Compressed voxels for high-resolution phantom simulations in GATE

The influence of small field output factors simulated uncertainties on the calculated dose in VMAT plans for brain metastases: a multicentre study

OBJECTIVES

This multicentric study was carried out to investigate the impact of small field output factors (OFs) inaccuracies on the calculated dose in volumetric arctherapy (VMAT) radiosurgery brain plans.

METHODS

Nine centres, realised the same five VMAT plans with common planning rules and their specific clinical equipment Linac/treatment planning system commissioned with their OFs measured values (OFbaseline). In order to simulate OFs errors, two new OFs sets were generated for each centre by changing only the OFs values of the smallest field sizes (from 3.2 × 3.2 cm² to 1 × 1 cm²) with well-defined amounts (positive and negative). Consequently, two virtual machines for each centre were recommissioned using the new OFs and the percentage dose differences ΔD (%) between the baseline plans and the same plans recalculated using the incremented (OFup) and decremented (OFdown) values were evaluated. The ΔD (%) were analysed in terms of planning target volume (PTV) coverage and organs at risk (OARs) sparing at selected dose/volume points.

RESULTS

The plans recalculated with OFdown sets resulted in higher variation of doses than baseline within 1.6 and 3.4% to PTVs and OARs respectively; while the plans with OFup sets resulted in lower variation within 1.3% to both PTVs and OARs. Our analysis highlights that OFs variations affect calculated dose depending on the algorithm and on the delivery mode (field jaw/MLC-defined). The Monte Carlo (MC) algorithm resulted significantly more sensitive to OFs variations than all of the other algorithms.

CONCLUSION

The aim of our study was to evaluate how small fields OFs inaccuracies can affect the dose calculation in VMAT brain radiosurgery treatments plans. It was observed that simulated OFs errors, return dosimetric calculation accuracies within the 3% between concurrent plans analysed in terms of percentage dose differences at selected dose/volume points of the PTV coverage and OARs sparing.

ADVANCES IN KNOWLEDGE

First multicentre study involving different Planning/Linacs about undetectable errors in commissioning output factor for small fields.

Development and validation of a full model of a four-headed neuroimaging single-photon emission computed tomography scanner

Objective

The Nucline X-Ring 4R is a four-headed gamma camera dedicated to neuroimaging. In this paper, we describe and validate a GATE (Geant4 Application for Tomographic Emission) model of the Nucline X-Ring 4R.

Materials and methods

Images produced during model simulations were compared with those acquired experimentally to confirm the model was an accurate representation of the scanner. The most commonly reported measurements used to validate a GATE model include energy resolution, spatial resolution and sensitivity. In addition to the commonly reported static imaging measures, single-photon emission computed tomography (SPECT) spatial resolution was investigated to confirm that the model produces similar SPECT images to the experimental output.

Results

The experimental full-width at half-maximum was calculated to be 12.3 keV, which corresponds to an energy resolution of 8.8%. The simulated full-width at half-maximum was measured to be 12 keV, giving an energy resolution of 8.6%. The average spatial resolutions were found to be well matched (5.69 mm – simulated and 5.64 mm – experimental). However, the sensitivity was overestimated using the GATE model (47.8 and 54.3 cps/MBq) compared with the values obtained experimentally (42.7 and 44.3 cps/MBq). Finally, the simulated SPECT spatial resolution images were found to produce qualitatively comparable results.

Conclusion

The model developed has been shown to produce similar results and images to those obtained experimentally. This model has the potential to simulate patient scans with the aim of improving patient care by optimizing scanner protocols.

Improved Woodcock tracking on Monte Carlo simulations for medical applications

This paper presents a new variance reduction technique called super voxel Woodcock (SVW), which combines Woodcock tracking technique with the super voxel concept, used in computer graphics. It consists in grouping the voxels of the volume in a super voxel grid (pre-processing step) by associating to each of the super voxels a local value of the most attenuate medium which will later serve to the interaction distances sampling. SVW allows reducing the sampling of the particle path while a high-density material is present within the simulated phantom. In order to evaluate the performance of the SVW method compare to both standard and Woodcock tracking methods, algorithms were implemented within the same GPU MCS framework GGEMS. This method improves the performance of the standard Woodcock method by a factor of 4.5 and 4.3 for x-ray imaging application and intraoperative radiotherapy respectively. The proposed SVW method did not introduce any bias on the simulations.

Multi-scale hybrid models for radiopharmaceutical dosimetry with Geant4

The accuracy of radiopharmaceutical absorbed dose distributions computed through Monte Carlo (MC) simulations is mostly limited by the low spatial resolution of 3D imaging techniques used to define the simulation geometry. This issue also persists with the implementation of realistic hybrid models built using polygonal mesh and/or NURBS as they require to be simulated in their voxel form in order to reduce computation times. The existing trade-off between voxel size and simulation speed leads on one side, in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs walls and, on the other, to unnecessarily detailed voxelization of large, homogeneous structures.We developed a set of computational tools based on VTK and Geant4 in order to build multi-resolution organ models. Our aim is to use different voxel sizes to represent anatomical regions of different clinical relevance: the MC implementation of these models is expected to improve spatial resolution in specific anatomical structures without significantly affecting simulation speed. Here we present the tools developed through a proof of principle example. Our approach is validated against the standard Geant4 technique for the simulation of voxel geometries.

Toward an organ based dose prescription method for the improved accuracy of murine dose in orthovoltage x-ray irradiators

PURPOSE

Accurate dosimetry is essential when irradiating mice to ensure that functional and molecular endpoints are well understood for the radiation dose delivered. Conventional methods of prescribing dose in mice involve the use of a single dose rate measurement and assume a uniform average dose throughout all organs of the entire mouse. Here, the authors report the individual average organ dose values for the irradiation of a 12, 23, and 33 g mouse on a 320 kVp x-ray irradiator and calculate the resulting error from using conventional dose prescription methods.

METHODS

Organ doses were simulated in the Geant4 application for tomographic emission toolkit using the MOBY mouse whole-body phantom. Dosimetry was performed for three beams utilizing filters A (1.65 mm Al), B (2.0 mm Al), and C (0.1 mm Cu + 2.5 mm Al), respectively. In addition, simulated x-ray spectra were validated with physical half-value layer measurements.

RESULTS

Average doses in soft-tissue organs were found to vary by as much as 23%-32% depending on the filter. Compared to filters A and B, filter C provided the hardest beam and had the lowest variation in soft-tissue average organ doses across all mouse sizes, with a difference of 23% for the median mouse size of 23 g.

CONCLUSIONS

This work suggests a new dose prescription method in small animal dosimetry: it presents a departure from the conventional approach of assigninga single dose value for irradiation of mice to a more comprehensive approach of characterizing individual organ doses to minimize the error and uncertainty. In human radiation therapy, clinical treatment planning establishes the target dose as well as the dose distribution, however, this has generally not been done in small animal research. These results suggest that organ dose errors will be minimized by calibrating the dose rates for all filters, and using different dose rates for different organs.