Azimuthal particle redistribution for the reduction of latent phase-space variance in Monte Carlo simulations

Effect of modulation factor and low dose threshold level on gamma pass rates of single isocenter multi-target SRT treatment plans

PURPOSE

SRS MapCHECK (SMC) is a commercially available patient-specific quality assurance (PSQA) tool for stereotactic radiosurgery (SRS) applications. This study investigates the effects of degree of modulation, location off-axis, and low dose threshold (LDT) selection on gamma pass rates (GPRs) between SMC and treatment planning system, Analytical Anisotropic Algorithm (AAA), or Vancouver Island Monte Carlo (VMC++ algorithm) system calculated dose distributions.

METHODS

Volumetric-modulated arc therapy (VMAT) plans with modulation factors (MFs) ranging from 2.7 to 10.2 MU/cGy were delivered to SMC at isocenter and 6 cm off-axis. SMC measured dose distributions were compared against AAA and VMC++ via gamma analysis (3%/1 mm) with LDT of 10% to 80% using SNC Patient software.

RESULTS

Comparing on-axis SMC dose against AAA and VMC++ with LDT of 10%, all AAA-calculated plans met the acceptance criteria of GPR ≥ 90%, and only one VMC++ calculated plan was marginally outside the acceptance criteria with pass rate of 89.1%. Using LDT of 80% revealed decreasing GPR with increasing MF. For AAA, GPRs reduced from 100% at MF of 2.7 MU/cGy to 57% at MF of 10.2 MU/cGy, and for VMC++ calculated plans, the GPRs reduced from 89% to 60% in the same MF range. Comparison of SMC dose off-axis against AAA and VMC++ showed more pronounced reduction of GPR with increasing MF. For LDT of 10%, AAA GPRs reduced from 100% to 83% in the MF range of 2.7 to 9.8 MU/cGy, and VMC++ GPR reduced from 100% to 91% in the same range. With 80% LDT, GPRs dropped from 100% to 42% for both algorithms.

CONCLUSIONS

MF, dose calculation algorithm, and LDT selections are vital in VMAT-based SRT PSQA. LDT of 80% enhances sensitivity of gamma analysis for detecting dose differences compared to 10% LDT. To achieve better agreement between calculated and SMC dose, it is recommended to limit the MF to 4.6 MU/cGy on-axis and 3.6 MU/cGy off-axis.

Dosimetric characterization of single- and dual-port temporary tissue expanders for postmastectomy radiotherapy using Monte Carlo methods

Purpose

The aim of this work was two-fold: a) to assess two treatment planning strategies for accounting CT artifacts introduced by temporary tissue-expanders (TTEs); b) to evaluate the dosimetric impact of two commercially available and one novel TTE.

Methods

The CT artifacts were managed using two strategies. 1) Identifying the metal in the RayStation treatment planning software (TPS) using image window-level adjustments, delineate a contour enclosing the artifact, and setting the density of the surrounding voxels to unity (RS1). 2) Registering a geometry template with dimensions and materials from the TTEs (RS2). Both strategies were compared for DermaSpan, AlloX2, and AlloX2-Pro TTEs using Collapsed Cone Convolution (CCC) in RayStation TPS, Monte Carlo simulations (MC) using TOPAS, and film measurements. Wax slab phantoms with metallic ports and breast phantoms with TTEs balloons were made and irradiated with a 6 MV AP beam and partial arc, respectively. Dose values along the AP direction calculated with CCC (RS2) and TOPAS (RS1 and RS2) were compared with film measurements. The impact in dose distributions was evaluated with RS2 by comparing TOPAS simulations with and without the metal port.

Results

For the wax slab phantoms, the dose differences between RS1 and RS2 were 0.5% for DermaSpan and AlloX2 but 3% for AlloX2-Pro. From TOPAS simulations of RS2, the impact in dose distributions caused by the magnet attenuation was (6.4 ± 0.4) %, (4.9 ± 0.7)%, and (2.0 ± 0.9)% for DermaSpan, AlloX2, and AlloX2-Pro, respectively. With breast phantoms, maximum differences in DVH parameters between RS1 and RS2 were as follows. For AlloX2 at the posterior region: (2.1 ± 1.0)%, (1.9 ± 1.0)% and (1.4 ± 1.0)% for D1, D10, and average dose, respectively. For AlloX2-Pro at the anterior region (-1.0 ± 1.0)%, (-0.6 ± 1.0)% and (-0.6 ± 1.0)% for D1, D10 and average dose, respectively. The impact in D10 caused by the magnet was at most (5.5 ± 1.0)% and (-0.8 ± 1.0)% for AlloX2 and AlloX2-Pro, respectively.

Conclusion

Two strategies for accounting for CT artifacts from three breast TTEs were assessed using CCC, MC, and film measurements. This study showed that the highest differences with respect to measurements occurred with RS1 and can be mitigated if a template with the actual port geometry and materials is used.

A comprehensive Monte Carlo study of CT dose metrics proposed by the AAPM Reports 111 and 200

PURPOSE

A Monte Carlo (MC) modeling of single axial and helical CT scan modes has been developed to compute single and accumulated dose distributions. The radiation emission characteristics of an MDCT scanner has been modeled and used to evaluate the dose deposition in infinitely long head and body PMMA phantoms. The simulated accumulated dose distributions determined the approach to equilibrium function, H(L). From these H ( L ) curves, dose-related information was calculated for different head and body clinical protocols.

METHODS

The PENELOPE/penEasy package has been used to model the single axial and helical procedures and the radiation transport of photons and electrons in the phantoms. The bowtie filters, heel effect, focal-spot angle, and fan-beam geometry were incorporated. Head and body protocols with different pitch values were modeled for x-ray spectra corresponding to 80, 100, 120, and 140 kV. The analytical formulation for the single dose distributions and experimental measurements of single and accumulated dose distributions were employed to validate the MC results. The experimental dose distributions were measured with OSLDs and a thimble ion chamber inserted into PMMA phantoms. Also, the experimental values of the C T D I 100 along the center and peripheral axes of the CTDI phantom served to calibrate the simulated single and accumulated dose distributions.

RESULTS

The match of the simulated dose distributions with the reference data supports the correct modeling of the heel effect and the radiation transport in the phantom material reflected in the tails of the dose distributions. The validation of the x-ray source model was done comparing the CTDI ratios between simulated, measured and CTDosimetry data. The average difference of these ratios for head and body protocols between the simulated and measured data was in the range of 13-17% and between simulated and CTDosimetry data varied 10-13%. The distributions of simulated doses and those measured with the thimble ion chamber are compatible within 3%. In this study, it was demonstrated that the efficiencies of the C T D I 100 measurements in head phantoms with nT = 20 mm and 120 kV are 80.6% and 87.8% at central and peripheral axes, respectively. In the body phantoms with n T = 40 mm and 120 kV, the efficiencies are 56.5% and 86.2% at central and peripheral axes, respectively. In general terms, the clinical parameters such as pitch, beam intensity, and voltage affect the D_eq values with the increase of the pitch decreasing the D_eq and the beam intensity and the voltage increasing its value. The H(L) function does not change with the pitch values, but depends on the phantom axis (central or peripheral).

CONCLUSIONS

The computation of the pitch-equilibrium dose product, D ̂ eq , evidenced the limitations of the C T D I 100 method to determine the dose delivered by a CT scanner. Therefore, quantities derived from the C T D I 100 propagate this limitation. The developed MC model shows excellent compatibility with both measurements and literature quantities defined by AAPM Reports 111 and 200. These results demonstrate the robustness and versatility of the proposed modeling method.

Monte Carlo calculated detector-specific correction factors for Elekta radiosurgery cones

A radiation field is considered small if its dimension is lower than the range of secondary electrons and the collimating devices partially occlude the source. Different detector types, such as unshielded diodes, diamond detectors, and small-volume ion chambers, are used for small-field measurements. Although the active volumes of these detectors are small, their non-water equivalent materials cause response variations. Herein, we aim to calculate the correction factors for our clinical detectors, EDGE detector (Sun Nuclear), 60017 diode (PTW), and CC01 ion chamber (IBA), for stereotactic radiosurgery cones of diameters of 5-15 mm in an Elekta Synergy linear accelerator using a Monte Carlo simulation. An Elekta Synergy linear accelerator treatment head was simulated using BEAMnrc Monte Carlo code as per the manufacturer specification. All three detectors were simulated as per the manufacturer specification. Three EGSnrc user codes were used for the detector simulation based on the detector geometry. The Monte Carlo model of the treatment head was validated against the measured data for a standard field size of 10 × 10 cm². The off-axis profile, percentage depth dose, and tissue phantom ratioTPR1020were verified in the validation procedure. The measured and Monte Carlo calculated relative output factors (ROFs) were not consistent. In a 5 mm field size, EDGE diode overestimated the ROF by 7.06%, and 60017 diode to 4.611%. In a 7.5 mm field size, the variations were 4.295% and 3.691% for EDGE and 60017 diodes, respectively. CC01 ion chamber under-responded up to 10% because of its low-density active volume. The maximum corrections were obtained in the smallest field size, which were 0.939(0.007), 0.962(0.006), and 1.117(0.008) for EDGE, PTW T60017, and CC01 detectors, respectively. After applying the Monte Carlo calculated correction factor to the measured ROF, it became consistent with the Monte Carlo calculated ROF.

A fast jaw-tracking model for VMAT and IMRT Monte Carlo simulations

Modern radiotherapy techniques involve routine use of volumetric arc therapy (VMAT) and intensity modulated radiotherapy (IMRT) with jaw‐tracking – dynamic motion of the secondary collimators (jaws) in tandem with multi‐leaf collimators (MLCs). These modalities require accurate dose calculations for the purposes of treatment planning and dose verification. Monte Carlo (MC) methods for radiotherapy dose calculation are widely accepted as capable of achieving high accuracy. This paper presents an efficiency‐enhancement method for secondary collimator modeling, presented in the context of a tool for MC‐based dose second checks. The model constitutes an accuracy trade‐off in the source model for the sake of efficiency enhancement, but maintains the advantages of MC transport in patient heterogeneities. The secondary collimator model is called Flat‐Absorbing‐Jaw‐Tracking (FAJT). Transmission through and scatter from the secondary collimators is neglected, and jaws are modeled as perfectly absorbing planes. To couple the motion of secondary collimators with MLCs for jaw‐tracking, the FAJT model was built into the VCU‐MLC model. Gamma‐index analysis of the dose distributions from FAJT against the full BEAMnrc MC simulations showed over 99% pass rate for a range of open fields, two clinical IMRT, and one VMAT treatment plan, for 2%/2 mm criteria above 10%. Using FAJT, the simulation speed of the secondary collimators for open fields increased by a factor of 237, 1489, and 1395 for 4 × 4, 10 × 10, and 30 × 30 cm², respectively. In general, clinically oriented simulation times are reduced from “hours” to “minutes” on identical hardware. Results for nine representative clinical cases (seven with jaw‐tracking) are presented. The average 2%/2 mm γ‐test success rate above the 80% isodose was 96.8% when tested against the EPIDose electronic portal image‐based dose reconstruction method and 97.3% against the Eclipse analytical anisotropic algorithm.

Evaluation of latent variances in Monte Carlo dose calculations with Varian TrueBeam photon phase-spaces used as a particle source

The purpose of this study was to evaluate the latent variance (LV) of Varian TrueBeam photon phase-space files (PSF) for open 10  ×  10 cm² and small stereotactic fields and estimate the number of phase spaces required to be summed up in order to maintain sub-percent LV in Monte Carlo (MC) dose calculations. BEAMnrc/DOSXYZnrc software was used to transport particles from Varian phase-space files (PSF_A) through the secondary collimators. Transported particles were scored into another phase-space located under the jaws (PSF_B), or transported further through the cone collimators and scored straight below, forming PSF_C. Phase-space files (PSF_B) were scored for 6 MV-FFF, 6 MV, 10 MV-FFF, 10 MV and 15 MV beams with 10  ×  10 cm² field size, and PSF_C were scored for 6 MV beam under circular cones of 0.13, 0.25, 0.35, and 1 cm diameter. Both PSF_B and PSF_C were transported into a water phantom with particle recycling number ranging from 10 to 1000. For 10  ×  10 cm² fields 0.5  ×  0.5  ×  0.5 cm³ voxels were used to score the dose, whereas the dose was scored in 0.1  ×  0.1  ×  0.5 cm³ voxels for beams collimated with small cones. In addition, for small 0.25 cm diameter cone-collimated 6 MV beam, phantom voxel size varied as 0.02  ×  0.02  ×  0.5 cm³, 0.05  ×  0.05  ×  0.5 cm³ and 0.1  ×  0.1  ×  0.5 cm³. Dose variances were scored in all cases and LV evaluated as per Sempau et al. For the 10  ×  10 cm² fields calculated LVs were greatest at the phantom surface and decreased with depth until they reached a plateau at 5 cm depth. LVs were found to be 0.54%, 0.96%, 0.35%, 0.69% and 0.57% for the 6 MV-FFF, 6 MV, 10 MV-FFF, 10 MV and 15 MV energies, respectively at the depth of 10 cm. For the 6 MV phase-space collimated with cones of 0.13, 0.25, 0.35, 1.0 cm diameter, the LVs calculated at 1.5 cm depth were 75.6%, 25.4%, 17.6% and 8.0% respectively. Calculated LV for the 0.25 cm cone-collimated 6 MV beam were 61.2%, 40.7%, 22.5% in 0.02  ×  0.02  ×  0.5 cm³, 0.05  ×  0.05  ×  0.5 cm³ and 0.1  ×  0.1  ×  0.5 cm³ voxels respectively. In order to achieve sub-percent LV in open 10  ×  10 cm² field MC simulations a single PSF can be used, whereas for small SRS fields (0.13-1.0 cm) more PSFs (66-8 PSFs) would have to be summed.

Monte Carlo systems used for treatment planning and dose verification

General-purpose radiation transport Monte Carlo codes have been used for estimation of the absorbed dose distribution in external photon and electron beam radiotherapy patients since several decades. Results obtained with these codes are usually more accurate than those provided by treatment planning systems based on non-stochastic methods. Traditionally, absorbed dose computations based on general-purpose Monte Carlo codes have been used only for research, owing to the difficulties associated with setting up a simulation and the long computation time required. To take advantage of radiation transport Monte Carlo codes applied to routine clinical practice, researchers and private companies have developed treatment planning and dose verification systems that are partly or fully based on fast Monte Carlo algorithms. This review presents a comprehensive list of the currently existing Monte Carlo systems that can be used to calculate or verify an external photon and electron beam radiotherapy treatment plan. Particular attention is given to those systems that are distributed, either freely or commercially, and that do not require programming tasks from the end user. These systems are compared in terms of features and the simulation time required to compute a set of benchmark calculations.

An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations

Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum dose difference within 1.7%. The maximum relative difference of output factors was within 0.5%. Over 98.5% passing rate was achieved in 3D gamma-index tests with 2%/2 mm criteria in both an IMRT prostate patient case and a head-and-neck case. These results demonstrated the efficacy of our model in terms of accurately representing a reference phase-space file. We have also tested the efficiency gain of our source model over our previously developed phase-space-let file source model. The overall efficiency of dose calculation was found to be improved by ~1.3-2.2 times in water and patient cases using our analytical model.

Independent calculation of monitor units for VMAT and SPORT

PURPOSE

Dose and monitor units (MUs) represent two important facets of a radiation therapy treatment. In current practice, verification of a treatment plan is commonly done in dose domain, in which a phantom measurement or forward dose calculation is performed to examine the dosimetric accuracy and the MU settings of a given treatment plan. While it is desirable to verify directly the MU settings, a computational framework for obtaining the MU values from a known dose distribution has yet to be developed. This work presents a strategy to calculate independently the MUs from a given dose distribution of volumetric modulated arc therapy (VMAT) and station parameter optimized radiation therapy (SPORT).

METHODS

The dose at a point can be expressed as a sum of contributions from all the station points (or control points). This relationship forms the basis of the proposed MU verification technique. To proceed, the authors first obtain the matrix elements which characterize the dosimetric contribution of the involved station points by computing the doses at a series of voxels, typically on the prescription surface of the VMAT/SPORT treatment plan, with unit MU setting for all the station points. An in-house Monte Carlo (MC) software is used for the dose matrix calculation. The MUs of the station points are then derived by minimizing the least-squares difference between doses computed by the treatment planning system (TPS) and that of the MC for the selected set of voxels on the prescription surface. The technique is applied to 16 clinical cases with a variety of energies, disease sites, and TPS dose calculation algorithms.

RESULTS

For all plans except the lung cases with large tissue density inhomogeneity, the independently computed MUs agree with that of TPS to within 2.7% for all the station points. In the dose domain, no significant difference between the MC and Eclipse Anisotropic Analytical Algorithm (AAA) dose distribution is found in terms of isodose contours, dose profiles, gamma index, and dose volume histogram (DVH) for these cases. For the lung cases, the MC-calculated MUs differ significantly from that of the treatment plan computed using AAA. However, the discrepancies are reduced to within 3% when the TPS dose calculation algorithm is switched to a transport equation-based technique (Acuros™). Comparison in the dose domain between the MC and Eclipse AAA/Acuros calculation yields conclusion consistent with the MU calculation.

CONCLUSIONS

A computational framework relating the MU and dose domains has been established. The framework does not only enable them to verify the MU values of the involved station points of a VMAT plan directly in the MU domain but also provide a much needed mechanism to adaptively modify the MU values of the station points in accordance to a specific change in the dose domain.

Improved efficiency in Monte Carlo simulation for passive-scattering proton therapy

The aim of this work was to improve the computational efficiency of Monte Carlo simulations when tracking protons through a proton therapy treatment head. Two proton therapy facilities were considered, the Francis H Burr Proton Therapy Center (FHBPTC) at the Massachusetts General Hospital and the Crocker Lab eye treatment facility used by University of California at San Francisco (UCSFETF). The computational efficiency was evaluated for phase space files scored at the exit of the treatment head to determine optimal parameters to improve efficiency while maintaining accuracy in the dose calculation. For FHBPTC, particles were split by a factor of 8 upstream of the second scatterer and upstream of the aperture. The radius of the region for Russian roulette was set to 2.5 or 1.5 times the radius of the aperture and a secondary particle production cut (PC) of 50 mm was applied. For UCSFETF, particles were split a factor of 16 upstream of a water absorber column and upstream of the aperture. Here, the radius of the region for Russian roulette was set to 4 times the radius of the aperture and a PC of 0.05 mm was applied. In both setups, the cylindrical symmetry of the proton beam was exploited to position the split particles randomly spaced around the beam axis. When simulating a phase space for subsequent water phantom simulations, efficiency gains between a factor of 19.9  ±  0.1 and 52.21  ±  0.04 for the FHTPC setups and 57.3  ±  0.5 for the UCSFETF setups were obtained. For a phase space used as input for simulations in a patient geometry, the gain was a factor of 78.6  ±  7.5. Lateral-dose curves in water were within the accepted clinical tolerance of 2%, with statistical uncertainties of 0.5% for the two facilities. For the patient geometry and by considering the 2% and 2mm criteria, 98.4% of the voxels showed a gamma index lower than unity. An analysis of the dose distribution resulted in systematic deviations below of 0.88% for 20% of the voxels with dose of 20% of the maximum or more.

A methodological approach to reporting corrected small field relative outputs

PURPOSE

The goal of this work was to set out a methodology for measuring and reporting small field relative output and to assess the application of published correction factors across a population of linear accelerators.

METHODS AND MATERIALS

Measurements were made at 6 MV on five Varian iX accelerators using two PTW T60017 unshielded diodes. Relative output readings and profile measurements were made for nominal square field sizes of side 0.5 to 1.0 cm. The actual in-plane (A) and cross-plane (B) field widths were taken to be the FWHM at the 50% isodose level. An effective field size, defined as √FS eff=A · B, was calculated and is presented as a field size metric. FSeff was used to linearly interpolate between published Monte Carlo (MC) calculated [Formula in text] values to correct for the diode over-response in small fields.

RESULTS

The relative output data reported as a function of the nominal field size were different across the accelerator population by up to nearly 10%. However, using the effective field size for reporting showed that the actual output ratios were consistent across the accelerator population to within the experimental uncertainty of ± 1.0%. Correcting the measured relative output using [Formula in text] at both the nominal and effective field sizes produce output factors that were not identical but differ by much less than the reported experimental and/or MC statistical uncertainties.

CONCLUSIONS

In general, the proposed methodology removes much of the ambiguity in reporting and interpreting small field dosimetric quantities and facilitates a clear dosimetric comparison across a population of linacs.

Geometrical splitting technique to improve the computational efficiency in Monte Carlo calculations for proton therapy

PURPOSE

To present the implementation and validation of a geometrical based variance reduction technique for the calculation of phase space data for proton therapy dose calculation.

METHODS

The treatment heads at the Francis H Burr Proton Therapy Center were modeled with a new Monte Carlo tool (TOPAS based on Geant4). For variance reduction purposes, two particle-splitting planes were implemented. First, the particles were split upstream of the second scatterer or at the second ionization chamber. Then, particles reaching another plane immediately upstream of the field specific aperture were split again. In each case, particles were split by a factor of 8. At the second ionization chamber and at the latter plane, the cylindrical symmetry of the proton beam was exploited to position the split particles at randomly spaced locations rotated around the beam axis. Phase space data in IAEA format were recorded at the treatment head exit and the computational efficiency was calculated. Depth-dose curves and beam profiles were analyzed. Dose distributions were compared for a voxelized water phantom for different treatment fields for both the reference and optimized simulations. In addition, dose in two patients was simulated with and without particle splitting to compare the efficiency and accuracy of the technique.

RESULTS

A normalized computational efficiency gain of a factor of 10-20.3 was reached for phase space calculations for the different treatment head options simulated. Depth-dose curves and beam profiles were in reasonable agreement with the simulation done without splitting: within 1% for depth-dose with an average difference of (0.2 ± 0.4)%, 1 standard deviation, and a 0.3% statistical uncertainty of the simulations in the high dose region; 1.6% for planar fluence with an average difference of (0.4 ± 0.5)% and a statistical uncertainty of 0.3% in the high fluence region. The percentage differences between dose distributions in water for simulations done with and without particle splitting were within the accepted clinical tolerance of 2%, with a 0.4% statistical uncertainty. For the two patient geometries considered, head and prostate, the efficiency gain was 20.9 and 14.7, respectively, with the percentages of voxels with gamma indices lower than unity 98.9% and 99.7%, respectively, using 2% and 2 mm criteria.

CONCLUSIONS

The authors have implemented an efficient variance reduction technique with significant speed improvements for proton Monte Carlo simulations. The method can be transferred to other codes and other treatment heads.

GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources

A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm(2) in water resulted in gamma passing rates of 99.96%, 99.92% and 98.66%, respectively. Relative output factors agreed within 1%. An intensity modulated radiation therapy patient plan using the PSL method resulted in a passing rate of 97%, and was calculated in 50 s (per GPU) compared to 8.4 h (per CPU) for BEAMnrc/DOSXYZnrc.

A PENELOPE-based system for the automated Monte Carlo simulation of clinacs and voxelized geometries-application to far-from-axis fields

PURPOSE

Two new codes, PENEASY and PENEASYLINAC, which automate the Monte Carlo simulation of Varian Clinacs of the 600, 1800, 2100, and 2300 series, together with their electron applicators and multileaf collimators, are introduced. The challenging case of a relatively small and far-from-axis field has been studied with these tools.

METHODS

PENEASY is a modular, general-purpose main program for the PENELOPE Monte Carlo system that includes various source models, tallies and variance-reduction techniques (VRT). The code includes a new geometry model that allows the superposition of voxels and objects limited by quadric surfaces. A variant of the VRT known as particle splitting, called fan splitting, is also introduced. PENEASYLINAC, in turn, automatically generates detailed geometry and configuration files to simulate linacs with PENEASY. These tools are applied to the generation of phase-space files, and of the corresponding absorbed dose distributions in water, for two 6 MV photon beams from a Varian Clinac 2100 C∕D: a 40 × 40 cm(2) centered field; and a 3 × 5 cm(2) field centered at (4.5, -11.5) cm from the beam central axis. This latter configuration implies the largest possible over-traveling values of two of the jaws. Simulation results for the depth dose and lateral profiles at various depths are compared, by using the gamma index, with experimental values obtained with a PTW 31002 ionization chamber. The contribution of several VRTs to the computing speed of the more demanding off-axis case is analyzed.

RESULTS

For the 40 × 40 cm(2) field, the percentages γ(1) and γ(1.2) of voxels with gamma indices (using 0.2 cm and 2% criteria) larger than unity and larger than 1.2 are 0.2% and 0%, respectively. For the 3 × 5 cm(2) field, γ(1) = 0%. These figures indicate an excellent agreement between simulation and experiment. The dose distribution for the off-axis case with voxels of 2.5 × 2.5 × 2.5 mm(3) and an average standard statistical uncertainty of 2% (1σ) is computed in 3.1 h on a single core of a 2.8 GHz Intel Core 2 Duo processor. This result is obtained with the optimal combination of the tested VRTs. In particular, fan splitting for the off-axis case accelerates execution by a factor of 240 with respect to standard particle splitting.

CONCLUSIONS

PENEASY and PENEASYLINAC can simulate the considered Varian Clinacs both in an accurate and efficient manner. Fan splitting is crucial to achieve simulation results for the off-axis field in an affordable amount of CPU time. Work to include Elekta linacs and to develop a graphical interface that will facilitate user input is underway.

The impact of dose calculation algorithms on partial and whole breast radiation treatment plans

Background

This paper compares the calculated dose to target and normal tissues when using pencil beam (PBC), superposition/convolution (AAA) and Monte Carlo (MC) algorithms for whole breast (WBI) and accelerated partial breast irradiation (APBI) treatment plans.

Methods

Plans for 10 patients who met all dosimetry constraints on a prospective APBI protocol when using PBC calculations were recomputed with AAA and MC, keeping the monitor units and beam angles fixed. Similar calculations were performed for WBI plans on the same patients. Doses to target and normal tissue volumes were tested for significance using the paired Student's t-test.

Results

For WBI plans the average dose to target volumes when using PBC calculations was not significantly different than AAA calculations, the average PBC dose to the ipsilateral breast was 10.5% higher than the AAA calculations and the average MC dose to the ipsilateral breast was 11.8% lower than the PBC calculations. For ABPI plans there were no differences in dose to the planning target volume, ipsilateral breast, heart, ipsilateral lung, or contra-lateral lung. Although not significant, the maximum PBC dose to the contra-lateral breast was 1.9% higher than AAA and the PBC dose to the clinical target volume was 2.1% higher than AAA. When WBI technique is switched to APBI, there was significant reduction in dose to the ipsilateral breast when using PBC, a significant reduction in dose to the ipsilateral lung when using AAA, and a significant reduction in dose to the ipsilateral breast and lung and contra-lateral lung when using MC.

Conclusions

There is very good agreement between PBC, AAA and MC for all target and most normal tissues when treating with APBI and WBI and most of the differences in doses to target and normal tissues are not clinically significant. However, a commonly used dosimetry constraint, as recommended by the ASTRO consensus document for APBI, that no point in the contra-lateral breast volume should receive >3% of the prescribed dose needs to be relaxed to >5%.

Ant colony algorithm implementation in electron and photon Monte Carlo transport: application to the commissioning of radiosurgery photon beams

PURPOSE

In this work, the authors describe an approach which has been developed to drive the application of different variance-reduction techniques to the Monte Carlo simulation of photon and electron transport in clinical accelerators.

METHODS

The new approach considers the following techniques: Russian roulette, splitting, a modified version of the directional bremsstrahlung splitting, and the azimuthal particle redistribution. Their application is controlled by an ant colony algorithm based on an importance map.

RESULTS

The procedure has been applied to radiosurgery beams. Specifically, the authors have calculated depth-dose profiles, off-axis ratios, and output factors, quantities usually considered in the commissioning of these beams. The agreement between Monte Carlo results and the corresponding measurements is within approximately 3%/0.3 mm for the central axis percentage depth dose and the dose profiles. The importance map generated in the calculation can be used to discuss simulation details in the different parts of the geometry in a simple way. The simulation CPU times are comparable to those needed within other approaches common in this field.

CONCLUSIONS

The new approach is competitive with those previously used in this kind of problems (PSF generation or source models) and has some practical advantages that make it to be a good tool to simulate the radiation transport in problems where the quantities of interest are difficult to obtain because of low statistics.

Fast Monte Carlo simulation on a voxelized human phantom deformed to a patient

PURPOSE

A method for performing fast simulations of absorbed dose using a patient's computerized tomography (CT) scan without explicitly relying on a calibration curve is presented.

METHODS

The method is based on geometrical deformations performed on a standard voxelized human phantom. This involves spatially transforming the human phantom to align it with the patient CT image. Since the chemical composition and density of each voxel are given in the phantom data, a calibration curve is not used in the proposed method. For this study, the Monte Carlo (MC) code PENELOPE has been used as the simulation of reference. The results obtained with PENELOPE simulations are compared to those obtained with PENFAST and with the collapsed cone convolution algorithm implemented in a commercial treatment planning system.

RESULTS

The comparisons of the absorbed doses calculated with the different algorithms on two patient CTs and the corresponding deformed phantoms show a maximum distance to agreement of 2 mm, and in general, the obtained absorbed dose distributions are compatible within the reached statistical uncertainty. The validity of the deformation method for a broad range of patients is shown using MC simulations in random density phantoms. A PENFAST simulation of a 6 MV photon beam impinging on a patient CT reaches 2% statistical uncertainty in the absorbed dose, in a 0.1 cm3 voxel along the central axis, in 10 min running on a single core of a 2.8 GHz CPU.

CONCLUSIONS

The proposed method of the absorbed dose calculation in a deformed voxelized phantom allows for dosimetric studies in the geometry of a patient CT scan. This is due to the fact that the chemical composition and material density of the phantom are known. Furthermore, simulation using the phantom geometry can provide dosimetric information for each organ. The method can be used for quality assurance procedures. In relation to PENFAST, it is shown that a purely condensed-history algorithm (class I) can be used for absorbed dose estimation in patient CTs.

Monte Carlo simulation of RapidArc radiotherapy delivery

RapidArc radiotherapy technology from Varian Medical Systems is one of the most complex delivery systems currently available, and achieves an entire intensity-modulated radiation therapy (IMRT) treatment in a single gantry rotation about the patient. Three dynamic parameters can be continuously varied to create IMRT dose distributions-the speed of rotation, beam shaping aperture and delivery dose rate. Modeling of RapidArc technology was incorporated within the existing Vancouver Island Monte Carlo (VIMC) system (Zavgorodni et al 2007 Radiother. Oncol. 84 S49, 2008 Proc. 16th Int. Conf. on Medical Physics). This process was named VIMC-Arc and has become an efficient framework for the verification of RapidArc treatment plans. VIMC-Arc is a fully automated system that constructs the Monte Carlo (MC) beam and patient models from a standard RapidArc DICOM dataset, simulates radiation transport, collects the resulting dose and converts the dose into DICOM format for import back into the treatment planning system (TPS). VIMC-Arc accommodates multiple arc IMRT deliveries and models gantry rotation as a series of segments with dynamic MLC motion within each segment. Several verification RapidArc plans were generated by the Eclipse TPS on a water-equivalent cylindrical phantom and re-calculated using VIMC-Arc. This includes one 'typical' RapidArc plan, one plan for dual arc treatment and one plan with 'avoidance' sectors. One RapidArc plan was also calculated on a DICOM patient CT dataset. Statistical uncertainty of MC simulations was kept within 1%. VIMC-Arc produced dose distributions that matched very closely to those calculated by the anisotropic analytical algorithm (AAA) that is used in Eclipse. All plans also demonstrated better than 1% agreement of the dose at the isocenter. This demonstrates the capabilities of our new MC system to model all dosimetric features required for RapidArc dose calculations.