Monte Carlo Dose Research Articles

Statistical breathing curve sampling to quantify interplay effects of moving lung tumors in a 4D Monte Carlo dose calculation framework

PurposeThe interplay between respiratory tumor motion and dose application by intensity modulated radiotherapy (IMRT) techniques can potentially lead to undesirable and non-intuitive deviations from the planned dose distribution. We developed a 4D Monte Carlo (MC) dose recalculation framework featuring statistical breathing curve sampling, to precisely simulate the dose distribution for moving target volumes aiming at a comprehensive assessment of interplay effects. MethodsWe implemented a dose accumulation tool that enables dose recalculations of arbitrary breathing curves including the actual breathing curve of the patient. This MC dose recalculation framework is based on linac log-files, facilitating a high temporal resolution up to 0.1 s. By statistical analysis of 128 different breathing curves, interplay susceptibility of different treatment parameters was evaluated for an exemplary patient case. To facilitate prospective clinical application in the treatment planning stage, in which patient breathing curves or linac log-files are not available, we derived a log-file free version with breathing curves generated by a random walk approach. Interplay was quantified by standard deviations σ in D5%, D50% and D95%. ResultsInterplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σD95% up to 1.3 %) showing a decrease with higher fraction doses and an increase with higher MU rates. Interplay effects for conformal treatment techniques were negligible (σ<0.1%). The log-file free version and the random walk generated breathing curves yielded similar results (deviations in σ< 0.1 %) and can be used as substitutes for interplay assessment. ConclusionIt is feasible to combine statistically sampled breathing curves with MC dose calculations. The universality of the presented framework allows comprehensive assessment of interplay effects in retrospective and prospective clinically relevant scenarios.

TransDose: a transformer-based UNet model for fast and accurate dose calculation for MR-LINACs

Objective. To present a transformer-based UNet model (TransDose) for fast and accurate dose calculation for magnetic resonance-linear accelerators (MR-LINACs). Approach. A 2D fluence map from each beam was first projected into a 3D fluence volume and then fed into the TransDose model together with patient density volume and output predicted beam dose. The proposed TransDose model combined a 3D residual UNet with a transformer encoder, where convolutional layers extracted the volumetric spatial features, and the transformer encoder processed the long-range dependencies in a global space. Ninety-eight cases with four tumor sites (brain, nasopharynx, lung, and rectum) treated with fixed-beam intensity-modulated radiotherapy were included in the dataset; 78 cases were used for model training and validation; and 20 cases were used for testing. The ground-truth beam doses were calculated with Monte Carlo (MC) simulations within 1% statistical uncertainty and magnetic field strength B = 1.5 T in the superior and inferior direction. Beam angles from the training and validation datasets were rotated 2–5 times, and doses were recalculated to augment the datasets. Results. The dose-volume histograms and indices between the predicted and MC doses showed good consistency. The average 3D γ-passing rates (3%/2 mm, for dose regions above 10% of maximum dose) were 99.13 ± 0.89% (brain), 98.31 ± 1.92% (nasopharynx), 98.74 ± 0.70% (lung), and 99.28 ± 0.25% (rectum). The average dose calculation time, which included the fluence projection and model prediction, was less than 310 ms for each beam. Significance. We successfully developed a transformer-based UNet dose calculation model—TransDose in magnetic fields. Its accuracy and efficiency indicated its potential for use in online adaptive plan optimization for MR-LINACs.

Development of a Monte Carlo based robustness calculation and evaluation tool.

BackgroundEvaluating plan robustness is a key step in radiotherapy.PurposeTo develop a flexible Monte Carlo (MC)‐based robustness calculation and evaluation tool to assess and quantify dosimetric robustness of intensity‐modulated radiotherapy (IMRT) treatment plans by exploring the impact of systematic and random uncertainties resulting from patient setup, patient anatomy changes, and mechanical limitations of machine components.MethodsThe robustness tool consists of two parts: the first part includes automated MC dose calculation of multiple user‐defined uncertainty scenarios to populate a robustness space. An uncertainty scenario is defined by a certain combination of uncertainties in patient setup, rigid intrafraction motion and in mechanical steering of the following machine components: angles of gantry, collimator, table‐yaw, table‐pitch, table‐roll, translational positions of jaws, multileaf‐collimator (MLC) banks, and single MLC leaves. The Swiss Monte Carlo Plan (SMCP) is integrated in this tool to serve as the backbone for the MC dose calculations incorporating the uncertainties. The calculated dose distributions serve as input for the second part of the tool, handling the quantitative evaluation of the dosimetric impact of the uncertainties. A graphical user interface (GUI) is developed to simultaneously evaluate the uncertainty scenarios according to user‐specified conditions based on dose‐volume histogram (DVH) parameters, fast and exact gamma analysis, and dose differences. Additionally, a robustness index (RI) is introduced with the aim to simultaneously evaluate and condense dosimetric robustness against multiple uncertainties into one number. The RI is defined as the ratio of scenarios passing the conditions on the dose distributions. Weighting of the scenarios in the robustness space is possible to consider their likelihood of occurrence. The robustness tool is applied on IMRT, a volumetric modulated arc therapy (VMAT), a dynamic trajectory radiotherapy (DTRT), and a dynamic mixed beam radiotherapy (DYMBER) plan for a brain case to evaluate the robustness to uncertainties of gantry‐, table‐, collimator angle, MLC, and intrafraction motion. Additionally, the robustness of the IMRT, VMAT, and DTRT plan against patient setup uncertainties are compared. The robustness tool is validated by Delta4 measurements for scenarios including all uncertainty types available.ResultsThe robustness tool performs simultaneous calculation of uncertainty scenarios, and the GUI enables their fast evaluation. For all evaluated plans and uncertainties, the planning target volume (PTV) margin prevented major clinical target volume (CTV) coverage deterioration (maximum observed standard deviation of D98%CTV was 1.3 Gy). OARs close to the PTV experienced larger dosimetric deviations (maximum observed standard deviation of D2%chiasma was 14.5 Gy). Robustness comparison by RI evaluation against patient setup uncertainties revealed better dosimetric robustness of the VMAT and DTRT plans as compared to the IMRT plan. Delta4 validation measurements agreed with calculations by >96% gamma‐passing rate (3% global/2 mm).ConclusionsThe robustness tool was successfully implemented. Calculation and evaluation of uncertainty scenarios with the robustness tool were demonstrated on a brain case. Effects of patient and machine‐specific uncertainties and the combination thereof on the dose distribution are evaluated in a user‐friendly GUI to quantitatively assess and compare treatment plans and their robustness.

Development of a GPU-accelerated Monte Carlo dose calculation module for nuclear medicine, ARCHER-NM: demonstration for a PET/CT imaging procedure

Objective. This paper describes the development and validation of a GPU-accelerated Monte Carlo (MC) dose computing module dedicated to organ dose calculations of individual patients undergoing nuclear medicine (NM) internal radiation exposures involving PET/CT examination. Approach. This new module extends the more-than-10-years-long ARCHER project that developed a GPU-accelerated MC dose engine by adding dedicated NM source-definition features. To validate the code, we compared dose distributions from the point ion source, including 18F, 11C, 15O, and 68Ga, calculated for a water phantom against a well-tested MC code, GATE. To demonstrate the clinical utility and advantage of ARCHER-NM, one set of 18F-FDG PET/CT data for an adult male NM patient is calculated using the new code. Radiosensitive organs in the CT dataset are segmented using a CNN-based tool called DeepViewer. The PET image intensity maps are converted to radioactivity distributions to allow for MC radiation transport dose calculations at the voxel level. The dose rate maps and corresponding statistical uncertainties were calculated at the acquisition time of PET image. Main results. The water-phantom results show excellent agreement, suggesting that the radiation physics module in the new NM code is adequate. The dose rate results of the 18F-FDG PET imaging patient show that ARCHER-NM’s results agree very well with those of the GATE within −2.45% to 2.58% (for a total of 28 organs considered in this study). Most impressively, ARCHER-NM obtains such results in 22 s while it takes GATE about 180 min for the same number of 5 × 108 simulated decay events. Significance. This is the first study presenting GPU-accelerated patient-specific MC internal radiation dose rate calculations for clinically realistic 18F-FDG PET/CT imaging case involving autosegmentation of whole-body PET/CT images. This study suggests that the proposed computing tools—ARCHER-NM— are accurate and fast enough for routine internal dosimetry in NM clinics.

TOPAS Monte Carlo simulation for a scanning proton therapy system in SPHIC

PurposeThis study aims to use TOPAS Monte Carlo (MC) code to model the beamline of a scanned proton therapy system in Shanghai Proton and Heavy Ion Center (SPHIC). This tool can be useful for treatment plan quality assurance. Methods and materialsIn-air lateral profiles of single proton spots at five positions along the Z-axis were measured, which can then be used to calculate the angular variance, spatial angular covariance, and spatial variance at the beam exit position. The mean energy and energy spread of the primary incident beam for 15 energies were tuned by comparing with measured relative integrated depth dose at the central axis. Three spread-out Bragg peak plans in homogeneous water cubes and one plan with a half anthropomorphic head phantom were created to verify the accuracy of the model. In addition, the comparison was also performed to RayStation TPS with an MC dose calculation engine for the plans. ResultsThe average difference of spot sizes was 1.3% for all five energies. For all 15 energies, the average range (D90) difference was 0.04 mm, the mean distal-fall-off (DDF) difference was 0.04 mm, and the mean full width at half maximum (FWHM) difference was 0.10 mm. For the three homogeneous cube plans, a maximum difference of 0.2 mm for the D90 was observed, and the absolute differences in the lateral penumbras for each plan all agreed within 1 mm. For the plan on the anthropomorphic half head phantom, the mean dose deviation is less than 1.2% compared to measurements. ConclusionWe successfully developed an MC model for the proton scanning system used in SPHIC, which can be helpful for dose verification of the Treatment Planning System (TPS) and quality assurance in the future.

Maintaining dosimetric quality when switching to a Monte Carlo dose engine for head and neck volumetric-modulated arc therapy planning.

Head and neck cancers present challenges in radiation treatment planning due to the large number of critical structures near the target(s) and highly heterogeneous tissue composition. While Monte Carlo (MC) dose calculations currently offer the most accurate approximation of dose deposition in tissue, the switch to MC presents challenges in preserving the parameters of care. The differences in dose‐to‐tissue were widely discussed in the literature, but mostly in the context of recalculating the existing plans rather than reoptimizing with the MC dose engine. Also, the target dose homogeneity received less attention. We adhere to strict dose homogeneity objectives in clinical practice. In this study, we started with 21 clinical volumetric‐modulated arc therapy (VMAT) plans previously developed in Pinnacle treatment planning system. Those plans were recalculated “as is” with RayStation (RS) MC algorithm and then reoptimized in RS with both collapsed cone (CC) and MC algorithms. MC statistical uncertainty (0.3%) was selected carefully to balance the dose computation time (1–2 min) with the planning target volume (PTV) dose‐volume histogram (DVH) shape approaching that of a “noise‐free” calculation. When the hot spot in head and neck MC‐based treatment planning is defined as dose to 0.03 cc, it is exceedingly difficult to limit it to 105% of the prescription dose, as we were used to with the CC algorithm. The average hot spot after optimization and calculation with RS MC was statistically significantly higher compared to Pinnacle and RS CC algorithms by 1.2 and 1.0 %, respectively. The 95% confidence interval (CI) observed in this study suggests that in most cases a hot spot of ≤107% is achievable. Compared to the 95% CI for the previous clinical plans recalculated with RS MC “as is” (upper limit 108%), in real terms this result is at least as good or better than the historic plans.

Abstract P3-19-10: Subcutaneous layer dosimetry of the breast and chest wall at clinical beam energies without bolus: A Monte Carlo and analytical anisotropic algorithm (AAA) calculation study

Abstract PURPOSE: Breast skin thickness is 3 mm (1). The subcutaneous layer (SL) lies immediately beneath the skin and is at risk for local recurrence after breast cancer surgery and adjuvant radiotherapy. As the SL lies within the buildup region for megavoltage radiation treatment, placement of bolus for patients receiving chest wall (CW) radiotherapy (RT) is routine at many centers. The dermal toxicity of bolus is well known: in 12 studies of CW RT, the pooled risk of Grade 3 acute toxicity is 9.6% with bolus and 1.2% without bolus (2). Meanwhile, bolus is rarely used after breast-conserving surgery (BCS) RT for patients with similar cancers. This study examines variation in tangential RT dose coverage of the SL in the intact breast and bolus-free CW with clinically relevant photon beam energies using Monte Carlo (MC) calculations and a commercial treatment planning system (TPS). METHODS: Thirty CT datasets from patients without skin involvement were identified. There were two groups of patients: 15 treated with BCS RT and 15 treated with CW RT. In each group, 5-patient subgroups had tangent-beam RT planned without bolus with 6, 10, and 15 MV photons, respectively, using the Analytical Anisotropic Algorithm (AAA) algorithm (v.13.6.23) in Eclipse v.15.6 (Varian Medical Systems Inc., Palo Alto, CA). On each CT, the SL was segmented as a high-resolution shell from 3 to 5 mm below the body contour in the Eclipse TPS v.15.6 (Varian Medical Systems Inc., Palo Alto, CA). A 1x1x1 mm MC dose simulation was performed using EGSnrc code (BEAMnrc/DOSXYZnrc). The MC dose distributions were imported back into the TPS for comparison with AAA calculations. The V95% and V90% for the SL were calculated for each case and the mean V95% and V90% were reported for each subgroup. A t-test was used with a two-sided alpha = 0.05 for statistical analysis. RESULTS: The mean separation increased with use of higher energies for both BCS and CW RT. The MC-calculated mean SL V90% and V95% were higher for CW RT than for BCS RT at each energy. The V90% coverage was 91.5% for CW and 74.4 % for BCS at 6 MV (p&amp;lt;0.001), 89.3% for CW and 61.3% for BCS (p&amp;lt;0.001) at 10 MV and 87.1% for CW and 60.9% for BCS (p&amp;lt;0.001) at 15 MV (Table 1). For SL V95% the CW coverage was higher than the BCS coverage for every energy. For SL V90% at 6 MV, the AAA and MC calculations agreed within 2.5%, with the MC being slightly higher. The agreement between AAA and MC decreased for higher energies with MC reporting higher SL V90% coverage by up to 16.3%. The higher MC-calculated dose to the SL is consistent with the literature (3). CONCLUSION: MC and AAA SL dose calculations agreed well for 6 MV, but AAA underestimated the dose for 10 and 15 MV. For 6-15 MV photons, the MC-calculated dosimetric coverage of the SL is higher for CW RT than BCS RT. Since radiation oncologists are satisfied with the SL coverage by BCS RT, bolus is not needed for CW RT, because, without bolus, CW RT delivers a higher SL dose than BCS RT. REFERENCES:. 1.Pope TL Jr, et al.J Can Assoc Radiol. 1984 Dec;35(4):365-8. PMID: 6526847. 2.Dahn HM, et al. Crit Rev Oncol Hematol. 2021 Jun 5;163:10339. PMID: 34102286. 3.Panettieri V, et al., Radiother Oncol 2009; 93: 94-101 Table 1.Monte Carlo calculated mean V90% and V95% for Breast and Chest Wall for each energyV95%V95%V95%V90%V90%V90%Energy(MV)Chest Wall(Mean)Breast. (Mean)p-valueChest Wall(Mean)Breast. (Mean)p-value661.9%35.1%&amp;lt;0.00191.5%74.4%&amp;lt;0.0011065.2%39.7%&amp;lt;0.00189.3%61.3%&amp;lt;0.0011561.7%38.9%0.01287.1%60.9%&amp;lt;0.001 Citation Format: Dylan Narinesingh, Alan Nichol, Alanah Bergman, Tony Popescu. Subcutaneous layer dosimetry of the breast and chest wall at clinical beam energies without bolus: A Monte Carlo and analytical anisotropic algorithm (AAA) calculation study [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P3-19-10.

Development of a virtual source model for Monte Carlo-based independent dose calculation for varian linac.

Monte Carlo (MC) independent dose calculations are often based on phase‐space files (PSF), as they can accurately represent particle characteristics. PSF generally are large and create a bottleneck in computation time. In addition, the number of independent particles is limited by the PSF, preventing further reduction of statistical uncertainty. The purpose of this study is to develop and validate a virtual source model (VSM) to address these limitations. Particles from existing PSF for the Varian TrueBeam medical linear accelerator 6X, 6XFFF, 10X, and 10XFFF beam configurations were tallied, analyzed, and used to generate a dual‐source photon VSM that includes electron contamination. The particle density distribution, kinetic energy spectrum, particle direction, and the correlations between characteristics were computed. The VSM models for each beam configuration were validated with water phantom measurements as well as clinical test cases against the original PSF. The new VSM requires 67 MB of disk space for each beam configuration, compared to 50 GB for the PSF from which they are based and effectively remove the bottleneck set by the PSF. At 3% MC uncertainty, the VSM approach reduces the calculation time by a factor of 14 on our server. MC doses obtained using the VSM approach were compared against PSF‐generated doses in clinical test cases and measurements in a water phantom using a gamma index analysis. For all tests, the VSMs were in excellent agreement with PSF doses and measurements (>90% passing voxels between doses and measurements). Results of this study indicate the successful derivation and implementation of a VSM model for Varian Linac that significantly saves computation time without sacrificing accuracy for independent dose calculation.

Evaluating the accuracy of electron pencil beam dosimetry based on Monte Carlo simulations using homogeneous and heterogeneous phantoms

PurposeThis study aimed to assess the accuracy of the electron pencil beam algorithm (PBA) regarding Monte Carlo (MC) simulations for irradiating homogeneous and heterogeneous phantoms. MethodsThe PBA program was reproduced in the MATLAB software package. The lateral scattering factors were calculated using MC simulations and imported to the PBA program. The line dose values (profile curves) in various depths for a simple water phantom, a slab phantom with different layers, and a heterogeneous phantom with rods equivalent to bone tissue were calculated using PBA and compared to the MC simulation results for 6, 10, and 12 MeV electron beams. The mean differences and root mean square of error (RMSE) were obtained between the PBA and MC calculations. Furthermore, gamma analysis was used to compare the profile doses of PBA calculations with MC simulations. ResultsThe mean differences between the PBA and MC dose calculations were less than 1% for 10 and 12 MeV electron energies, and lower than 2% for the 6 MeV electron irradiation in all the assessed phantoms. The profile dose calculations showed that the separation of two isodose curves was less than 2 mm in central regions of the fields and less than 3 mm in the fields’ edge/penumbra regions and inhomogeneity interfaces. The gamma pass rate values ranged from 94.1 to 100% (average of 96.4%) in different phantoms, depths, and energy ranges. ConclusionThe PBA provided acceptable accuracy for radiotherapy electron dose calculations in a water phantom, slab phantom (with different materials), and heterogeneous phantom compared to MC dose simulations, as a reference dose calculation method.

Monte Carlo Dose Calculation - A QA Method for SRT and SBRT Plans in Treating Multiple and Small Metastatic Lesions.

To provide accurate and fast 3-D dose verification for hypofractionated stereotactic radiotherapy (SRT/SBRT) of small and multi targets calculated with a Varian Eclipse treatment planning system (TPS) delivered on a Varian accelerator. Ten brain and lung hypofractionated SRT/SBRT linac-based and CyberKnife plans were generated by the Eclipse system for delivery on the accelerator with the Millenium-120 leaf multileaf collimator (MLC) and Multiplan for the CyberKnife machine. These clinical SRT/SBRT plans required accurate quality assurance measurements to obtain absolute point dose and 3-D dose distributions due to the low number of fractions and high fraction doses. For small-field and multi-target plans, the EGS4/MCSIM code was used to calculate the dose distribution. A 0.125 cc ion chamber, a 0.016 cc pin-point chamber and Kodak EDR2 film were used for the measurements and the results were compared with Monte Carlo (MC) calculations. The dosimetry for small-field and multi-target treatment plans is challenging due to the comparable range of secondary electrons and the field sizes defined by SRT/SBRT MLC segments. Our MC simulations can accurately reproduce the linac dose distributions (within 1%/1 mm) three dimensionally. For the clinical SRT/SBRT plans investigated in this work, the MC doses agreed within 3% with ion chamber measurements and within 2%/2 mm with film measurements. The doses calculated by the Eclipse AAA algorithm and Multiplan differed by no more than 5% from MC calculations for small (4–40 cc) Planning Target Volumes (PTVs). MC dose calculation provides accurate and fast 3-D dose verification for hypofractionated SRT for small and multi-target treatment plans generated by a Varian Eclipse TPS on a Varian accelerator and Multiplan treatment planning on the CyberKnife System.

A Systematic Approach to Optimise the Number of Beams for Intensity Modulated Radiotherapy in Pituitary Adenoma using Radiobiological Parameters

Introduction: The number of beams used in a Radiotherapy (RT) plan effects the overall quality of the plan and hence the treatment. The inclusion of radiobiological concepts in finding the optimum number of beams for a particular planning technique has the potential to provide a step ahead of the routine clinical practice where clinical decisions are more dependent on the physical dose parameters. Aim: To optimise the number of beams for Intensity Modulated Radiotherapy (IMRT) plan based on Tumour Control Probability (TCP) and Normal Tissue Complication Probability (NTCP) biological parameters. Materials and Methods: This retrospective study was done on 30 patients with pituitary macro-adenoma who underwent radiotherapy with a prescribed dose of 50.4 Gy in 28 fractions in Delhi State Cancer Institutes, Delhi, India from December 2012 to August 2018. The study data was collected and analysed between June 2018 and April 2020. These patients were treated with step and shoot IMRT technique on ONCORTM Expression linear accelerator (Siemens Healthineers, USA). But, the number of beams used to deliver IMRT plans were different as decided by the medical physicist and hence planner dependent rather than the disease. Being a centrally located disease, a symmetric beam arrangement was adopted for IMRT planning. For dosimetric comparison, three IMRT plans with five, seven, and nine equispaced beams were generated in Monaco treatment planning system for each patient and thus, a total of 90 IMRT plans were created and evaluated. For fair comparison, same IMRT planning parameters were utilized in all three plans of each patient. Monte Carlo (MC) dose calculation algorithm was used for all the plans. Resulting Cumulative Dose Volume Histograms (CDVHs) were exported to MATLAB, where these cDVHs were processed as per Niemierko’s radiobiological model to calculate the values of TCP and NTCP based on the Equivalent Uniform Dose (EUD). After this, the analysis of variance, ANOVA test was conducted over the resulting values of EUD, TCP, and NTCP to assess the difference of quality among plans having different beam arrangements at 0.05 level of significance. Results: The mean tumour control probability (TCP) for IMRT plans with seven and nine beams were found to be 89.0±0.8% and 89.1±0.9% respectively for planning target volume (PTV). These values were not significantly different from each other. However, the mean TCP value for IMRT plans with five beams was found to be 88.4±1.1% for PTV. Further, this TCP value was proved to be significantly lower as compared to IMRT plans with seven and nine beams with a p-value of 0.008 and 0.004 respectively. On the other hand, the mean Normal Tissue Complication Probability (NTCP) was assessed to be less than 1% for all critical organs irrespective of the beam arrangement, indicating almost no probability of radiation induced toxicity in any of the organ. Conclusion: This study concludes that the plan efficiency can be improved by using optimum number of beams for IMRT planning of pituitary adenoma.

Dose kernel decomposition for spot-based radiotherapy treatment planning.

Pre-calculation of accurate dose deposition kernels for treatment planning of spot-based radiotherapies, such as Gamma Knife (GK) and Gamma Pod (GP), can be very time-consuming and may require large data storage with an enormous number of possible spots. We proposed a novel kernel decomposition (KD) model to address accurate and fast (real-time) dose calculation with reduced data storage requirements for spot-based treatment planning. The application of the KD model was demonstrated for clinical GK and GP radiotherapy platforms. The dose deposition kernel at each spot (shot position) is modeled as the product of a shift-invariant kernel based on a reference kernel and spatially variant scale factor. The reference kernel, one for each collimator, is defined at the center of the commissioning phantom for GK and at the center of the treatment target for GP and calculated using the Monte Carlo (MC) method. The spatially variant scale factor is defined as the ratio of the mean tissue maximum ratio (TMR) at the candidate shot position to that at the reference kernel position, and the mean TMR map is calculated within the entire volume through parallel beam ray tracing on the density image followed by averaging over all source directions. The proposed KD dose calculations were compared with the MC method and with the GK and GP treatment planning system (TPS) computations for various shot positions and collimator sizes utilizing a phantom and 14 and 12 clinical plans for GK and GP, respectively. For the phantom study, the KD Gamma index (3%/1mm) passing rates were greater than 99% (median 100%) relative to the MC doses, except for the shots close to the boundary. The passing rates dropped below 90% for 8mm (16mm) shots positioned within ∼1cm (∼2cm) of the boundary. For the clinical GK plans, the KD Gamma passing rates were greater than 99% (median 100%) compared to the MC and greater than 92% (median 99%) compared to the TPS. For the clinical GP plans, the KD Gamma passing rates were greater than 95% (median 98%) compared to the MC and greater than 91% (median 97%) compared to the TPS. The scale factors were calculated in sub-seconds with GPU implementation and only need to be calculated once before treatment plan optimization. The calculation of the dose kernel was also within sub-seconds without requiring beam-by-beam calculation commonly done in the TPS. The proposed model can provide an accurate dose and enables real-time dose and derivative calculations by kernel shifting and scaling without pre-calculating or requiring large data storage for GK and GP dose deposition kernels during treatment planning. This model could be useful for spot-based radiotherapy treatment planning by allowing an efficient global fine search for optimal spots.

Development and Benchmarking of a Monte Carlo Dose Engine for Proton Radiation Therapy

Dose calculation algorithms based on Monte Carlo (MC) simulations play a crucial role in radiotherapy. Here, the development and benchmarking of a novel MC dose engine, MonteRay, is presented for proton therapy aiming to support clinical activity at the Heidelberg Ion Beam Therapy center (HIT) and the development of MRI (magnetic resonance imaging)-guided particle therapy. Comparisons against dosimetric data and gold standard MC FLUKA calculations at different levels of complexity, ranging from single pencil beams in water to patient plans, showed high levels of agreement, validating the physical approach implemented in the dose engine. Additionally, MonteRay has been found to match satisfactorily to FLUKA dose predictions in magnetic fields both in homogeneous and heterogeneous scenarios advocating its use for future MRI-guided proton therapy applications. Benchmarked on 150 MeV protons transported on a 2 × 2 × 2 mm3 grid, MonteRay achieved a high computational throughput and was able to simulate the histories of more than 30,000 primary protons per second on a single CPU core.

Integration of rotatable tandem applicator to conventional ovoid applicator toward complete framework of intensity modulated brachytherapy (IMBT) for cervical cancer

A new tandem applicator with tungsten shield for Ir-192 radiation source used in intra-cavitary brachytherapy (ICBT) enabled intensity modulated brachytherapy (IMBT) in cervical cancer treatment through fluence-modulation by rotating shield. Our previous work employed group-wise and element-wise sparsity constraints for plan optimization of tandem applicator to minimizes the number of activated angles and source dwell points for delivery efficiency. It, however, did not incorporate the ovoid applicators into the optimizing process, which is generally used to prevent cancer recurrence. To integrate ovoid applicators to the new tandem applicator, this work proposed a comprehensive framework that modifies 1) dose deposition matrix for inverse planning, and 2) plan optimizing algorithm. The dose deposition matrix was newly formulated by the Monte-Carlo simulated dose distribution for 10 positions of ovoid applicators, followed by combining those with tandem-associated dose deposition matrix. The plan optimizing algorithm decomposed entire elements into tandem and ovoid applicators, which were governed by different constraints adaptive to specified plan objectives. The integrated framework was compared against conventional ICBT, and IMBT with tandem only for three patients with asymmetric dose distributions. Integrated IMBT framework resulted in the most optimal plans. Including fluence-modulation by rotating-shield outperformed conventional ICBT in dose sparing to critical organs. Adopting ovoid applicators to the optimization yielded more conformal dose distribution around inferior, laterally expanded region of target volume. The resulting plans reduced D5cc and D2cc by 30.9% and 27.8% for critical organs over conventional ICBT, and by 20.6% and 21.5% for target volume over IMBT with tandem only.

Cone Beam CT-Based Online Evaluation in Two Minutes Using a Commercial Treatment Planning Software for Proton Therapy

Daily online treatment evaluation is essential for proton therapy, which is sensitive to daily anatomy and setup uncertainties. We have developed a program based on a commercial treatment planning system (TPS) to streamline the online evaluation process using pre-treatment cone-beam CT (CBCT) images. Herein, we evaluate the speed and accuracy of the tool based on clinical proton plans.Data from 25 previously treated proton patients (7 HN, 11 lung, and 7 prostate) at our institution were evaluated. Corrected CBCT (cCBCT) images were generated using a research version of the TPS, which removes artifacts and calibrates HU for proton dose calculation. A quality assurance simulation CT (QACT) scanned on the same day as the CBCT is deformed to the cCBCT and used as a reference (dQACT). The cCBCT is deformed to the treatment planning CT (TPCT), and all contours on the initial TPCT were deformed to the cCBCT and then rigidly copied to the dQACT. Original clinical treatment plans were applied to both the cCBCT and dQACT, and the doses were calculated with the GPU-based Monte-Carlo dose calculation engine at 0.5% statistical uncertainty. The entire evaluation time (Eval_time) from importing CBCT image to completing final dose calculation for cCBCT was recorded. Plan parameters, including the number of beams (N_bm), proton spot number (N_sp), dose grid voxel numbers (N_voxel), were collected. Pearson correlation coefficient between the Eval_time and the N_bm, N_sp, and N_vosel were calculated. Dosimetric parameters were calculated for the cCBCT and compared to those calculated from the reference dQACT. Dosimetric parameters of interest included the following: for all, CTV D99, D95, and V100, and plan maximum dose (Dmax); for H&N cases, parotid mean dose (P_Dmean) and V30Gy (P_V30), and oral cavity mean dose (C_Dmean); and for H&N and lung cases, spinal cord max dose (SC_Dmax).Mean online Eval_time is 106.6 ± 24.9s for all patients, with HN as the fastest site 87.9 ± 17.5s for HN, 104.5 ± 15.9s for lung, 128.5 ± 28.0s for prostate, P < 0.01. The corresponding (N_bm, N_sp, N_voxel) were (3.9, 7781, 2.6E6) for HN, (3.3, 11080, 2.4E6) for lung, and (3.0, 10484, 3.8E6) for prostate. Eval_time was significantly correlated to N_sp (P = 0.02), but not to N_bm and N_voxel. The absolute differences for CTV D99, D95, V100, plan Dmax, HN P_Dmean, P_V30, C_Dmean, and SC_Dmax are 0.85 ± 0.60%, 0.39 ± 0.22%, 0.48 ± 0.41%, 0.46 ± 0.48%, 0.08 ± 0.05Gy, 0.05 ± 0.06%, 0.21 ± 0.20 Gy, and 0.57 ± 0.53Gy, respectively.Online evaluation can be achieved within 2 minutes for most clinical proton cases (80% in this study) with the commercial TPS. The speed can be further increased with reduced OAR mapping, fine-tuned deformable registration, optimized and reduced spot number in the initial plans, and upgraded computer server. This proposed method may optimize the efficiency and quality of care for proton radiotherapy.

Technical Note: Clinical modeling and validation of breast tissue expander metallic ports in a commercial treatment planning system for proton therapy.

To validate breast tissue expander metallic port (MP) models in a commercial treatment planning system (TPS) in proton pencil beam scanning (PBS) treatments for breast cancer patients with breast tissue expanders. Three types of MPs taken out of a Mentor CPX4, a Natrelle 133, and a PMT Integra breast tissue expanders and a 650 cc saline filled Mentor CPX4 expander were placed on top of acrylic slabs, and scanned using a Siemens Somatom Definition AS Open RT CT scanner. Structure templates for each of the MPs were designed within Eclipse TPS. The CT numbers for the metallic parts were overridden to reflect measured or calculated relative proton stopping powers (RPSPs). Mock targets were contoured in acrylic to represent postmastectomy chest-wall radiation therapy (PMRT) targets. Plans with different beam incident angles were optimized using the Eclipse TPS to deliver uniform prescription dose to the target using Hitachi Probeat-V PBS beams. Eclipse calculated doses and an in-house Monte Carlo (MC) code calculated doses were compared to the measured Gafchromic EBT3 film doses in acrylic. TPS/MC and film dose comparison results showed that (1) 3%/2mm/10% threshold Gamma pass rates were better than 90.8% in the acrylic target region for all plans; (2) comparing TPS and film doses for the individual beam plans in the MP dose shadow areas, the area with dose difference above 5% ([ΔA] 5%) ranged from 1.1 to 5.0 cm2 , and the maximum dose difference ([ΔD] 0.01 cm2 ) ranged from 12.5% to 25.0%; (3) comparing MC and film doses for the individual beam plans in the MP dose shadow areas, the (ΔA) 5% varied from 1.1 to 2.9 cm2 and (ΔD) 0.01 cm2 varied from 8.5% to 24.2%; (4) for a plan composed of three individual beams treating through the Mentor CPX4 expander, the TPS (ΔA) 5% was less than 0.13 cm2 , and the (ΔD) 0.01 cm2 was less than 6% in the MP dose shadow areas. It is feasible to treat patients with tissue expanders using multiple PBS beams using a structure template with CT number overridden to represent the measured/calculated RPSP for MPs for PBS treatment planning. MC dose was more accurate than analytical dose in the areas with high dose gradient caused by the density heterogeneity of the breast tissue expander MPs.

Dose calculation accuracy in particle therapy: Comparing carbon ions with protons.

PurposeThis work presents the validation of an analytical pencil beam dose calculation algorithm in a commercial treatment planning system (TPS) for carbon ions by measurements of dose distributions in heterogeneous phantom geometries. Additionally, a comparison study of carbon ions versus protons is performed considering current best solutions in commercial TPS.MethodsAll treatment plans were optimized and calculated using the RayStation TPS (RaySearch, Sweden). The dose distributions calculated with the TPS were compared with measurements using a 24‐pinpoint ionization chamber array (T31015, PTW, Germany). Tissue‐like inhomogeneities (bone, lung, and soft tissue) were embedded in water, while a target volume of 4 x 4 x 4 cm3 was defined at two different depths behind the heterogeneities. In total, 10 different test cases, with and without range shifter as well as different air gaps, were investigated. Dose distributions inside as well as behind the target volume were evaluated.ResultsInside the target volume, the mean dose difference between calculations and measurements, averaged over all test cases, was 1.6% for carbon ions. This compares well to the final agreement of 1.5% obtained in water at the commissioning stage of the TPS for carbon ions and is also within the clinically acceptable interval of 3%. The mean dose difference and maximal dose difference obtained outside the target area were 1.8% and 13.4%, respectively. The agreement of dose distributions for carbon ions in the target volumes was comparable or better to that between Monte Carlo (MC) dose calculations and measurements for protons. Percentage dose differences of more than 10% were present outside the target area behind bone–lung structures, where the carbon ion calculations systematically over predicted the dose. MC dose calculations for protons were superior to carbon ion beams outside the target volumes.ConclusionThe pencil beam dose calculations for carbon ions in RayStation were found to be in good agreement with dosimetric measurements in heterogeneous geometries for points of interest located within the target. Large local discrepancies behind the target may contribute to incorrect dose predictions for organs at risk.

A simulation study of ionizing radiation acoustic imaging (iRAI) as a real-time dosimetric technique for ultra-high dose rate radiotherapy (UHDR-RT).

Electron-based ultra-high dose rate radiation therapy (UHDR-RT), also known as Flash-RT, has shown the ability to improve the therapeutic index in comparison to conventional radiotherapy (CONV-RT) through increased sparing of normal tissue. However, the extremely high dose rates in UHDR-RT have raised the need for accurate real-time dosimetry tools. This work aims to demonstrate the potential of the emerging technology of Ionized Radiation Acoustic Imaging (iRAI) through simulation studies and investigate its characteristics as a promising relative in vivo dosimetric tool for UHDR-RT. The detection of induced acoustic waves following a single UHDR pulse of a modified 6 MeV 21EX Varian Clinac in a uniform porcine gelatin phantom that is brain-tissue equivalent was simulated for an ideal ultrasound transducer. The full 3D dose distributions in the phantom for a 1×1 cm2 field were simulated using EGSnrc (BEAMnrc∖DOSXYZnrc) Monte Carlo (MC) codes. The relative dosimetry simulations were verified with dose experimental measurements using Gafchromic films. The spatial dose distribution was converted into an initial pressure source spatial distribution using the medium-dependent dose-pressure relation. The MATLAB-based toolbox k-Wave was then used to model the propagation of acoustic waves through the phantom and perform time-reversal (TR)-based imaging reconstruction. The effect of the various linear accelerator (linac) operating parameters, including linac pulse duration and pulse repetition rate (frequency), were investigated as well. The MC dose simulation results agreed with the film measurement results, specifically at the central beam region up to 80% dose within approximately 5% relative error for the central profile region and a local relative error of<6% for percentage dose depth. IRAI-based FWHM of the radiation beam was within approximately 3mm relative to the MC-simulated beam FWHM at the beam entrance. The real-time pressure signal change agreed with the dose changes proving the capability of the iRAI for predicting the beam position. IRAI was tested through 3D simulations of its response to be based on the temporal changes in the linac operating parameters on a dose per pulse basis as expected theoretically from the pressure-dose proportionality. The pressure signal amplitude obtained through 2D simulations was proportional to the dose per pulse. The instantaneous pressure signal amplitude decreases as the linac pulse duration increases, as predicted from the pressure wave generation equations, such that the shorter the linac pulse the higher the signal and the better the temporal (spatial) resolutions of iRAI. The effect of the longer linac pulse duration on the spatial resolution of the 3D constructed iRAI images was corrected for linac pulse deconvolution. This correction has improved the passing rate of the 1%/1mm gamma test criteria, between the pressure-constructed and dosimetric beam characteristics, to as high as 98%. A full simulation workflow was developed for testing the effectiveness of iRAI as a promising relative dosimetry tool for UHDR-RT radiation therapy. IRAI has shown the advantage of 3D dose mapping through the dose signal linearity and, hence, has the potential to be a useful dosimeter at depth dose measurement and beam localization and, hence, potentially for in vivo dosimetry in UHDR-RT.

A NOVEL METHOD FOR ESTIMATING PATIENT-SPECIFIC PRIMARY DOSE IN CONE-BEAM COMPUTED TOMOGRAPHY.

For the purpose of real-time scan-protocol optimisation and patient-specific dose management in cone-beam computed tomography, we introduce a numerical algorithm that estimates the primary dose distributions in reconstructed images. The proposed algorithm is based on the ray-tracing technique and utilises reconstructed voxel data and scanning protocol. The algorithm is validated with the Monte Carlo (MC) and conventional model-based dose reconstruction methods for the simple cylindrical water and anthropomorphic head phantoms. The algorithm shows good agreement with both methods in terms of the zeroth-order x-ray interactions, which exclude the higher-order x-ray interactions at sites distant from the first interactions, and it consumes a significantly lower computational cost compared with the MC method. The differences between the proposed algorithm and the model-based dose reconstruction method as well as the improvement strategies of the algorithm are discussed in detail.

Denoising proton therapy Monte Carlo dose distributions in multiple tumor sites: A comparative neural networks architecture study.

Monte Carlo (MC) algorithms provide accurate modeling of dose calculation by simulating the delivery and interaction of many particles through patient geometry. Fast MC simulations using large number of particles are desirable as they can lead to reliable clinical decisions. In this work, we assume that faster simulations with fewer particles can approximate slower ones by denoising them with deep learning. We use mean squared error (MSE) as loss function to train networks (sNet and dUNet), with 2.5D and 3D setups considering volumes of 7 and 24 slices. Our models are trained on proton therapy MC dose distributions of six different tumor sites acquired from 50 patients. We provide networks with input MC dose distributions simulated using 1×106 particles while keeping 1×109 particles as reference. On average over 10 new patients with different tumor sites, in 2.5D and 3D, our models recover relative residual error on target volume, ΔD95TV of 0.67±0.43% and 1.32±0.87% for sNet vs. 0.83±0.53% and 1.66±0.98% for dUNet, compared to the noisy input at 12.40±4.06%. Moreover, the denoising time for a dose distribution is: < 9s and <1s for sNet vs. < 16s and <1.5s for dUNet in 2.5D and 3D, in comparison to about 100min (MC simulation using 1×109 particles). We propose a fast framework that can successfully denoise MC dose distributions. Starting from MC doses with 1×106 particles only, the networks provide comparable results as MC doses with1×109 particles, reducing simulation time significantly.