ESTRO 36 Abstract Book

S792 ESTRO 36 _______________________________________________________________________________________________

tests makes it difficult to implement and results out of tolerance are often left unexplained. Experimental designs are a robust statistical method which minimizes the number of tests to be performed and provides a statistical analysis of the results. They were used to compare computed and measured doses for several algorithms. Material and Methods Tests were chosen using a Taguchi table L36 (2 11 x3 12 ) to enable the quantification of the influence of each parameter. Five algorithms were studied: the AAA (version 11, Varian) is used in clinical routine and the collapsed- cone convolution-superposition (CCCS) algorithm (version 1.5, Mobius Medical Systems) is used as a secondary dose calculation plan check. The AcurosXB (AXB) algorithm (version 11, Varian) was also investigated as well the pencil beam (PB) and Monte Carlo (MC) algorithms available on Iplan (version 4.5, Brainlab). Absorbed dose was first calculated in water for 72 beams with varying parameters: energy, MLC, depth, wedge angle, wedge jaw, X, Y 1 and Y 2 dimensions. Computations were then conducted for 72 beams in a CIRS Thorax phantom with varying parameters: energy, wedge angle, wedge jaw, X and Y dimensions, medium and gantry angle. Calculated doses were compared to measurements conducted on a Novalis TrueBeam STx (Varian) with a CC04 ionisation chamber (IBA). Results In water, all algorithms gave a mean difference between computed and measured doses centred on zero (within the uncertainty). No studied parameter led to statistically significant deviation. In the thorax phantom, the mean difference between computed and measured doses was - 0.7 ± 1.1 % for AAA, -1.4 ± 1.4 % for CCCS, -2.5 ± 1.0 % for AXB, 2.3 ± 2.2 % for PB and 0.3 ± 1.9 for MC. For AAA and CCCS, calculations in bone medium led to a statistically significant underestimation of the computed dose while the other parameters had no influence on the results. For MC, calculated dose was overestimated for gantry angle of 225° which was attributed to the modelization of the treatment table by the TPS. Conclusion Experimental designs were used as a statistical method to validate the AAA, CCCS and MC algorithms. The PB algorithm was rejected for clinical use because it overestimates the dose in heterogeneous medium. Results showed that the AXB algorithm systematically underestimates the dose in heterogeneous medium which could be linked to the dose to water - dose to medium conversion as referred in the literature. Further investigation is needed before its implementation in clinical routine, especially for modulated beams. The tests described by the experimental designs were also used to define the tolerance levels of the secondary plan check software and are now part of the ongoing quality assurance of the TPS . EP-1482 Signal Prediction for an On-line Delivery Verification System R. Heaton 1 , M. Farrokhkish 1 , G. Wilson 1 , B. Norrlinger 1 , D.A. Jaffray 1 , M.K. Islam 1 1 Princess Margaret Cancer Centre University Health Network, Radiation Physics, Toronto, Canada Purpose or Objective Dynamic radiation delivery techniques like VMAT introduce challenges in treatment verification. Complex treatments, as well as hypofraction and adaptive radiation therapy, require new verification approaches to ensure safe delivered. One approach is the introduction of entrance fluence monitoring device, like the Integral Quality Monitoring (IQM) System (iRT Germany), which provides a spatially encoded dose area product signal as a

unique delivery fingerprint. Complementary to this measurement is the signal calculation based on the treatment plan. This work describes the calculation for the IQM system and examines the impact of selected components on clinical fields. Material and Methods The calculation models the spatial response of the IQM chamber and the fluence transmitted through the individual collimating elements. The chamber response is modelled as a 2D map. The fluence from the machine is divided into 2 components: a point source at the target and an extended source at the flattening filter, referred to as the primary and extended source, respectively. The primary source is characterized by a radial intensity profile and is attenuated through the jaws and multileaf collimator. Transmission is calculated for a 2D array matching the chamber response map, and area averaged fluence is calculated for moving collimating elements during beam delivery. The extended source is modeled as a Gaussian distributed source with a Compton angular intensity distribution. The contribution of the Gaussian source to each element in the fluence array is raytraced through the collimation to obtain the area averaged fluence. An element-wise multiplication of the chamber response map with the primary and extended source fluence is summed to generate the predicted signal, modified by factors reflecting the chamber volume, the intensity of the primary and extended sources and change in machine output with field aperture. The model has been implemented for Varian and Elekta treatment units, with calculations and measurements compared for clinically relevant fields. Results Parameters for the model were determined from a series of rectangular field measurements with the IQM chamber combined with ion chamber measurements. Iterative optimization of parameter values to match rectangular field IQM measurement were performed. Similar techniques were used to extract normalization parameters. The agreement between the calculated and measured signals on a Varian TrueBeam unit for over 300 different IMRT field segments from Prostate and Head & Neck plans show 99% of segments agree within ±5%; 95% within ±3%. Similar results were seen for an Elekta Agility unit in a sample of over 400 different IMRT field segments, with 97% of segments agreeing within ±5% and 91% within ±3%. Conclusion A 2-source calculation model has been implemented for an area-fluence monitor designed for on-line patient QA. EP-1483 Pre-Treatment QA of MLC plans on a CyberKnife M6 using a liquid ion chamber array. L. Masi 1 , R. Doro 1 , O. Blanck 2 , S. Calusi 3 , I. Bonucci 4 , S. Cipressi 4 , V. Di Cataldo 4 , L. Livi 5 1 IFCA, Medical Physics, Firenze, Italy 2 Saphir Radiosurgery Center, Medical Physics, Frankfurt/ Gustrow, Germany 3 University of Florence, Department of Clinical and Experimental Biomedical Sciences "Mario Serio", Firenze, Italy

4 IFCA, Radiation Oncology, Firenze, Italy 5 Azienda Ospedaliera Universitaria Careggi, Radiotherapy Unit, Firenze, Italy

Purpose or Objective CyberKnife MLC plans require accurate patient-specific QA. The purpose of this study is to validate the use of a liquid ion chamber array for Delivery Quality Assurance (DQA) of robotic MLC plans, using several test scenarios and routine patient plans and comparing results to film dosimetry.