Characterization and validation of a Monte Carlo code for independent dose calculation in proton therapy treatments with pencil beam scanning

We propose a method of creating and validating a Monte Carlo (MC) model of a proton Pencil Beam Scanning (PBS) machine using only commissioning measurements and avoiding the nozzle modeling. Measurements with a scintillating screen coupled with a CCD camera, ionization chamber and a Faraday Cup were used to model the beam in TOPAS without using any machine parameter information but the virtual source distance from the isocenter. Then the model was validated on simple Spread Out Bragg Peaks (SOBP) delivered in water phantom and with six realistic clinical plans (many involving 3 or more fields) on an anthropomorphic phantom. In particular the behavior of the moveable Range Shifter (RS) feature was investigated and its modeling has been proposed. The gamma analysis (3%,3 mm) was used to compare MC, TPS (XiO-ELEKTA) and measured 2D dose distributions (using radiochromic film). The MC modeling proposed here shows good results in the validation phase, both for simple irradiation geometry (SOBP in water) and for modulated treatment fields (on anthropomorphic phantoms). In particular head lesions were investigated and both MC and TPS data were compared with measurements. Treatment plans with no RS always showed a very good agreement with both of them (γ-Passing Rate (PR)  >  95%). Treatment plans in which the RS was needed were also tested and validated. For these treatment plans MC results showed better agreement with measurements (γ-PR  >  93%) than the one coming from TPS (γ-PR  <  88%). This work shows how to simplify the MC modeling of a PBS machine for proton therapy treatments without accounting for any hardware components and proposes a more reliable RS modeling than the one implemented in our TPS. The validation process has shown how this code is a valid candidate for a completely independent treatment plan dose calculation algorithm. This makes the code an important future tool for the patient specific QA verification process.

[1]  Harald Paganetti,et al.  Quantification of proton dose calculation accuracy in the lung. , 2014, International journal of radiation oncology, biology, physics.

[2]  L Grevillot,et al.  A Monte Carlo pencil beam scanning model for proton treatment plan simulation using GATE/GEANT4 , 2011, Physics in medicine and biology.

[3]  H. Kooy,et al.  Monte Carlo study of the potential reduction in out-of-field dose using a patient-specific aperture in pencil beam scanning proton therapy , 2012, Physics in medicine and biology.

[4]  A J Lomax,et al.  Respiratory liver motion estimation and its effect on scanned proton beam therapy , 2012, Physics in medicine and biology.

[5]  D. Low,et al.  A technique for the quantitative evaluation of dose distributions. , 1998, Medical physics.

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

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

[8]  Harald Paganetti,et al.  The influence of patient positioning uncertainties in proton radiotherapy on proton range and dose distributions. , 2014, Medical physics.

[9]  A. Lomax,et al.  Characterizing a proton beam scanning system for Monte Carlo dose calculation in patients , 2015, Physics in medicine and biology.

[10]  H Paganetti,et al.  Efficient voxel navigation for proton therapy dose calculation in TOPAS and Geant4 , 2012, Physics in medicine and biology.

[11]  T Sasaki,et al.  Effect of inhomogeneity in a patient's body on the accuracy of the pencil beam algorithm in comparison to Monte Carlo , 2012, Physics in medicine and biology.

[12]  H Paganetti,et al.  A modular method to handle multiple time-dependent quantities in Monte Carlo simulations , 2012, Physics in medicine and biology.

[13]  T. Bortfeld,et al.  Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. , 2000, Physics in medicine and biology.

[14]  A. Lomax,et al.  Intensity modulation methods for proton radiotherapy. , 1999, Physics in medicine and biology.

[15]  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.

[16]  S Safai,et al.  Proton beam monitor chamber calibration , 2014, Physics in medicine and biology.

[17]  A J Lomax,et al.  Experimental verification of IMPT treatment plans in an anthropomorphic phantom in the presence of delivery uncertainties , 2011, Physics in medicine and biology.

[18]  Harald Paganetti,et al.  Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy. , 2013, Medical physics.

[19]  Stephen V. Musolino,et al.  Absorbed Dose Determination in External Beam Radiotherapy: An International Code of Practice for Dosimetry Based on Standards of Absorbed Dose to Water; Technical Reports Series No. 398, , 2001 .

[20]  G Ciangaru,et al.  Experimental validation of a Monte Carlo proton therapy nozzle model incorporating magnetically steered protons , 2009, Physics in medicine and biology.

[21]  Takeshi Himukai,et al.  Improved dose-calculation accuracy in proton treatment planning using a simplified Monte Carlo method verified with three-dimensional measurements in an anthropomorphic phantom , 2010, Physics in medicine and biology.

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

[23]  C Nauraye,et al.  Monte Carlo modelling of the treatment line of the Proton Therapy Center in Orsay , 2009, Physics in medicine and biology.

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

[25]  J Schuemann,et al.  Site-specific range uncertainties caused by dose calculation algorithms for proton therapy , 2014, Physics in medicine and biology.