CLINICAL IMPLEMENTATION, VALIDATION AND USE OF THE DPM MONTE CARLO CODE FOR RADIOTHERAPY TREATMENT PLANNING

The purpose of this paper is to describe the implementation, validation, and use of the Dose Planning Method (DPM) for clinical radiotherapy treatment planning. Experimental validation of the coupled photon-electron transport model employed within DPM has been conducted using 50 MeV electron pencil beams (from a racetrack microtron), in phantoms consisting of water and lung and bone-equivalent materials. DPM depth dose and profile calculations were within 2% of measurements, except for 50 MeV incident on the water/lung/water phantom, where differences of up to 15% were observed. A method to potentially reconcile these differences is discussed. DPM photon beam calculations are conducted using a source model, reconstructed from phase space simulation of a linear accelerator treatment head, using the BEAMnrc Monte Carlo code. The photon source model has been integrated within the UMPlan radiotherapy planning system and benchmarked over a range of field sizes from 2x2 to 40x40 cm 2 ; agreement with measurements was found to be within 2%/2 mm for square and irregularly shaped fields. Treatment planning calculations, for patient lesions within the lung, comparing DPM with a conventionally used (equivalent path-length) algorithm, exemplifies the issues of lateral electron transport and underdosing of the planning target volume (PTV) with the conventional algorithm. These issues are clinically important. The dosimetric effects of patient motion have been incorporated in the DPM calculations by convolving the fluence maps with functions representative of motion. This method is compared with static dose distributions. Preliminary results of the “motion” study are presented. The availability of fast, accurate calculations with DPM allows us to realize the benefits of the Monte Carlo method for radiotherapy treatment planning in the clinical setting.

[1]  T. Solberg,et al.  A virtual source model for Monte Carlo modeling of arbitrary intensity distributions. , 2000, Medical physics.

[2]  P J Keall,et al.  A fluence-convolution method to calculate radiation therapy dose distributions that incorporate random set-up error. , 2002, Physics in medicine and biology.

[3]  G. C. Pomraning.  Transport and diffusion in a statistical medium , 1986 .

[4]  J. Sempau,et al.  Monte Carlo simulation of electron beams from an accelerator head using PENELOPE , 2001, Physics in Medicine and Biology.

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

[6]  I. Kawrakow,et al.  3D electron dose calculation using a Voxel based Monte Carlo algorithm (VMC). , 1996, Medical physics.

[7]  I. Kawrakow,et al.  History by history statistical estimators in the BEAM code system. , 2002, Medical physics.

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

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

[10]  R. Mohan,et al.  The impact of electron transport on the accuracy of computed dose. , 2000, Medical physics.

[11]  C. Ma,et al.  Clinical implementation of a Monte Carlo treatment planning system. , 1999, Medical physics.

[12]  P J Keall,et al.  A method to predict the effect of organ motion and set-up variations on treatment plans. , 1999, Australasian physical & engineering sciences in medicine.

[13]  J. Leong,et al.  Implementation of random positioning error in computerised radiation treatment planning systems as a result of fractionation. , 1987, Physics in medicine and biology.

[14]  G. Starkschall,et al.  American Association of Physicists in Medicine Radiation Therapy Committee Task Group 53: quality assurance for clinical radiotherapy treatment planning. , 1998, Medical physics.

[15]  P. Andreo.  Monte Carlo techniques in medical radiation physics. , 1991, Physics in medicine and biology.

[16]  H Svensson,et al.  Electron and photon beams from a 50 MeV racetrack microtron. , 1980, Acta Radiologica Oncology.

[17]  C. Chui,et al.  A patient-specific Monte Carlo dose-calculation method for photon beams. , 1998, Medical physics.

[18]  J J DeMarco,et al.  A CT-based Monte Carlo simulation tool for dosimetry planning and analysis. , 1998, Medical physics.

[19]  E. Larsen,et al.  A method for incorporating organ motion due to breathing into 3D dose calculations. , 1999, Medical physics.

[20]  T. Mackie,et al.  MMC--a high-performance Monte Carlo code for electron beam treatment planning. , 1995, Physics in medicine and biology.

[21]  Paul J. Keall,et al.  Performance benchmarks of the MCV Monte Carlo system , 2000 .

[22]  Indrin J Chetty,et al.  Experimental validation of the DPM Monte Carlo code using minimally scattered electron beams in heterogeneous media. , 2002, Physics in medicine and biology.

[23]  H Svensson,et al.  Electron beam characteristics of the 50-MeV racetrack microtron. , 1992, Medical physics.

[24]  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.

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