ESTRO 2020 Abstract book
S105 ESTRO 2020
investigates if the plan quality can be improved using a system for knowledge-based planning (KBP). Material and Methods 69 patients previously treated with VMAT for high-risk prostate cancer was included in a RapidPlan model created in Eclipse V15.5 (Varian). Prescribed dose was 50, 60, 67.5 and 72.5 Gy in 25 fractions to the pelvic lymph nodes, prostate and seminal vesicles, prostate gland and prostate tumor(s), respectively. Three auxiliary structures were included in the model, in order to define dose limits for parts of the target volumes not overlapping with higher dose level targets. OARs were bladder, bowel and rectum. The dose-volume objectives and priorities were tuned to obtain optimal balance between target coverage and normal tissue sparing in the final model. For 20 patients not included in the model, a RapidPlan (RP) plan was created without any user intervention during the optimization phase, and compared with the manually optimized clinical plan (CP). gEUD was calculated using k = 8, 4 and 12 for bladder, bowel and rectum, respectively. Significance was tested with the paired samples t-test for normally distributed variables and the Wilcoxon signed- rank test for non-normal variables. Results Target coverage was similar between RP and CP (Figure 1a), with D98% > 95% of prescribed dose for all targets in all plans. Mean (95% CI) reduction in D mean with RP was 2.1 Gy (1.3-3.0) for bladder, 1.0 Gy (0.6-1.3) for bowel and 1.5 Gy (0.6-2.4) for rectum (p < 0.05). Mean reduction in gEUD with RP was 0.9 Gy (0.6-1.2) for bladder, 0.9 Gy (0.6-1.2) for bowel and 0.6 Gy (0.4-0.7) for rectum (p < 0.05). Figure 1b-c and Figure 2 show how the inter-patient variation in rectum and bladder DVH was reduced with RP, mainly by limiting the volume receiving 20-50 Gy. The number of auxiliary structures was reduced from 10 in the CPs to 3 with RP. Estimated planning time with RP in our clinic is 55 min, where 30 min is VMAT optimization without user interaction, and the remaining 25 include preparations for planning and evaluation of the treatment plan. Planning time for the CPs was not recorded, but manual planning usually involved 2-3 rounds of repeated optimization and evaluation.
where D i
is the delivered dose of fraction i, N 0
nominal plan dose and P 0 is the prescribed dose distribution in the target. As such, the optimizer minimizes the difference of the daily plan to this target dose. For evaluation, target homogeneity (D 2% - D 98% / D Prescripton ) and organ at risk D 2% values for accumulated treatment doses have been considered. Results Compared to the nominal plan, degradation of target dose homogeneity in the accumulated dose due to delivery/algorithmic uncertainties was between 1.2 and 3.4% (Fig 1). By feeding back the off-line reconstructed dose into the optimization, homogeneity could be improved by >2% for all three patients. In addition, an average reduction of D 2% for all OARs could be achieved with feedback compared to delivery without adaption (Fig 2).
Conclusion Dose inaccuracies introduced through the use of a fast and simple dose calculation for daily re-optimization of plans in DAPT and/or due to delivery uncertainties, can be compensated for by including previously reconstructed doses, calculated off-line using log-files and MC, into the daily (on-line) re-optimization process. Although improvements are small (~2%), the approach can mitigate more than half of delivery/dose calculation degradations. The proposed approach is thus a promising candidate for improving treatment accuracy, whilst preserving fast on- line re-optimization. The method still needs to be tested in areas of deforming anatomy however, where dose PD-0191 Knowledge-based planning improves plan quality for high-risk prostate cancer with four dose levels K. Fjellanger 1 , H.E.S. Pettersen 1 , J.A. Hundvin 1 , B. Nygaard 1 , K. Revheim 1 , T.H. Sulen 1 , L.B. Hysing 1 1 Haukeland University Hospital, Department of Oncology and Medical Physics, Bergen, Norway Purpose or Objective Manual VMAT treatment planning for high-risk prostate cancer with four dose levels (SIB) is complex and time consuming, with a number of auxiliary structures and many objectives to be balanced in the optimization. This study accumulation may be more challenging. (1) Matter et al, Acta. Oncol. 2019
Made with FlippingBook - Online magazine maker