ESTRO 36 Abstract Book

S814 ESTRO 36 2017 _______________________________________________________________________________________________

Purpose or Objective To determine whether a knowledge based treatment planning system can efficiently produce VMAT plans for lung cancer patients treated with SABR and to assess plan quality in relation to different training plan data and model parameters. Material and Methods Three Lung SABR models were developed using the Varian RapidPlan™ DVH estimation algorithm. 1. Model A was trained using 60 plans calculated with both standard and HD MLCs, 6MV flattened /10 MV flattening filter free (FFF) utilising one algorithm (AAA version 10.0.28) with no plans excluded.

further investigation of the correlation between particular MC-scores and dosimetric accuracy can be the basis for the definition of tolerance criteria to identify potentially problematic plans. EP-1534 Automate the Complex Stuff: Pathways, Pitfalls and Results of Planning Automation in Raystation B. Archibald-Heeren 1,2 , M. Byrne 1 , Y. Wang 1 , Y. Hu 3 1 Radiation Oncology Centres, Wahroonga, Sydney, Australia 2 University of Wollongong, Clinical Medical Physics, Wollongong, Australia 3 Radiation Oncology Centres, Gosford, Sydney, Australia Purpose or Objective Automation provides the real possibility of providing exceptional plan quality to an enormous population of patients where time constraints or staffing levels may form a barrier. It is thus the authors hope that by openly sharing the constructed methodologies incorporated at Radiation Oncology Centre, Sydney, they may in some way expedite adoption of automation across the greater community. The work will focus on prostate and breast deliveries, but touch on other areas and solutions Material and Methods Atlas Based Segmentation (ABS) was utilized for automatic volume delineation. Volume metrics and DICE coefficient scores were compared between multiple manual delineation, ABS and ABS with post processing. Automatic planning was achieved by python code in the Raystation treatment planning environment. Initial optimization objectives were determined by a min- difference optimization of database entries from previous clinical plans. Plan evaluation checks against both standard guidelines and previous plan quality scores are produced through python code and inbuilt look up tables. Non-linear scoring systems are incorporated for total plan scores that provide score weighting to crucial structures. Adaptive planning and dose tracking is achieved in a Varian-Mosaiq-Raystation environment. In all case time measurements were use to provide comparisons between manual and automated processing of typical radiotherapy planning tasks. Results Contouring of DICE scores showed strong agreement (over 0.90) for the vast majority of regions of interest, with an average DICE coefficient of 77.7 for breast patients and 81.8 for prostate. Results were improved with post processing. Breast and prostate plans show comparable plan quality with manual planning for both simple single phase and advanced 3-4 target volume techniques with dose volume histogram differences consistently within 5% TD Point to point comparisons between automatic deformation matches and manual user deformations showed varying results highlighting the current need for visual QA of deformable registrations. Time improvements over manual processes are recoreded for both breast and prostate patients in all areas of testing Conclusion The possibility of automation to provide efficiency and consistency on a departmental and larger scale is demonstrated. The work represents a step in the correct direction rather than a finished produce to radiotherapy automation and the current limitations and problems are opened to the audience for responses and questions. EP-1535 knowledge based planning for lung cancer patients with stereotactic ablative radiotherapy S. Smith 1 , P. Houston 1 , G. Currie 1 1 NHS Greater Glasgow & Clyde, Radiotherapy Physics, Glasgow, United Kingdom

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Model B included data from model A and a further 40 plans; 22 plans with statistical outliers were excluded. Model C included the data from model B. A further 78 plans calculated with a new algorithm version (AAA version 13.6.23) were added to the model. Statistical outliers were excluded. The resulting models were then used to generate plans for ten patients who had not been included in the model training process. Comparisons of plans generated by each RapidPlan model with corresponding clinical plans were performed against clinical objectives. Clinical plans were generated by an experienced physicist using 10MV FFF, HD MLC and AAA (version 13.6.23).

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Results All of the plans generated by each model met the clinical objectives. The PTV V99 (Volume of the PTV receiving at least 99% of the prescription) was comparable between all three model plans and the plan generated by the experience physicist (p>>0.05). The R50 (Ratio of the 50% prescription isodose volume to the PTV) and D2cm (the maximum dose at 2cm from the PTV) values were significantly reduced when using the RapidPlan (p<0.05) for all three models. Model B gave the best results and was statistically better than model A (p<0.05). Model B also gave better results for the R100 (Ratio of the 100% prescription isodose volume to the PTV) than the experienced planner (P<0.05). This may be due to the differences in the out of field dose calculation between versions of AAA. OAR doses were comparable between all models and the experienced planner (p>0.05) Conclusion The RapidPlan™ system was able to generate clinically acceptable VMAT treatment plans for lung SABR patients, in a single optimisation, with comparable OAR sparing and equal or better plan conformity than the original clinically acceptable plans. allowing for improved consistency and efficiency in the treatment planning process. EP-1536 The advantages of Collimator Optimization for Intensity Modulated Radiation Therapy S. Pella 1 , B. Brian Doozan 2 1 21st Century Radiation Oncology- Florida Atlantic- Univeristy and Advanced Radiation Physics Inc., Radiation Oncology/Physics, Boca Raton, USA 2 Florida Atlantic University, Physics/Medical Physics, Boca Raton, USA Purpose or Objective The goal of this study was to improve dosimetry for pelvic, head and neck and other cancer sites with aspherical planning target volumes (PTV) using a new algorithm for collimator angles optimization for intensity modulated radiation therapy (IMRT). Material and Methods A retroactive study on the effects of the collimator optimization for 20 patients was performed by comparing the dosimetric effects, number of monitor units (MU), and