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.

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.

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.

The first investigation of spot-scanning proton arc (SPArc) delivery time and accuracy with different delivery tolerance window settings.

Objective. To investigate the impact of various delivery tolerance window settings on the treatment delivery time and dosimetric accuracy of spot-scanning proton arc (SPArc) therapy.Approach. SPArc plans were generated for three representative disease sites (brain, lung, and liver cancer) with an angle sampling frequency of 2.5°. An in-house dynamic arc controller was used to simulate the arc treatment delivery with various tolerance windows (±0.25, ±0.5, ±1, and ±1.25°). The controller generates virtual logfiles during the arc delivery simulation, such as gantry speed, acceleration and deceleration, spot position, and delivery sequence, similar to machine logfiles. The virtual logfile was then imported to the treatment planning system to reconstruct the delivered dose distribution and compare it to the initial SPArc nominal plan. A three-dimensional gamma index was used to quantitatively assess delivery accuracy. Total treatment delivery time and relative lost time (dynamic arc delivery time-fix beam delivery time)/fix beam delivery time) were reported.Main Results. The 3D gamma passing rate (GPR) was greater than 99% for all cases when using 3%/3 mm and 2%/2 mm criteria and the GPR (1%/1 mm criteria) degraded as the tolerance window opens. The total delivery time for dynamic arc delivery increased with the decreasing delivery tolerance window length. The average delivery time and the relative lost time (%) were 630 ± 212 s (253% ± 68%), 322 ± 101 s (81% ± 31%), 225 ± 60 s (27% ± 16%), 196 ± 41 s (11% ± 6%), 187 ± 29 s (6% ± 1%) for tolerance windows ±0.25, ±0.5, ±1, and ±1.25° respectively.Significance. The study quantitatively analyzed the dynamic SPArc delivery time and accuracy with different delivery tolerance window settings, which offer a critical reference in the future SPArc plan optimization and delivery controller design.

A Novel Ultrahigh-Dose-Rate Proton Therapy Technology: Spot-Scanning Proton Arc Therapy + FLASH (SPLASH).

PURPOSE: To take full advantage of FLASH dose rate (40 Gy/s) and high-dose conformity, we introduce a novel optimization and delivery technique, the spot-scanning proton arc therapy (SPArc) + FLASH (SPLASH). METHODS AND MATERIALS: SPLASH framework was implemented in an open-source proton planning platform (MatRad, Department of Medical Physics in Radiation Oncology, German Cancer Research Center). It optimizes with the clinical dose-volume constraint based on dose distribution and the dose-average dose rate by minimizing the monitor unit constraint on spot weight and accelerator beam current sequentially, enabling the first dynamic arc therapy with voxel-based FLASH dose rate. This new optimization framework minimizes the overall cost function value combined with plan quality and voxel-based dose-rate constraints. Three representative cases (brain, liver, and prostate cancer) were used for testing purposes. Dose-volume histogram, dose-rate-volume histogram, and dose-rate map were compared among intensity modulated proton radiation therapy (IMPT), SPArc, and SPLASH. RESULTS: SPLASH/SPArc could offer superior plan quality over IMPT in terms of dose conformity. The dose-rate-volume histogram results indicated SPLASH could significantly improve V40 Gy/s in the target and region of interest for all tested cases compared with SPArc and IMPT. The optimal beam current per spot is simultaneously generated, which is within the existing proton machine specifications in the research version (<200 nA). CONCLUSIONS: SPLASH offers the first voxel-based ultradose-rate and high-dose conformity treatment using proton beam therapy. Such a technique has the potential to fit the needs of a broad range of disease sites and simplify clinical workflow without applying a patient-specific ridge filter, which has never before been demonstrated.

Ultra-fast, high spatial resolution single-pulse scintillation imaging of synchrocyclotron pencil beam scanning proton delivery.

Objective.To demonstrates the ability of an ultra-fast imaging system to measure high resolution spatial and temporal beam characteristics of a synchrocyclotron proton pencil beam scanning (PBS) system.Approach.An ultra-fast (1 kHz frame rate), intensified CMOS camera was triggered by a scintillation sheet coupled to a remote trigger unit for beam on detection. The camera was calibrated using the linear (R2> 0.9922) dose response of a single spot beam to varying currents. Film taken for the single spot beam was used to produce a scintillation intensity to absolute dose calibration.Main results. Spatial alignment was confirmed with the film, where thexandy-profiles of the single spot cumulative image agreed within 1 mm. A sample brain patient plan was analyzed to demonstrate dose and temporal accuracy for a clinically-relevant plan, through agreement within 1 mm to the planned and delivered spot locations. The cumulative dose agreed with the planned dose with a gamma passing rate of 97.5% (2 mm/3%, 10% dose threshold).Significance. This is the first system able to capture single-pulse spatial and temporal information for the unique pulse structure of a synchrocyclotron PBS systems at conventional dose rates, enabled by the ultra-fast sampling frame rate of this camera. This study indicates that, with continued camera development and testing, target applications in clinical and FLASH proton beam characterization and validation are possible.

Introduce a rotational robust optimization framework for spot-scanning proton arc (SPArc) therapy.

Objective. Proton dosimetric uncertainties resulting from the patient's daily setup errors in rotational directions exist even with advanced image-guided radiotherapy techniques. Thus, we developed a new rotational robust optimization SPArc algorithm (SPArcrot) to mitigate the dosimetric impact of the rotational setup error in Raystation ver. 6.02 (RaySearch Laboratory AB, Stockholm, Sweden).Approach.The initial planning CT was rotated ±5° simulating the worst-case setup error in the roll direction. The SPArcrotuses a multi-CT robust optimization framework by taking into account of such rotational setup errors. Five cases representing different disease sites were evaluated. Both SPArcoriginaland SPArcrotplans were generated using the same translational robust optimized parameters. To quantitatively investigate the mitigation effect from the rotational setup errors, all plans were recalculated using a series of pseudo-CT with rotational setup error (±1°/±2°/±3°/±5°). Dosimetric metrics such as D98% of CTV, and 3D gamma analysis were used to assess the dose distribution changes in the target and OARs.Main results.The magnitudes of dosimetric changes in the targets due to rotational setup error were significantly reduced by the SPArcrotcompared to SPArc in all cases. The uncertainties of the max dose to the OARs, such as brainstem, spinal cord and esophagus were significantly reduced using SPArcrot. The uncertainties of the mean dose to the OARs such as liver and oral cavity, parotid were comparable between the two planning techniques. The gamma passing rate (3%/3 mm) was significantly improved for CTV of all tumor sites through SPArcrot.Significance.Rotational setup error is one of the major issues which could lead to significant dose perturbations. SPArcrotplanning approach can consider such rotational error from patient setup or gantry rotation error by effectively mitigating the dose uncertainties to the target and in the adjunct series OARs.

Bi-criteria Pareto optimization to balance irradiation time and dosimetric objectives in proton arc therapy.

Objective. Proton arc therapy (PAT) is a new delivery technique that exploits the continuous rotation of the gantry to distribute the therapeutic dose over many angular windows instead of using a few static fields, as in conventional (intensity-modulated) proton therapy. Although coming along with many potential clinical and dosimetric benefits, PAT has also raised a new optimization challenge. In addition to the dosimetric goals, the beam delivery time (BDT) needs to be considered in the objective function. Considering this bi-objective formulation, the task of finding a good compromise with appropriate weighting factors can turn out to be cumbersome.Approach. We have computed Pareto-optimal plans for three disease sites: a brain, a lung, and a liver, following a method of iteratively choosing weight vectors to approximate the Pareto front with few points. Mixed-integer programming (MIP) was selected to state the bi-criteria PAT problem and to find Pareto optimal points with a suited solver.Main results. The trade-offs between plan quality and beam irradiation time (staticBDT) are investigated by inspecting three plans from the Pareto front. The latter are carefully picked to demonstrate significant differences in dose distribution and delivery time depending on their location on the frontier. The results were benchmarked against IMPT and SPArc plans showing the strength of degrees of freedom coming along with MIP optimization.Significance. This paper presents for the first time the application of bi-criteria optimization to the PAT problem, which eventually permits the planners to select the best treatment strategy according to the patient conditions and clinical resources available.

Treatment planning in arc proton therapy: Comparison of several optimization problem statements and their corresponding solvers.

Arc proton therapy (ArcPT) is an emerging modality in cancer treatments. It delivers the proton beams following a sequence of irradiation angles while the gantry is continuously rotating around the patient. Compared to conventional proton treatments (intensity modulated proton therapy, IMPT), the number of beams is significantly increased bringing new degrees of freedom that leads to potentially better cancer care. However, the optimization of such treatment plans becomes more complex and several alternative statements of the problem can be considered and compared in order to solve the ArcPT problem. Three such problem statements, distinct in their mathematical formulation and properties, are investigated and applied to solving the ArcPT optimization problem. They make use of (i) fast iterative shrinkage-thresholding algorithm (FISTA), (ii) local search (LS) and (iii) mixed-integer programming (MIP). The treatment plans obtained with those methods are compared among them, but also with IMPT and an existing state-of-the-art method: Spot-Scanning Proton Arc (SPArc). MIP stands out at low scale problems both in terms of dose quality and time delivery efficiency. FISTA shows high dose quality but experiences difficulty to optimize the energy sequence while LS is mostly the antagonist. This detailed study describes independent approaches to solve the ArcPT problem and depending on the clinical case, one should be cautiously picked rather than the other. This paper gives the first formal definition of the problem at stake, as well as a first reference benchmark. Finally, empirical conclusions are drawn, based on realistic assumptions.

An evolutionary optimization algorithm for proton arc therapy.

Objective. Proton arc plan normally contains thousands of spot numbers and hundreds of energy layers. A recent study reported that the beam delivery time (BDT) is proportional to the spot numbers. Thus, it is critical to find an optimal plan with a fast delivery speed while maintaining a good plan quality. Thus, we developed a novel evolutionary algorithm to directly search for the optimal spot sparsity solution to balance plan quality and BDT.Approach. The planning platform included a plan quality objective, a generator, and a selector. The generator is based on trust-region-reflective solver. A selector was designed to filter or add the spot according to the expected spot number, based on the user's input of BDT. The generator and selector are used alternatively to optimize a spot sparsity solution. Three clinical cases' CT and structure datasets, e.g. brain, lung, and liver cancer, were used for testing purposes. A series of user-defined BDTs from 15 to 250 s were used as direct inputs. The relationship between the plan's cost function value and BDT was evaluated in these three cases.Main results. The evolutionary algorithm could optimize a proton arc plan based on clinical user input BDT directly. The plan quality remains optimal in the brain, lung, and liver cases until the BDT was shorter than 25 s, 50 s and 100 s, respectively. The plan quality degraded as the input delivery time became too short, indicating that the plan lacked enough spot or degree of freedom.Significance. This is the first proton arc planning framework to directly optimize plan quality with the BDT as an input for the new generation of proton therapy systems. This work paved the roadmap for implementing such new technology in a routine clinic and provided a planning platform to explore the trade-off between the BDT and plan quality.

Redefine the Role of Spot-Scanning Proton Beam Therapy for the Single Brain Metastasis Stereotactic Radiosurgery.

Purpose: To explore the role of using Pencil Beam Scanning (PBS) proton beam therapy in single lesion brain stereotactic radiosurgery (SRS), we developed and validated a dosimetric in silico model to assist in the selection of an optimal treatment approach among the conventional Volumetric Modulated Arc Therapy (VMAT), Intensity Modulated Proton Therapy (IMPT) and Spot-scanning Proton Arc (SPArc). Material and Methods: A patient's head CT data set was used as an in silico model. A series of targets (volume range from 0.3 cc to 33.03 cc) were inserted in the deep central and peripheral region, simulating targets with different sizes and locations. Three planning groups: IMPT, VMAT, and SPArc were created for dosimetric comparison purposes and a decision tree was built based on this in silico model. Nine patients with single brain metastases were retrospectively selected for validation. Multiple dosimetric metrics were analyzed to assess the plan quality, such as dose Conformity Index (CI) (ratio of the target volume to 100% prescription isodose volume); R50 (ratio of 50% prescription isodose volume to the target volume); V12Gy (volume of brain tissue minus GTV receiving 12 Gy), and mean dose of the normal brain. Normal tissue complication probability (NTCP) of brain radionecrosis (RN) was calculated using the Lyman-Kutcher-Burman (LKB) model and total treatment delivery time was calculated. Six physicians from different institutions participated in the blind survey to evaluate the plan quality and rank their choices. Results: The study showed that SPArc has a dosimetric advantage in the V12Gy and R50 with target volumes > 9.00 cc compared to VMAT and IMPT. A significant clinical benefit can be found in deep centrally located lesions larger than 20.00 cc using SPArc because of the superior dose conformity and mean dose reduction in healthy brain tissue. Nine retrospective clinical cases and the blind survey showed good agreement with the in silico dosimetric model and decision tree. Additionally, SPArc significantly reduced the treatment delivery time compared to VMAT (SPArc 184.46 ± 59.51s vs. VMAT: 1574.78 ± 213.65s). Conclusion: The study demonstrated the feasibility of using Proton beam therapy for single brain metastasis patients utilizing the SPArc technique. At the current stage of technological development, VMAT remains the current standard modality of choice for single lesion brain SRS. The in silico dosimetric model and decision tree presented here could be used as a practical clinical decision tool to assist the selection of the optimal treatment modality among VMAT, IMPT, and SPArc in centers that have both photon and proton capabilities.

Developing an accurate model of spot-scanning treatment delivery time and sequence for a compact superconducting synchrocyclotron proton therapy system.

BACKGROUND: A new compact superconducting synchrocyclotron single-room proton solution delivers pulsed proton beams to each spot through several irradiation bursts calculated by an iterative layer delivery algorithm. Such a mechanism results in a new beam parameter, burst switching time (BST) in the total beam delivery time (BDT) which has never been studied before. In this study, we propose an experimental approach to build an accurate BDT and sequence prediction model for this new proton solution. METHODS: Test fields and clinical treatment plans were used to investigate each beam delivery parameter that impacted BDT. The machine delivery log files were retrospectively analyzed to quantitatively model energy layer switching time (ELST), spot switching time (SSWT), spot spill time (SSPT), and BST. A total of 102 clinical IMPT treatment fields' log files were processed to validate the accuracy of the BDT prediction model in comparison with the result from the current commercial system. Interplay effect is also investigated as a clinical application by comparing this new delivery system model with a conventional cyclotron accelerator model. RESULTS: The study finds that BST depends on the amount of data to be transmitted between two sequential radiation bursts, including a machine irradiation log file of the previous burst and a command file to instruct the proton system to deliver the next burst. The 102 clinical treatment fields showed that the accuracy of each component of the BDT matches well between machine log files and BDT prediction model. More specifically, the difference of ELST, SSWT, SSPT, and BST were (- 3.1 ± 5.7)%, (5.9 ± 3.9)%, (2.6 ± 8.7)%, and (- 2.3 ± 5.3)%, respectively. The average total BDT was about (2.1 ± 3.0)% difference compared to the treatment log files, which was significantly improved from the current commercial proton system prediction (58 ± 15)%. Compared to the conventional cyclotron system, the burst technique from synchrocyclotron effectively reduced the interplay effect in mobile tumor treatment. CONCLUSION: An accurate BDT and sequence prediction model was established for this new clinical compact superconducting synchrocyclotron single-room proton solution. Its application could help users of similar facilities better assess the interplay effect and estimate daily patient treatment throughput.

Building a precise machine-specific time structure of the spot and energy delivery model for a cyclotron-based proton therapy system.

Objective. We proposed an experimental approach to build a precise machine-specific beam delivery time (BDT) prediction and delivery sequence model for standard, volumetric, and layer repainting delivery based on a cyclotron accelerator system.Approach. Test fields and clinical treatment plans' log files were used to experimentally derive three main beam delivery parameters that impacted BDT: energy layer switching time (ELST), spot switching time, and spot drill time. This derived machine-specific model includes standard, volumetric, and layer repainting delivery sequences. A total of 103 clinical treatment fields were used to validate the model.Main results. The study found that ELST is not stochastic in this specific machine. Instead, it is actually the data transmission time or energy selection time, whichever takes longer. The validation showed that the accuracy of each component of the BDT matches well between machine log files and the model's prediction. The average total BDT was about (-0.74 ± 3.33)% difference compared to the actual treatment log files, which is improved from the current commercial proton therapy system's prediction (67.22%±26.19%).Significance. An accurate BDT prediction and delivery sequence model was established for an cyclotron-based proton therapy system IBA ProteusPLUS®. Most institutions could adopt this method to build a machine-specific model for their own proton system.

Lung Stereotactic Body Radiotherapy (SBRT) Using Spot-Scanning Proton Arc (SPArc) Therapy: A Feasibility Study.

PURPOSE: We developed a 4D interplay effect model to quantitatively evaluate breathing-induced interplay effects and assess the feasibility of utilizing spot-scanning proton arc (SPArc) therapy for hypo-fractionated lung stereotactic body radiotherapy (SBRT). The model was then validated by retrospective application to clinical cases. MATERIALS AND METHODS: A digital lung 4DCT phantoms was used to mimic targets in diameter of 3cm with breathing motion amplitudes: 5, 10, 15, and 20 mm, respectively. Two planning groups based on robust optimization were generated: (1) Two-field Intensity Modulated Proton Therapy (IMPT) plans and (2) SPArc plans via a partial arc. 5,000 cGy relative biological effectiveness (RBE) was prescribed to the internal target volume (ITV) in five fractions. To quantitatively assess the breathing induced interplay effect, the 4D dynamic dose was calculated by synchronizing the breathing pattern with the simulated proton machine delivery sequence, including IMPT, Volumetric repainting (IMPTvolumetric), iso-layered repainting (IMPTlayer) and SPArc. Ten lung patients' 4DCT previously treated with VMAT SBRT, were used to validate the digital lung tumor model. Normal tissue complicated probability (NTCP) of chestwall toxicity was calculated. RESULT: Target dose were degraded as the tumor motion amplitude increased. The 4D interplay effect phantom model indicated that motion mitigation effectiveness using SPArc was about five times of IMPTvolumetric or IMPTlayer using maximum MU/spot as 0.5 MU at 20 mm motion amplitude. The retrospective study showed that SPArc has an advantage in normal tissue sparing. The probability of chestwall's toxicity were significantly improved from 40.2 ± 29.0% (VMAT) (p = 0.01) and 16.3 ± 12.0% (IMPT) (p = 0.01) to 10.1 ± 5.4% (SPArc). SPArc could play a significant role in the interplay effect mitigation with breathing-induced motion more than 20 mm, where the target D99 of 4D dynamic dose for patient #10 was improved from 4,514 ± 138 cGy [RBE] (IMPT) vs. 4,755 ± 129 cGy [RBE] (SPArc) (p = 0.01). CONCLUSION: SPArc effectively mitigated the interplay effect for proton lung SBRT compared to IMPT with repainting and was associated with normal tissue sparing. This technology may make delivery of proton SBRT more technically feasible and less complex with fewer concerns over underdosing the target compared to other proton therapy techniques.

Feasibility study: spot-scanning proton arc therapy (SPArc) for left-sided whole breast radiotherapy.

BACKGROUND: This study investigated the feasibility and potential clinical benefit of utilizing a new proton treatment technique: Spot-scanning proton arc (SPArc) therapy for left-sided whole breast radiotherapy (WBRT) to further reduce radiation dose to healthy tissue and mitigate the probability of normal tissue complications compared to conventional intensity modulated proton therapy (IMPT). METHODS: Eight patients diagnosed with left-sided breast cancer and treated with breast-preserving surgery followed by whole breast irradiation without regional nodal irradiation were included in this retrospective planning. Two proton treatment plans were generated for each patient: vertical intensity-modulated proton therapy used for clinical treatment (vIMPT, gantry angle 10°-30°) and SPArc for comparison purpose. Both SPArc and vIMPT plans were optimized using the robust optimization of ± 3.5% range and 5 mm setup uncertainties. Root-mean-square deviation dose (RMSD) volume histograms were used for plan robustness evaluation. All dosimetric results were evaluated based on dose-volume histograms (DVH), and the interplay effect was evaluated based on the accumulation of single-fraction 4D dynamic dose on CT50. The treatment beam delivery time was simulated based on a gantry rotation with energy-layer-switching-time (ELST) from 0.2 to 5 s. RESULTS: The average D1 to the heart and LAD were reduced to 53.63 cGy and 82.25 cGy compared with vIMPT 110.38 cGy (p = 0.001) and 170.38 cGy (p = 0.001), respectively. The average V5Gy and V20Gy of ipsilateral lung was reduced to 16.77% and 3.07% compared to vIMPT 25.56% (p = 0.001) and 4.68% (p = 0.003). Skin3mm mean and maximum dose were reduced to 3999.38 cGy and 4395.63 cGy compared to vIMPT 4104.25 cGy (p = 0.039) and 4411.63 cGy (p = 0.043), respectively. A significant relative risk reduction (RNTCP = NTCPSPArc/NTCPvIMPT) for organs at risk (OARs) was obtained with SPArc ranging from 0.61 to 0.86 depending on the clinical endpoint. The RMSD volume histogram (RVH) analysis shows SPArc provided better plan robustness in OARs sparing, including the heart, LAD, ipsilateral lung, and skin. The average estimated treatment beam delivery times were comparable to vIMPT plans when the ELST is about 0.5 s. CONCLUSION: SPArc technique can further reduce dose delivered to OARs and the probability of normal tissue complications in patients treated for left-sided WBRT.

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.