatomy to the registration algorithm. We included three datasets from different institutes and CT manufacturers. The first was used for training and testing the ConvNet, where the second and the third were used for evaluation of the proposed pipeline. The system performance was quantified geometrically using the dice similarity coefficient (DSC), the mean surface distance (MSD), and the 95% Hausdorff distance (HD). The propagated contours were validated clinically through generating the associated IMPT plans and compare it with the IMPT plans based on the manual delineations. Propagated contours were considered clinically acceptable if their treatment plans met the dosimetric coverage constraints on the manual contours.

Results

The bladder segmentation network achieved a DSC of 88% and 82% on the test datasets. The proposed registration pipeline achieved a MSD of 1.29 ± 0.39, 1.48 ± 1.16, and 1.49 ± 0.44 mm for the prostate, seminal vesicles, and lymph nodes, respectively, on the second dataset and a MSD of 2.31 ± 1.92 and 1.76 ± 1.39 mm for the prostate and seminal vesicles on the third dataset. The automatically propagated contours met the dose coverage constraints in 86%, 91%, and 99% of the cases for the prostate, seminal vesicles, and lymph nodes, respectively. A Conservative Success Rate (CSR) of 80% was obtained, compared to 65% when only using intensity‐based registration.

Conclusion

The proposed registration pipeline obtained highly promising results for generating treatment plans adapted to the daily anatomy. With 80% of the automatically generated treatment plans directly usable without manual correction, a substantial improvement in system robustness was reached compared to a previous approach. The proposed method therefore facilitates more precise proton therapy of prostate cancer, potentially leading to fewer treatment‐related adverse side effects.

The first prototype of spot-scanning proton arc treatment delivery

PURPOSE

We report the first prototype of spot-scanning arc treatment (SPArc) delivery on a clinical proton beam therapy machine and evaluate its delivery accuracy and efficiency.

METHODS AND MATERIALS

A new module called Proton Dynamic Arc Delivery (PDAD) was developed to allow simultaneously delivering spot-scanning proton beam treatments while rotating the gantry on an IBA Proteus®One proton machine. A series of measurements was performed to validate the basic beam characteristics. Subsequently, patient specific quality assurance (QA) of a brain SPArc plan was performed. Total SPArc treatment delivery time was also recorded and compared to the clinically delivered intensity modulated proton therapy (IMPT) treatment time. Finally, the log file of the SPArc plan was analyzed and processed to reconstruct the actual delivered dose.

RESULTS

All the basic beam characteristics were confirmed in the PDAD mode, similar as those measured using fixed gantry deliveries in clinical mode. The brain SPArc plan with similar or superior plan quality was delivered in 4 mins compared to total 11 mins for the clinical treatment of the three-field IMPT plan. The patient QA result showed a good agreement between the measured and calculated dose distributions with the gamma index of 98.6% (3%/3 mm). The analysis of the log file confirmed the accuracy of the SPArc plan delivery, with the gamma index of 98.3% (1%/1 mm) between reconstructed and the planned doses.

CONCLUSION

The first prototype of dynamic proton arc delivery on a clinical proton therapy system was successfully performed. The measurements and simulations demonstrated the feasibility of SPArc treatment within the clinical requirements.

Improving dosimetric outcome for hippocampus and cochlea sparing whole brain radiotherapy using spot-scanning proton arc therapy

This feasibility study shows that Spot-scanning Proton Arc therapy (SPArc) is able to significantly reduce the dose to the hippocampus and cochlea compared to both Volumetric Modulated Arc Photon Therapy (VMAT) and the robust optimized Intensity Modulated Proton Therapy (ro-IMPT) plans in whole brain radiotherapy. Furthermore, SPArc not only improves plan robustness but could potentially deliver a treatment as efficient as ro-IMPT when proton system's energy layer switch time is less than 1 s.

Impact of varying planning parameters on proton pencil beam scanning dose distributions in four commercial treatment planning systems

PURPOSE

In pencil beam scanning proton therapy, target coverage is achieved by scanning the pencil beam laterally in the x- and y-directions and delivering spots of dose to positions at a given radiological depth (layer). Dose is delivered to the spots on different layers by pencil beams of different energy until the entire volume has been irradiated. The aim of this study is to investigate the implementation of proton planning parameters (spot spacing, layer spacing and margins) in four commercial proton treatment planning systems (TPSs): Eclipse, Pinnacle3 , RayStation and XiO.

MATERIALS AND METHODS

Using identical beam data in each TPS, plans were created on uniform material synthetic phantoms with cubic targets. The following parameters were systematically varied in each TPS to observe their different implementations: spot spacing, layer spacing and margin. Additionally, plans were created in Eclipse to investigate the impact of these parameters on plan delivery and optimal values are suggested.

RESULTS

It was found that all systems except Eclipse use a variable layer spacing per beam, based on the Bragg peak width of each energy layer. It is recommended that if this cannot be used, then a constant value of 5 mm will ensure good dose homogeneity. Only RayStation varies the spot spacing according to the variable spot size with depth. If a constant spot spacing is to be used, a value of 5 mm is recommended as a good compromise between dose homogeneity, plan robustness and planning time. It was found that both Pinnacle3 and RayStation position spots outside of the defined volume (target plus margin).

CONCLUSIONS

All four systems are capable of delivering uniform dose distributions to simple targets, but their implementation of the various planning parameters is different. In this paper comparisons are made between the four systems and recommendations are made as to the values that will provide the best compromise in dose homogeneity and planning time.

Validation of new 2D ripple filters in proton treatments of spherical geometries and non-small cell lung carcinoma cases

A ripple filter (RiFi) is a passive energy modulator used in scanned particle therapy to broaden the Bragg peak, thus lowering the number of accelerator energies required for homogeneous target coverage, which significantly reduces the irradiation time. As we have previously shown, a new 6 mm thick RiFi with 2D groove shapes produced with 3D printing can be used in carbon ion treatments with a similar target coverage and only a marginally worse planning conformity compared to treatments with in-use 3 mm thick RiFis of an older 1D design. Where RiFis are normally not used with protons due to larger scattering and straggling effects, this new design would be beneficial in proton therapy too. Measurements of proton Bragg curves and lateral beam profiles were carried out for different RiFi designs and thicknesses as well as for no RiFi at the Heidelberg Ionenstrahl-Therapiezentrum. Base data for proton treatment planning were generated with the Monte Carlo code SHIELD-HIT12A with and without the 2D 6 mm RiFi. Plans on spherical targets in water were calculated with TRiP98 for a systematic RiFi performance analysis and for comparisons with carbon ion plans for the same respective energy depth step sizes. Plans for 9 stage I static non small cell lung cancer patients were calculated with Eclipse 13.7.15. Dose-volume-histograms, spatial dose distributions and dosimetric indexes were used for plan evaluation. Measurements confirm the functionality of the new 2D RiFi design, which reduces the beam spot size compared to 1D RiFis of the same thickness. Planning studies show that a 6 mm thick 2D RiFi could be used in proton therapy to lower the irradiation time. Although slightly worse planning conformity and dose homogeneity were found for plans with the RiFi compared to plans without, satisfactory results within the planning objective were obtained for all cases.

Advanced Treatment Planning

Treatment planning for protons and heavier ions is adapting technologies originally developed for photon dose optimization, but also has to meet its particular challenges. Since the quality of the applied dose is more sensitive to geometric uncertainties, treatment plan robust optimization has a much more prominent role in particle therapy. This has led to specific planning tools, approaches, and research into new formulations of the robust optimization problems. Tools for solution space navigation and automatic planning are also being adapted to particle therapy. These challenges become even greater when detailed models of relative biological effectiveness (RBE) are included into dose optimization, as is required for heavier ions.

Energy layer optimization strategies for intensity-modulated proton therapy of lung cancer patients

PURPOSE

When treating lung cancer patients with intensity-modulated proton therapy (IMPT), target coverage can only be guaranteed when utilizing motion mitigation. The three motion mitigation techniques, gating, breath-hold, and dose repainting, all benefit from a more rapid application of the treatment plan. A lower limit for the ungated treatment time is defined by the number of energy layers in the IMPT plan. By limiting this number during treatment planning, IMPT could become more viable for lung cancer patients. We investigate to what extend the number of layers can be reduced in single-field optimization (SFO) and multifield optimization (MFO) plans and which implications it has on the plan quality and robustness.

METHODS

We have implemented three distinct layer-reducing strategies in the treatment planning system Hyperion; constant energy steps, exponential energy steps, and an adaptive strategy, where the spot weights are exposed to a group sparsity penalty in combination with layer exclusion during optimization. Four levels of increasing layer removal are planned for each strategy. SFO and MFO plans with three treatment fields are created for eleven locally advanced NSCLC patients on the midventilation 4DCT phase to simulate a breath-hold. A minimum dose to the target is ensured for each degree of layer reduction, reflecting the plan quality in the homogeneity index (HI). Plan quality was also assessed by a robustness evaluation, where the patient setup was shifted 2 mm or 4 mm in six directions.

RESULTS

The three strategies result in very similar target coverages and robustness levels as a function of removed layers. The HI increases unacceptably for all the SFO plans after 50% layer removal as compared to the reference plan, while all the MFO plans are clinically acceptable with up to a highest removed percentage of 75%. The robustness level is constant as a function of removed layers. The SFO plans are significantly more robust than the MFO plans with all P-values below 0.001 (Wilcoxon signed-rank). The overall mean D98% CTV dose difference is at 2-mm setup error amplitude: 0.7 Gy (SFO) and 1.9 Gy (MFO), and at 4 mm: 3.2 Gy (SFO) and 5.4 Gy (MFO), respectively.

CONCLUSIONS

The number of layers in MFO plans can be reduced substantially more than in SFO plans without compromising plan quality. Furthermore, as the robustness is independent of the number of layers, it follows that if the level of robustness is acceptable or enforced via robust optimization, MFO plans could be candidates for treatment time reductions via energy layer reductions.

An automated planning strategy for near real-time adaptive proton therapy in prostate cancer

Proton therapy plans are very sensitive to anatomical changes such as density changes along the pencil-beam paths and changes in organ shape and location. Previously, we developed a restoration method which compensates for density changes along the pencil-beam paths but which is unable to adapt for anatomical changes. This study's purpose is to develop and evaluate an automated method for adaptation of IMPT plans in near real-time to the anatomy of the day. We developed an automated treatment plan adaptation method using (1) a restoration of spot positions (Bragg peaks) by adapting the energies to the new water equivalent path lengths; and (2) a spot addition to fully cover the target of the day, followed by a fast reference point method optimization of the spot weights resulting in a Pareto optimal plan for the daily anatomy. The method was developed and evaluated using 8-10 repeat CT scans of 11 prostate cancer patients, prescribing 55 Gy(RBE) (seminal vesicles and lymph nodes) with a boost to 74 Gy(RBE) (prostate). Applying the automated adaptation method resulted in a clinically acceptable target coverage (V _95% [Formula: see text] 98% and V _107% [Formula: see text] 2%) for 96% of the scans after a single iteration of adding 2500 spots. The other scans obtained target coverages with V _95% [Formula: see text] 98% and 2  <  V _107% [Formula: see text] 5%. When using two spot-addition iterations, all scans obtained clinically acceptable results. Compared to the restoration method the adaptation lowered the mean dose to rectum and bladder with median values of 6.2 Gy(RBE) and 4.7 Gy(RBE) respectively. The largest improvements were obtained for V _45Gy(RBE) for both rectum and bladder, with median differences of 10.3%-point and 10.8%-point respectively, and maximum differences up to 22%-point. The two adaptation steps took on average 7.3 s and 1.7 min respectively. No user interaction was needed, making this fast and fully automated method a first step towards online adaptive proton therapy.

Anatomical robust optimization to account for nasal cavity filling variation during intensity-modulated proton therapy: a comparison with conventional and adaptive planning strategies

The aim of this study is to develop an anatomical robust optimization method for intensity-modulated proton therapy (IMPT) that accounts for interfraction variations in nasal cavity filling, and to compare it with conventional single-field uniform dose (SFUD) optimization and online plan adaptation. We included CT data of five patients with tumors in the sinonasal region. Using the planning CT, we generated for each patient 25 'synthetic' CTs with varying nasal cavity filling. The robust optimization method available in our treatment planning system 'Erasmus-iCycle' was extended to also account for anatomical uncertainties by including (synthetic) CTs with varying patient anatomy as error scenarios in the inverse optimization. For each patient, we generated treatment plans using anatomical robust optimization and, for benchmarking, using SFUD optimization and online plan adaptation. Clinical target volume (CTV) and organ-at-risk (OAR) doses were assessed by recalculating the treatment plans on the synthetic CTs, evaluating dose distributions individually and accumulated over an entire fractionated 50 Gy_RBE treatment, assuming each synthetic CT to correspond to a 2 Gy_RBE fraction. Treatment plans were also evaluated using actual repeat CTs. Anatomical robust optimization resulted in adequate CTV doses (V_95%  ⩾  98% and V_107%  ⩽  2%) if at least three synthetic CTs were included in addition to the planning CT. These CTV requirements were also fulfilled for online plan adaptation, but not for the SFUD approach, even when applying a margin of 5 mm. Compared with anatomical robust optimization, OAR dose parameters for the accumulated dose distributions were on average 5.9 Gy_RBE (20%) higher when using SFUD optimization and on average 3.6 Gy_RBE (18%) lower for online plan adaptation. In conclusion, anatomical robust optimization effectively accounted for changes in nasal cavity filling during IMPT, providing substantially improved CTV and OAR doses compared with conventional SFUD optimization. OAR doses can be further reduced by using online plan adaptation.

Data for TROTS - The Radiotherapy Optimisation Test Set

The Radiotherapy Optimisation Test Set (TROTS) is an extensive set of problems originating from radiotherapy (radiation therapy) treatment planning. This dataset is created for 2 purposes: (1) to supply a large-scale dense dataset to measure performance and quality of mathematical solvers, and (2) to supply a dataset to investigate the multi-criteria optimisation and decision-making nature of the radiotherapy problem. The dataset contains 120 problems (patients), divided over 6 different treatment protocols/tumour types. Each problem contains numerical data, a configuration for the optimisation problem, and data required to visualise and interpret the results. The data is stored as HDF5 compatible Matlab files, and includes scripts to work with the dataset.

Dual-Energy CT in Head and Neck Imaging

PURPOSE OF REVIEW

To explain the technique of Dual-energy CT (DECT) and highlight its applications and advantages in head and neck radiology.

RECENT FINDINGS

Using DECT, additional datasets can be created next to conventional images. In head and neck radiology, three material decomposition algorithms can be used for improved lesion detection and delineation of the tumor. Iodine concentration measurements can aid in differentiating malignant from nonmalignant lymph nodes and benign posttreatment changes from tumor recurrence. Virtual non-calcium images can be used for detection of bone marrow edema. Virtual mono-energetic imaging can be useful for improved iodine conspicuity at lower keV and for reduction of metallic artifacts and increase in signal-to-noise ratio at higher keV.

SUMMARY

DECT and its additional reconstructions can play an important role in head and neck cancer patients, from initial diagnosis and staging, to therapy planning, evaluation of treatment response and follow-up. Moreover, it can be helpful in imaging of infections and inflammation and parathyroid imaging as supplementary reconstructions can be obtained at lower or equal radiation dose compared with conventional single energy scanning.

Spot-Scanning Proton Arc (SPArc) Therapy: The First Robust and Delivery-Efficient Spot-Scanning Proton Arc Therapy

PURPOSE

To present a novel robust and delivery-efficient spot-scanning proton arc (SPArc) therapy technique.

METHODS AND MATERIALS

A SPArc optimization algorithm was developed that integrates control point resampling, energy layer redistribution, energy layer filtration, and energy layer resampling. The feasibility of such a technique was evaluated using sample patients: 1 patient with locally advanced head and neck oropharyngeal cancer with bilateral lymph node coverage, and 1 with a nonmobile lung cancer. Plan quality, robustness, and total estimated delivery time were compared with the robust optimized multifield step-and-shoot arc plan without SPArc optimization (Arc_multi-field) and the standard robust optimized intensity modulated proton therapy (IMPT) plan. Dose-volume histograms of target and organs at risk were analyzed, taking into account the setup and range uncertainties. Total delivery time was calculated on the basis of a 360° gantry room with 1 revolutions per minute gantry rotation speed, 2-millisecond spot switching time, 1-nA beam current, 0.01 minimum spot monitor unit, and energy layer switching time of 0.5 to 4 seconds.

RESULTS

The SPArc plan showed potential dosimetric advantages for both clinical sample cases. Compared with IMPT, SPArc delivered 8% and 14% less integral dose for oropharyngeal and lung cancer cases, respectively. Furthermore, evaluating the lung cancer plan compared with IMPT, it was evident that the maximum skin dose, the mean lung dose, and the maximum dose to ribs were reduced by 60%, 15%, and 35%, respectively, whereas the conformity index was improved from 7.6 (IMPT) to 4.0 (SPArc). The total treatment delivery time for lung and oropharyngeal cancer patients was reduced by 55% to 60% and 56% to 67%, respectively, when compared with Arc_multi-field plans.

CONCLUSION

The SPArc plan is the first robust and delivery-efficient proton spot-scanning arc therapy technique, which could potentially be implemented into routine clinical practice.

Which cervical and endometrial cancer patients will benefit most from intensity-modulated proton therapy?

In this dosimetric comparison study it was shown that IMPT with robust planning reduces dose to surrounding organs in cervical and endometrial cancer treatment compared with IMRT. Especially for the para-aortic region, clinically relevant dose reductions were obtained for kidneys, spinal cord and bowel, justifying the use of proton therapy for this indication.