ESTRO 36 Abstract Book

S776 ESTRO 36 _______________________________________________________________________________________________

EP-1454 Comparison of Treatment Planning Algorithms and Monte Carlo Simulations in Oesophageal Radiotherapy D. Johns 1 , E. Spezi 2 , P. Downes 1 , D. Lewis 1 1 Velindre Cancer Centre, Medical Physics, Cardiff, United Kingdom 2 Cardiff University, School Of Engineering, Cardiff, United Kingdom Purpose or Objective Many workers have published comparisons of dose distributions generated by conventional radiotherapy planning systems and those produced by various Monte Carlo (MC) dose calculation packages [1]. However, due to the large computational load involved in producing each MC plan, the number of cases cited in each study is relatively small and hence the statistical power of these studies is low. In this work, distributed computing resources have been used to simulate over fifty oesophageal radiotherapy treatment plans, to provide a more statistically powerful comparison of analytical dose calculations and MC dose calculations. Material and Methods Radical oesophageal radiotherapy plans are routinely produced in our centre according to a protocol originally developed for the national SCOPE trial [2]. Plans were produced using the Pencil Beam Enhanced (PBE) algorithm, and re-calculated using the Collapsed Cone Enhanced (CCE) algorithm, of Oncentra MasterPlan (OMP) v4.3. MC simulations were performed using the BEAMnrc package. Results An initial sample of 12 oesophageal radiotherapy treatment plans were simulated using the RTGrid system. The differences between the dose calculation methods, and the variance in the twelve cases, were used to calculate the sample size needed to detect a 3% difference in the proportion of the Planning Target Volume receiving 95% of the prescription dose (PTV V95%) with 90% power, following the method of Altman [3]. The required sample size was determine to be 38, so a further 40 oesophageal cases were subsequently simulated. The volumetric dose data for the different dose calculation methods was used to calculate the Tumour Control Probability (TCP) using the method of Geh [4]. Conclusion A statistically significant decrease in the PTV V95% when changing from CCE to MC dose calculations has been demonstrated, in a sample of 40 cases. A statistically significant decrease in the values of TCP calculated based on the CCE and MC dose calculations was also found, suggesting that the differences in physical dose would have clinical significance. References 1. Rogers DWO. Fifty years of Monte Carlo simulations for medical physics . Physics in Medicine and Biology. 2006, 51 (13), R287-301. 2. Wills L, Millin A, Paterson J, Crosby T, Staffurth J. The effect of planning algorithms in oesophageal radiotherapy in the context of the SCOPE 1 trial. Radiotherapy and Oncology 2009, 93 (3), 462-7. 3. Altman DG Practical Statistics for Medical Research 1999 (Boca Raton: Chapman & Hall/CRC) 455-461 4. Geh, J.I. et al, Systematic overview of preoperative (neoadjuvant) chemoradiotherapy trials in oesophageal cancer: Evidence of a radiation and chemotherapy dose response. Radiotherapy and Oncology, 2006, 78 (3), pp.236–244.

relative electron density (rED) of both CF and Foam volumes was adjusted iteratively to match the measured and calculated dose attenuation in several angles. Finally 36 VMAT patients of different pathologies previously irradiated on the Octavius4D phantom were compared with the calculated plans both with and without couch. The gamma passing rates of both cases were compared to determine the overall impact of including the couch in the calculations. Results The rED densities that best reproduced the measured values were 0.5ρ e,w and 0.1 ρ e,w for both CF and Foam, respectively (see Figure 1). The agreement between measured and calculated attenuation is good, mainly in the posterior angles, with differences under 1%. At 110 and 250 gantry degrees we measured differences up to 4.2% and 2.4% for both 6 and 15 MV, respectively. These angles match the lateral edges of the couch, where there are many different components, which make this simplified model less accurate.

For the 36 VMAT plans we compared the 3D global gamma passing rates with (W) and without (W/O) the couch, and the average results were (detailed in Figure 2): γ(3%,3mm): W/O: 98.9%, W: 99.3%; γ (2%2mm): W/O: 92.5%, W: 93.8%. The median improvement is 0.3% for γ(3,3) and 1.1% for γ(2,2). Conclusion Relying on the results, it is advisable to implement the treatment couch in the TPS, especially using techniques such as VMAT. In this work we present a successful model of the iBEAM® evo Couchtop in Monaco for both 6 and 15 MV. We plan to implement it for all our both 3D and IMRT/VMAT plans.