Quantification of dose differences between two versions of Acuros XB algorithm compared to Monte Carlo simulations — the effect on clinical patient treatment planning

A commercialized implementation of linear Boltzmann transport equation solver, the Acuros XB algorithm (AXB), represents a class of most advanced type ‘c’ photon radiotherapy dose calculation algorithms. The purpose of the study was to quantify the effects of the modifications implemented in the more recent version 11 of the AXB (AXB11) compared to the first commercial implementation, version 10 of the AXB (AXB10), in various anatomical regions in clinical treatment planning. Both versions of the AXB were part of Varian's Eclipse clinical treatment planning system and treatment plans for 10 patients were created using intensity‐modulated radiotherapy (IMRT) and volumetric‐modulated arc radiotherapy (VMAT). The plans were first created with the AXB10 and then recalculated with the AXB11 and full Monte Carlo (MC) simulations. Considering the full MC simulations as reference, a DVH analysis for gross tumor and planning target volumes (GTV and PTV) and organs at risk was performed, and also 3D gamma agreement index (GAI) values within a 15% isodose region and for the PTV were determined. Although differences up to 12% in DVH analysis were seen between the MC simulations and the AXB, based on the results of this study no general conclusion can be drawn that the modifications made in the AXB11 compared to the AXB10 would imply that the dose calculation accuracy of the AXB10 would be inferior to the AXB11 in the clinical patient treatment planning. The only clear improvement with the AXB11 over the AXB10 is the dose calculation accuracy in air cavities. In general, no large deviations are present in the DVH analysis results between the two versions of the algorithm, and the results of 3D gamma analysis do not favor one or the other. Thus it may be concluded that the results of the comprehensive studies assessing the accuracy of the AXB10 may be extended to the AXB11. PACS numbers: 87.55.‐x, 87.55.D‐, 87.55.K‐, 87.55.kd, 87.55.Qr

[1]  Peter K. N. Yu,et al.  A Review on the Use of Grid-Based Boltzmann Equation Solvers for Dose Calculation in External Photon Beam Treatment Planning , 2013, BioMed research international.

[2]  D. G. Lewis,et al.  A DICOM-RT-based toolbox for the evaluation and verification of radiotherapy plans. , 2002, Physics in medicine and biology.

[3]  F. Mourtada,et al.  Feasibility of a multigroup deterministic solution method for three-dimensional radiotherapy dose calculations. , 2008, International journal of radiation oncology, biology, physics.

[4]  Dietrich Harder,et al.  A Triple Gaussian Pencil beam Model for Photon beam Treatment Planning , 1995 .

[5]  S. Zavgorodni,et al.  Absolute dose calculations for Monte Carlo simulations of radiotherapy beams , 2005, Physics in medicine and biology.

[6]  M. Schell,et al.  Stereotactic body radiation therapy: the report of AAPM Task Group 101. , 2010, Medical physics.

[7]  J. Ojala.  The accuracy of the Acuros XB algorithm in external beam radiotherapy – a comprehensive review , 2014 .

[8]  Luca Cozzi,et al.  Dosimetric evaluation of Acuros XB Advanced Dose Calculation algorithm in heterogeneous media , 2011, Radiation oncology.

[9]  Firas Mourtada,et al.  Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model-based convolution methods in heterogeneous media. , 2011, Medical physics.

[10]  M. Pitkänen,et al.  Performance of dose calculation algorithms from three generations in lung SBRT: comparison with full Monte Carlo‐based dose distributions , 2014, Journal of applied clinical medical physics.

[11]  Two new DOSXYZnrc sources for 4D Monte Carlo simulations of continuously variable beam configurations, with applications to RapidArc, VMAT, TomoTherapy and CyberKnife. , 2010, Physics in medicine and biology.

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

[13]  Luca Cozzi,et al.  Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations , 2006, Physics in medicine and biology.

[14]  L. Cozzi,et al.  On the dosimetric impact of inhomogeneity management in the Acuros XB algorithm for breast treatment , 2011, Radiation oncology.

[15]  H Helminen,et al.  A 3D pencil-beam-based superposition algorithm for photon dose calculation in heterogeneous media , 2008, Physics in medicine and biology.

[16]  P. Mancosu,et al.  Dosimetric validation of the Acuros XB Advanced Dose Calculation algorithm: fundamental characterization in water , 2011, Physics in medicine and biology.

[17]  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.

[18]  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.

[19]  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.

[20]  W. Ulmer,et al.  The inverse problem of a Gaussian convolution and its application to the finite size of the measurement chambers/detectors in photon and proton dosimetry. , 2003, Physics in medicine and biology.

[21]  K. Bush,et al.  Dosimetric validation of Acuros XB with Monte Carlo methods for photon dose calculations. , 2011, Medical physics.

[22]  M. Waligórski,et al.  Performance of two commercial electron beam algorithms over regions close to the lung-mediastinum interface, against Monte Carlo simulation and point dosimetry in virtual and anthropomorphic phantoms. , 2014, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

[23]  Helen H Liu,et al.  Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. , 2007, Medical physics.

[24]  Joseph O Deasy,et al.  CERR: a computational environment for radiotherapy research. , 2003, Medical physics.

[25]  Shawn D. Pautz,et al.  Discontinuous Finite Element SN Methods on Three-Dimensional Unstructured Grids , 2001 .

[26]  S. Dieterich,et al.  Experimental comparison of seven commercial dosimetry diodes for measurement of stereotactic radiosurgery cone factors. , 2011, Medical physics.

[27]  Mika Kapanen,et al.  The accuracy of Acuros XB algorithm for radiation beams traversing a metallic hip implant — comparison with measurements and Monte Carlo calculations , 2014, Journal of applied clinical medical physics.

[28]  S. Pokharel,et al.  Dose-to-medium vs. dose-to-water: Dosimetric evaluation of dose reporting modes in Acuros XB for prostate, lung and breast cancer , 2014 .

[29]  Steve B. Jiang,et al.  Effect of statistical fluctuation in Monte Carlo based photon beam dose calculation on gamma index evaluation , 2012, Physics in medicine and biology.

[30]  Firas Mourtada,et al.  Validation of a new grid-based Boltzmann equation solver for dose calculation in radiotherapy with photon beams , 2010, Physics in medicine and biology.

[31]  Dietrich Harder,et al.  Applications of a Triple Gaussian Pencil Beam Model for Photon Beam Treatment Planning , 1996 .