Integration of the M6 Cyberknife in the Moderato Monte Carlo platform and prediction of beam parameters using machine learning

PurposeThis work describes the integration of the M6 Cyberknife in the Moderato Monte Carlo platform, and introduces a machine learning method to accelerate the modelling of a linac.MethodsThe MLC-equipped M6 Cyberknife was modelled and integrated in Moderato, our in-house platform offering independent verification of radiotherapy dose distributions. The model was validated by comparing TPS dose distributions with Moderato and by film measurements. Using this model, a machine learning algorithm was trained to find electron beam parameters for other M6 devices, by simulating dose curves with varying spot size and energy. The algorithm was optimized using cross-validation and tested with measurements from other institutions equipped with a M6 Cyberknife.ResultsOptimal agreement in the Monte Carlo model was reached for a monoenergetic electron beam of 6.75 MeV with Gaussian spatial distribution of 2.4 mm FWHM. Clinical plan dose distributions from Moderato agreed within 2% with the TPS, and film measurements confirmed the accuracy of the model. Cross-validation of the prediction algorithm produced mean absolute errors of 0.1 MeV and 0.3 mm for beam energy and spot size respectively. Prediction-based simulated dose curves for other centres agreed within 3% with measurements, except for one device where differences up to 6% were detected.ConclusionsThe M6 Cyberknife was integrated in Moderato and validated through dose re-calculations and film measurements. The prediction algorithm was successfully applied to obtain electron beam parameters for other M6 devices. This method would prove useful to speed up modelling of new machines in Monte Carlo systems.     

Clinical implementation of a Monte Carlo based treatment plan QA platform for validation of Cyberknife and Tomotherapy treatments

PurposeThe main focus of the current paper is the clinical implementation of a Monte Carlo based platform for treatment plan validation for Tomotherapy and Cyberknife, without adding additional tasks to the dosimetry department.MethodsThe Monte Carlo platform consists of C++ classes for the actual functionality and a web based GUI that allows accessing the system using a web browser. Calculations are based on BEAMnrc/DOSXYZnrc and/or GATE and are performed automatically after exporting the dicom data from the treatment planning system. For Cyberknife treatments of moving targets, the log files saved during the treatment (position of robot, internal fiducials and external markers) can be used in combination with the 4D planning CT to reconstruct the actually delivered dose. The Monte Carlo platform is also used for calculation on MRI images, using pseudo-CT conversion.ResultsFor Tomotherapy treatments we obtain an excellent agreement (within 2%) for almost all cases. However, we have been able to detect a problem regarding the CT Hounsfield units definition of the Toshiba Large Bore CT when using a large reconstruction diameter. For Cyberknife treatments we obtain an excellent agreement with the Monte Carlo algorithm of the treatment planning system. For some extreme cases, when treating small lung lesions in low density lung tissue, small differences are obtained due to the different cut-off energy of the secondary electrons.ConclusionsA Monte Carlo based treatment plan validation tool has successfully been implemented in clinical routine and is used to systematically validate all Cyberknife and Tomotherapy plans.     

Validation of the MC-GPU Monte Carlo code against the PENELOPE/penEasy code system and benchmarking against experimental conditions for typical radiation qualities and setups in interventional radiology and cardiology

IntroductionInterventional procedures are associated with potentially high radiation doses to the skin. The 2013/59/EURATOM Directive establishes that the equipment used for interventional radiology must have a device or a feature informing the practitioner of relevant parameters for assessing patient dose at the end of the procedure. Monte Carlo codes of radiation transport are considered to be one of the most reliable tools available to assess doses. However, they are usually too time consuming for use in clinical practice. This work presents the validation of the fast Monte Carlo code MC-GPU for application in interventional radiology.MethodologiesMC-GPU calculations were compared against the well-validated Monte Carlo simulation code PENELOPE/penEasy by simulating the organ dose distribution in a voxelized anthropomorphic phantom. In a second phase, the code was compared against thermoluminescent measurements performed on slab phantoms, both in a calibration laboratory and at a hospital.ResultsThe results obtained from the two simulation codes show very good agreement, differences in the output were within 1%, whereas the calculation time on the MC-GPU was 2500 times shorter. Comparison with measurements is of the order of 10%, within the associated uncertainty.ConclusionsIt has been verified that MC-GPU provides good estimates of the dose when compared to PENELOPE program. It is also shown that it presents very good performance when assessing organ doses in very short times, less than one minute, in real clinical set-ups. Future steps would be to simulate complex procedures with several projections.     

Assessment of out-of-field doses in radiotherapy treatments of paediatric patients using Monte Carlo methods and measurements

PurposeTo assess out-of-field doses in radiotherapy treatments of paediatric patients, using Monte Carlo methods to implement a new model of the linear accelerator validated against measurements and developing a voxelized anthropomorphic paediatric phantom.MethodsCT images of a physical anthropomorphic paediatric phantom were acquired and a dosimetric planning using a TPS was obtained. The CT images were used to perform the voxelization of the physical phantom using the ImageJ software and later implemented in MCNP. In order to validate the Monte Carlo model, dose measurements of the 6 MV beam and Linac with 120 MLC were made in a clinical setting, using ionization chambers and a water phantom. Afterwards TLD measurements in the physical anthropomorphic phantom were performed in order to assess the out-of-field doses in the eyes, thyroid, c-spine, heart and lungs.ResultsThe Monte Carlo model was validated for in-field and out-of-field doses with average relative differences below 3%. The average relative differences between TLD measurements and Monte Carlo is 14,3% whilst the average relative differences between TLD and TPS is 55,8%. Moreover, organs up to 22.5 cm from PTV center show TLD and MCNP6 relative differences and TLD and TPS relative differences up to 21.2% and 92.0%, respectively.ConclusionsOur study provides a novel model that could be used in clinical research, namely in dose evaluation outside the treatment fields. This is particularly relevant, especially in pediatric patients, for studying new radiotherapy treatment techniques, since it can be used to estimate the development of secondary tumours.     

Combined PET/CT for IMRT treatment planning of NSCLC: Contrast-enhanced CT images for Monte Carlo dose calculation

PurposeCombined PET/CT imaging has been proposed as an integral part of radiotherapy treatment planning (TP). Contrast-enhanced CT (ceCT) images are frequently acquired as part of the PET/CT examination to support target delineation. The aim of this dosimetric planning study was to investigate the error introduced by using a ceCT for intensity modulated radiotherapy (IMRT) TP with Monte Carlo dose calculation for non-small cell lung cancer (NSCLC).Material and methodsNine patients with NSCLC prior to chemo-RT were included in this retrospective study. For each patient non-enhanced, low-dose CT (neCT), ceCT and [¹⁸F]-FDG-PET emission data were acquired within a single examination. Manual contouring and TP were performed on the ceCT. An additional set of independent target volumes was auto-segmented in PET images. Dose distributions were recalculated on the neCT. Differences in dosimetric parameters were evaluated.ResultsDose differences in PTV and lungs were small for all patients. The maximum difference in all PTVs when using ceCT images for dose calculation was ?2.1%, whereas the mean difference was less than ?1.7%. Maximum differences in the lungs ranged from ?1.8% to 2.1% (mean: ?0.1%). In four patients an underestimation of the maximum spinal cord dose between 2% and 3.2% was observed, but treatment plans remained clinically acceptable.ConclusionsMonte Carlo based IMRT planning for NSCLC patients using ceCT allows for correct dose calculation. A direct comparison to neCT-based treatment plans revealed only small dose differences. Therefore, ceCT-based TP is clinically safe as long as the maximum acceptable dose to organs at risk is not approached.     

Comparison of the RayStation photon Monte Carlo dose calculation algorithm against measured data under homogeneous and heterogeneous irradiation geometries

PurposeThis work compares Monte Carlo dose calculations performed using the RayStation treatment planning system against data measured on a Varian Truebeam linear accelerator with 6 MV and 10 MV FFF photon beams.MethodsThe dosimetric performance of the RayStation Monte Carlo calculations was evaluated in a variety of irradiation geometries employing homogeneous and heterogeneous phantoms. Profile and depth dose comparisons against measurement were carried out in relative mode using the gamma index as a quantitative measure of similarity within the central high dose regions.ResultsThe results demonstrate that the treatment planning system dose calculation engine agrees with measurement to within 2%/1 mm for more than 95% of the data points in the high dose regions for all test cases. A systematic underestimation was observed at the tail of the profile penumbra and out of field, with mean differences generally <0.5 mm or 1% of curve dose maximum respectively. Out of field agreement varied between evaluated beam models.ConclusionsThe RayStation implementation of photon Monte Carlo dose calculations show good agreement with measured data for the range of scenarios considered in this work and is deemed sufficiently accurate for introduction into clinical use.     

Precision IORT – Image guided intraoperative radiation therapy (igIORT) using online treatment planning including tissue heterogeneity correction

BackgroundTo the present date, IORT has been eye and hand guided without treatment planning and tissue heterogeneity correction. This limits the precision of the application and the precise documentation of the location and the deposited dose in the tissue. Here we present a set-up where we use image guidance by intraoperative cone beam computed tomography (CBCT) for precise online Monte Carlo treatment planning including tissue heterogeneity correction.Materials and methodsAn IORT was performed during balloon kyphoplasty using a dedicated Needle Applicator. An intraoperative CBCT was registered with a pre-op CT. Treatment planning was performed in Radiance using a hybrid Monte Carlo algorithm simulating dose in homogeneous (MCwater) and heterogeneous medium (MChet). Dose distributions on CBCT and pre-op CT were compared with each other. Spinal cord and the metastasis doses were evaluated.ResultsThe MCwater calculations showed a spherical dose distribution as expected. The minimum target dose for the MChet simulations on pre-op CT was increased by 40% while the maximum spinal cord dose was decreased by 35%. Due to the artefacts on the CBCT the comparison between MChet simulations on CBCT and pre-op CT showed differences up to 50% in dose.ConclusionsigIORT and online treatment planning improves the accuracy of IORT. However, the current set-up is limited by CT artefacts. Fusing an intraoperative CBCT with a pre-op CT allows the combination of an accurate dose calculation with the knowledge of the correct source/applicator position. This method can be also used for pre-operative treatment planning followed by image guided surgery.     

Dosimetric effect of tissue heterogeneity for 125I prostate implants

AimTo use Monte Carlo (MC) together with voxel phantoms to analyze the tissue heterogeneity effect in the dose distributions and equivalent uniform dose (EUD) for ¹²⁵I prostate implants.BackgroundDose distribution calculations in low dose-rate brachytherapy are based on the dose deposition around a single source in a water phantom. This formalism does not take into account tissue heterogeneities, interseed attenuation, or finite patient dimensions effects. Tissue composition is especially important due to the photoelectric effect.Materials and methodsThe computed tomographies (CT) of two patients with prostate cancer were used to create voxel phantoms for the MC simulations. An elemental composition and density were assigned to each structure. Densities of the prostate, vesicles, rectum and bladder were determined through the CT electronic densities of 100 patients. The same simulations were performed considering the same phantom as pure water. Results were compared via dose–volume histograms and EUD for the prostate and rectum.ResultsThe mean absorbed doses presented deviations of 3.3–4.0% for the prostate and of 2.3–4.9% for the rectum, when comparing calculations in water with calculations in the heterogeneous phantom. In the calculations in water, the prostate D₉₀ was overestimated by 2.8–3.9% and the rectum D_0.1cc resulted in dose differences of 6–8%. The EUD resulted in an overestimation of 3.5–3.7% for the prostate and of 7.7–8.3% for the rectum.ConclusionsThe deposited dose was consistently overestimated for the simulation in water. In order to increase the accuracy in the determination of dose distributions, especially around the rectum, the introduction of the model-based algorithms is recommended.     

Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident

BackgroundThe excess incidence of thyroid cancer in Ukraine and Belarus observed a few years after the Chernobyl accident is considered to be largely the result of ¹³¹I released from the reactor. Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error.MethodsWe examined dose-response patterns in a thyroid screening prevalence cohort of 11,732 persons aged under 18 at the time of the accident, diagnosed during 1996–2004, who had direct thyroid ¹³¹I activity measurement, and were resident in the most radio-actively contaminated regions of Belarus. Three methods of dose-error correction (regression calibration, Monte Carlo maximum likelihood, Bayesian Markov Chain Monte Carlo) were applied.ResultsThere was a statistically significant (p<0.001) increasing dose-response for prevalent thyroid cancer, irrespective of regression-adjustment method used. Without adjustment for dose errors the excess odds ratio was 1.51 Gy⁻ (95% CI 0.53, 3.86), which was reduced by 13% when regression-calibration adjustment was used, 1.31 Gy⁻ (95% CI 0.47, 3.31). A Monte Carlo maximum likelihood method yielded an excess odds ratio of 1.48 Gy⁻ (95% CI 0.53, 3.87), about 2% lower than the unadjusted analysis. The Bayesian method yielded a maximum posterior excess odds ratio of 1.16 Gy⁻ (95% BCI 0.20, 4.32), 23% lower than the unadjusted analysis. There were borderline significant (p = 0.053–0.078) indications of downward curvature in the dose response, depending on the adjustment methods used. There were also borderline significant (p = 0.102) modifying effects of gender on the radiation dose trend, but no significant modifying effects of age at time of accident, or age at screening as modifiers of dose response (p>0.2).ConclusionsIn summary, the relatively small contribution of unshared classical dose error in the current study results in comparatively modest effects on the regression parameters.     

Multiple-source models for electron beams of a medical linear accelerator using BEAMDP computer code

AimThe aim of this work was to develop multiple-source models for electron beams of the NEPTUN 10PC medical linear accelerator using the BEAMDP computer code.BackgroundOne of the most accurate techniques of radiotherapy dose calculation is the Monte Carlo (MC) simulation of radiation transport, which requires detailed information of the beam in the form of a phase-space file. The computing time required to simulate the beam data and obtain phase-space files from a clinical accelerator is significant. Calculation of dose distributions using multiple-source models is an alternative method to phase-space data as direct input to the dose calculation system.Materials and methodsMonte Carlo simulation of accelerator head was done in which a record was kept of the particle phase-space regarding the details of the particle history. Multiple-source models were built from the phase-space files of Monte Carlo simulations. These simplified beam models were used to generate Monte Carlo dose calculations and to compare those calculations with phase-space data for electron beams.ResultsComparison of the measured and calculated dose distributions using the phase-space files and multiple-source models for three electron beam energies showed that the measured and calculated values match well each other throughout the curves.ConclusionIt was found that dose distributions calculated using both the multiple-source models and the phase-space data agree within 1.3%, demonstrating that the models can be used for dosimetry research purposes and dose calculations in radiotherapy.     

Integration of Diffusion Magnetic Resonance Tractography into tomotherapy radiation treatment planning for high-grade gliomas

IntroductionFractionated radiotherapy in brain tumors is commonly associated with several detrimental effects, largely related to the higher radiosensitivity of the white matter (WM) with respect to gray matter. However, no dose constraints are applied to preserve WM structures at present. Magnetic Resonance (MR) Tractography is the only technique that allows to visualize in vivo the course of WM eloquent tracts in the brain. In this study, the feasibility of integrating MR Tractography in tomotherapy treatment planning has been investigated, with the aim to spare eloquent WM regions from the dose delivered during treatment.MethodsNineteen high grade glioma patients treated with fractionated radiotherapy were enrolled. All the patients underwent pre-treatment MR imaging protocol including Diffusion Tensor Imaging (DTI) acquisitions for MR Tractography analysis. Bilateral tracts involved in several motor, language, cognitive functions were reconstructed and these fiber bundles were integrated into the Tomotherapy Treatment planning system. The original plans without tracts were compared with the optimized plans incorporating the fibers, to evaluate doses to WM structures in the two differently optimized plans.ResultsNo significant differences were found between plans in terms of planning target volume (PTV) coverage between the original plans and the optimized plans incorporating fiber tracts. Comparing the mean as well as the maximal dose (Dmean and Dmax), a significant dose reduction was found for most of the tracts. The dose sparing was more relevant for contralateral tracts (P < 0.0001).ConclusionThe integration of MR Tractography into radiotherapy planning is feasible and beneficial to preserve important WM structures without reducing the clinical goal of radiation treatment.     

Monte Carlo modeling of the Siemens Optifocus multileaf collimator

We have developed a new component module for the BEAMnrc software package, called SMLC, which models the tongue-and-groove structure of the Siemens Optifocus multileaf collimator. The ultimate goal is to perform accurate Monte Carlo simulations of the IMRT treatments carried out with Optifocus. SMLC has been validated by direct geometry checks and by comparing quantitatively the results of simulations performed with it and with the component module VARMLC. Measurements and Monte Carlo simulations of absorbed dose distributions of radiation fields sensitive to the tongue-and-groove effect have been performed to tune the free parameters of SMLC. The measurements cannot be accurately reproduced with VARMLC. Finally, simulations of a typical IMRT field showed that SMLC improves the agreement with experimental measurements with respect to VARMLC in clinically relevant cases.PACS number87.55. K-     

Dosimetric accuracy of three dose calculation algorithms for radiation therapy of in situ non-small cell lung carcinoma

BackgroundStudy determines differences in calculated dose distributions for non-small cell lung carcinoma (NSC LC) patients. NSC LC cases were investigated, being the most common lung cancer treated by radiotherapy in our clinical practice.Materials and methodsA retrospective study of 15 NSCLC patient dose distributions originally calculated using standard superposition (SS) and recalculated using collapsed cone (CC ) and Monte Carlo (MC) based algorithm expressed as dose to medium in medium (MCD_m) and dose to water in medium (MCD_w,) was performed so that prescribed dose covers at least 99% of the gross target volume (GTV). Statistical analysis was performed for differences of conformity index (CI), heterogeneity index (HI), gradient index (GI), dose delivered to 2% of the volume (D_2%), mean dose (D_mean) and percentage of volumes covered by prescribed dose (V_70Gy). For organs at risk (OARs), D_mean and percentage of volume receiving 20 Gy and 5Gy (V_20Gy, V_5Gy) were analysed.ResultsStatistically significant difference for GTVs was observed between MCD_w and SS algorithm in mean dose only. For planning target volumes (PTVs), statistically significant differences were observed in prescribed dose coverage for CC, MCD_m and MCD_w. The differences in mean CI value for the CC algorithm and mean HI value for MCD_m and MCD_w were statistically significant. There is a statistically significant difference in the number of MUs for MCD_m and MCD_w compared to SS.ConclusionAll investigated algorithms succeed in managing the restrictive conditions of the clinical goals. This study shows the drawbacks of the CC algorithm compared to other algorithms used.     

Advanced optimization methods for whole pelvic and local prostate external beam therapy

PurposeRadiation treatment planning inherently involves multiple conflicting planning goals, which makes it a suitable application for multicriteria optimization (MCO). This study investigates a MCO algorithm for VMAT planning (VMAT–MCO) for prostate cancer treatments including pelvic lymph nodes and uses standard inverse VMAT optimization (sVMAT) and Tomotherapy planning as benchmarks.MethodsFor each of ten prostate cancer patients, a two stage plan was generated, consisting of a stage 1 plan delivering 22 Gy to the prostate, and a stage 2 plan delivering 50.4 Gy to the lymph nodes and 56 Gy to the prostate with a simultaneous integrated boost. The single plans were generated by three planning techniques (VMAT–MCO, sVMAT, Tomotherapy) and subsequently compared with respect to plan quality and planning time efficiency.ResultsPlan quality was similar for all techniques, but sVMAT showed slightly better rectum (on average D_mean −7%) and bowel sparing (D_mean −17%) compared to VMAT–MCO in the whole pelvic treatments. Tomotherapy plans exhibited higher bladder dose (D_mean +42%) in stage 1 and lower rectum dose (D_mean −6%) in stage 2 than VMAT–MCO. Compared to manual planning, the planning time with MCO was reduced up to 12 and 38 min for stage 1 and 2 plans, respectively.ConclusionMCO can generate highly conformal prostate VMAT plans with minimal workload in the settings of prostate-only treatments and prostate plus lymph nodes irradiation. In the whole pelvic plan manual VMAT optimization led to slightly improved OAR sparing over VMAT–MCO, whereas for the primary prostate treatment plan quality was equal.     

Clinical verification of treatment planning dose calculation in lung SBRT with GATE Monte Carlo simulation code

PurposeThis study aims to use GATE/Geant4 simulation code to evaluate the performance of dose calculations with Anisotropic Analytical Algorithm (AAA) in the context of lung SBRT for complex treatments considering images of patients.MethodsFour cases of non-small cell lung cancer treated with SBRT were selected for this study. Irradiation plans were created with AAA and recalculated end to end using Monte Carlo (MC) method maintaining field configurations identical to the original plans. Each treatment plan was evaluated in terms of PTV and organs at risk (OARs) using dose-volume histograms (DVH). Dosimetric parameters obtained from DVHs were used to compare AAA and MC.ResultsThe comparison between the AAA and MC DVH using gamma analysis with the passing criteria of 3%/3% showed an average passing rate of more than 90% for the PTV structure and 97% for the OARs. Tightening the criteria to 2%/2% showed a reduction in the average passing rate of the PTV to 86%. The agreement between the AAA and MC dose calculations for PTV dosimetric parameters (V₁₀₀; V₉₀; Homogeneity index; maximum, minimum and mean dose; CI_Paddick and D_2cm) was within 18.4%. For OARs, the biggest differences were observed in the spinal cord and the great vessels.ConclusionsIn general, we did not find significant differences between AAA and MC. The results indicate that AAA could be used in complex SBRT cases that involve a larger number of small treatment fields in the presence of tissue heterogeneities.