Using density computed tomography images for photon dose calculations in radiation oncology: A patient study

Background and purpose: Conventional workflows for dose calculations require conversions between Hounsfield Units (HU) and the mass or electron density for Computed Tomography (CT) images in the Treatment Planning System (TPS). These conversions are scanner– and mostly kVp–dependent. A density representation or reconstruction at the CT level can potentially simplify the workflow. This study aimed to investigate the agreement between these two methods for patients and different calculation algorithms. Materials and methods: Density conversions for conventional HU–density conversions were first established using two phantoms with appropriate inserts. Next, the differences in density and dose calculations between both methods were assessed using 95% Limits of Agreement (LOA) Bland–Altman analysis for 44 consecutive clinical patient cases. These cases represented a mix of indications, algorithms (collapsed cone, convolution superposition, ray tracing, finite–size pencil beam, and Monte Carlo), and scan kVp (80 to 140) in two different commercial TPS. Results: No statistically significant bias in density or dose calculations was found between the two methods. Furthermore, 95% LOAs between both methods were ±0.05 g/cm3 and ±0.1 Gy for density and dose, respectively. Small but clinically irrelevant dose differences were found in high–density gradient regions for convolution superposition calculations or CT scans with non-delayed contrast agent injections with targets nearby vessels. Conclusions: The in vivo density–reconstructed images at the CT level were assessed to be equivalent. Therefore, they can simplify and improve clinical workflows, allowing patient–specific acquisitions for contouring and density–reconstructed images for dose calculations

On the conversion of dose to bone to dose to water in radiotherapy treatment planning systems

Background and purpose: Conversion factors between dose to medium (Dm,m) and dose to water (Dw,w) provided by treatment planning systems that model the patient as water with variable electron density are currently based on stopping power ratios. In the current paper it will be illustrated that this conversion method is not correct. Materials and methods: Monte Carlo calculations were performed in a phantom consisting of a 2 cm bone layer surrounded by water. Dw,w was obtained by modelling the bone layer as water with the electron density of bone. Conversion factors between Dw,w and Dm,m were obtained and compared to stopping power ratios and ratios of mass-energy absorption coefficients in regions of electronic equilibrium and interfaces. Calculations were performed for 6 MV and 20 MV photon beams. Results: In the region of electronic equilibrium the stopping power ratio of water to bone (1.11) largely overestimates the conversion obtained using the Monte Carlo calculations (1.06). In that region the MC dose conversion corresponds to the ratio of mass energy absorption coefficients. Near the water to bone interface, the MC ratio cannot be determined from stopping powers or mass energy absorption coefficients. Conclusion: Stopping power ratios cannot be used for conversion from Dm,m to Dw,w provided by treatment planning systems that model the patient as water with variable electron density, either in regions of electronic equilibrium or near interfaces. In regions of electronic equilibrium mass energy absorption coefficient ratios should be used. Conversions at interfaces require detailed MC calculations. Keywords: Dose to water, Monte Carlo, Dosimetry, TPS compariso

The influence of small field sizes, penumbra, spot size and measurement depth on perturbation factors for microionization chambers

The purpose of this study was the investigation of perturbation factors for microionization chambers in small field dosimetry and the influence of penumbra for different spot sizes. To this purpose, correlated sampling was implemented in the EGSnrc Monte Carlo (MC) user code cavity: CScavity. CScavity was first benchmarked against results in the literature for an NE2571 chamber. An efficiency increase of 17 was attained for the calculation of a realistic chamber perturbation factor in a water phantom. Calculations have been performed for microionization chambers of type PinPoint 31006 and PinPoint 31016 in full BEAMnrc linac simulations. Investigating the physical backgrounds of the differences for these small field settings, perturbation factors have been split up into (1) central electrode perturbation, (2) wall perturbation, (3) air-to-water perturbation (chamber volume air-to-water) and (4) water volume perturbation (water chamber volume to 1 mm(3) voxel). The influence of different spot sizes, position in penumbra, measuring depth and detector geometry on these perturbation factors has been investigated, in a 0.8 x 0.8 cm(2) field setting. p(cel) for the PP31006 steel electrode shows a variation of up to 1% in the lateral position, but only 0.4% for the PP31016 with an Al electrode. The air-to-water perturbation in the optimal scanning direction for both profiles and depth is most influenced by the radiation field, and only to a small extent the chamber geometry. The PP31016 geometry (shorter, larger radius) requires less total perturbation within the central axis of the field, but results in slightly larger variations off axis in the optimal scanning direction. Smaller spot sizes (0.6 mm FWHM) and sharper penumbras, compared to larger spot sizes ( 2 mm FWHM), result in larger perturbation starting in the penumbra. The longer geometries of the PP31006/14/15 exhibit in the non-optimal scanning direction large variations in total perturbation (p(tot) 1.201(4) (0.6 mm spot, 3 mm off axis, type A MC uncertainty) to 0.803(4) (5 mm off axis)) mainly due to volume perturbation. Therefore in IMRT settings, when the detector is not always in the optimal scanning direction, the PP31016 geometry requires less extreme perturbation (max p(tot) 1.130(3)) and shows less variation. However, these results suggest that small variations in positioning, spot size or MLC result in large differences in perturbation factors. Therefore even these 0.016 cm(3) ionization chambers are limited in their use for a field setting of 0.8 x 0.8 cm(2), as used in this investigation