The dose accumulation and the impact of deformable image registration on dose reporting parameters in a moving patient undergoing proton radiotherapy

INTRODUCTION

Potential changes in patient anatomy during proton radiotherapy may lead to a deviation of the delivered dose. A dose estimate can be computed through a deformable image registration (DIR) driven dose accumulation. The present study evaluates the accumulated dose uncertainties in a patient subject to an inadvertent breathing associated motion.

MATERIALS AND METHODS

A virtual lung tumour was inserted into a pair of single participant landmark annotated computed tomography images depicting opposite breathing phases, with the deep inspiration breath-hold the planning reference and the exhale the off-reference geometry. A novel Monte Carlo N-Particle, Version 6 (MCNP6) dose engine was developed, validated and used in treatment plan optimization. Three DIR methods were compared and used to transfer the exhale simulated dose to the reference geometry. Dose conformity and homogeneity measures from International Committee on Radioactivity Units and Measurements (ICRU) reports 78 and 83 were evaluated on simulated dose distributions registered with different DIR algorithms.

RESULTS

The MCNP6 dose engine handled patient-like geometries in reasonable dose calculation times. All registration methods were able to align image associated landmarks to distances, comparable to voxel sizes. A moderate deterioration of ICRU measures was encountered in comparing doses in on and off-reference anatomy. There were statistically significant DIR driven differences in ICRU measures, particularly a 10% difference in the relative D98% for planning tumour volume and in the 3 mm/3% gamma passing rate.

CONCLUSIONS

T he dose accumulation over two anatomies resulted in a DIR driven uncertainty, important in reporting the associated ICRU measures for quality assurance.

A tool for precise calculation of organ doses in voxelised geometries using GAMOS/Geant4 with a graphical user interface

Introduction: The limit of the method of calculating organ doses using voxelised phantoms with a Monte Carlo simulation code is that dose calculation errors in the boundaries of the organs are especially relevant for thin, small or complex geometries. In this report, we describe a tool that helps overcome this problem, accurately calculating organ doses by applying the “parallel geometry” utility feature of Geant4 through the GAMOS framework.

Methods and methods: We have tried to simplify the use of this tool by automatically processing the different DICOM image modalities (CT, PT, ST, NM), and by including the automatic conversion of the structures found in a DICOM RTSTRUCT file into Geant4 volumes that build the parallel geometry. For Nuclear Medicine applications, the DICOM PT, ST or NM images are converted into probabilities of generation of primary particles in each voxel, and the DICOM CT images into materials and material densities. For radiotherapy treatments, the DICOM RTPlan or RTIonPlan may also be used, hence the user only needs to describe the accelerator geometry. We also provide a Graphical User Interface for ease of use by for inexperienced users in Monte Carlo.

Results: We have tested the functionality of the tool with an I-131 thyroid cancer treatment, and obtained the expected energy deposition and dose differences, given that the particle source, geometry and structures are defined.

Conclusions: In summary, we provide an easy-to-use tool to calculate, with high accuracy, organ doses, taking into account their exact geometry as painted by the medical personnel on a voxelised phantom.

Enhanced optimization of volumetric modulated arc therapy plans using Monte Carlo generated beamlets

PURPOSE

A treatment planning system (TPS) produces volumetric modulated arc therapy (VMAT) plans by applying an optimization process to an objective function, followed by an accurate calculation of the final, deliverable dose. However, during the optimization step, a rapid dose calculation algorithm is required, which reduces its accuracy and its representation of the objective function space. Monte Carlo (MC) routines, considered the gold standard in accuracy, are currently too slow for practical comprehensive VMAT optimization. Therefore, we propose a novel approach called enhanced optimization (EO), which employs the TPS VMAT plan as a starting point, and applies small perturbations to nudge the solution closer to a true objective minimum. The perturbations consist of beamlet dose matrices, calculated using MC routines on a distributed-computing framework.

METHODS

DICOM files for clinical VMAT plans files are exported from the TPS and used to generate input files for the EGSnrc MC toolkit. Beamlet doses are calculated using the MC routines, each corresponding to a single multileaf collimator leaf from a single control point traveling 0.5 cm in or out of the field. A typical VMAT plan requires 5000 to 10 000 beamlets, which may be calculated overnight. This results in a ternary-valued objective function, which may use the same clinical objectives as the original VMAT plan. A simple greedy search algorithm is applied to minimize this function and determine the optimal set of ternary variables. The resulting modified control point parameters are imported into the TPS to calculate the final, deliverable dose, and to compare the EO plan with the original. EO was evaluated retrospectively on seven VMAT plans (two adult brain, one pediatric brain, two head and neck, and two prostate). Additionally, the use of stricter objectives was investigated for two of the cases: the left cochlea planning organ at risk (OAR) volume objective for the pediatric brain case, and the rectum objective for a prostate case.

RESULTS

EO produced improved objective scores (by 6% to 60%) and dose-volume histograms (DVH) for the brain plans and the head and neck plans. For each of these plans, the target dose minimum and homogeneity were preserved, while one or more of the OAR DVH's was reduced. Although EO also reduced the objective scores for the prostate plans (by 46% and 79%), their absolute score and DVH improvements were not substantial. The stricter objective on the pediatric brain case resulted in lower dose to the OAR without compromising the target dose. However, the rectum dose in the prostate case could not be improved without reducing dose homogeneity to the planning target volume, suggesting that VMAT prostate cases may already be highly optimized by the TPS.

CONCLUSION

We have developed a novel approach to improving the dose distribution of VMAT plans, which relies on MC calculations to provide small modifications to the control points. This method may be particularly useful for complex treatments in which a certain OAR is of concern and it is difficult for the treatment planner to obtain an acceptable solution with the TPS. Further development will reduce the beamlet computation time and result in more sophisticated EO treatment planning methods.

An Integrated Framework Based on Full Monte Carlo Simulations for Double-Scattering Proton Therapy

PURPOSE

We developed an integrated framework that employs a full Monte Carlo (MC) model for treatment-plan simulations of a passive double-scattering proton system.

MATERIALS AND METHODS

We have previously validated a virtual machine source model for full MC proton-dose calculations by comparing the percentage of depth-dose curves, spread-out Bragg peaks, and lateral profiles against measured commissioning data. This study further expanded our previous work by developing an integrate framework that facilitates its clinical use. Specifically, we have (1) constructed patient-specific applicator and compensator numerically from the plan data and incorporated them into the beamline, (2) created the patient anatomy from the computed tomography image and established the transformation between patient and machine coordinate systems, and (3) developed a graphical user interface to ease the whole process from importing the treatment plan in the Digital Imaging and Communications in Medicine format to parallelization of the MC calculations. End-to-end tests were performed to validate the functionality, and 3 clinical cases were used to demonstrate clinical utility of the framework.

RESULTS

The end-to-end tests demonstrated that the framework functioned correctly for all tested functionality. Comparisons between the treatment planning system calculations and MC results in 3 clinical cases revealed large dose difference up to 17%, especially in the beam penumbra and near the end of beam range. The discrepancy likely originates from a variety of sources, such as the dose algorithms, modeling of the beamline, and the dose metric. The agreement for other regions was acceptable.

CONCLUSION

An integrated framework was developed for full MC simulations of double-scattering proton therapy. It can be a valuable tool for dose verification and plan evaluation.

A Monte Carlo model and its commissioning for the Leksell Gamma Knife Perfexion radiosurgery system

PURPOSE

To develop and commission a Monte Carlo (MC) simulation model for the Leksell Gamma Knife (LGK) Perfexion (PFX) radiosurgery system.

METHOD

We previously established a source model for MC simulations of the LGK PFX for the purpose of the treatment planning system (TPS) dose verification and plan evaluation. To make practical and effective use of the model in clinic, several issues need to be addressed. First, thorough commissioning procedures are needed to ensure the validity of the model parameters, such as the source-to-focus (STF) distance, the source solid angle. Second, an efficient source particle sampling method is required to facilitate dose calculations for multitarget and multishot configurations in patient treatment plans. Third, inseparably, it is interesting to know the dose difference between the two GK TPS algorithms (TMR and convolution) and the MC method in extreme heterogeneous cases resulting from the inhomogeneous effect. We report our recent development in addressing these issues. Phantoms with the frame fiducials were manually created in the format of DICOM CT image to eliminate the uncertainties associated with scanner artifacts and image registration. The created homogeneous phantom was used to calibrate the model parameters to match the output factors with the manufacturer provided data, and the heterogeneous phantom with multilayer materials was used to study the inhomogeneous effect.

RESULTS

The agreement between the MC calculation and TPS was very good for the homogeneous spherical phantom. The difference of the full width at half maximum (FWHM) of the profiles was less than 1 mm except for the profile for 16 mm collimator along z-axis (less than 2 mm). For the extreme heterogeneous test case, it was shown that the TMR algorithm can overestimate the target dose by up to 22% using the measure of dose volume parameter D95. The agreement between the MC method and the TPS convolution method was better (within 3.6%) for the target near the center of phantom, however, discrepancy (up to 10.7%) existed for the target close to the skull. The difference between the two TPS dose algorithms was about 11%.

CONCLUSIONS

Considerable dose difference may result from the effect of heterogeneity, such as in the regions of the air cavities and bones. As the MC method has been extensively used in conventional external beams, it is worthwhile for further investigation in applying the MC method to accurate dose planning in the new GK PFX radiosurgery platform.

Experimental Validation of Monte Carlo Simulations Based on a Virtual Source Model for TomoTherapy in a RANDO Phantom

A virtual source model for Monte Carlo simulations of helical TomoTherapy has been developed previously by the authors. The purpose of this work is to perform experiments in an anthropomorphic (RANDO) phantom with the same order of complexity as in clinical treatments to validate the virtual source model to be used for quality assurance secondary check on TomoTherapy patient planning dose. Helical TomoTherapy involves complex delivery pattern with irregular beam apertures and couch movement during irradiation. Monte Carlo simulation, as the most accurate dose algorithm, is desirable in radiation dosimetry. Current Monte Carlo simulations for helical TomoTherapy adopt the full Monte Carlo model, which includes detailed modeling of individual machine component, and thus, large phase space files are required at different scoring planes. As an alternative approach, we developed a virtual source model without using the large phase space files for the patient dose calculations previously. In this work, we apply the simulation system to recompute the patient doses, which were generated by the treatment planning system in an anthropomorphic phantom to mimic the real patient treatments. We performed thermoluminescence dosimeter point dose and film measurements to compare with Monte Carlo results. Thermoluminescence dosimeter measurements show that the relative difference in both Monte Carlo and treatment planning system is within 3%, with the largest difference less than 5% for both the test plans. The film measurements demonstrated 85.7% and 98.4% passing rate using the 3 mm/3% acceptance criterion for the head and neck and lung cases, respectively. Over 95% passing rate is achieved if 4 mm/4% criterion is applied. For the dose–volume histograms, very good agreement is obtained between the Monte Carlo and treatment planning system method for both cases. The experimental results demonstrate that the virtual source model Monte Carlo system can be a viable option for the accurate dose calculation of helical TomoTherapy.

Development of a Monte Carlo model for treatment planning dose verification of the Leksell Gamma Knife Perfexion radiosurgery system

Detailed Monte Carlo (MC) modeling of the Leksell Gamma Knife (GK) Perfexion (PFX) collimator system is the only accurate ab initio approach appearing in the literature. As a different approach, in this work, we present a MC model based on film measurement. By adjusting the model parameters and fine-tuning the derived fluence map for each individual source to match the manufacturer's ring output factors, we created a reasonable virtual source model for MC simulations to verify treatment planning dose for the GK PFX radiosurgery system. The MC simulation model was commissioned by simple single shots. Dose profiles and both ring and collimator output factors were compared with the treatment planning system (TPS). Good agreement was achieved for dose profiles especially for the region of plateau (< 2%), while larger difference (< 5%) came from the penumbra region. The maximum difference of the calculated output factor was within 0.7%. The model was further validated by a clinical test case. Good agreement was obtained. The DVHs for brainstem and the skull were almost identical and, for the target, the volume covered by the prescription (12.5 Gy to 50% isodose line) was 95.6% from MC calculation versus 100% from the TPS.