Clinical implementation of full Monte Carlo dose calculation in proton beam therapy

The goal of this work was to facilitate the clinical use of Monte Carlo proton dose calculation to support routine treatment planning and delivery. The Monte Carlo code Geant4 was used to simulate the treatment head setup, including a time-dependent simulation of modulator wheels (for broad beam modulation) and magnetic field settings (for beam scanning). Any patient-field-specific setup can be modeled according to the treatment control system of the facility. The code was benchmarked against phantom measurements. Using a simulation of the ionization chamber reading in the treatment head allows the Monte Carlo dose to be specified in absolute units (Gy per ionization chamber reading). Next, the capability of reading CT data information was implemented into the Monte Carlo code to model patient anatomy. To allow time-efficient dose calculation, the standard Geant4 tracking algorithm was modified. Finally, a software link of the Monte Carlo dose engine to the patient database and the commercial planning system was established to allow data exchange, thus completing the implementation of the proton Monte Carlo dose calculation engine ('DoC++'). Monte Carlo re-calculated plans are a valuable tool to revisit decisions in the planning process. Identification of clinically significant differences between Monte Carlo and pencil-beam-based dose calculations may also drive improvements of current pencil-beam methods. As an example, four patients (29 fields in total) with tumors in the head and neck regions were analyzed. Differences between the pencil-beam algorithm and Monte Carlo were identified in particular near the end of range, both due to dose degradation and overall differences in range prediction due to bony anatomy in the beam path. Further, the Monte Carlo reports dose-to-tissue as compared to dose-to-water by the planning system. Our implementation is tailored to a specific Monte Carlo code and the treatment planning system XiO (Computerized Medical Systems Inc.). However, this work describes the general challenges and considerations when implementing proton Monte Carlo dose calculation in a clinical environment. The presented solutions can be easily adopted for other planning systems or other Monte Carlo codes.

[1]  Katia Parodi,et al.  PET/CT imaging for treatment verification after proton therapy: a study with plastic phantoms and metallic implants. , 2007, Medical physics.

[2]  S. Tanaka,et al.  DICOM data handling for Geant4-based medical physics application , 2004, IEEE Symposium Conference Record Nuclear Science 2004..

[3]  Thomas Bortfeld,et al.  Monitor unit calculations for range-modulated spread-out Bragg peak fields. , 2003, Physics in medicine and biology.

[4]  P Rüegsegger,et al.  Simple beam models for Monte Carlo photon beam dose calculations in radiotherapy. , 2000, Medical physics.

[5]  M. Bussière,et al.  Treatment Planning for Conformal Proton Radiation Therapy , 2003, Technology in cancer research & treatment.

[6]  M. Fippel.  Fast Monte Carlo dose calculation for photon beams based on the VMC electron algorithm. , 1999, Medical physics.

[7]  M. Rosetti,et al.  Effects of nuclear interactions on energy and stopping power in proton beam dosimetry , 1996 .

[8]  R. K. Bull,et al.  Stopping powers for electrons and positrons: ICRU Report 37; 271 pp.; 24 figures; U.S. $24.00. , 1986 .

[9]  I. Kawrakow.  Accurate condensed history Monte Carlo simulation of electron transport. I. EGSnrc, the new EGS4 version. , 2000, Medical physics.

[10]  Brian Wang,et al.  Simulation of organ-specific patient effective dose due to secondary neutrons in proton radiation treatment , 2005, Physics in medicine and biology.

[11]  D Granero,et al.  Phantom size in brachytherapy source dosimetric studies. , 2004, Medical physics.

[12]  P Andreo,et al.  Monte Carlo calculated stopping-power ratios, water/air, for clinical proton dosimetry (50-250 MeV). , 1997, Physics in medicine and biology.

[13]  Harald Paganetti,et al.  Relative biological effectiveness (RBE) values for proton beam therapy. , 2002, International journal of radiation oncology, biology, physics.

[14]  M Goitein,et al.  Radiobiological significance of beamline dependent proton energy distributions in a spread-out Bragg peak. , 2000, Medical physics.

[15]  Joao Seco,et al.  Effects of Hounsfield number conversion on CT based proton Monte Carlo dose calculations. , 2007, Medical physics.

[16]  Frank Verhaegen,et al.  Assigning nonelastic nuclear interaction cross sections to Hounsfield units for Monte Carlo treatment planning of proton beams , 2005, Physics in medicine and biology.

[17]  U. Oelfke,et al.  Two-dimensional pencil beam scaling: an improved proton dose algorithm for heterogeneous media. , 2002, Physics in medicine and biology.

[18]  W. Kalender,et al.  Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions , 2000 .

[19]  S. Tanaka,et al.  DICOM interface and visualization tool for Geant4-based dose calculation , 2005, IEEE Nuclear Science Symposium Conference Record, 2005.

[20]  J. Sempau,et al.  DPM, a fast, accurate Monte Carlo code optimized for photon and electron radiotherapy treatment planning dose calculations , 2000 .

[21]  S B Jiang,et al.  Monte Carlo verification of IMRT dose distributions from a commercial treatment planning optimization system. , 2000, Physics in medicine and biology.

[22]  B. Faddegon,et al.  Description and dosimetric verification of the PEREGRINE Monte Carlo dose calculation system for photon beams incident on a water phantom. , 2001, Medical physics.

[23]  R. Mohan,et al.  Converting absorbed dose to medium to absorbed dose to water for Monte Carlo based photon beam dose calculations. , 2000, Physics in medicine and biology.

[24]  R. Mohan,et al.  The effect of dose calculation uncertainty on the evaluation of radiotherapy plans. , 2000, Medical physics.

[25]  J. Sempau,et al.  PENELOPE-2006: A Code System for Monte Carlo Simulation of Electron and Photon Transport , 2009 .

[26]  H Paganetti,et al.  Nuclear interactions in proton therapy: dose and relative biological effect distributions originating from primary and secondary particles. , 2002, Physics in medicine and biology.

[27]  H Paganetti,et al.  Test of GEANT3 and GEANT4 nuclear models for 160 MeV protons stopping in CH2. , 2003, Medical physics.

[28]  Harald Paganetti,et al.  The prediction of output factors for spread-out proton Bragg peak fields in clinical practice , 2005, Physics in medicine and biology.

[29]  C. Ma,et al.  BEAM: a Monte Carlo code to simulate radiotherapy treatment units. , 1995, Medical physics.

[30]  Harald Paganetti,et al.  Monte Carlo calculations for absolute dosimetry to determine machine outputs for proton therapy fields , 2006, Physics in medicine and biology.

[31]  Harald Paganetti,et al.  Assessment of organ-specific neutron equivalent doses in proton therapy using computational whole-body age-dependent voxel phantoms , 2008, Physics in medicine and biology.

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

[33]  L. Beaulieu,et al.  Validation of GEANT4, an object-oriented Monte Carlo toolkit, for simulations in medical physics. , 2004, Medical physics.

[34]  H Paganetti,et al.  Four-dimensional Monte Carlo simulation of time-dependent geometries , 2004, Physics in medicine and biology.

[35]  H Helen Liu,et al.  Dm rather than Dw should be used in Monte Carlo treatment planning. For the proposition. , 2002, Medical physics.

[36]  Hsiao-Ming Lu,et al.  Optimization of current modulation function for proton spread-out Bragg peak fields. , 2006, Medical physics.

[37]  J. Seuntjens,et al.  Consistency test of the electron transport algorithm in the GEANT4 Monte Carlo code , 2005, Physics in medicine and biology.

[38]  J. F. Briesmeister.  MCNP-A General Monte Carlo N-Particle Transport Code , 1993 .

[39]  P Andreo,et al.  Monte Carlo and analytical calculation of proton pencil beams for computerized treatment plan optimization , 1997, Physics in medicine and biology.

[40]  Katia Parodi,et al.  Patient study of in vivo verification of beam delivery and range, using positron emission tomography and computed tomography imaging after proton therapy. , 2007, International journal of radiation oncology, biology, physics.

[41]  A. Trofimov,et al.  4D Monte Carlo simulation of proton beam scanning: modelling of variations in time and space to study the interplay between scanning pattern and time-dependent patient geometry , 2005, Physics in medicine and biology.

[42]  T Pawlicki,et al.  Removing the effect of statistical uncertainty on dose-volume histograms from Monte Carlo dose calculations. , 2000, Physics in medicine and biology.

[43]  M. Fix,et al.  Monte Carlo simulation of a dynamic MLC based on a multiple source model. , 2001, Physics in medicine and biology.

[44]  I. Kawrakow,et al.  Investigation of variance reduction techniques for Monte Carlo photon dose calculation using XVMC , 2000, Physics in medicine and biology.

[45]  H Paganetti,et al.  Monte Carlo method to study the proton fluence for treatment planning. , 1998, Medical physics.

[46]  H Paganetti,et al.  Adaptation of GEANT4 to Monte Carlo dose calculations based on CT data. , 2004, Medical physics.

[47]  Harald Paganetti,et al.  Proton Beams to Replace Photon Beams in Radical Dose Treatments , 2003, Acta oncologica.

[48]  Robert J. Schneider,et al.  Range modulators for protons and heavy ions , 1975 .

[49]  G T Chen,et al.  Degradation of the Bragg peak due to inhomogeneities. , 1986, Physics in medicine and biology.

[50]  Antonio M Lallena,et al.  Dosimetry characterization of 32P intravascular brachytherapy source wires using Monte Carlo codes PENELOPE and GEANT4. , 2004, Medical physics.

[51]  H. Paganetti,et al.  Physics Settings for Using the Geant4 Toolkit in Proton Therapy , 2008, IEEE Transactions on Nuclear Science.

[52]  M. Fix,et al.  A multiple source model for 6 MV photon beam dose calculations using Monte Carlo. , 2001, Physics in medicine and biology.

[53]  T Pawlicki,et al.  Monte Carlo simulation for MLC-based intensity-modulated radiotherapy. , 2001, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[54]  H Paganetti,et al.  Accurate Monte Carlo simulations for nozzle design, commissioning and quality assurance for a proton radiation therapy facility. , 2004, Medical physics.

[55]  M Goitein,et al.  A pencil beam algorithm for proton dose calculations. , 1996, Physics in medicine and biology.

[56]  Harald Paganetti,et al.  Monte Carlo simulations with time-dependent geometries to investigate effects of organ motion with high temporal resolution. , 2004, International journal of radiation oncology, biology, physics.