ESTRO 36 Abstract Book

S819 ESTRO 36 _______________________________________________________________________________________________

3 Odense University Hospital, Department of Oncology, Odense, Denmark Purpose or Objective Automatic treatment planning is of high interest, since the optimization process is highly complex and the current plan quality is dependent on the treatment planner. In a clinical setting where time for treatment planning is sparse, automatic treatment plan generation would be desirable. This study evaluates automatic treatment planning for high risk prostate cancer in comparison to a current clinical plan quality. Material and Methods All patients (#42) treated for high risk prostate cancer during 2015 at our clinic were replanned using the Autoplan module in Pinnacle® (ver. 9.10). Similar to the manual plan (MA) the autoplan (AP) was generated for an Elekta® Synergy linac, consisting of one full VMAT arc and using 18 MV photons. All APs were calculated by the same medical physicist. There was no comparison of the MA and AP in the plan generation process. Using a template model it took on average 90 sec to start autoplanning, which took approximately 1 hour to complete optimization. Hereafter it took on average 173 sec (range 45 to 550) of active planning for one or two post-optimizations with 15 iterations per run to fine-tune the plan to meet the acceptance criteria. The plan quality was evaluated by comparing DVHs, dose metrics, delivery time and dose accuracy when delivered on an ArcCheck phantom. For each patient the MA and AP were blindly evaluated side-by-side by a radiation oncologist, who concluded which plan was better, and if the differences were predicted to be clinically relevant. All differences were tested for statistical significance with a Wilcoxon signed rank test (p<0.05). Results The DVHs show small but significant differences in the doses to both CTV and PTV. The APs spared all OARs significantly. For the rectum the average of the mean doses is reduced from 42.6 Gy to 31.8 Gy. The reduction in rectal dose is significant between 1 Gy and 73 Gy (figure 1). Table 1 shows the results for targets as well as OARs, their standard deviations (std) and the corresponding p- values.

Conclusion Plan generation for breast with locoregional nodes was successfully automated using the Eclipse scripting API to create a workflow that integrates the RP knowledge-based planning system, and a combination of different techniques: open fields, slip zone, RA. Automated generation of treatment plans is anticipated to lead to more consistent and efficient planning. It may also facilitate the transfer of complex treatment planning techniques between centers. EP-1525 Automatic treatment plan generation for Prostate Cancer S. Agergaard 1 , C.R. Hansen 1,2 , L. Dysager 3 , A. Bertelsen 1 , H.R. Jensen 1 , S. Hansen 2,3 , C. Brink 1,2 1 Odense University Hospital, Laboratory of Radiation Physics, Odense, Denmark 2 University of Southern Denmark, Faculty of Health Sciences, Odense, Denmark