OC-0466 VIRTUAL SOURCE MODELLING OF PHOTON BEAMS FOR MONTE CARLO BASED RADIATION THERAPY TREATMENT PLANNING

Comparison of planned dose on different CT image sets to four-dimensional Monte Carlo dose recalculation using the patient's actual breathing trace for lung stereotactic body radiation therapy

PURPOSE

The need for four-dimensional (4D) treatment planning becomes indispensable when it comes to radiation therapy for moving tumors in the thoracic and abdominal regions. The primary purpose of this study is to combine the actual breathing trace during each individual treatment fraction with the Linac's log file information and Monte Carlo 4D dose calculations. We investigated this workflow on multiple computed tomography (CT) datasets in a clinical environment for stereotactic body radiation therapy (SBRT) treatment planning.

METHODS

We have developed a workflow, which allows us to recalculate absorbed dose to a 4DCT dataset using Monte Carlo calculation methods and accumulate all 4D doses in order to compare them to the planned dose using the Linac's log file, a 4DCT dataset, and the patient's actual breathing curve for each individual fraction. For five lung patients, three-dimensional-conformal radiation therapy (3D-CRT) and volumetric modulated arc treatment (VMAT) treatment plans were generated on four different CT image datasets: a native free-breathing 3DCT, an average intensity projection (AIP) and a maximum intensity projection (MIP) CT both obtained from a 4DCT, and a 3DCT with density overrides based on the 3DCT (DO). The Monte Carlo 4D dose has been calculated on each 4DCT phase using the Linac's log file and the patient's breathing trace as a surrogate for tumor motion and dose was accumulated to the gross tumor volume (GTV) at the 50% breathing phase (end of exhale) using deformable image registration.

RESULTS

Δ D 98 % and Δ D 2 % between 4D dose and planned dose differed largely for 3DCT-based planning and also for DO in three patients. Least dose differences between planned and recalculated dose have been found for AIP and MIP treatment planning which both tend to be superior to DO, but the results indicate a dependency on the breathing variability, tumor motion, and size. An interplay effect has not been observed in the small patient cohort.

CONCLUSIONS

We have developed a workflow which, to our best knowledge, is the first incorporation of the patient breathing trace over the course of all individual treatment fractions with the Linac's log file information and 4D Monte Carlo recalculations of the actual treated dose. Due to the small patient cohort, no clear recommendation on which CT can be used for SBRT treatment planning can be given, but the developed workflow, after adaption for clinical use, could be used to enhance a priori 4D Monte Carlo treatment planning in the future and help with the decision on which CT dataset treatment planning should be carried out.

Agility MLC transmission optimization in the Monaco treatment planning system

The Monaco Monte Carlo treatment planning system uses three-beam model components to achieve accuracy in dose calculation. These components include a virtual source model (VSM), transmission probability filters (TPFs), and an x-ray voxel Monte Carlo (XVMC) engine to calculate the dose in the patient. The aim of this study was to assess the TPF component of the Monaco TPS and optimize the TPF parameters using measurements from an Elekta linear accelerator with an Agility™ multileaf collimator (MLC). The optimization began with all TPF parameters set to their default value. The function of each TPF parameter was characterized and a value was selected that best replicated measurements with the Agility™ MLC. Both vendor provided fields and a set of additional test fields were used to create a rigorous systematic process, which can be used to optimize the TPF parameters. It was found that adjustment of the TPF parameters based on this process resulted in improved point dose measurements and improved 3D gamma analysis pass rates with Octavius 4D. All plans calculated with the optimized beam model had a gamma pass rate of > 95% using criteria of 2% global dose/2 mm distance-to-agreement, while some plans calculated with the default beam model had pass rates as low as 88.4%. For measured point doses, the improvement was particularly noticeable in the low-dose regions of the clinical plans. In these regions, the average difference from the planned dose reduced from 4.4 ± 4.5% to 0.9 ± 2.7% with a coverage factor (k = 2) using the optimized beam model. A step-by-step optimization guide is provided at the end of this study to assist in the optimization of the TPF parameters in the Monaco TPS. Although it is possible to achieve good clinical results by randomly selecting TPF parameter values, it is recommended that the optimization process outlined in this study is followed so that the transmission through the TPF is characterized appropriately.

Validation of a virtual source model for Monte Carlo dose calculations of a flattening filter free linac

PURPOSE

A linac delivering intensity-modulated radiotherapy (IMRT) can benefit from a flattening filter free (FFF) design which offers higher dose rates and reduced accelerator head scatter than for conventional (flattened) delivery. This reduction in scatter simplifies beam modeling, and combining a Monte Carlo dose engine with a FFF accelerator could potentially increase dose calculation accuracy. The objective of this work was to model a FFF machine using an adapted version of a previously published virtual source model (VSM) for Monte Carlo calculations and to verify its accuracy.

METHODS

An Elekta Synergy linear accelerator operating at 6 MV has been modified to enable irradiation both with and without the flattening filter (FF). The VSM has been incorporated into a commercially available treatment planning system (Monaco™ v 3.1) as VSM 1.6. Dosimetric data were measured to commission the treatment planning system (TPS) and the VSM adapted to account for the lack of angular differential absorption and general beam hardening. The model was then tested using standard water phantom measurements and also by creating IMRT plans for a range of clinical cases.

RESULTS

The results show that the VSM implementation handles the FFF beams very well, with an uncertainty between measurement and calculation of <1% which is comparable to conventional flattened beams. All IMRT beams passed standard quality assurance tests with >95% of all points passing gamma analysis (γ < 1) using a 3%/3 mm tolerance.

CONCLUSIONS

The virtual source model for flattened beams was successfully adapted to a flattening filter free beam production. Water phantom and patient specific QA measurements show excellent results, and comparisons of IMRT plans generated in conventional and FFF mode are underway to assess dosimetric uncertainties and possible improvements in dose calculation and delivery.