Lin, Liyong

Abstract Background Standardizing beam modeling in the treatment planning system is challenging due to machine‐specific configuration variations. Because of the proton therapy system (PTS) complexity and continuous development, there is no vendor's representative (“golden”) beam data like in LINACs at this stage. Purpose The primary goal of this study is to create a PTS‐specific repository of source model parameters and beam commissioning data for scanning proton therapy treatment planning systems and establish a set of reference values with associated bands of variations for this data. Methods We conducted a survey of 31 PTSs at 27 proton therapy centers to gather beam commissioning source model parameters used in their treatment planning system, ensuring a diverse selection of PTSs from major vendors: Hitachi, IBA, Varian, and Mevion. For each proton therapy center, we collected (i) beam meterset calibration in protons per MU, (ii) in‐air spot size at isocenter in terms of standard deviation in x‐ (crossline, σ x ) and y‐ (inline, σ y ) directions, (iii) in‐air angular spread at isocenter in x‐direction (θ x ) and y‐direction (θ y ) and (iv) distal falloff. For each PTS, we plotted each parameter as a function of nominal energy and performed polynomial regression analysis with optimal model selection based on Akaike Information Criterion. We calculated intraclass correlation coefficients (ICC) to quantify inter‐PTS variability and generated uncertainty bands representing standard deviations across PTSs for each parameter. Additionally, we computed percentage deviations of each individual PTS from the overall multi‐vendor mean to identify systematic vendor‐specific patterns and outliers across the 31 total PTSs analyzed. Results Multi‐vendor beam parameter analysis across 31 PTSs revealed systematic vendor‐specific patterns in inter‐PTS consistency and energy dependencies. Beam meterset calibration demonstrated excellent inter‐PTS consistency across most vendors (ICC: Varian ProBeam ≈ 0, IBA Proteus ONE = 0.006, Mevion S250i with HYPERSCAN = 0.015), with IBA Proteus PLUS systems showing moderate variation (ICC = 0.156 for the dedicated nozzle, ICC = 0.248, for the universal nozzle). Spot size and angular spread variability were highly vendor‐dependent, ranging from excellent consistency in IBA Proteus ONE to substantial variation in IBA Proteus PLUS with the universal nozzle (angular spread ICC = 0.566). Distal falloff maintained excellent consistency across all vendors (ICC < 0.023), indicating reliable energy spread characteristics. Uncertainty band analysis revealed characteristic energy‐dependent patterns, with most systems showing larger uncertainties at lower energies for spot size and angular spread, while IBA Proteus PLUS with the universal nozzle exhibited the largest uncertainty bands overall. Percentage deviation analysis demonstrated vendor‐specific clustering patterns, with some systems showing systematic positive or negative deviations from the multi‐vendor mean. Conclusions The reference data provided in this work will help to cross‐check the beam model during treatment planning system commissioning. Furthermore, this information is useful for Monte Carlo applications and research, where beam characteristics are required to set up phase space parameters, thereby avoiding the need to model the entire PTS. Finally, the results of this study will have indispensable educational value by providing valuable insights into the characteristics and capabilities of different PTSs.

Background/Objectives: Proton therapy delivers highly conformal doses to the target area without producing an exit dose, minimizing cumulative doses to healthy liver tissue. This study aims to evaluate current practices, challenges, and variations in the implementation of proton stereotactic body radiation therapy (SBRT) and hypofractionated therapy for liver malignancies, with the goal of providing a technical assessment to promote broader adoption and support future clinical trials. Methods and Materials: An extensive survey was conducted by NRG Oncology across North American proton treatment centers to assess the current practices of proton liver SBRT and hypofractionated therapy. The survey focused on key aspects, including patient selection, prescription and normal tissue constraints, simulation and motion management, treatment planning, quality assurance (QA), treatment delivery, and the use of image-guided radiation therapy (IGRT). Results: This survey captures the current practice patterns and status of proton SBRT and hypofractionated therapy in liver cancer treatment. Proton therapy is increasingly preferred for treating inoperable liver malignancies due to its ability to minimize healthy tissue exposure. However, the precision required for proton therapy presents challenges, particularly in managing uncertainties and target motion during high-dose fractions and short treatment courses. Survey findings revealed significant variability in clinical practices across centers, highlighting differences in motion management, dose fractionation schedules, and QA protocols. Conclusion: Proton SBRT and hypofractionated therapy offer significant potential for treating liver malignancies. A comprehensive approach involving precise patient selection, treatment planning, and QA is essential for ensuring safety and effectiveness. This survey provides valuable insights into current practices and challenges, offering a foundation for technical recommendations to optimize the use of proton therapy and guide future clinical trials.

AbstractPurposeThe 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.MethodsA 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.ResultsThe 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.ConclusionThe 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.

AbstractPurposeMetallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images.MethodsThe proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours.ResultsFor in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm3for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm3, respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm3for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt–chromium alloys by different vendors.ConclusionsA component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof‐of‐concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head‐and‐neck patients where tight margins are required to spare organs at risk.

Abstract Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

PurposeTo commission an open source Monte Carlo (MC) dose engine, “MCsquare” for a synchrotron‐based proton machine, integrate it into our in‐house C++‐based I/O user interface and our web‐based software platform, expand its functionalities, and improve calculation efficiency for intensity‐modulated proton therapy (IMPT).MethodsWe commissioned MCsquare using a double Gaussian beam model based on in‐air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread‐out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++‐based dose calculation code and web‐based second check platform “DOSeCHECK.” We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well‐benchmarked GPU‐accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)‐related model‐dependent biological dose calculation.ResultsDifferences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients’ geometries using an inexpensive CPU workstation (Intel Xeon E5‐2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.ConclusionsMCsquare was successfully commissioned for a synchrotron‐based proton beam therapy delivery system and integrated into our web‐based second check platform. After adopting CT resampling and implementing LET model‐dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo‐based and LET‐guided robust optimization in IMPT, which will be done in the future studies.

BACKGROUNDExisting data supporting the use of proton‐beam therapy (PBT) for limited‐stage small cell lung cancer (LS‐SCLC) are limited to a single 6‐patient case series. This is the first prospective study to evaluate clinical outcomes and toxicities of PBT for LS‐SCLC.METHODSThis study prospectively analyzed patients with primary, nonrecurrent LS‐SCLC definitively treated with PBT and concurrent chemotherapy from 2011 to 2016. Clinical backup intensity‐modulated radiotherapy (IMRT) plans were generated for each patient and were compared with PBT plans. Outcome measures included local control (LC), recurrence‐free survival (RFS), and overall survival (OS) rates and toxicities.RESULTSThirty consecutive patients were enrolled and evaluated. The median dose was 63.9 cobalt gray equivalents (range, 45‐66.6 cobalt gray equivalents) in 33 to 37 fractions delivered daily (n = 18 [60.0%]) or twice daily (n = 12 [40.0%]). The concurrent chemotherapy was cisplatin/etoposide (n = 21 [70.0%]) or carboplatin/etoposide (n = 9 [30.0%]). In comparison with the backup IMRT plans, PBT allowed statistically significant reductions in the cord, heart, and lung mean doses and the volume receiving at least 5 Gy but not in the esophagus mean dose or the lung volume receiving at least 20 Gy. At a median follow‐up of 14 months, the 1‐/2‐year LC and RFS rates were 85%/69% and 63%/42%, respectively. The median OS was 28.2 months, and the 1‐/2‐year OS rates were 72%/58%. There was 1 case each (3.3%) of grade 3 or higher esophagitis, pneumonitis, anorexia, and pericardial effusion. Grade 2 pneumonitis and esophagitis were seen in 10.0% and 43.3% of patients, respectively.CONCLUSIONSIn the first prospective registry study and largest analysis to date of PBT for LS‐SCLC, PBT was found to be safe with a limited incidence of high‐grade toxicities. Cancer 2017;123:4244–4251. © 2017 American Cancer Society.

Because treatment planning systems (TPSs) generally do not provide monitor units (MUs) for double‐scattered proton plans, models to predict MUs as a function of the range and the nominal modulation width requested of the beam delivery system, such as the one developed by the MGH group, have been proposed. For a given nominal modulation width, however, the measured modulation width depends on the accuracy of the vendor's calibration process and may differ from this nominal value, and also from one beamline to the next. Although such a difference can be replicated in our TPS, the output dependence on range and modulation width for each beam option or suboption has to be modeled separately for each beamline in order to achieve maximal 3% inaccuracy. As a consequence, the MGH output model may not be directly transferable. This work, therefore, serves to extend the model to more general clinic situations. In this paper, a parameterized linear‐quadratic transformation is introduced to convert the nominal modulation width to the measured modulation width for each beam option or suboption on a per‐beamline basis. Fit parameters are derived for each beamline from measurements of 60 reference beams spanning the minimum and maximum ranges, and modulation widths from 2 cm to full range per option or suboption. Using the modeled modulation width, we extract the MGH parameters for the output dependence on range and modulation width. Our method has been tested with 1784 patient‐specific fields delivered across three different beamlines at our facility. For these fields, all measured outputs fall within 3%, and 64.4% fall within 1%, of our model. Using a parameterized linear‐quadratic modulation width, MU calculation models can be established on a per‐beamline basis for each double scattering beam option or suboption.PACS number: 87.53.Qc