Presentation is loading. Please wait.

Presentation is loading. Please wait.

Tissue inhomogeneities in Monte Carlo treatment planning for proton therapy L. Beaulieu 1, M. Bazalova 2,3, C. Furstoss 4, F. Verhaegen 2,5 (1) Centre.

Similar presentations


Presentation on theme: "Tissue inhomogeneities in Monte Carlo treatment planning for proton therapy L. Beaulieu 1, M. Bazalova 2,3, C. Furstoss 4, F. Verhaegen 2,5 (1) Centre."— Presentation transcript:

1 Tissue inhomogeneities in Monte Carlo treatment planning for proton therapy L. Beaulieu 1, M. Bazalova 2,3, C. Furstoss 4, F. Verhaegen 2,5 (1) Centre Hospitalier Univ de Quebec, Quebec, QC, CA, (2) McGill University, Montreal, QC, CA, (3) Stanford University, Stanford, CA, (4) Hopital Maisonneuve-Rosemont, Montreal, QC, CA, (5) Maastro Clinic, Maastricht, NL Proton therapy is gaining popularity in the treatment of cancer and the need for an accurate treatment planning system is obvious. Monte Carlo (MC) dose calculation, despite the relatively long computation time, is the most accurate way to determine the dose delivered to the patient during radiation therapy. Whereas MC dose calculations for conventional photon and electron radiotherapy have been studied extensively, proton beam MC dose calculations have only recently received attention. In this work, the importance of tissue segmentation in proton therapy is investigated using dual-energy CT (DECT) imaging. Another challenge in MC dose calculation treatment planning is metal streaking CT artifacts with the associated tissue and mass density miss-assignment. Their effect on MC proton beam dose calculations is studied for a prostate patient with bilateral hip prostheses. Introduction Tissue segmentation with dual-energy CT: CT images of a 30 cm diameter cylindrical phantom with 9 tissue equivalent inserts (table1, fig 1a) were segmented into material and mass density maps using single- energy CT (fig 1b) and DECT (fig 1c) material extraction. DECT tissue segmentation can distinguish materials with similar relative electron densities ρ e having different effective atomic numbers Z eff. The effect of inaccurate material segmentation for the two soft bone equivalent materials (B200 and CB2-10) and an adipose-equivalent material (PE) with the commonly used single energy CT material segmentation was studied. A left lateral 16×16 cm 2 200 MeV proton beam was simulated in the MCNPX code. The mass densities for (1.9×1.9×20) mm 3 voxels were binned into 0.1 g/cm 3 bins. The dose was calculated for the exact geometry (D exact ), the single energy CT geometry (D single ) and the dual- energy CT geometry (D dual ). Materials and Methods Metal streaking artifacts: The effect of metal streaking artifacts and their correction based on sinogram interpolation on MC proton beam dose calculations was studied on a patient with bilateral hip prostheses. Dose calculations were performed for three different simulation geometries: considering only tissue of uniform density 1 g/cm 3 (the water-only geometry), and using a CT number to material and mass density calibration curve with original CT images containing streaking artifacts and with artifact corrected CT images. A treatment plan with two 147 MeV proton beams (45° and 315°) was simulated in the MCNPX code. First, the spread-out Bragg peak (SOBP) was designed using simulations in a uniform water phantom (fig 2a). It is impossible to model a modulator wheel in the MCNPX code, and therefore the steps of the modulator wheel were approximated by 5 mm thick PMMA blocks. In order to calculate the dose distribution of the SOBP in the patient in a single MC simulation, 11 PMMA blocks were inserted in the path of the (6×6) cm 2 beams and the source particles (147 MeV protons) were sampled with their respective weights from the volume between the blocks (fig 2b). The patient CT images with (1.9×1.9×20) mm 3 voxels were segmented into 4 materials (air, tissue, bone and steel) using 0.1 g/cm 3 mass density bins. Tissue segmentation with dual-energy CT: Fig 3 presents the results of the phantom study. The exact dose distribution is shown in fig 4a and the differences from D single and D dual are presented in fig 3b and 3c, respectively. In both D single and D dual, the position of the Bragg peak is shifted with respect to the true position of the Bragg peak. The shift is 0.7 cm for D single and 0.7 cm or less for D dual. This is possibly due to mass density differences in the single energy CT and DECT geometry from the exact geometry. Fig 3d demonstrates the dose calculation error in the miss-assigned B200 soft bone tissue equivalent insert. The dose in the B200 insert was by 2% lower than in the exact and DECT geometry. Metal streaking artifacts: The dose distributions calculated based on the water-only geometry, on the original CT geometry and the artifact corrected geometry are presented in fig 4. The shape of the 80% isodose line conforms to the prostate in the water-only dose calculation (fig 4a). Results The dose distribution is significantly distorted in the original CT geometry due to the artifacts (fig 4b). The apparent air between the prostheses results in inaccurate doses with large statistical errors. Additionally due to the air, the 20% and 30% isodose lines extend by 1.5 cm in the healthy tissue. This might cause problems in treatment planning and its optimization. The artifact corrected geometry produced a dose distribution similar to the water-only dose distribution (fig 4b). The true dose distribution is not known. Figure 3: The exact dose distribution (D exact ) using a 200 MeV proton beam (a). PDD with two inhomogeneities (SB3 and B200) (b), the 2% dose calculation error is indicated by the arrow. The dose differences from D exact for D single (c) and D dual (d). The shift in the Bragg peak demonstrates the need for careful mass density assignment in MC dose calculations for proton beams. The dose calculation errors using the conventional single-energy CT tissue segmentation below 2% suggest that the use of DECT for proton dose calculations might only have a small added benefit. The patient study shows that a metal artifact correction is necessary for patients with bilateral hip prostheses. Conclusions Figure 4: Dose distribution for a prostate patient calculated on the basis of homogeneous water geometry (a), on the basis on the geometry with metal artifacts (b) and using the artifact correct images (c). The arrows indicate the apparent range of protons due to artifacts. MATERIALρeρe Z eff lung (LN300)0.2927.864 lung (LN450)0.4387.835 polyethylene (PE)0.9455.740 CT Solid Water (SW)0.9868.111 B200 bone mineral1.09710.897 CB2 - 10% CaCO 3 1.1428.905 CB2 - 30% CaCO 3 1.28611.393 CB2 - 50% CaCO 3 1.47012.978 SB3 cortical bone1.69214.141 Figure 1: Figure 1: The exact geometry (a), the single-energy material segmentation (b) and the dual-energy CT material segmentation (c). Table 1:Relative electron densities ρ e and effective atomic numbers Z eff for materials used in the tissue inhomogeneity study. a) b) All CT geometries were converted into lattices and the dose was scored using the *F8:H,P,E energy deposition tally. Protons, photons and electrons were transported using the la150u cross section library with energy cutoffs of 10 keV. In all simulations, 107 particles were simulated in approximately 15 hours on a 3 GHz machine. Figure2: The spread-out Bragg peak for patient dose calculations (a) and the MCNP geometry showing 0.5 cm PMMA blocks for modulation of the 147 MeV proton beam (b). c) a)b) d) a) b)c)


Download ppt "Tissue inhomogeneities in Monte Carlo treatment planning for proton therapy L. Beaulieu 1, M. Bazalova 2,3, C. Furstoss 4, F. Verhaegen 2,5 (1) Centre."

Similar presentations


Ads by Google