Explore the feasibility of using spot-scanning proton arc therapy for a synchrotron accelerator-based proton therapy system - A simulation study.

OBJECTIVE: The aim of this study was to evaluate the feasibility and plan quality of spot-scanning proton arc therapy (SPArc) using a synchrotron-accelerator-based proton therapy system compared to intensity-modulated proton therapy (IMPT). APPROACH: Five representative disease sites, including head and neck, lung, liver, brain chordoma, and prostate cancers, were retrospectively selected. Both IMPT and SPArc plans are generated with the HITACHI ProBEAT PBS system's minimum MU constraints and physics beam model. The SPArc plans are generated with 2.5° sampling frequency. The static delivery time was simulated based on the previously published synchrotron delivery sequence model, and the dynamic delivery time was simulated using a proton arc gantry mechanical model integrated with the synchrotron delivery sequence. Both dosimetric plan quality and delivery efficiency are evaluated. MAIN RESULTS: A superior plan quality is reached compared with the IMPT plans generated for the same disease site. However, a relatively prolonged static and dynamic delivery time post new challenge, as static time increased by 49.22% and dynamic time 59.10% on average. SIGNIFICANCE: This study presents the first simulation results of delivering the SPArc plans using a synchrotron-accelerated proton therapy system. The result shows its feasibility and limitations, which could guide future development.

Time structures of proton pencil beam scanning delivery on a microsecond scale measured with a pixelated semiconductor detector Timepix3.

PURPOSE: The time structures of proton spot delivery in proton pencil beam scanning (PBS) radiation therapy are essential in many clinical applications. This study aims to characterize the time structures of proton PBS delivered by both synchrotron and synchrocyclotron accelerators using a non-invasive technique based on scattered particle tracking. METHODS: A pixelated semiconductor detector, AdvaPIX-Timepix3, with a temporal resolution of 1.56 ns, was employed to measure time of arrival of secondary particles generated by a proton beam. The detector was placed laterally to the high-flux area of the beam in order to allow for single particle detection and not interfere with the treatment. The detector recorded counts of radiation events, their deposited energy and the timestamp associated with the single events. Individual recorded events and their temporal characteristics were used to analyze beam time structures, including energy layer switch time, magnet switch time, spot switch time, and the scanning speeds in the x and y directions. All the measurements were repeated 30 times on three dates, reducing statistical uncertainty. RESULTS: The uncertainty of the measured energy layer switch times, magnet switch time, and the spot switch time were all within 1% of average values. The scanning speeds uncertainties were within 1.5% and are more precise than previously reported results. The measurements also revealed continuous sub-milliseconds proton spills at a low dose rate for the synchrotron accelerator and radiofrequency pulses at 7 µs and 1 ms repetition time for the synchrocyclotron accelerator. CONCLUSION: The AdvaPIX-Timepix3 detector can be used to directly measure and monitor time structures on microseconds scale of the PBS proton beam delivery. This method yielded results with high precision and is completely independent of the machine log files.

MR-based synthetic CT image for intensity-modulated proton treatment planning of nasopharyngeal carcinoma patients.

PURPOSE: To develop an advanced deep convolutional neural network (DCNN) architecture to generate synthetic CT (SCT) images from MR images for intensity-modulated proton therapy (IMPT) treatment planning of nasopharyngeal cancer (NPC) patients. METHODS: T1-weighted MR images and paired CT (PCT) images were obtained from 206 NPC patients. For each patient, deformable image registration was performed between MR and PCT images to create an MR-CT image pair. Thirty pairs were randomly chosen as the independent test set and the remaining 176 pairs (14 for validation and 162 for training) were used to build two conditional generative adversarial networks (GANs): 1) GAN3D: using a 3D U-net enhanced with residual connections and attentional mechanism as the generator and 2) GAN2D: using a 2D U-net as the generator. For each test patient, SCT images were generated using the generators with the MR images as input and were compared with respect to the corresponding PCT image. A clinical IMPT plan was created and optimized on the PCT image. The dose was recalculated on the SCT images and compared with the one calculated on the PCT image. RESULTS: The mean absolute errors (MAEs) between the PCT and SCT, within the body, were (64.89 ± 5.31) HU and (64.31 ± 4.61) HU for the GAN2D and GAN3D. Within the high-density bone (HU > 600), the GAN3D achieved a smaller MAE compared with the GAN2D (p < 0.001). Within the body, the absolute point dose deviation was reduced from (0.58 ± 1.61) Gy for the GAN2D to (0.47 ± 0.94) Gy for the GAN3D. The (3 mm/3%) gamma passing rates were above 97.32% for all SCT images. CONCLUSIONS: The SCT images generated using GANs achieved clinical acceptable dosimetric accuracy for IMPT of NPC patients. Using advanced DCNN architecture design, such as residual connections and attention mechanism, SCT image quality was further improved and resulted in a small dosimetric improvement.

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 (BDTfixed) and 2. An in-house dynamic arc scanning controller simulation which considered of gantry rotation speed, acceleration and deceleration (BDTarc). 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 BDTfixed 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 BDTarc 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.

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.

Proton therapy in adjuvant treatment of gastric cancer: planning comparison with advanced x-ray therapy and feasibility report.

BACKGROUND: Adjuvant chemoradiotherapy improves both overall- and relapse-free survival in patients with resected gastric cancer. However, this comes at the cost of increased treatment-related toxicity. Proton therapy (PT) has distinct dosimetric characteristics that may reduce dose to normal tissues, improving the therapeutic ratio. The purpose of this treatment planning study is to compare PT and intensity-modulated x-ray therapy (IMXT) in gastric cancer with regards to normal tissue sparing. MATERIAL AND METHODS: The patient population consisted of resected gastric cancer patients treated at a single institution between 2008 and 2013. Patients who had undergone 4D CT simulation were replanned to the originally delivered doses (45-54 Gy in 25-30 daily fractions) using six-field photon IMXT and 2-3-field PT (double scattering-uniform scanning techniques). RESULTS: Thirteen patients were eligible for the planning comparison. IMXT provided slightly higher homogeneity indices (median values 0.04 ± 0.01 vs. 0.07 ± 0.01, p = 0.03). PT resulted in significantly (p < 0.05) lower intermediate-low doses for all the normal tissues examined (small bowel V15 82 ml vs. 133 ml, liver mean doses Gy 11.9 vs. 14.4 Gy, left/right kidney mean doses 5/0.9 Gy vs. 7.8/3.1 Gy, heart mean doses 7.4 Gy vs. 9.5 Gy). The total energy deposited outside the target volume was significantly lower with PT (median integral dose 90.1 J vs. 129 J). Four patients were treated with PT: treatment was feasible and verifications scans showed that target coverage was robust. CONCLUSION: PT can contribute to normal tissue sparing in the adjuvant treatment of gastric cancer, with a potential benefit in terms of compliance to treatment, acute and late toxicities.

The first investigation of the dosimetric perturbations from the spot position errors in spot-scanning arc therapy (SPArc).

Objective. To quantitatively investigate the impact of spot position error (PE) on the dose distribution in (Spot-scanning arc therapy) SPArc plans compared to Intensity-Modulated Proton Therapy (IMPT).Approach.Twelve representative cases, including brain, lung, liver, and prostate cancers, were retrospectively selected. Spot PEs were simulated during dynamic SPArc treatment delivery. Two types of errors were generated, including random error and systematic error. Two different probability distributions of random errors were used (1) Gaussian distribution (PEran-GS) (2) uniform distribution (PEran-UN). In PEran-UN, four sub-scenarios were considered: 25%, 50%, 75%, and 100% spots were randomly selected in various directions on the scale of 0-1 mm or 0-2 mm of PE. Additionally, systematic error was simulated by shifting all the spot uniformly by 1 or 2 mm in various directions (PEsys). Gamma-index Passing Rate (GPR) is applied to assess the dosimetric perturbation quantitatively.Main results.For PEran-GSin the 1 mm scenario, both SPArc and IMPT are comparable with a GPR exceeding 99%. However, for PEran-GSin 2 mm scenario, SPArc could provide better GPR. As PEsysof 2 mm, SPArc plans have a much better GPR compared to IMPT plans: SPArc's GPR is 99.59 ± 0.47%, 93.82 ± 4.07% and 64.58 ± 15.83% for 3 mm/3%, 2 mm/2% and 1 mm/1% criteria compared to IMPT with 97.49 ± 2.44%, 84.59 ± 4.99% and 42.02 ± 6.31%.Significance.Compared to IMPT, SPArc shows better dosimetric robustness in spot PEs. This study presents the first simulation results and the methodology that serves as a reference to guide future investigations into the accuracy and quality assurance of SPArc treatment delivery.

Impact of and interplay between proton arc therapy and range uncertainties in proton therapy for head-and-neck cancer.

Objective. Proton therapy reduces the integral dose to the patient compared to conventional photon treatments. However,in vivoproton range uncertainties remain a considerable hurdle. Range uncertainty reduction benefits depend on clinical practices. During intensity-modulated proton therapy (IMPT), the target is irradiated from only a few directions, but proton arc therapy (PAT), for which the target is irradiated from dozens of angles, may see clinical implementation by the time considerable range uncertainty reductions are achieved. It is therefore crucial to determine the impact of PAT on range uncertainty reduction benefits.Approach. For twenty head-and-neck cancer patients, four different treatment plans were created: an IMPT and a PAT treatment plan assuming current clinical range uncertainties of 3.5% (IMPT3.5%and PAT3.5%), and an IMPT and a PAT treatment plan assuming that range uncertainties can be reduced to 1% (IMPT1%and PAT1%). Plans were evaluated with respect to target coverage and organ-at-risk doses as well as normal tissue complication probabilities (NTCPs) for parotid glands (endpoint: parotid gland flow <25%) and larynx (endpoint: larynx edema).Main results. Implementation of PAT (IMPT3.5%-PAT3.5%) reduced mean NTCPs in the nominal and worst-case scenario by 3.2 percentage points (pp) and 4.2 pp, respectively. Reducing range uncertainties from 3.5% to 1% during use of IMPT (IMPT3.5%-IMPT1%) reduced evaluated NTCPs by 0.9 pp and 2.0 pp. Benefits of range uncertainty reductions subsequently to PAT implementation (PAT3.5%-PAT1%) were 0.2 pp and 1.0 pp, with considerably higher benefits in bilateral compared to unilateral cases.Significance. The mean clinical benefit of implementing PAT was more than twice as high as the benefit of a 3.5%-1% range uncertainty reduction. Range uncertainty reductions are expected to remain beneficial even after PAT implementation, especially in cases with target positions allowing for full leveraging of the higher number of gantry angles during PAT.

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.

First direct machine-specific parameters incorporated in Spot-scanning Proton Arc (SPArc) optimization algorithm.

BACKGROUND: Spot-scanning Proton Arc (SPArc) has been of significant interest in recent years because of its superior plan quality. Currently, the primary focus of research and development is on deliverability and treatment efficiency. PURPOSE: To address the challenges in generating a deliverable and efficient SPArc plan for a proton therapy system with a massive gantry, we developed a novel SPArc optimization algorithm (SPArcDMPO) by directly incorporating the machine-specific parameters such as gantry mechanical constraints and proton delivery sequence. METHODS: SPArc delivery sequence model (DSMarc) was built based on the machine-specific parameters of the prototype arc delivery system, IBA ProteusONE®, including mechanical constraint (maximum gantry speed, acceleration, and deceleration) and proton delivery sequence (energy and spot delivery sequence, and irradiation time). SPArcDMPO resamples and adjusts each control point's delivery speed based on the DSMarc calculation through the iterative approach. In SPArcDMPO, users could set a reasonable arc delivery time during the plan optimization, which aims to minimize the gantry momentum changes and improve the delivery efficiency. Ten cases were selected to test SPArcDMPO. Two kinds of SPArc plans were generated using the same planning objective functions: (1) original SPArc plan (SPArcoriginal); (2) SPArcDMPO plan with a user-pre-defined delivery time. Additionally, arc delivery sequence was simulated based on the DSMarc and was compared. Treatment delivery time was compared between SPArcoriginal and SPArcDMPO. Dynamic arc delivery time, the static irradiation time, and its corresponding time differential (time differential = dynamic arc delivery time-static irradiation time) were analyzed, respectively. The total gantry velocity change was accumulated throughout the treatment delivery. RESULTS: With a similar plan quality, objective value, number of energy layers, and spots, both SPArcoriginal and SPArcDMPO plans could be delivered continuously within the ± 1 degree tolerance window. However, compared to the SPArcoriginal, the strategy of SPArcDMPO is able to reduce the time differential from 30.55 ± 11.42%(90 ± 32 s) to 14.67 ± 6.97%(42 ± 20 s), p < 0.01. Furthermore, the corresponding total variations of gantry velocity during dynamic arc delivery are mitigated (SPArcoriginal vs. SPArcDMPO) from 14.73 ± 9.14 degree/s to 4.28 ± 2.42 degree/s, p < 0.01. Consequently, the SPArcDMPO plans could minimize the gantry momentum change based on the clinical user's input compared to the SPArcoriginal plans, which could help relieve the mechanical challenge of accelerating or decelerating the massive proton gantry. CONCLUSIONS: For the first time, clinical users not only could generate a SPArc plan meeting the mechanical constraint of their proton system but also directly control the arc treatment speed and momentum changes of the gantry during the plan optimization process. This work paved the way for the routine clinical implementation of proton arc therapy in the treatment planning system.

Dosimetric comparison of IMPT vs VMAT for multiple lung lesions: an NTCP model-based decision-making strategy.

To compare the dosimetric differences in volumetric modulated arc therapy (VMAT) and intensity modulated proton therapy (IMPT) in stereotactic body radiation therapy (SBRT) of multiple lung lesions and determine a normal tissue complication probability (NTCP) model-based decision strategy that determines which treatment modality the patient will use. A total of 41 patients were retrospectively selected for this study. The number of patients with 1-6 lesions was 5, 16, 7, 6, 3, and 4, respectively. A prescription dose of 70 GyRBE in 10 fractions was given to each lesion. SBRT plans were generated using VMAT and IMPT. All the IMPT plans used robustness optimization with ± 3.5% range uncertainties and 5 mm setup uncertainties. Dosimetric metrics and the predicted NTCP value of radiation pneumonitis (RP), esophagitis, and pericarditis were analyzed to evaluate the potential clinical benefits between different planning groups. In addition, a threshold for the ratio of PTV to lungs (%) to determine whether a patient would benefit highly from IMPT was determined using receiver operating characteristic curves. All plans reached target coverage (V70GyRBE ≥ 95%). Compared with VMAT, IMPT resulted in a significantly lower dose of most thoracic normal tissues. For the 1-2, 3-4 and 5-6 lesion groups, the lung V5 was 29.90 ± 9.44%, 58.33 ± 13.35%, and 81.02 ± 5.91% for VMAT and 11.34 ± 3.11% (p < 0.001), 21.45 ± 3.80% (p < 0.001), and 32.48 ± 4.90% (p < 0.001) for IMPT, respectively. The lung V20 was 12.07 ± 4.94%, 25.57 ± 6.54%, and 43.99 ± 11.83% for VMAT and 6.76 ± 1.80% (p < 0.001), 13.14 ± 2.27% (p < 0.01), and 19.62 ± 3.48% (p < 0.01) for IMPT. The Dmean of the total lung was 7.65 ± 2.47 GyRBE, 14.78 ± 2.75 GyRBE, and 21.64 ± 4.07 GyRBE for VMAT and 3.69 ± 1.04 GyRBE (p < 0.001), 7.13 ± 1.41 GyRBE (p < 0.001), and 10.69 ± 1.81 GyRBE (p < 0.001) for IMPT. Additionally, in the VMAT group, the maximum NTCP value of radiation pneumonitis was 73.91%, whereas it was significantly lower in the IMPT group at 10.73%. The accuracy of our NTCP model-based decision model, which combines the number of lesions and PTV/Lungs (%), was 97.6%. The study demonstrated that the IMPT SBRT for multiple lung lesions had satisfactory dosimetry results, even when the number of lesions reached 6. The NTCP model-based decision strategy presented in our study could serve as an effective tool in clinical practice, aiding in the selection of the optimal treatment modality between VMAT and IMPT.

Optimizing linear energy transfer distribution in intensity-modulated proton therapy using the alternating direction method of multipliers.

Purpose: This study develop a novel linear energy transfer (LET) optimization method for intensity-modulated proton therapy (IMPT) with minimum monitor unit (MMU) constraint using the alternating direction method of multipliers (ADMM). Material and methods: The novel LET optimization method (ADMM-LET) was proposed with (1) the dose objective and the LET objective as the optimization objective and (2) the non-convex MMU threshold as a constraint condition. ADMM was used to solve the optimization problem. In the ADMM-LET framework, the optimization process entails iteratively solving the dose sub-problem and the LET sub-problem, simultaneously ensuring compliance with the MMU constraint. Three representative cases, including brain, liver, and prostate cancer, were utilized to evaluate the performance of the proposed method. The dose and LET distributions from ADMM-LET were compared to those obtained using the published iterative convex relaxation (ICR-LET) method. Results: The results demonstrate the superiority of ADMM-LET over ICR-LET in terms of LET distribution while achieving a comparable dose distribution. More specifically, for the brain case, the maximum LET (unit: keV/µm) at the optic nerve decreased from 5.45 (ICR-LET) to 1.97 (ADMM-LET). For the liver case, the mean LET (unit: keV/µm) at the clinical target volume increased from 4.98 (ICR-LET) to 5.50 (ADMM-LET). For the prostate case, the mean LET (unit: keV/µm) at the rectum decreased from 2.65 (ICR-LET) to 2.14 (ADMM-LET). Conclusion: This study establishes ADMM-LET as a new approach for LET optimization with the MMU constraint in IMPT, offering potential improvements in treatment outcomes and biological effects.

A novel fast robust optimization algorithm for intensity-modulated proton therapy with minimum monitor unit constraint.

BACKGROUND: Intensity-modulated proton therapy (IMPT) optimizes spot intensities and position, providing better conformability. However, the successful application of IMPT is dependent upon addressing the challenges posed by range and setup uncertainties. In order to address the uncertainties in IMPT, robust optimization is essential. PURPOSE: This study aims to develop a novel fast algorithm for robust optimization of IMPT with minimum monitor unit (MU) constraint. METHODS AND MATERIALS: The study formulates a robust optimization problem and proposes a novel, fast algorithm based on the alternating direction method of multipliers (ADMM) framework. This algorithm enables distributed computation and parallel processing. Ten clinical cases were used as test scenarios to evaluate the performance of the proposed approach. The robust optimization method (RBO-NEW) was compared with plans that only consider nominal optimization using CTV (NMO-CTV) without handling uncertainties and PTV (NMO-PTV) to handle the uncertainties, as well as with conventional robust-optimized plans (RBO-CONV). Dosimetric metrics, including D95, homogeneity index, and Dmean, were used to evaluate the dose distribution quality. The area under the root-mean-square dose (RMSD)-volume histogram curves (AUC) and dose-volume histogram (DVH) bands were used to evaluate the robustness of the treatment plan. Optimization time cost was also assessed to measure computational efficiency. RESULTS: The results demonstrated that the RBO plans exhibited better plan quality and robustness than the NMO plans, with RBO-NEW showing superior computational efficiency and plan quality compared to RBO-CONV. Specifically, statistical analysis results indicated that RBO-NEW was able to reduce the computational time from 389.70 ± 207.40 $389.70\pm 207.40$ to 228.60 ± 123.67 $228.60\pm 123.67$ s ( p < 0.01 $p<0.01$ ) and reduce the mean organ-at-risk (OAR) dose from 9.38 ± 12.80 $9.38\pm 12.80$ % of the prescription dose to 9.07 ± 12.39 $9.07\pm 12.39$ % of the prescription dose ( p < 0.05 $p<0.05$ ) compared to RBO-CONV. CONCLUSION: This study introduces a novel fast robust optimization algorithm for IMPT treatment planning with minimum MU constraint. Such an algorithm is not only able to enhance the plan's robustness and computational efficiency without compromising OAR sparing but also able to improve treatment plan quality and reliability.

Particle arc therapy: Status and potential.

There is a rising interest in developing and utilizing arc delivery techniques with charged particle beams, e.g., proton, carbon or other ions, for clinical implementation. In this work, perspectives from the European Society for Radiotherapy and Oncology (ESTRO) 2022 physics workshop on particle arc therapy are reported. This outlook provides an outline and prospective vision for the path forward to clinically deliverable proton, carbon, and other ion arc treatments. Through the collaboration among industry, academic, and clinical research and development, the scientific landscape and outlook for particle arc therapy are presented here to help our community understand the physics, radiobiology, and clinical principles. The work is presented in three main sections: (i) treatment planning, (ii) treatment delivery, and (iii) clinical outlook.