A standardized commissioning framework of Monte Carlo dose calculation algorithms for proton pencil beam scanning treatment planning systems.

PURPOSE Treatment planning systems (TPSs) from different vendors can involve different implementations of Monte Carlo dose calculation (MCDC) algorithms for pencil beam scanning (PBS) proton therapy. There are currently no guidelines for validating non-water materials in TPSs. Furthermore, PBS-specific parameters can vary by 1-2 orders of magnitude among different treatment delivery systems (TDSs). This paper proposes a standardized framework on the use of commissioning data and steps to validate TDS-specific parameters and TPS-specific heterogeneity modeling to potentially reduce these uncertainties. METHODS A standardized commissioning framework was developed to commission the MCDC algorithms of RayStation 8A and Eclipse AcurosPT v13.7.20 using water and non-water materials. Measurements included Bragg peak depth-dose and lateral spot profiles and scanning field outputs for Varian ProBeam. The phase-space parameters were obtained from in-air measurements and the number of protons per MU from output measurements of 10x10 cm2 square fields at a 2 cm depth. Spot profiles and various PBS field measurements at additional depths were used to validate TPS. Human tissues in TPS, Gammex phantom materials, and artificial materials were used for the TPS benchmark and validation. RESULTS The maximum differences of phase parameters, spot sigma, and divergence between MCDC algorithms are below 4.5 µm and 0.26 mrad in air, respectively. Comparing TPS to measurements at depths, both MC algorithms predict the spot sigma within 0.5 mm uncertainty intervals, the resolution of the measurement device. Beam Configuration in AcurosPT is found to underestimate numbers of protons per MU by ~2.5% and requires user adjustment to match measured data, while RayStation is within 1% of measurements using Auto model. A solid water phantom was used to validate the range accuracy of non-water materials within 1% in AcurosPT. CONCLUSION The proposed standardized commissioning framework can detect potential issues during PBS TPS MCDC commissioning processes, and potentially can shorten commissioning time and improve dosimetric accuracies. Secondary MCDC can be used to identify the root sources of disagreement between primary MCDC and measurement.

[1]  J. Wood,et al.  The chemical composition of fat tissues in the pig: Effects of castration and feeding treatment , 1986 .

[2]  Liyong Lin,et al.  A novel technique for measuring the low-dose envelope of pencil-beam scanning spot profiles , 2013, Physics in medicine and biology.

[3]  Timothy D. Solberg,et al.  A benchmarking method to evaluate the accuracy of a commercial proton monte carlo pencil beam scanning treatment planning system , 2017, Journal of applied clinical medical physics.

[4]  K Parodi,et al.  A Monte Carlo-based treatment planning tool for proton therapy , 2013, Physics in medicine and biology.

[5]  E. Pedroni,et al.  The calibration of CT Hounsfield units for radiotherapy treatment planning. , 1996, Physics in medicine and biology.

[6]  Rongxiao Zhang,et al.  Nuclear halo measurements for accurate prediction of field size factor in a Varian ProBeam proton PBS system , 2019, Journal of applied clinical medical physics.

[7]  Liyong Lin,et al.  Experimentally validated pencil beam scanning source model in TOPAS , 2014, Physics in medicine and biology.

[8]  K Parodi,et al.  Monte Carlo simulations to support start-up and treatment planning of scanned proton and carbon ion therapy at a synchrotron-based facility , 2012, Physics in medicine and biology.

[9]  Ralph C. Smith,et al.  Uncertainty Quantification: Theory, Implementation, and Applications , 2013 .

[10]  Katia Parodi,et al.  Clinical implementation of full Monte Carlo dose calculation in proton beam therapy , 2008, Physics in medicine and biology.

[11]  Lei Dong,et al.  Comparison of multi‐institutional Varian ProBeam pencil beam scanning proton beam commissioning data , 2017, Journal of applied clinical medical physics.

[12]  Tony Wong,et al.  Dosimetric evaluation of a commercial proton spot scanning Monte-Carlo dose algorithm: comparisons against measurements and simulations , 2017, Physics in medicine and biology.

[13]  Indra J. Das,et al.  AAPM Medical Physics Practice Guideline 5.a.: Commissioning and QA of Treatment Planning Dose Calculations — Megavoltage Photon and Electron Beams , 2015, Journal of applied clinical medical physics.

[14]  H Paganetti,et al.  TOPAS: an innovative proton Monte Carlo platform for research and clinical applications. , 2012, Medical physics.

[15]  Matthias Fippel,et al.  A pencil beam algorithm for intensity modulated proton therapy derived from Monte Carlo simulations , 2005, Physics in medicine and biology.

[16]  H. Paganetti Range uncertainties in proton therapy and the role of Monte Carlo simulations , 2012, Physics in medicine and biology.

[17]  Uwe Titt,et al.  Commissioning of the discrete spot scanning proton beam delivery system at the University of Texas M.D. Anderson Cancer Center, Proton Therapy Center, Houston. , 2009, Medical physics.

[18]  Timothy D. Solberg,et al.  Use of a novel two‐dimensional ionization chamber array for pencil beam scanning proton therapy beam quality assurance , 2015, Journal of applied clinical medical physics.

[19]  Minglei Kang,et al.  Commissioning and Beam Characterization of The First Gantry-Mounted Accelerator Pencil Beam Scanning Proton System. , 2019, Medical physics.

[20]  Zuofeng Li,et al.  A comprehensive dosimetric study of Monte Carlo and pencil‐beam algorithms on intensity‐modulated proton therapy for breast cancer , 2018, Journal of applied clinical medical physics.

[21]  Ying Xiao,et al.  Validation and application of a fast Monte Carlo algorithm for assessing the clinical impact of approximations in analytical dose calculations for pencil beam scanning proton therapy , 2018, Medical physics.

[22]  J. Mechalakos,et al.  IMRT commissioning: multiple institution planning and dosimetry comparisons, a report from AAPM Task Group 119. , 2009, Medical physics.

[23]  Francesco Fracchiolla,et al.  Improvements in pencil beam scanning proton therapy dose calculation accuracy in brain tumor cases with a commercial Monte Carlo algorithm , 2018, Physics in medicine and biology.

[24]  Beate Timmermann,et al.  Evaluation of detectors for acquisition of pristine depth‐dose curves in pencil beam scanning , 2015, Journal of applied clinical medical physics.

[25]  Radhe Mohan,et al.  Comparison of Monte Carlo and analytical dose computations for intensity modulated proton therapy , 2018, Physics in medicine and biology.

[26]  Harald Paganetti,et al.  Assessing the Clinical Impact of Approximations in Analytical Dose Calculations for Proton Therapy. , 2015, International journal of radiation oncology, biology, physics.

[27]  Radhe Mohan,et al.  Physical Uncertainties in the Planning and Delivery of Light Ion Beam Treatments , 2020 .