MCDE: a new Monte Carlo dose engine for IMRT

Monte Carlo simulation of linac using PRIMO

Background

Monte Carlo simulation is considered as the most accurate method for dose calculation in radiotherapy. PRIMO is a Monte-Carlo program with a user-friendly graphical interface.

Material and method

A VitalBeam with 6MV and 6MV flattening filter free (FFF), equipped with the 120 Millennium multileaf collimator was simulated by PRIMO. We adjusted initial energy, energy full width at half maximum (FWHM), focal spot FWHM, and beam divergence to match the measurements. The water tank and ion-chamber were used in the measurement. Percentage depth dose (PDD) and off axis ratio (OAR) were evaluated with gamma passing rates (GPRs) implemented in PRIMO. PDDs were matched at different widths of standard square fields. OARs were matched at five depths. Transmission factor and dose leaf gap (DLG) were simulated. DLG was measured by electronic portal imaging device using a sweeping gap method.

Result

For the criterion of 2%/2 mm, 1%/2 mm and 1%/1 mm, the GPRs of 6MV PDD were 99.33–100%, 99–100%, and 99–100%, respectively; the GPRs of 6MV FFF PDD were 99.33–100%, 98.99–99.66%, and 97.64–98.99%, respectively; the GPRs of 6MV OAR were 96.4–100%, 90.99–100%, and 85.12–98.62%, respectively; the GPRs of 6MV FFF OAR were 95.15–100%, 89.32–100%, and 87.02–99.74%, respectively. The calculated DLG matched well with the measurement (6MV: 1.36 mm vs. 1.41 mm; 6MV FFF: 1.07 mm vs. 1.03 mm, simulation vs measurement). The transmission factors were similar (6MV: 1.25% vs. 1.32%; 6MV FFF: 0.8% vs. 1.12%, simulation vs measurement).

Conclusion

The calculated PDD, OAR, DLG and transmission factor were all in good agreement with measurements. PRIMO is an independent (with respect to analytical dose calculation algorithm) and accurate Monte Carlo tool.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13014-022-02149-5.

Primo software as a tool for Monte Carlo simulations of intensity modulated radiotherapy: a feasibility study

Background

IMRT provides higher dose conformation to the target and dose sparing to surrounding tissues than 3DCRT. Monte Carlo method in Medical Physics is not a novelty to approach dosimetric problems. A new PENELOPE based code named PRIMO recently was published. The most intriguing features of PRIMO are the user-friendly approach, the stand-alone property and the built-in definition of different linear accelerators models. Nevertheless, IMRT simulations are not yet implemented.

Methods

A Varian Trilogy with a Millennium120 MLC and a Varian Novalis with 120HD MLC were studied. A RW3 multi-slab phantom was irradiated with Gafchromic films inserted between slabs. An Expression 10000XL scanner (Seiko Epson Corp., Nagano, Japan) was used to digitalize the films. PTW-Verisoft software using the global Gamma Function (2%, 2 mm) was used to compare simulated and experimental results.

The primary beam parameters were adjusted to best match reference data previously obtained in a water phantom. Static MLC simulations were performed to validate the MLC models in use. Two Dynamic IMRT preliminary tests were performed with leaves moving with constant and variable speed. A further test of an in phantom delivery of a real IMRT field allowed simulating a clinical-like MLC modulation.

Results

Simulated PDD, X- and Y-profiles in reference conditions showed respectively 100.0%, 100.0% and 99.4% of Gamma points < 1 (2%, 2 mm). Static MLC simulations showed 100.0% of Gamma points < 1 with the 120HD MLC and 99.1% with the Millennium compared with the scanned images.

The fixed speed test showed 99.5 and 98.9% of Gamma points < 1 respectively with two different MLC configuration-sampling algorithms when the 120HD MLC was used. The higher modulation MLC motion simulation showed 99.1% of Gamma points < 1 with respect to the experimental. This result depends on the number of the fields to reproduce the MLC motion, as well as calculation time. The clinical-like simulation showed 96.2% of Gamma points < 1 using the same analysis conditions.

Conclusions

The numerical model of the Varian Trilogy and Novalis in the PRIMO software was validated. The algorithms to simulate MLC motion were considered reliable. A clinical-like procedure was successfully simulated.

Use of an in-house Monte Carlo platform to assess the clinical impact of algorithm-related dose differences on DVH constraints

PURPOSE

The aim of the present work is to evaluate a semi-automatic prescription and validation system of treatment plans for complex delivery techniques, integrated in a Monte Carlo platform, and to investigate the clinical impact of dose differences due to the calculation algorithms, by assessing the changes in DVH constraints.

METHODS

A new prescription module was implemented into the Moderato system, an in-house Monte Carlo platform, with corresponding dose constraints generated depending on the anatomical region and fractionation scheme considered. The platform was tested on 83 cases treated with Cyberknife and Tomotherapy machines, to assess whether dose variations between the re-calculated dose and the Treatment Planning System might impact the dose constraints on the sensitive structures.

RESULTS

Dose differences were small (within 3%) between calculation algorithms in most of the thoracic, pelvic and abdominal cases, both for the Cyberknife and Tomotherapy machines. On the other hand, spinal and head and neck treatments presented a few significant dose deviations for constraints on small volumes, such as the optic pathways and the spinal cord. These differences range from -11% to +6%, inducing constraint violations of up to 8% over the dose limit.

CONCLUSIONS

The Moderato platform offers an interesting tool for plan quality validation, with a prescription module highlighting crucial features in the structures list, and a Monte Carlo dose re-calculation for complex modern techniques. Due to the high number of warnings appearing in some situations, display optimization is required in practice.

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.

Monte Carlo calculation based on hydrogen composition of the tissue for MV photon radiotherapy

The purpose of this study was to demonstrate that Monte Carlo treatment planning systems require tissue characterization (density and composition) as a function of CT number. A discrete set of tissue classes with a specific composition is introduced. In the current work we demonstrate that, for megavoltage photon radiotherapy, only the hydrogen content of the different tissues is of interest. This conclusion might have an impact on MRI‐based dose calculations and on MVCT calibration using tissue substitutes. A stoichiometric calibration was performed, grouping tissues with similar atomic composition into 15 dosimetrically equivalent subsets. To demonstrate the importance of hydrogen, a new scheme was derived, with correct hydrogen content, complemented by oxygen (all elements differing from hydrogen are replaced by oxygen). Mass attenuation coefficients and mass stopping powers for this scheme were calculated and compared to the original scheme. Twenty‐five CyberKnife treatment plans were recalculated by an in‐house developed Monte Carlo system using tissue density and hydrogen content derived from the CT images. The results were compared to Monte Carlo simulations using the original stoichiometric calibration. Between 300 keV and 3 MeV, the relative difference of mass attenuation coefficients is under 1% within all subsets. Between 10 keV and 20 MeV, the relative difference of mass stopping powers goes up to 5% in hard bone and remains below 2% for all other tissue subsets. Dose‐volume histograms (DVHs) of the treatment plans present no visual difference between the two schemes. Relative differences of dose indexes D98,D95,D50,D05,D02, and Dmean were analyzed and a distribution centered around zero and of standard deviation below 2% (3σ) was established. On the other hand, once the hydrogen content is slightly modified, important dose differences are obtained. Monte Carlo dose planning in the field of megavoltage photon radiotherapy is fully achievable using only hydrogen content of tissues, a conclusion that might impact MRI dose calculation, but can also help selecting the optimal tissue substitutes when calibrating MVCT devices.

PACS numbers: 87.55.D‐, 87.55.dk, 87.55.K‐, 87.57.Q‐

Red bone marrow dose calculations in radiotherapy of prostate cancer based on the updated VCH adult male phantom

Red bone marrow (RBM) is an important dose-limiting tissue that has high radiosensitivity but is difficult to identify on clinical medical images. In this study, we investigated dose distribution in RBM for prostate cancer radiotherapy. Four suborgans were identified in the skeleton of the visible Chinese human phantom: cortical bone (CB), trabecular bone (TB), RBM, and yellow bone marrow (YBM). Dose distributions in the phantom were evaluated by the Monte Carlo method. When the left os coxae was taken as the organ-at-risk (OAR), the difference in absorbed dose between RBM and each CB and TB was up to 20%, but was much less (≤3.1%) between RBM and YBM. When the left os coxae and entire bone were both taken as OARs, RBM dose also increased with increasing planning target volume size. The results indicate the validity of using dose to homogeneous bone marrow mixture for estimating dose to RBM when RBM is not available in computational phantoms. In addition, the human skeletal system developed in this study provides a model for considering RBM dose in radiotherapy planning.

Evaluation of uncertainty-based stopping criteria for monte carlo calculations of intensity-modulated radiotherapy and arc therapy patient dose distributions

PURPOSE

To formulate uncertainty-based stopping criteria for Monte Carlo (MC) calculations of intensity-modulated radiotherapy and intensity-modulated arc therapy patient dose distributions and evaluate their influence on MC simulation times and dose characteristics.

METHODS AND MATERIALS

For each structure of interest, stopping criteria were formulated as follows: sigma(rel) <or=sigma(rel,tol) or Dsigma(rel) <or=D(lim)sigma(rel,tol) within >or=95% of the voxels, where sigma(rel) represents the relative statistical uncertainty on the estimated dose, D. The tolerated uncertainty (sigma(rel,tol)) was 2%. The dose limit (D(lim)) equaled the planning target volume (PTV) prescription dose or a dose value related to the organ at risk (OAR) planning constraints. An intensity-modulated radiotherapy-lung, intensity-modulated radiotherapy-ethmoid sinus, and intensity-modulated arc therapy-rectum patient case were studied. The PTV-stopping criteria-based calculations were compared with the PTV+OAR-stopping criteria-based calculations.

RESULTS

The MC dose distributions complied with the PTV-stopping criteria after 14% (lung), 21% (ethmoid), and 12% (rectum) of the simulation times of a 100 million histories reference calculation, and increased to 29%, 44%, and 51%, respectively, by the addition of the OAR-stopping criteria. Dose-volume histograms corresponding to the PTV-stopping criteria, PTV+OAR-stopping criteria, and reference dose calculations were indiscernible. The median local dose differences between the PTV-stopping criteria and the reference calculations amounted to 1.4% (lung), 2.1% (ethmoid), and 2.5% (rectum).

CONCLUSIONS

For the patient cases studied, the MC calculations using PTV-stopping criteria only allowed accurate treatment plan evaluation. The proposed stopping criteria provided a flexible tool to assist MC patient dose calculations. The structures of interest and appropriate values of sigma(rel,tol) and D(lim) should be selected for each patient individually according to the clinical treatment planning goals.

Monte carlo evaluation of the AAA treatment planning algorithm in a heterogeneous multilayer phantom and IMRT clinical treatments for an Elekta SL25 linear accelerator

The Anisotropic Analytical Algorithm (AAA) is a new pencil beam convolution/superposition algorithm proposed by Varian for photon dose calculations. The configuration of AAA depends on linear accelerator design and specifications. The purpose of this study was to investigate the accuracy of AAA for an Elekta SL25 linear accelerator for small fields and intensity modulated radiation therapy (IMRT) treatments in inhomogeneous media. The accuracy of AAA was evaluated in two studies. First, AAA was compared both with Monte Carlo (MC) and the measurements in an inhomogeneous phantom simulating lung equivalent tissues and bone ribs. The algorithm was tested under lateral electronic disequilibrium conditions, using small fields (2 x 2 cm(2)). Good agreement was generally achieved for depth dose and profiles, with deviations generally below 3% in lung inhomogeneities and below 5% at interfaces. However, the effects of attenuation and scattering close to the bone ribs were not fully taken into account by AAA, and small inhomogeneities may lead to planning errors. Second, AAA and MC were compared for IMRT plans in clinical conditions, i.e., dose calculations in a computed tomography scan of a patient. One ethmoid tumor, one orophaxynx and two lung tumors are presented in this paper. Small differences were found between the dose volume histograms. For instance, a 1.7% difference for the mean planning target volume dose was obtained for the ethmoid case. Since better agreement was achieved for the same plans but in homogeneous conditions, these differences must be attributed to the handling of inhomogeneities by AAA. Therefore, inherent assumptions of the algorithm, principally the assumption of independent depth and lateral directions in the scaling of the kernels, were slightly influencing AAA's validity in inhomogeneities. However, AAA showed a good accuracy overall and a great ability to handle small fields in inhomogeneous media compared to other pencil beam convolution algorithms.

Monte Carlo modeling of the ModuLeaf miniature MLC for small field dosimetry and quality assurance of the clinical treatment planning system

The purpose of this investigation was the verification of both the measured data and quality of the implementation of the add-on ModuLeaf miniature multileaf collimator (ML mMLC) into the clinical treatment planning system for conformal stereotactic radiosurgery treatment. To this end the treatment head with ML mMLC was modeled in the BEAMnrc Monte Carlo (MC) code. The 6 MV photon beams used in the setup were first benchmarked with a set of measurements. A total ML mMLC transmission of 1.13% of the 10 x 10 cm2 open field dose was measured and reproduced with the BEAMnrc/DOSXYZnrc code. Correspondence between calculated and measured output factors (OFs) was within 2%. Correspondence between MC and measured profiles was within 2% dose and 2 mm distance, only for the smallest 0.5 x 0.5 cm2 field the results were within 3% dose. In the next step, the MC model was compared with Gafchromic film measurements and Pinnacle(3) 7.4 f (convolution superposition algorithm) calculated dose distributions, using a gamma evaluation comparison, for a multi-beam patient setup delivered to a Lucytrade mark phantom. The gamma evaluation of the MC versus Gafchromic film resulted in 3.4% of points not fulfilling gamma <or= 1 for a 2%/2 mm criterion, the Pinnacle(3) 7.4 f versus Gafchromic results 3.8% and Pinnacle versus MC less than 1%. For specific patients with lesions of 8 cc and 0.2 cc, Monte Carlo and Pinnacle simulations of the plans were performed and compared using DVH evaluation. DVHs corresponded within 2% dose and 2% volume.

Quantification of the impact of MLC modeling and tissue heterogeneities on dynamic IMRT dose calculations

This study quantifies the dose prediction errors (DPEs) in dynamic IMRT dose calculations resulting from (a) use of an intensity matrix to estimate the multi-leaf collimator (MLC) modulated photon fluence (DPE(IGfluence) instead of an explicit MLC particle transport, and (b) handling of tissue heterogeneities (DPE(hetero)) by superposition/convolution (SC) and pencil beam (PB) dose calculation algorithms. Monte Carlo (MC) computed doses are used as reference standards. Eighteen head-and-neck dynamic MLC IMRT treatment plans are investigated. DPEs are evaluated via comparing the dose received by 98% of the GTV (GTV D 98%), the CTV D 95%, the nodal D 90%, the cord and the brainstem D 02%, the parotid D 50%, the parotid mean dose (D (Mean)), and generalized equivalent uniform doses (gEUDs) for the above structures. For the MC-generated intensity grids, DPE(IGfluence) is within +/- 2.1% for all targets and critical structures. The SC algorithm DPE(hetero) is within +/- 3% for 98.3% of the indices tallied, and within +/- 3.4% for all of the tallied indices. The PB algorithm DPE(hetero) is within +/- 3% for 92% of the tallied indices. Statistical equivalence tests indicate that PB DPE(hetero) requires a +/- 3.6% interval to state equivalence with the MC standard, while the intervals are < 1.5% for SC DPE(hetero) and DPE(IGfluence). Overall, these results indicate that SC and MC IMRT dose calculations which use MC-derived intensity matrices for fluence prediction do not introduce significant dose errors compared with full Monte Carlo dose computations; however, PB algorithms may result in clinically significant dose deviations.

Comparison of 6MV and 18MV photons for IMRT treatment of lung cancer

BACKGROUND AND PURPOSE

To compare 6 MV and 18 MV photon intensity modulated radiotherapy (IMRT) for non-small cell lung cancer.

MATERIALS AND METHODS

Doses for a cohort of 10 patients, typical for our department, were computed with a commercially available convolution/superposition (CS) algorithm. Final dose computation was also performed with a dedicated IMRT Monte Carlo dose engine (MCDE).

RESULTS

CS plans showed higher D(95%) (Gy) for the GTV (68.13 vs 67.36, p=0.004) and CTV (67.23 vs 66.87, p=0.028) with 18 than with 6 MV photons. MCDE computations demonstrated higher doses with 6 MV than 18 MV in D(95%) for the PTV (64.62 vs 63.64, p=0.009), PTV(optim) (65.48 vs 64.83, p=0.014) and CTV (66.22 vs 65.64, p=0.027). Dose inhomogeneity was lower with 18 than with 6 MV photons for GTV (0.08 vs 0.09, p=0.007) and CTV (0.10 vs 0.11, p=0.045) in CS but not MCDE plans. 6 MV photons significantly (D(33%); p=0.045) spared the esophagus in MCDE plans. Observed dose differences between lower and higher energy IMRT plans were dependent on the individual patient.

CONCLUSIONS

Selection of photon energy depends on priority ranking of endpoints and individual patients. In the absence of highly accurate dose computation algorithms such as CS and MCDE, 6 MV photons may be the prudent choice.

Comparison of dose-volume histograms of IMRT treatment plans for ethmoid sinus cancer computed by advanced treatment planning systems including Monte Carlo

BACKGROUND AND PURPOSE

To recompute clinical intensity-modulated treatment plans for ethmoid sinus cancer and to compare quantitatively the dose-volume histograms (DVHs) of the planning target volume (PTV) and the optic organs at risk.

MATERIAL AND METHODS

Ten step-and-shoot intensity-modulated treatment plans were enrolled in this study. Large natural and surgical air cavities challenged the calculation systems. Each optimized treatment plan was recalculated by two superposition convolution (TMS and Pinnacle) and a Monte Carlo system (MCDE). To compare the resulting DVHs, a one-way ANOVA for repeated measurements was performed and multiple pairwise comparisons were made.

RESULTS

The tails of the PTV-DVHs were significantly higher for the Monte Carlo system. The DVHs of the critical organs displayed some statistically but not always clinically significant differences. For the individual patients, the three planning systems sometimes reproduced clinically discrepant DVHs that were not significantly different when averaged over all patients.

CONCLUSIONS

Dose to air cavities contains computational uncertainty. As this dose is clinically irrelevant and optimizing it is meaningless, we recommended extracting the air from the PTV when constructing the PTV-DVH. The planning systems considered reproduce DVHs that are significantly different, especially in the tail region of PTV-DVHs.

Accuracy of patient dose calculation for lung IMRT: A comparison of Monte Carlo, convolution/superposition, and pencil beam computations

The accuracy of dose computation within the lungs depends strongly on the performance of the calculation algorithm in regions of electronic disequilibrium that arise near tissue inhomogeneities with large density variations. There is a lack of data evaluating the performance of highly developed analytical dose calculation algorithms compared to Monte Carlo computations in a clinical setting. We compared full Monte Carlo calculations (performed by our Monte Carlo dose engine MCDE) with two different commercial convolution/superposition (CS) implementations (Pinnacle-CS and Helax-TMS's collapsed cone model Helax-CC) and one pencil beam algorithm (Helax-TMS's pencil beam model Helax-PB) for 10 intensity modulated radiation therapy (IMRT) lung cancer patients. Treatment plans were created for two photon beam qualities (6 and 18 MV). For each dose calculation algorithm, patient, and beam quality, the following set of clinically relevant dose-volume values was reported: (i) minimal, median, and maximal dose (Dmin, D50, and Dmax) for the gross tumor and planning target volumes (GTV and PTV); (ii) the volume of the lungs (excluding the GTV) receiving at least 20 and 30 Gy (V20 and V30) and the mean lung dose; (iii) the 33rd percentile dose (D33) and Dmax delivered to the heart and the expanded esophagus; and (iv) Dmax for the expanded spinal cord. Statistical analysis was performed by means of one-way analysis of variance for repeated measurements and Tukey pairwise comparison of means. Pinnacle-CS showed an excellent agreement with MCDE within the target structures, whereas the best correspondence for the organs at risk (OARs) was found between Helax-CC and MCDE. Results from Helax-PB were unsatisfying for both targets and OARs. Additionally, individual patient results were analyzed. Within the target structures, deviations above 5% were found in one patient for the comparison of MCDE and Helax-CC, while all differences between MCDE and Pinnacle-CS were below 5%. For both Pinnacle-CS and Helax-CC, deviations from MCDE above 5% were found within the OARs: within the lungs for two (6 MV) and six (18 MV) patients for Pinnacle-CS, and within other OARs for two patients for Helax-CC (for Dmax of the heart and D33 of the expanded esophagus) but only for 6 MV. For one patient, all four algorithms were used to recompute the dose after replacing all computed tomography voxels within the patient's skin contour by water. This made all differences above 5% between MCDE and the other dose calculation algorithms disappear. Thus, the observed deviations mainly arose from differences in particle transport modeling within the lungs, and the commissioning of the algorithms was adequately performed (or the commissioning was less important for this type of treatment). In conclusion, not one pair of the dose calculation algorithms we investigated could provide results that were consistent within 5% for all 10 patients for the set of clinically relevant dose-volume indices studied. As the results from both CS algorithms differed significantly, care should be taken when evaluating treatment plans as the choice of dose calculation algorithm may influence clinical results. Full Monte Carlo provides a great benchmarking tool for evaluating the performance of other algorithms for patient dose computations.

Denoising of Monte Carlo dose calculations: smoothing capabilities versus introduction of systematic bias

In order to evaluate the performance of denoising algorithms applied to Monte Carlo calculated dose distributions, conventional evaluation methods (rms difference, 1% and 2% difference) can be used. However, it is illustrated that these evaluation methods sometimes underestimate the introduction of bias, since possible bias effects are averaged out over the complete dose distribution. In the present work, a new evaluation method is introduced based on a sliding window superimposed on a difference dose distribution (reference dose-noisy/denoised dose). To illustrate its importance, a new denoising technique (ANRT) is presented based upon a combination of the principles of bilateral filtering and Savitzky-Golay filters. This technique is very conservative in order to limit the introduction of bias in high dose gradient regions. ANRT is compared with IRON for three challenging cases, namely an electron and photon beam impinging on heterogeneous phantoms and two IMRT treatment plans of head-and-neck cancer patients to determine the clinical relevance of the obtained results. For the electron beam case, IRON outperforms ANRT concerning the smoothing capabilities, while no differences in systematic bias are observed. However, for the photon beam case, although ANRT and IRON perform equally well on the conventional evaluation tests (rms difference, 1% and 2% difference), IRON clearly introduces much more bias in the penumbral regions while ANRT seems to introduce no bias at all. When applied to the IMRT patient cases, both denoising methods perform equally well regarding smoothing and bias introduction. This is probably caused by the summation of a large set of different beam segments, decreasing dose gradients compared to a single beam. A reduction in calculation time without introducing large systematic bias can shorten a Monte Carlo treatment planning process considerably and is therefore very useful for the initial trial and error phase of the treatment planning process.

Investigation of geometrical and scoring grid resolution for Monte Carlo dose calculations for IMRT

Monte Carlo based treatment planning of two different patient groups treated with step-and-shoot IMRT (head-and-neck and lung treatments) with different CT resolutions and scoring methods is performed to determine the effect of geometrical and scoring voxel sizes on DVHs and calculation times. Dose scoring is performed in two different ways: directly into geometrical voxels (or in a number of grouped geometrical voxels) or into scoring voxels defined by a separate scoring grid superimposed on the geometrical grid. For the head-and-neck cancer patients, more than 2% difference is noted in the right optical nerve when using voxel dimensions of 4 x 4 x 4 mm3 compared to the reference calculation with 1 x 1 x 2 mm3 voxel dimensions. For the lung cancer patients, 2% difference is noted in the spinal cord when using voxel dimensions of 4 x 4 x 10 mm3 compared to the 1 x 1 x 5 mm3 calculation. An independent scoring grid introduces several advantages. In cases where a relatively high geometrical resolution is required and where the scoring resolution is less important, the number of scoring voxels can be limited while maintaining a high geometrical resolution. This can be achieved either by grouping several geometrical voxels together into scoring voxels or by superimposing a separate scoring grid of spherical voxels with a user-defined radius on the geometrical grid. For the studied lung cancer cases, both methods produce accurate results and introduce a speed increase by a factor of 10-36. In cases where a low geometrical resolution is allowed, but where a high scoring resolution is required, superimposing a separate scoring grid on the geometrical grid allows a reduction in geometrical voxels while maintaining a high scoring resolution. For the studied head-and-neck cancer cases, calculations performed with a geometrical resolution of 2 x 2 x 2 mm3 and a separate scoring grid containing spherical scoring voxels with a radius of 2 mm produce accurate results and introduce a speed increase by a factor of 13. The scoring grid provides an additional degree of freedom for limiting calculation time and memory requirements by selecting optimized scoring and geometrical voxel dimensions in an independent way.

The importance of accurate linear accelerator head modelling for IMRT Monte Carlo calculations

Two Monte Carlo dose engines for radiotherapy treatment planning, namely a beta release of Peregrine and MCDE (Monte Carlo dose engine), were compared with Helax-TMS (collapsed cone superposition convolution) for a head and neck patient for the Elekta SLi plus linear accelerator. Deviations between the beta release of Peregrine and MCDE up to 10% were obtained in the dose volume histogram of the optical chiasm. It was illustrated that the differences are not caused by the particle transport in the patient, but by the modelling of the Elekta SLi plus accelerator head and more specifically the multileaf collimator (MLC). In MCDE two MLC modules (MLCQ and MLCE) were introduced to study the influence of the tongue-and-groove geometry, leaf bank tilt and leakage on the actual dose volume histograms. Differences in integral dose in the optical chiasm up to 3% between the two modules have been obtained. For single small offset beams though the FWHM of lateral profiles obtained with MLCE can differ by more than 1.5 mm from profiles obtained with MLCQ. Therefore, and because the recent version of MLCE is as fast as MLCQ, we advise to use MLCE for modelling the Elekta MLC. Nevertheless there still remains a large difference (up to 10%) between Peregrine and MCDE. By studying small offset beams we have shown that the profiles obtained with Peregrine are shifted, too wide and too flat compared with MCDE and phantom measurements. The overestimated integral doses for small beam segments explain the deviations observed in the dose volume histograms. The Helax-TMS results are in better agreement with MCDE, although deviations exceeding 5% have been observed in the optical chiasm. Monte Carlo dose deviations of more than 10% as found with Peregrine are unacceptable as an influence on the clinical outcome is possible and as the purpose of Monte Carlo treatment planning is to obtain an accuracy of 2%. We would like to emphasize that only the Elekta MLC has been tested in this work, so it is certainly possible that alpha releases of Peregrine provide more accurate results for other accelerators.

DOSSCORE: an accelerated DOSXYZnrc code with an efficient stepping algorithm and scoring grid

DOSSCORE is an accelerated version of DOSXYZnrc that allows photons to cross voxel boundaries of the same medium and utilizes a separate scoring grid superimposed on the geometrical grid. Two different stepping algorithms, the hownear method and the scaling method are implemented in DOSSCORE. The hownear method allows particles to travel larger distances in homogeneous regions where there is no interest in the dose deposition of these particles, whilst the scaling method utilizes a stepping algorithm in which particles are only slowed down by the boundaries of the geometrical voxels and not by the boundaries of the scoring voxels. For CT-based phantoms, only photon ray tracing is applied, which results in a rather modest speed gain of factor 1.2 compared to DOSXYZnrc. The hownear method and scaling method do not increase the speed for CT-based phantoms, but only for homogeneous phantoms and phantoms with a limited number of small heterogeneities. In cases where a small number of scoring voxels are needed, the hownear method performs better than the scaling method, whilst the opposite is true for cases when many scoring voxels are needed. The photon transport is accelerated by almost a factor of 2 for all phantoms (homogeneous, heterogeneous with much homogeneity and CT-based phantoms) compared to DOSXYZnrc. For a small number of scoring voxels, the hownear method is up to a factor of 2.6 and 1.9 faster than DOSXYZnrc for homogeneous and heterogeneous phantoms in the case of photon beams. For an electron beam, a speed gain of factor 2.4 is obtained. For a full scoring grid like the one used in DOSXYZnrc, the scaling method is up to a factor of 2.2 and 1.7 faster than DOSXYZnrc for homogeneous and heterogeneous phantoms in the case of photon beams. For an electron beam, a speed gain of factor 2 is obtained. A speed increase without biasing the results is very relevant. The use of two separate grids, the more efficient stepping algorithms and the accelerated photon transport can be applied to every EGS-based or other Monte Carlo code.