Impact on the estimated dose of different tissue assignment strategies during partial breast irradiations with INTRABEAM

PURPOSE

Partial breast irradiations with electronic brachytherapy or kilovoltage intraoperative radiotherapy devices such as Axxent or INTRABEAM are becoming more common every day. Breast is mainly composed of glandular and adipose tissues, which are not always clearly disentangled in planning breast CTs. In these cases, breast tissues are replaced with an average soft tissue, or even water. However, at kilovoltage energies, this may lead to large differences in the delivered dose, due to the dominance of photoelectric effect. Therefore, the aim of this work was to study the effect on the dose prescribed in breast with the INTRABEAM device using different soft tissue assignment strategies that would replace the adipose and glandular tissues that constitute the breast in cases where these tissues cannot be adequately distinguished in a CT scan.

METHODS AND MATERIALS

Dose was computed with a Monte Carlo code in five patients with a 3 cm diameter INTRABEAM spherical applicator. Tissues within the breast were assigned following six different strategies: one based on the TG-43 recommendations, representing the whole breast as water of unity density, another one also water-based but with CT derived density, and the other four also based on CT-derived densities, using a single tissue resulting from different mixes of glandular and adipose tissues. These were compared against the reference dose computed in an accurately segmented CT, following TG-186 recommendations. Relative differences and dose ratios between the reference and the other tissue assignment strategies were obtained in three regions of interest inside the breast.

RESULTS AND CONCLUSIONS

Dose planning in water-based tissues was found inaccurate for breast treatment with INTRABEAM, as it would incur in up to 30% under-prescription of dose. If accurate soft tissue assignments in the breast cannot be safely done, a single-tissue composition of 80% adipose and 20% glandular tissue, or even a 100% adipose tissue, would be recommended to avoid dose under-prescription.

Treatment planning of scanned proton beams in RayStation

The use of scanned proton beams in external beam radiation therapy has seen a rapid development over the past decade. This technique places new demands on treatment planning, as compared to conventional photon-based radiation therapy. In this article, several proton specific functions as implemented in the treatment planning system RayStation are presented. We will cover algorithms for energy layer and spot selection, basic optimization including the handling of spot weight limits, optimization of the linear energy transfer (LET) distribution, robust optimization including the special case of 4D optimization, proton arc planning, and automatic planning using deep learning. We will further present the Monte Carlo (MC) proton dose engine in RayStation to some detail, from the material interpretation of the CT data, through the beam model parameterization, to the actual MC transport mechanism. Useful tools for plan evaluation, including robustness evaluation, and the versatile scripting interface are also described. The overall aim of the paper is to give an overview of some of the key proton planning functions in RayStation, with example usages, and at the same time provide the details about the underlying algorithms that previously have not been fully publicly available.

Validation of a deep learning-based material estimation model for Monte Carlo dose calculation in proton therapy

Objective. Computed tomography (CT) to material property conversion dominates proton range uncertainty, impacting the quality of proton treatment planning. Physics-based and machine learning-based methods have been investigated to leverage dual-energy CT (DECT) to predict proton ranges. Recent development includes physics-informed deep learning (DL) for material property inference. This paper aims to develop a framework to validate Monte Carlo dose calculation (MCDC) using CT-based material characterization models.Approach.The proposed framework includes two experiments to validatein vivodose and water equivalent thickness (WET) distributions using anthropomorphic and porcine phantoms. Phantoms were irradiated using anteroposterior proton beams, and the exit doses and residual ranges were measured by MatriXX PT and a multi-layer strip ionization chamber. Two pre-trained conventional and physics-informed residual networks (RN/PRN) were used for mass density inference from DECT. Additional two heuristic material conversion models using single-energy CT (SECT) and DECT were implemented for comparisons. The gamma index was used for dose comparisons with criteria of 3%/3 mm (10% dose threshold).Main results. The phantom study showed that MCDC with PRN achieved mean gamma passing rates of 95.9% and 97.8% for the anthropomorphic and porcine phantoms. The rates were 86.0% and 79.7% for MCDC with the empirical DECT model. WET analyses indicated that the mean WET variations between measurement and simulation were -1.66 mm, -2.48 mm, and -0.06 mm for MCDC using a Hounsfield look-up table with SECT and empirical and PRN models with DECT. Validation experiments indicated that MCDC with PRN achieved consistent dose and WET distributions with measurement.Significance. The proposed framework can be used to identify the optimal CT-based material characterization model for MCDC to improve proton range uncertainty. The framework can systematically verify the accuracy of proton treatment planning, and it can potentially be implemented in the treatment room to be instrumental in online adaptive treatment planning.

A component method to delineate surgical spine implants for proton Monte Carlo dose calculation

PURPOSE

Metallic implants have been correlated to local control failure for spinal sarcoma and chordoma patients due to the uncertainty of implant delineation from computed tomography (CT). Such uncertainty can compromise the proton Monte Carlo dose calculation (MCDC) accuracy. A component method is proposed to determine the dimension and volume of the implants from CT images.

METHODS

The proposed component method leverages the knowledge of surgical implants from medical supply vendors to predefine accurate contours for each implant component, including tulips, screw bodies, lockers, and rods. A retrospective patient study was conducted to demonstrate the feasibility of the method. The reference implant materials and samples were collected from patient medical records and vendors, Medtronic and NuVasive. Additional CT images with extensive features, such as extended Hounsfield units and various reconstruction diameters, were used to quantify the uncertainty of implant contours.

RESULTS

For in vivo patient implant estimation, the reference and the component method differences were 0.35, 0.17, and 0.04 cm³ for tulips, screw bodies, and rods, respectively. The discrepancies by a conventional threshold method were 5.46, 0.76, and 0.05 cm³ , respectively. The mischaracterization of implant materials and dimensions can underdose the clinical target volume coverage by 20 cm³ for a patient with eight lumbar implants. The tulip dominates the dosimetry uncertainty as it can be made from titanium or cobalt-chromium alloys by different vendors.

CONCLUSIONS

A component method was developed and demonstrated using phantom and patient studies with implants. The proposed method provides more accurate implant characterization for proton MCDC and can potentially enhance the treatment quality for proton therapy. The current proof-of-concept study is limited to the implant characterization for lumbar spine. Future investigations could be extended to cervical spine and dental implants for head-and-neck patients where tight margins are required to spare organs at risk.

Investigation of four-dimensional (4D) Monte Carlo dose calculation in real-time tumor tracking stereotatic body radiotherapy for lung cancers

PURPOSE

To investigate the dosimetric variations and radiobiological impacts as a consequence of delivering treatment plans of 3D nature in 4D manner based on the 4D Monte Carlo treatment planning framework implemented on Cyberknife.

METHODS AND MATERIALS

Dose distributions were optimized on reference 3D images at end of exhale phase of a 4DCT dataset for twenty-five lung cancer patients treated with 60 Gy / 3Fx or 48 Gy / 4Fx. Deformable image registrations (DIR) between individual 3DCT images to the reference 3DCT image in the 4DCT study were performed to interpolate doses calculated on multiple anatomical geometries back on to the reference geometry to compose a 4D dose distribution that included the tracking beam motion and organ deformation. The 3D and 4D dose distributions that were initially calculated with the equivalent path-length (EPL) algorithm (3DEPL dose and 4DEPL dose) were recalculated with the Monte Carlo algorithm (3DMC dose and 4DMC dose). Dosimetric variations of V60Gy / 48Gy and D99 of GTV, mean doses to the lung and the heart and maximum dose (D1 ) of the spinal cord as a consequence of tracking beam motion in deforming anatomy, dose calculation algorithm, and both were quantified by the relative change from 4DMC to 3DMC doses, from 4DMC to 4DEPL doses, and from 4DMC to 3DEPL doses, respectively.

RESULTS

Comparing 4DMC to 3DEPL plans, V60Gy / 48Gy and D99 of GTV decreased considerably by 13 ± 22% (mean ± 1SD) and 9.2 ± 5.5 Gy but changes of normal tissue doses were not more than 0.5 Gy on average. The generalized equivalent uniform dose (gEUD) and tumor control probability (TCP) were reduced by 14.3 ± 8.8 Gy and 7.5 ± 5.2%, and normal tissue complication probability (NTCP) for myelopathy and pericarditis were close to zero and NTCP for radiation pneumonitis was reduced by 2.5 ± 4.1%. Comparing 4DMC to 4DEPL plans found decreased V60Gy / 48Gy and D99 by 12.3 ± 21.6% and 7.3 ± 5.3 Gy, the normal tissues doses by 0.5 Gy on average, gEUD and TCP by 13.0 ± 8.6 Gy and 7.1 ± 5.1%. Comparing 4DMC to 3DMC doses, V60Gy / 48Gy and D99 of GTV was reduced by 5.2 ± 8.8 %and 2.6 ± 3.3 Gy, and normal tissues hardly changed from 4DMC to 3DMC doses. The corresponding decreases of gEUD and TCP were 2.8 ± 4.0 Gy and 1.6 ± 2.4%.

CONCLUSION

The large discrepancy between original 3DEPL plan and benchmarking 4DMC plan is predominately due to dose calculation algorithms as the tracking beam motion and organ deformation hardly influenced doses of normal tissues and moderately decreased V60Gy / 48Gy and D99 of GTV. It is worth to make a thoughtful weight of the benefits of full 4D MC dose calculation and consider 3D MC dose calculation as a compromise of 4D MC dose calculation considering the multifold computation time. This article is protected by copyright. All rights reserved.

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

PURPOSE

The 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.

METHODS

We 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 D_5%, D_50% and D_95%.

RESULTS

Interplay induced dose deviations for single fractions were observed and evaluated for IMRT and volumetric arc therapy (σ_D95% 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.

CONCLUSION

It 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.

Detailed tooth models for ICRP mesh-type reference computational phantoms

For use in electron paramagnetic resonance dosimetry with tooth enamel, in the present study, very detailed mesh-type tooth models composed of 198 individual tooth models (i.e. newborn: 20; 1 year: 28; 5 years: 48; 10 years: 38; 15 years: 32; and adult: 32) were developed for each sex. The developed tooth models were then implanted in the International Commission on Radiological Protection pediatric and adult mesh-type reference computational phantoms and used to calculate tooth enamel doses, by Monte Carlo simulations with Geant4, for external photon exposures in several idealized irradiation geometries. The calculated dose values were then compared to investigate the dependency of the enamel dose on the age and sex of the phantom and the sites of the teeth. The results of the present study generally show that, if the photon energy is low (i.e. <0.1 MeV), the enamel dose is significantly affected by the age and sex of the phantom and also the sites of the teeth used for dose calculation; the differences are frequently greater than a few times or even orders of magnitude. However, with a few exceptions, the enamel dose was hardly affected by these parameters for energies between 0.1 and 3 MeV. For energies >3 MeV, moderate differences were observed (i.e., up to a factor of two), due to the existence of dose build-up in the head of the phantom for high-energy photons. The calculated dose values were also compared with those of the previous studies where voxel and mathematical models were used to calculate the enamel doses. The results again show significant differences at low energies, e.g., up to ∼3500 times at 0.015 MeV, which are mainly due to the differences in the level of tooth-modeling detailedness.

Validation of histogram-based virtual source models for different IGRT kV-imaging systems

PURPOSE

Image-guided radiotherapy (IGRT) improves tumor control but its intensive use may entrain late side effects caused by the additional imaging doses. There is a need to better quantify the additional imaging doses, so they can be integrated in the therapeutic workflow. Currently, no dedicated software enables to compute patient-specific imaging doses on a wide range of systems and protocols. As a first step toward this objective, we propose a common methodology to model four different kV-imaging systems used in radiotherapy (Varian's OBI, Elekta's XVI, Brainlab's ExacTrac, and Accuray's Cyberknife) using a new type of virtual source model based on Monte Carlo calculations.

METHODS

We first describe our method to build a simplified description of the photon output, or virtual source models (VSMs), of each imaging system. Instead of being constructed using measurement data, as it is most commonly the case, our VSM is used as the summary of the phase-space files (PSFs) resulting from a first Monte Carlo simulation of the considered x-ray tube. Second, the VSM is used as a photon generator for a second MC simulation in which we compute the dose. Then, the proposed VSM is thoroughly validated against standard MC simulation using PSFs on the XVI system. Last, each modeled system is compared to profiles and depth-dose-curve measurements performed in homogeneous phantom.

RESULTS

Comparisons between PSF-based and VSM-based calculations highlight that VSMs could provide equivalent dose results (within 1% of difference) than PSFs inside the imaging field-of-view (FOV). In contrast, VSMs tend to underestimate (for up to 20%) calculated doses outside of the imaging FOV due to the assumptions underlying the VSM construction. In addition, we showed that the use of VSMs allows reducing calculation time by at least a factor of 2.8. Indeed, for identical simulation times, statistical uncertainties on dose distributions computed using VSMs were much lower than those obtained from PSF-based calculations.

CONCLUSIONS

For each of the four imaging systems, VSMs were successfully validated against measurements in homogeneous phantoms, and are therefore ready to be used for future preclinical studies in heterogeneous or anthropomorphic phantoms. The cross system modeling methodology developed here should enable, later on, to estimate precisely and accurately patient-specific 3D dose maps delivered during a large range of kV-imaging procedures.

A standardized commissioning framework of Monte Carlo dose calculation algorithms for proton pencil beam scanning treatment planning systems

PURPOSE

Treatment planning systems (TPSs) from different vendors can involve different implementations of Monte Carlo dose calculation (MCDC) algorithms for pencil beam scanning (PBS) proton therapy. There are currently no guidelines for validating non-water materials in TPSs. Furthermore, PBS-specific parameters can vary by 1-2 orders of magnitude among different treatment delivery systems (TDSs). This paper proposes a standardized framework on the use of commissioning data and steps to validate TDS-specific parameters and TPS-specific heterogeneity modeling to potentially reduce these uncertainties.

METHODS

A standardized commissioning framework was developed to commission the MCDC algorithms of RayStation 8A and Eclipse AcurosPT v13.7.20 using water and non-water materials. Measurements included Bragg peak depth-dose and lateral spot profiles and scanning field outputs for Varian ProBeam. The phase-space parameters were obtained from in-air measurements and the number of protons per MU from output measurements of 10 × 10 cm² square fields at a 2 cm depth. Spot profiles and various PBS field measurements at additional depths were used to validate TPS. Human tissues in TPS, Gammex phantom materials, and artificial materials were used for the TPS benchmark and validation.

RESULTS

The maximum differences of phase parameters, spot sigma, and divergence between MCDC algorithms are below 4.5 µm and 0.26 mrad in air, respectively. Comparing TPS to measurements at depths, both MC algorithms predict the spot sigma within 0.5 mm uncertainty intervals, the resolution of the measurement device. Beam Configuration in AcurosPT is found to underestimate number of protons per MU by ~2.5% and requires user adjustment to match measured data, while RayStation is within 1% of measurements using Auto model. A solid water phantom was used to validate the range accuracy of non-water materials within 1% in AcurosPT.

CONCLUSIONS

The proposed standardized commissioning framework can detect potential issues during PBS TPS MCDC commissioning processes, and potentially can shorten commissioning time and improve dosimetric accuracies. Secondary MCDC can be used to identify the root sources of disagreement between primary MCDC and measurement.

Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157

Dose calculation plays an important role in the accuracy of radiotherapy treatment planning and beam delivery. The Monte Carlo (MC) method is capable of achieving the highest accuracy in radiotherapy dose calculation and has been implemented in many commercial systems for radiotherapy treatment planning. The objective of this task group was to assist clinical physicists with the potentially complex task of acceptance testing and commissioning MC-based treatment planning systems (TPS) for photon and electron beam dose calculations. This report provides an overview on the general approach of clinical implementation and testing of MC-based TPS with a specific focus on models of clinical photon and electron beams. Different types of beam models are described including those that utilize MC simulation of the treatment head and those that rely on analytical methods and measurements. The trade-off between accuracy and efficiency in the various source-modeling approaches is discussed together with guidelines for acceptance testing of MC-based TPS from the clinical standpoint. Specific recommendations are given on methods and practical procedures to commission clinical beam models for MC-based TPS.

Novel Monte Carlo dose calculation algorithm for robotic radiosurgery with multi leaf collimator: Dosimetric evaluation

PURPOSE

At introduction in 2014, dose calculation for the first MLC on a robotic SRS/SBRT platform was limited to a correction-based Finite-Size Pencil Beam (FSPB) algorithm. We report on the dosimetric accuracy of a novel Monte Carlo (MC) dose calculation algorithm for this MLC, included in the Precision™ treatment planning system.

METHODS

A phantom was built of one slab (5.0 cm) of lung-equivalent material (0.09…0.29 g/cc) enclosed by 3.5 cm (above) and 5 cm (below) slabs of solid water (1.045 g/cc). This was irradiated using rectangular (15.4 × 15.4 mm² to 53.8 × 53.7 mm²) and two irregular MLC-fields. Radiochromic film (EBT3) was positioned perpendicular to the slabs and parallel to the beam. Calculated dose distributions were compared to film measurements using line scans and 2D gamma analysis.

RESULTS

Measured and MC calculated percent depth dose curves showed a characteristic dose drop within the low-density region, which was not correctly reproduced by FSPB. Superior average gamma pass rates (2%/1 mm) were found for MC (91.2 ± 1.5%) compared to FSPB (55.4 ± 2.7%). However, MC calculations exhibited localized anomalies at mass density transitions around 0.15 g/cc, which were traced to a simplification in electron transport. Absence of these anomalies was confirmed in a modified build of the MC engine, which increased gamma pass rates to 96.6 ± 1.2%.

CONCLUSIONS

The novel MC algorithm greatly improves dosimetric accuracy in heterogeneous tissue, potentially expanding the clinical use of robotic radiosurgery with MLC. In-depth, independent validation is paramount to identify and reduce the residual uncertainties in any software solution.

Clinical evaluation for the difference of absorbed doses calculated to medium and calculated to water by Monte Carlo method

BACKGROUND

To evaluate the difference of absorbed doses calculated to medium and to water by a Monte Carlo (MC) algorithm based treatment planning system (TPS), and to assess the potential clinical impact to dose prescription.

METHODS

Thirty patients, 10 nasopharyngeal cancer (NPC), 10 lung cancer and 10 bone metastases cases, were selected for this study. For each case, the treatment plan was generated using a commercial MC based TPS and dose was calculated to medium (D_m). The plan was recalculated for dose to water (D_w) using the same Monitor Units (MU) and control points. The differences between D_m and D_w were qualitatively evaluated by dose-volume parameters and by the plan subtraction method. All plans were measured using the MapCheck2, and gamma passing rates were calculated.

RESULTS

For NPC and Lung cases, the mean differences between D_w and D_m for the targets were less than 2% and the maximum difference was 3.9%. The maximum difference of D_2% for the organs at risk (OARs) was 6.7%. The maximum differences between D_w and D_m were as high as 10% in certain high density regions. For bone metastases cases, the mean differences between D_w and D_m for the targets were more than 2.2% and the maximum difference was 7.1%. The differences between D_w and D_m for the OARs were basically negligible. At 3%&3 mm criterion, the gamma passing rate of D_w plan and D_m plan were close (> 94%).

CONCLUSION

The differences between D_w and D_m has little clinical impact for most clinical cases. In bony structures the differences may become clinically significant if the target/OAR is receiving doses close to its tolerance limit which can potentially influence the selection or rejection of a particular plan.

Dose painting by means of Monte Carlo treatment planning at the voxel level

PURPOSE

To develop a new optimization algorithm to carry out true dose painting by numbers (DPBN) planning based on full Monte Carlo (MC) calculation.

METHODS

Four configurations with different clustering of the voxel values from PET data were proposed. An optimization method at the voxel level under Lineal Programming (LP) formulation was used for an inverse planning and implemented in CARMEN, an in-house Monte Carlo treatment planning system.

RESULTS

Beamlet solutions fulfilled the objectives and did not show significant differences between the different configurations. More differences were observed between the segment solutions. The plan for the dose prescription map without clustering was the better solution.

CONCLUSIONS

LP optimization at voxel level without dose-volume restrictions can carry out true DPBN planning with the MC accuracy.

A benchmarking method to evaluate the accuracy of a commercial proton monte carlo pencil beam scanning treatment planning system

AcurosPT is a Monte Carlo algorithm in the Eclipse 13.7 treatment planning system, which is designed to provide rapid and accurate dose calculations for proton therapy. Computational run-time in minimized by simplifying or eliminating less significant physics processes. In this article, the accuracy of AcurosPT was benchmarked against both measurement and an independent MC calculation, TOPAS. Such a method can be applied to any new MC calculation for the detection of potential inaccuracies. To validate multiple Coulomb scattering (MCS) which affects primary beam broadening, single spot profiles in a Solidwater^® phantom were compared for beams of five selected proton energies between AcurosPT, measurement and TOPAS. The spot Gaussian sigma in AcurosPT was found to increase faster with depth than both measurement and TOPAS, suggesting that the MCS algorithm in AcurosPT overestimates the scattering effect. To validate AcurosPT modeling of the halo component beyond primary beam broadening, field size factors (FSF) were compared for multi-spot profiles measured in a water phantom. The FSF for small field sizes were found to disagree with measurement, with the disagreement increasing with depth. Conversely, TOPAS simulations of the same FSF consistently agreed with measurement to within 1.5%. The disagreement in absolute dose between AcurosPT and measurement was smaller than 2% at the mid-range depth of multi-energy beams. While AcurosPT calculates acceptable dose distributions for typical clinical beams, users are cautioned of potentially larger errors at distal depths due to overestimated MCS and halo implementation.

Full Monte Carlo and measurement-based overall performance assessment of improved clinical implementation of eMC algorithm with emphasis on lower energy range

New version 13.6.23 of the electron Monte Carlo (eMC) algorithm in Varian Eclipse™ treatment planning system has a model for 4MeV electron beam and some general improvements for dose calculation. This study provides the first overall accuracy assessment of this algorithm against full Monte Carlo (MC) simulations for electron beams from 4MeV to 16MeV with most emphasis on the lower energy range. Beams in a homogeneous water phantom and clinical treatment plans were investigated including measurements in the water phantom. Two different material sets were used with full MC: (1) the one applied in the eMC algorithm and (2) the one included in the Eclipse™ for other algorithms. The results of clinical treatment plans were also compared to those of the older eMC version 11.0.31. In the water phantom the dose differences against the full MC were mostly less than 3% with distance-to-agreement (DTA) values within 2mm. Larger discrepancies were obtained in build-up regions, at depths near the maximum electron ranges and with small apertures. For the clinical treatment plans the overall dose differences were mostly within 3% or 2mm with the first material set. Larger differences were observed for a large 4MeV beam entering curved patient surface with extended SSD and also in regions of large dose gradients. Still the DTA values were within 3mm. The discrepancies between the eMC and the full MC were generally larger for the second material set. The version 11.0.31 performed always inferiorly, when compared to the 13.6.23.