Abstract Book

S69

ESTRO 37

Material and Methods A deformable phantom (Fig.1) molded from flexible foam with lung density, holding a cylindrical plug containing a silicon rubber tumor with density of tissue was built. 30 Lucite beads were injected as landmarks throughout the phantom to help with the deformable registration and quantifying the phantom motion features. A piston at the inferior end of the phantom attached to a DC motor provided sinusoidal motion with 1.35 cm peak-to–peak respiratory motion at the tumor center.

mean ionization potential using MRI and CT by categorizing biologically-based molecules into 3 major categories: water (H2O), organic (org), and hydroxyapatite (HA). In doing so, the Bragg additivity rule (BAR) to determine mean ionization potential by elemental constituents can be reordered as a sum over molecular compounds and reduced to: , where w is the mass content percentage for a particular type of molecule. An exponential relationship between organic molecule hydrogen density and its mean ionization potential was determined and was used to further simplify this equation to quantities measurable by MRI (water content and hydrogen density) and CT (HA/bone density): where A and B are exponential fit constants and h is the hydrogen density within a voxel. We evaluated this model for determination of SPR in the 'reference’ tissues of ICRU 44 and in others available in the literature. A simple phantom was created of chemicals with known elemental compositions. Theoretical SPR was calculated by known elemental composition/density and used as a reference. MRI and CT scans were completed in this phantom to determine SPR using this multi-modal method, where the CT was used to determine mass/electron density. As a comparison against current clinical practice, CT was used to determine SPR directly using the stoichiometric method. Results Of the ‘reference’ tissues theoretically tested, this model leads to a mean error in SPR (for a 250 MeV proton) of 0.03% (<0.2% max error) and 0.2% (<0.3% max error) relative to a calculation by all elemental constituents using BAR for soft tissue and cortical bone, respectively. Model RMSE in soft tissue were 0.77% and 0.09% for mean ionization potential and SPR, respectively. Model RMSE in cortical bone were 1.8% and 0.2% for mean ionization potential and SPR, respectively. In the simple phantom, SPR was calculated to 1% using this multi-modal imaging method compared with theoretical SPR values. In comparison, SPR determined with CT by the stoichiometric method was found to be 3% different from theoretical SPR values. Conclusion We have proposed a novel method to model human tissue compositions for the purpose of accurate mean ionization potential and stopping power ratio calculation. For soft tissue, this model requires quantification of two parameters, percent water content by mass and percent content of hydrogen in organic molecules by mass, both of which are measurable using clinically available MR imaging techniques. In this work, we have demonstrated that this multi-modal imaging method can be used to accurately quantify proton SPR. PV-0139 Experimental verification of 4D Monte Carlo simulations of dose delivered to a deforming anatomy S. Gholampourkashi 1 , J.E. Cygler 1,2,3 , B. Lavigne 3 , E. Heath 1 1 Carleton University, Physics, Ottawa, Canada 2 University of Ottawa, Radiology, Ottawa, Canada 3 The Ottawa Hospital Cancer Center, Medical Physics, Ottawa, Canada Purpose or Objective To validate 4D Monte Carlo (MC) simulations of dose delivery to a deformable lung phantom.

Measurements were performed on an Elekta Agility linac with the phantom in stationary and moving (3.3 s period) states. Dose within the tumour was measured using calibrated Gafchromic EBT3 film and the RADPOS 4D dosimetry system 1 . To measure the dose inside the lung, another RADPOS detector was mounted on the top surface of the plug. RADPOS position tracker recorded the phantom motion with time steps of 100 ms. 4D CT scans of the moving phantom were ac quired using a Big Bore helical CT scanner. Static 3×3 cm 2 square and VMAT plans were created on the end-of-inhale CT scans of the phantom in Monaco V.5.11.01 to deliver 100 cGy to the center of the tumour. A previously validated BEAMnrc model of our 6MV Elekta Agility linac was used for all simulations 2 . DOSXYZnrc and 4DdefDOSXYZnrc 3 user codes were used, respectively, for stationary and moving anatomy dose simulations with 8×10 7 histories to achieve a statistical uncertainty of 0.7% on a dose grid resolution of 2.0×2.0×2.0 mm 3 . Data from delivery log files were extracted to generate input files for simulations. For 4D simulations, deformation vectors were obtained by deformably registering 4DCT scans of the end-of-exhale to end-of-inhale states using Velocity AI 3.2.0. Deformation vectors, along with the phantom motion trace measured with RADPOS, were used to model the phantom motion. It was assured that the exact same motion as in irradiations was used in simulations by synchronizing the start of the phantom motion with the linac beam-on time. Results Motion reproducibility of the phantom was found to be 1.2 mm as measured with RADPOS detectors. Dose values from MC simulations and measurements at the center of the tumor and top surface of the plug from were found to be within 2% and 2σ of experimental uncertainties (3.5%), respectively, for all deliveries. On the stationary phantom all data points from MC simulations passed a 3%/2 mm gamma analysis. On the moving phantom, passing rates were better than 98%.