A 3D pencil-beam-based superposition algorithm for photon dose calculation in heterogeneous media

In this work, a novel three-dimensional superposition algorithm for photon dose calculation is presented. The dose calculation is performed as a superposition of pencil beams, which are modified based on tissue electron densities. The pencil beams have been derived from Monte Carlo simulations, and are separated into lateral and depth-directed components. The lateral component is modeled using exponential functions, which allows accurate modeling of lateral scatter in heterogeneous tissues. The depth-directed component represents the total energy deposited on each plane, which is spread out using the lateral scatter functions. Finally, convolution in the depth direction is applied to account for tissue interface effects. The method can be used with the previously introduced multiple-source model for clinical settings. The method was compared against Monte Carlo simulations in several phantoms including lung- and bone-type heterogeneities. Comparisons were made for several field sizes for 6 and 18 MV energies. The deviations were generally within (2%, 2 mm) of the field central axis d(max). Significantly larger deviations (up to 8%) were found only for the smallest field in the lung slab phantom for 18 MV. The presented method was found to be accurate in a wide range of conditions making it suitable for clinical planning purposes.

[1]  Firas Mourtada,et al.  Comparison of a finite-element multigroup discrete-ordinates code with Monte Carlo for radiotherapy calculations , 2006, Physics in medicine and biology.

[2]  P M Evans,et al.  Assessing the effect of electron density in photon dose calculations. , 2006, Medical physics.

[3]  E Sterpin,et al.  Monte carlo evaluation of the AAA treatment planning algorithm in a heterogeneous multilayer phantom and IMRT clinical treatments for an Elekta SL25 linear accelerator. , 2007, Medical physics.

[4]  L. Cozzi,et al.  Dosimetric validation of the anisotropic analytical algorithm for photon dose calculation: fundamental characterization in water , 2006, Physics in medicine and biology.

[5]  H Hansson,et al.  Verification of a pencil beam based treatment planning system: output factors for open photon beams shaped with MLC or blocks. , 1999, Physics in medicine and biology.

[6]  L Tillikainen,et al.  A multiple-source photon beam model and its commissioning process for VMC++ Monte Carlo code , 2008 .

[7]  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.

[8]  Mauro Iori,et al.  Testing of the analytical anisotropic algorithm for photon dose calculation. , 2006, Medical physics.

[9]  M Miften,et al.  Implementation of FFT convolution and multigrid superposition models in the FOCUS RTP system. , 2000, Physics in medicine and biology.

[10]  Comment on "Testing of the analytical anisotropic algorithm for photon dose calculation" [Med. Phys. 33, 4130-4148 (2006)]. , 2007, Medical physics.

[11]  M R Sontag,et al.  Corrections to absorbed dose calculations for tissue inhomogeneities. , 1977, Medical physics.

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

[13]  A. Tikhonov,et al.  Numerical Methods for the Solution of Ill-Posed Problems , 1995 .

[14]  P. Storchi,et al.  Calculation of a pencil beam kernel from measured photon beam data. , 1999, Physics in medicine and biology.

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

[16]  Iwan Kawrakow,et al.  VMC ++ , a fast MC algorithm for Radiation Treatment planning , 2000 .

[17]  P. Keall Dm rather than Dw should be used in Monte Carlo treatment planning. Against the proposition. , 2002, Medical physics.

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

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

[20]  A L Boyer,et al.  Calculation of photon dose distributions in an inhomogeneous medium using convolutions. , 1986, Medical physics.

[21]  A. Ahnesjö,et al.  Dose calculations for external photon beams in radiotherapy. , 1999, Physics in medicine and biology.

[22]  J J Battista,et al.  Dose calculations using convolution and superposition principles: the orientation of dose spread kernels in divergent x-ray beams. , 1993, Medical physics.

[23]  W. Ulmer,et al.  A 3D photon superposition/convolution algorithm and its foundation on results of Monte Carlo calculations , 2005, Physics in medicine and biology.

[24]  J. Alakuijala,et al.  Determination of parameters for a multiple-source model of megavoltage photon beams using optimization methods , 2007, Physics in medicine and biology.

[25]  R. P. Parker,et al.  The implementation of a generalised Batho inhomogeneity correction for radiotherapy planning with direct use of CT numbers. , 1981, Physics in medicine and biology.

[26]  J. Battista,et al.  A convolution method of calculating dose for 15-MV x rays. , 1985, Medical physics.

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